.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2015
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|--------------------------------------------------------------------------|-------------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere..... | 1 |
+| 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 4 |
+| 6 General description..... | 4 |
+| 6.1 Networking challenges in cloud computing..... | 4 |
+| 6.2 High-level concept of NaaS..... | 5 |
+| 7 Functional requirements of NaaS application..... | 6 |
+| 7.1 Performance..... | 7 |
+| 7.2 Operation and management..... | 7 |
+| 7.3 Service chain ..... | 7 |
+| 7.4 Multiple IP addresses ..... | 7 |
+| 8 Functional requirements of NaaS platform..... | 7 |
+| 8.1 Programmable NaaS platform ..... | 7 |
+| 8.2 Dynamic and flexible network services composition and steering ..... | 8 |
+| 8.3 Isolation of service chains for tenants ..... | 8 |
+| 8.4 Flexible scaling of NaaS platform..... | 8 |
+| 8.5 Integration of software applications ..... | 8 |
+| 9 Functional requirements of NaaS connectivity..... | 8 |
+| 9.1 Common control mechanism for NaaS connectivity..... | 8 |
+| 9.2 Unified SLA for multiple optimized networks..... | 8 |
+| 9.3 Leveraging transport networks dynamically ..... | 9 |
+| 9.4 Unified network control mechanism ..... | 9 |
+| 9.5 Elastic network reconfiguration ..... | 9 |
+| 9.6 Seamless and end-to-end solution of bandwidth allocation ..... | 9 |
+| 9.7 Symmetric or asymmetric capacity ..... | 9 |
+| 9.8 Optimized and fine-grained traffic engineering ..... | 9 |
+| 9.9 Coexistence with legacy network services and functions ..... | 9 |
+| 9.10 Centralized control view and abstraction view of resources ..... | 9 |
+| 9.11 CSC limited control of services..... | 10 |
+| 9.12 Logically isolated network partition..... | 10 |
+| 9.13 Overlay network mechanism..... | 10 |
+| 9.14 Overlapped private IP addresses ..... | 10 |
+| 9.15 Interworking among different VPN solutions ..... | 10 |
+| 9.16 VPN connection in mobile environment ..... | 10 |
+
+| | Page |
+|------------------------------------------------------------------------------------------------|-------------|
+| 9.17 Connection to NaaS CSP's network through public Internet..... | 10 |
+| 10 Security considerations ..... | 10 |
+| Appendix I – Development methodology of NaaS functional requirements and
architecture ..... | 11 |
+| Appendix II – Use cases of NaaS..... | 12 |
+| II.1 Use case template ..... | 12 |
+| II.2 NaaS applications related use cases ..... | 12 |
+| II.3 NaaS platform related use cases ..... | 15 |
+| II.4 NaaS connectivity related use cases ..... | 17 |
+| Appendix III – Considerations on CSP's network related activities ..... | 26 |
+| Bibliography..... | 28 |
+
+## Recommendation ITU-T Y.3512
+
+# Cloud computing – Functional requirements of Network as a Service
+
+# 1 Scope
+
+This Recommendation provides use cases and functional requirements of Network as a Service (NaaS), one of the representative cloud service categories. This Recommendation covers the following:
+
+- High-level concept of NaaS;
+- Functional requirements of NaaS;
+- Typical NaaS use cases.
+
+This Recommendation provides use cases and functional requirements of NaaS application, NaaS platform and NaaS connectivity.
+
+NOTE – General requirements of NaaS can be found in [ITU-T Y.3501].
+
+## 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- | | |
+|----------------|-----------------------------------------------------------------------------------------------------------------|
+| [ITU-T X.1601] | Recommendation ITU-T X.1601 (2014), Security framework for cloud computing . |
+| [ITU-T Y.3011] | Recommendation ITU-T Y.3011 (2012), Framework of network virtualization for future networks . |
+| [ITU-T Y.3500] | Recommendation ITU-T Y.3500 (2014), Information technology – Cloud computing – Overview and Vocabulary . |
+| [ITU-T Y.3501] | Recommendation ITU-T Y.3501 (2013), Cloud computing framework and high-level requirements . |
+| [ITU-T Y.3502] | Recommendation ITU-T Y.3502 (2014), Information technology – Cloud computing – Reference architecture . |
+
+## 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 application capabilities type** [ITU-T Y.3500]: Cloud capabilities type in which the cloud service customer can use the cloud service provider's applications.
+
+**3.1.2 cloud capabilities type** [ITU-T Y.3500]: Classification of the functionality provided by a cloud service to the cloud service customer, based on resource used.
+
+NOTE – The cloud capabilities types are application capabilities type, infrastructure capabilities type and platform capabilities type.
+
+**3.1.3 cloud computing** [ITU-T Y.3500]: Paradigm for enabling network access to a scalable and elastic pool of shareable physical or virtual resources with self-service provisioning and administration on-demand.
+
+NOTE – Examples of resources include servers, operating systems, networks, software, applications, and storage equipment.
+
+**3.1.4 cloud service** [ITU-T Y.3500]: One or more capabilities offered via cloud computing invoked using a defined interface.
+
+**3.1.5 cloud service category** [ITU-T Y.3500]: Group of cloud services that possess some common set of qualities.
+
+NOTE – A cloud service category can include capabilities from one or more cloud capabilities types.
+
+**3.1.6 cloud service customer** [ITU-T Y.3500]: Party which is in a business relationship for the purpose of using cloud services.
+
+**3.1.7 cloud service provider** [ITU-T Y.3500]: Party which makes cloud services available.
+
+**3.1.8 cloud service user** [ITU-T Y.3500]: Natural person, or entity on their behalf, associated with a cloud service customer that uses cloud services.
+
+**3.1.9 Communications as a Service (CaaS)** [ITU-T Y.3500]: Cloud service category in which the capability provided to the cloud service customer is real time interaction and collaboration.
+
+NOTE – CaaS can provide both application capabilities type and platform capabilities type.
+
+**3.1.10 infrastructure capabilities type** [ITU-T Y.3500]: Cloud capabilities type in which the cloud service customer can provision and use processing, storage and networking resources.
+
+**3.1.11 logically isolated network partition** [ITU-T Y.3011]: A network that is composed of multiple virtual resources which is isolated from other LINPs.
+
+NOTE – Term "logically isolated", which is the counter concept of "physically isolated", means mutual exclusiveness of the subjects (e.g., network partition, in this case), while the original subjects may be physically united/shared within the common physical constraints.
+
+**3.1.12 Network as a Service (NaaS)** [ITU-T Y.3500]: Cloud service category in which the capability provided to the cloud service customer is transport connectivity and related network capabilities.
+
+NOTE – NaaS can provide any of the three cloud capabilities types.
+
+**3.1.13 platform capabilities type** [ITU-T Y.3500]: Cloud capabilities type in which the cloud service customer can deploy, manage and run customer-created or customer-acquired applications using one or more programming languages and one or more execution environments supported by the cloud service provider.
+
+**3.1.14 tenant** [ITU-T Y.3500]: Group of cloud service users sharing access to a set of physical and virtual resources.
+
+### **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following term:
+
+**3.2.1 service chain:** An ordered set of functions that is used to enforce differentiated traffic handling policies for a traffic flow.
+
+## **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+BGP Border Gateway Protocol
+
+| | |
+|-------|--------------------------------------|
+| BoD | Bandwidth on Demand |
+| BSS | Business Support System |
+| CaaS | Communications as a Service |
+| CDN | Content Delivery Network |
+| CPE | Customer Premises Equipment |
+| CSC | Cloud Service Customer |
+| CSP | Cloud Service Provider |
+| CSU | Cloud Service User |
+| DNS | Domain Name System |
+| DPI | Deep Packet Inspection |
+| EPC | Evolved Packet Core |
+| GW | Gateway |
+| HQ | Headquarter |
+| IaaS | Infrastructure as a Service |
+| IDE | Integrated Development Environment |
+| IMS | IP Multimedia Subsystem |
+| IP | Internet Protocol |
+| IPS | Intrusion Protection System |
+| IPsec | IP security |
+| L2 | Layer 2 |
+| L3 | Layer 3 |
+| LAN | Local Area Network |
+| LINP | Logically Isolated Network Partition |
+| MAC | Medium Access Control |
+| MEF | Metro Ethernet Forum |
+| MEN | Metro Ethernet Network |
+| MPLS | Multi-Protocol Label Switching |
+| NaaS | Network as a Service |
+| NNI | Network-to-Network Interface |
+| NOS | Network Operating System |
+| OSS | Operations Support System |
+| QoE | Quality of Experience |
+| QoS | Quality of Service |
+| P2P | Peer-to-Peer |
+| PaaS | Platform as a Service |
+| PoP | Point of Presence |
+| SaaS | Software as a Service |
+
+| | |
+|---------|----------------------------------|
+| SAL | Software Abstraction Layer |
+| SDN | Software Defined Networking |
+| SLA | Service Level Agreement |
+| SSL | Secure Socket Layer |
+| UNI | User-to-Network Interface |
+| vCDN | virtual Content Delivery Network |
+| vDPI | virtual Deep Packet Inspection |
+| vEPC | virtualised Evolved Packet Core |
+| vFW | virtual Firewall |
+| vRouter | virtual Router |
+| VDI | Virtual Desktop Infrastructure |
+| VM | Virtual Machine |
+| VoIP | Voice over IP |
+| VPLS | Virtual Private LAN Service |
+| VPN | Virtual Private Network |
+| VRP | Virtual Routing and Forwarding |
+| WAN | Wide Area Network |
+
+## 5 Conventions
+
+The keywords "**is required to**" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this Recommendation is to be claimed.
+
+The keywords "**is recommended**" indicate a requirement which is recommended but which is not absolutely required. Thus this requirement need not be present to claim conformance.
+
+The keywords "**can optionally**" indicate an optional requirement which is permissible, without implying any sense of being recommended. This term is not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with the specification.
+
+In the body of this Recommendation and its annexes, the words shall, shall not, should, and may sometimes appear, in which case they are to be interpreted, respectively, as is required to, is prohibited from, is recommended, and can optionally. The appearance of such phrases or keywords in an appendix or in material explicitly marked as informative is to be interpreted as having no normative intent.
+
+## 6 General description
+
+### 6.1 Networking challenges in cloud computing
+
+There are several challenges to build an efficient and reliable network application and infrastructure to provide cloud services. Having both compute, storage and network capabilities may face the following challenges:
+
+- Coordination of compute and storage virtualization with network capabilities
+Compute and storage performance challenges in cloud computing systems are successfully solved using virtualization as a core technique. Server virtualization introduced virtual
+
+machines' (VMs) dynamic and static migration, which imposes demands on the networking environments. Network is expected to provide suitable and flexible support for highly variable cloud applications, when they run inside complex and diverse system architecture. In such system it is possible to provide the compute and storage resources, but it is also expected to dynamically provide the necessary networking support required to assure overall system performance, reliability and quality of service (QoS) demands.
+
+- Harmonized control of heterogeneous network technologies
+Due to the increasing geographical distribution of cloud computing systems several network technologies can be utilised to assure end-to-end connectivity. It is expected that support of efficient control mechanisms for heterogeneous network technologies be provided.
+- On-demand reconfiguration
+Cloud computing system allows for dynamic computing and storage resources reconfiguration or migration to meet the changing requirements. It is desirable that networks provide on-demand reconfiguration to satisfy the requirements of cloud services, e.g., change of bandwidth, modification of network topology or addition of new network elements.
+
+### 6.2 High-level concept of NaaS
+
+As defined in [ITU-T Y.3500], Network as a Service (NaaS) is a category of cloud services in which the capability provided to the cloud service customer (CSC) is transport connectivity and related network capabilities in order to solve the challenges mentioned above. NaaS services are divided into NaaS application service, NaaS platform service and NaaS connectivity service. In particular, NaaS connectivity service is an "infrastructure capabilities type" service limited to networking resources.
+
+The high-level concept of NaaS using the layering framework defined in [ITU-T Y.3502] is illustrated on Figure 6-1.
+
+NaaS can provide any of the three cloud capabilities identified in [ITU-T Y.3500] as follows:
+
+- **NaaS application:** application capabilities type of service where NaaS CSC can use network applications provided by NaaS cloud service provider (CSP). These network applications are considered and used as a virtual network functions provided by NaaS CSP. This includes any network function for either fixed or mobile or both core and access as well as for control and forwarding planes network elements. Examples of NaaS applications include virtual router, virtual content delivery network (vCDN), virtualised evolved packet core (vEPC) and virtual firewall (vFW).
+In this category, CSP offers a set of interfaces for network functionalities.
+- **NaaS platform:** platform capabilities type of service where NaaS CSC can use the network platform provided by NaaS CSP. The NaaS platform offers one or more software execution environments and one or more programming languages to deploy, manage and run customer-created or customer-acquired network applications. Such network applications can be created or acquired by CSC as self-implemented network services. Network applications can implement various network functionalities or services, e.g., router, firewall, load balancer, as well as groups of network functionalities. Groups of network applications and functionalities can form an integrated network solution.
+In this category, CSP offers a programmable environment for network functionalities that can be employed by cloud service customer or cloud service partner software.
+- **NaaS connectivity:** infrastructure capabilities type of service where NaaS CSC can provision and use networking connectivity resources provided by NaaS CSP. This includes for example flexible and extended virtual private network (VPN), bandwidth on demand (BoD), etc. NaaS can provide basic networking functionalities such as connectivity, using whatever physical, logical or virtual networking capabilities the CSP chooses to offer. There is often a desire to
+
+offer more than IP networking. For example, a CSC may wish for elastic, on-demand control of optical networks, or even for access to dark fibre using photonic switching.
+
+In this category, CSP offers network connections between two or more endpoints, which may include additional network functionalities.
+
+NOTE 1 – The creation, control, management and removal of NaaS connectivity is performed as a cloud service.
+
+NOTE 2 – NaaS typically provides "bearer" connectivity of raw data without regard to the type of data carried between endpoints. Services that are specific to a type of carried data, such as telephony, voice over IP (VoIP), video conferencing, and instant messaging, are typically categorised as Communications as a Service (CaaS).
+
+NOTE 3 – The endpoints of NaaS connectivity can reside either within the NaaS service interface itself, in another cloud service, in a non-cloud service or at a traditional network endpoint.
+
+NaaS services can be utilized by both cloud and non-cloud services.
+
+Network capabilities can be delivered through any combination of the three types of cloud capabilities. In particular, network capabilities could support cloud computing in aspects of interconnection of the CSP and the CSC, topology and route related functionality to share topologies, discovery related functionality to perform other services needed by inter-cloud related activities as well as other functionalities related to monitoring, protection, verification, etc.
+
+Network functionality can be provided as a composite NaaS service where the NaaS service consists of more than one network functionality services. Hierarchically nested NaaS composite services can also be provided. Composite NaaS services could apply for different NaaS capabilities types provided to CSC according to the performance objectives expressed in the service level agreement (SLA).
+
+
+
+Y.3512(14)\_F6-1
+
+Figure 6-1: High-level concept of NaaS. The diagram shows a four-layer architecture. From top to bottom: 1. User layer (orange box). 2. Access layer (orange box). 3. Service layer (orange box) containing a pink box labeled 'NaaS Application/platform/connectivity'. 4. Resource layer (dark orange box) containing a grey box labeled 'Physical/virtual resources (Processing, storage and networking)'. Three vertical double-headed arrows connect the Service layer box to the Resource layer box, indicating bidirectional interaction. The label 'Y.3512(14)\_F6-1' is at the bottom right of the diagram.
+
+**Figure 6-1 – High-level concept of NaaS**
+
+Appendix II provides NaaS use cases in which the three cloud capabilities types (i.e., application, platform and infrastructure capabilities) are provided to the CSC.
+
+Appendix III provides considerations on the CSP's network related activities.
+
+NOTE 4 – Regarding the network connectivity, one important difference between Infrastructure as a Service (IaaS) and NaaS is that IaaS is a cloud service category that is offered in only one flavour of cloud capability type, and that is infrastructure capabilities type [ITU-T Y.3500]. However, NaaS is a cloud service category that can be offered in all three cloud capabilities types.
+
+## **7 Functional requirements of NaaS application**
+
+This clause provides requirements of NaaS application derived from the use cases described in Appendix II.
+
+### **7.1 Performance**
+
+- NaaS application performance is recommended to be manageable to satisfy the CSC's needs.
+- It is recommended that NaaS CSP monitors the utilization and delivery performance of NaaS application.
+- NaaS application is recommended to be provided to the CSC according to the performance objectives expressed in the SLA.
+
+### **7.2 Operation and management**
+
+- The operation of NaaS application is required to be manageable and deterministic in accordance with the CSP operational policies.
+- It is recommended that each NaaS application be managed by NaaS CSP efficiently and automatically, complying with the CSP's common framework of service management and service operation management.
+- It is recommended the NaaS CSP provide the CSC with an efficient management solution of provisioned NaaS applications allowing to integrate the management of the provisioned NaaS applications into the CSC's network operation environment.
+
+### **7.3 Service chain**
+
+- It is recommended that NaaS CSP provides mechanisms allowing for the chaining of NaaS applications, e.g., the required NaaS applications components and associated order.
+
+### **7.4 Multiple IP addresses**
+
+- It is recommended that NaaS application support multiple IP addresses on a network interface when it delivers network appliance functions (such as firewalls, load balancers).
+- NOTE – This requirement is also applicable to NaaS platform and NaaS connectivity.
+
+## **8 Functional requirements of NaaS platform**
+
+This clause provides requirements of NaaS platform derived from the use cases described in Appendix II.
+
+### **8.1 Programmable NaaS platform**
+
+- It is recommended that NaaS CSP supports deployment of network applications on NaaS platform by both the CSP and the CSC.
+- It is recommended that NaaS platform provides hardware or software modules specialized for network function acceleration.
+- It is recommended that NaaS platform assures and indicates performance available to the CSC's applications which are running on it.
+- It is recommended that NaaS platform service provides a modular software framework to select and integrate networking functions, security functions and third party applications.
+- It is recommended that NaaS CSP provides platform support for the CSC to manage (e.g., install, upgrade or uninstall) CSC owned modules.
+- It is recommended that NaaS platform provides network enablers for the CSC to initiate (e.g., design, build, manage) and operate the flexible, scalable, functionally expandable networks.
+- It is recommended that NaaS platform provides a unified control and management function over distributed NaaS platforms for the CSC to change, move, or remove network enablers between NaaS platforms.
+
+### **8.2 Dynamic and flexible network services composition and steering**
+
+- It is recommended that NaaS CSP steers the CSC's traffic via service chain which is dynamically and flexibly composed by customized sequences of NaaS applications on the NaaS platform according to the CSC's specific service logic.
+
+### **8.3 Isolation of service chains for tenants**
+
+- NaaS CSP can optionally support isolation of service chains for tenants, combining different network services, implemented on the NaaS platform.
+
+### **8.4 Flexible scaling of NaaS platform**
+
+- It is recommended that NaaS CSP assures flexible scaling of the resources assigned to the NaaS platform to achieve performance objectives of the network services and applications implemented on the NaaS platform.
+
+NOTE – This requirement is to meet the changes in services or applications utilization caused by e.g., growth of traffic, change in number of users, adding new services, implementing new applications.
+
+### **8.5 Integration of software applications**
+
+- It is recommended that NaaS CSP supports integration of software applications deployed on the NaaS platform by either the CSP or the CSC, or both, to allow building of the combined solutions.
+
+## **9 Functional requirements of NaaS connectivity**
+
+This clause provides requirements of NaaS connectivity derived from the use cases described in Appendix II.
+
+### **9.1 Common control mechanism for NaaS connectivity**
+
+- It is recommended that the NaaS connectivity control mechanism provided by the NaaS CSP supports the negotiation of connectivity parameters (such as interface characteristics, connection endpoints, IP version support, QoS, L3/L2VPN type, connectivity extension approach (e.g., clause 10 of [b-IETF RFC 4364], routing information (e.g., border gateway protocol (BGP) route target).
+- It is recommended that NaaS CSP provides a common NaaS connectivity control mechanism allowing identified NaaS connectivity to be provided in a secure and QoS guaranteed manner.
+- It is recommended that the NaaS connectivity control mechanism is able to cope with potentially different CSC identification schemes used on the NaaS CSP side and on the connected endpoint.
+- NaaS CSP can optionally provide isolated connectivity for the network tenants.
+
+### **9.2 Unified SLA for multiple optimized networks**
+
+- It is recommended that NaaS CSP provides network connectivity services using unified SLA for CSC's management of multiple optimized networks in order to simplify and unify the control and management of networks.
+
+NOTE – This mechanism allows the CSP to create and add new features to their networks to provide high quality services which can meet CSC's differentiated requirements.
+
+- It is recommended that composite NaaS services policy should be expressed in the SLA.
+
+NOTE 1 – NaaS service can be a composite service, where the service consists of more than one NaaS service.
+
+NOTE 2 – This requirement is also applicable to the NaaS application and the NaaS platform.
+
+### **9.3 Leveraging transport networks dynamically**
+
+- It is recommended that NaaS CSP leverages transport networks dynamically from multiple choices of physical and virtual networks for the purpose of providing network connectivity services, such as recovery, BoD, QoS guarantee, etc.
+
+NOTE – The transport networks can be heterogeneous in terms of technology and administrative domain.
+
+### **9.4 Unified network control mechanism**
+
+- It is recommended that NaaS CSP provides a unified control mechanism for the end-to-end NaaS connectivity given to a CSC.
+
+NOTE – NaaS connectivity could be provided either by multiple heterogeneous networks or by a network employing one or more NaaS platforms or applications, which perform(s) network functions.
+
+### **9.5 Elastic network reconfiguration**
+
+- It is recommended for the CSP to provide the elastic network reconfiguration in order to match the computing and storage elasticity and to maintain service continuity.
+
+### **9.6 Seamless and end-to-end solution of bandwidth allocation**
+
+- It is recommended that NaaS CSP provides seamless and end-to-end solution of bandwidth allocation independent of network technology and architecture.
+
+### **9.7 Symmetric or asymmetric capacity**
+
+- It is recommended that NaaS CSP provides symmetric or asymmetric network link capacity based on the CSC's demand.
+
+### **9.8 Optimized and fine-grained traffic engineering**
+
+- It is recommended that NaaS CSP provides the CSC with fine-grained view on usage of network resources.
+- It is recommended that NaaS CSP collects near real time utilization metrics and topology data from its own network equipment.
+- It is recommended that NaaS CSP controls the network resource allocation by reconfiguring network profiles as well as properties (e.g., topology, bandwidth) in response to dynamically changing traffic demands.
+- NaaS CSP can optionally provide centralized traffic management to achieve optimized traffic engineering.
+
+### **9.9 Coexistence with legacy network services and functions**
+
+- It is recommended that NaaS CSP avoids or mitigates possible performance and flexibility impacts when introducing new network connectivity services.
+- It is recommended that NaaS CSP supports coexistence of new network connectivity services with legacy systems.
+
+### **9.10 Centralized control view and abstraction view of resources**
+
+- NaaS CSP can optionally support logically centralized management and control view of the network resources.
+- NaaS CSP can optionally provide to the CSC an abstraction view of the underlying network resources.
+
+### **9.11 CSC limited control of services**
+
+- It is recommended that NaaS CSP provides to the CSC appropriate services control in order to respond to the time-sensitive performance requirements, including bandwidth quantities, maximum latencies and other QoS parameters.
+
+### **9.12 Logically isolated network partition**
+
+- NaaS CSP can optionally implement logically isolated network partition (LINP).
+NOTE – LINP is described in [ITU-T Y.3011]. See clause 3.1.14.
+
+### **9.13 Overlay network mechanism**
+
+- NaaS connectivity can optionally support virtual overlay networks on top of the physical underlay network.
+
+### **9.14 Overlapped private IP addresses**
+
+- It is recommended that NaaS CSP allows different CSCs to use their own private IP addresses even when the subnet addresses are overlapped.
+
+### **9.15 Interworking among different VPN solutions**
+
+- It is recommended that NaaS CSP supports interworking among different VPN technologies.
+
+### **9.16 VPN connection in mobile environment**
+
+- It is recommended that NaaS CSP supports VPN connectivity in mobile environment.
+
+### **9.17 Connection to NaaS CSP's network through public Internet**
+
+- It is recommended that NaaS CSP allows the CSC to connect to the NaaS CSP through the public Internet.
+
+## **10 Security considerations**
+
+Security aspects for consideration within cloud computing environments, including NaaS, are addressed by security challenges for the CSPs, as described in [ITU-T X.1601]. In particular, [ITU-T X.1601] analyses security threats and challenges, and describes security capabilities that could mitigate these threats and meet security challenges.
+
+## **Appendix I**
+
+## **Development methodology of NaaS functional requirements and architecture**
+
+(This appendix does not form an integral part of this Recommendation.)
+
+Considering the standardization methodology and conventional study sequence, the abstractions of functional entities and their mutual interactions are based on the functional requirements and the corresponding use cases analysis, which form a standardization body together. Therefore, it is required to progress NaaS functional requirements and architecture according to the following steps and priorities.
+
+Step 1: Use cases and functional requirements of NaaS which are included in Appendix II and clauses 7-9, respectively, of this Recommendation. Note that all the functional requirements are derived from the corresponding use cases.
+
+Step 2: Functional architecture of NaaS should be based on this Recommendation.
+
+Additionally, the general requirements of NaaS are described in [ITU-T Y.3501].
+
+## Appendix II
+
+## Use cases of NaaS
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix includes three types of NaaS use cases: NaaS application related use cases, NaaS platform related use cases and NaaS connectivity related use cases. Each type of NaaS use case is further divided into general and detailed use cases.
+
+### II.1 Use case template
+
+The use cases developed in Appendix II should adopt the following unified format for consistent readability and convenient material organization.
+
+| | |
+|----------------------------|--------------------------------------------------------------------------------------------------------------|
+| Title | Title of the use case |
+| Description | Scenario description of the use case |
+| Roles | Roles involved in the use case |
+| Figure (optional) | Figure to explain the use case, but is not mandatory |
+| Pre-conditions (optional) | The necessary pre-conditions that should be achieved before starting the use case. |
+| Post-conditions (optional) | The post-condition that will be carried out after the termination of current use case. |
+| Derived requirements | Requirements derived from the use cases, whose detailed descriptions are presented in the dedicated clauses. |
+
+### II.2 NaaS applications related use cases
+
+This clause provides description of use cases related where NaaS CSC can provision and use network applications.
+
+NOTE – In the following clauses, XaaS represents any categories of cloud services such as Software as a Service (SaaS), Platform as a Service (PaaS), IaaS, CaaS, etc.
+
+#### II.2.1 General use cases
+
+##### II.2.1.1 General NaaS application use case
+
+| | |
+|-------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Name | General NaaS application use case |
+| Description | A XaaS CSC or XaaS CSP uses the network applications (e.g., virtual DPI (vDPI), vFW, vCDN) provided by NaaS CSP. These network applications can be chained by NaaS CSP. |
+| Roles | CSC, CSP |
+
+| | |
+|----------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure | Image: Diagram illustrating NaaS application use case for application provision. It shows a central cloud labeled 'CSP NaaS' containing a vCDN, vFW, and vRouter. This central cloud is connected to three external clouds: 'CSC A' (containing a vDPI), 'CSP X XaaS' (containing a server icon), and 'CSP Y XaaS' (containing a server icon). Arrows indicate connectivity between these components. A legend below the diagram identifies the icons: vDPI (server icon), vFW (firewall icon), vRouter (router icon), and vCDN (cloud icon). The reference 'Y.3512(14)_F11.2.1.1' is noted at the bottom right of the diagram area.
Y.3512(14)_F11.2.1.1
NOTE – Virtual router (vRouter) can also be applicable to NaaS connectivity.
|
+| Pre-conditions (optional) | - – There is connectivity between XaaS CSC A and XaaS CSP Y.
- – There is connectivity between XaaS CSP X and XaaS CSP Y.
- – Either the XaaS CSP or the CSC requests a network application (vFW, vCDN, vDPI, vRouter etc. ) to be chained with the connectivity.
|
+| Post-conditions (optional) | - – NaaS CSP offers network applications for the XaaS CSC/CSP over existing network connectivity.
|
+| Derived requirements | - – On-demand virtual network application
- – Scalable network application
- – Chain of network applications
- – QoS-guaranteed applications
- – Secure network applications
- – Resilient network applications
- – Multiple IP addresses (refer to clause 7.4)
NOTE – The first six requirements belong to general requirements of NaaS which are provided in [ITU-T Y.3501].
|
+
+##### II.2.1.2 NaaS application use case for application provision
+
+| | |
+|-------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS application use case for application provision |
+| Description | Assume that company CSC-B looks for NaaS application services to benefit from key characteristics of the cloud computing services. As an example, the company wants to accelerate network traffic saturated with business applications. Wide area network (WAN) optimization is very crucial for the success of its business applications. CSC-B wants usage-based deployment of WAN optimizations and flexible feature support on-demand. Traditional WAN optimization appliance devices cannot fulfil those requirements, in particular, in terms of total cost of ownership and deployment elasticity.
NaaS CSP needs to provide virtual WAN acceleration solution to CSC-B, coping with its dynamic business needs.
|
+| Roles | CSP, CSC |
+
+| | |
+|----------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional) |
The diagram illustrates a NaaS provider architecture. At the top, a blue oval labeled 'NaaS provider' contains a red-bordered box labeled 'Application capabilities type service (e.g., virtualized WAN optimization controllers)'. Below this, a large purple cloud represents the service layer. Yellow lines connect the NaaS provider to several client groups, each enclosed in an orange cloud: 'CSC-B business client' (people at computers), 'CSC-B data centre' (server racks), 'CSC-B branch office' (people at computers), 'CSC-B mobile users' (people with mobile devices), and 'Company (CSC-B) HQ' (server racks and a building). The text 'Y.3512(14)_FII.2.1.2' is located in the bottom right corner of the diagram area.
|
+| Pre-conditions (optional) | CSC-B needs to accelerate network traffic saturated with business applications. |
+| Post-conditions (optional) | CSC-B used virtual WAN acceleration solution provided by NaaS CSP to satisfy the dynamic business needs. |
+| Derived requirements | - – On-demand self-service
- – Multi-tenancy
- – Resource pooling
- – Rapid elasticity and scalability
- – Measured service
- – Performance assurance and monitoring
- – Co-existence and compatibility with CSC's legacy network equipment
- – Interoperability support for management and orchestration
- – Security and resilience
- – Performance (refer to clause 7.1)
- – Operation and management (refer to clause 7.2)
NOTE – The first nine requirements belong to general requirements of NaaS which are provided in [ITU-T Y.3501].
|
+
+#### II.2.2 Detailed use cases
+
+##### II.2.2.1 NaaS platform use case for cloud CDN
+
+| | |
+|----------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS platform use case for cloud content delivery network (CDN) |
+| Description | Content provider acting as CSC stores the content in the data centre and monitors the usage of the content. When the usage of the content reaches certain level of popularity or if according to some predictions content provider expects a growth of popularity in a defined period of time, e.g., video transmission of a sport event, content provider creates a virtual CDN to temporarily move the content from the data centre to the network (vCDN). XaaS CSP receives the content from the content provider (which can itself create a distribution service). Content is delivered to the cloud service users (CSUs) from XaaS CSP data centre using the network of NaaS CSP. The XaaS CSP offers the possibilities to store the content and to monitor usage parameters. XaaS CSP in cooperation with the NaaS CSP can duplicate the content in the network nodes, building a virtual CDN service. Basically XaaS CSP supports CDN functions, thus CDN is in some way "emulated" by the XaaS CSP, which cooperates with the NaaS CSP. |
+| Roles | CSU, CSC, CSP |
+| Figure (optional) | Image: Diagram illustrating the NaaS platform use case for cloud content delivery network (CDN). The diagram shows a network topology where Content Service Users (CSUs) connect to a Content Service Center (CSC) via a Network as a Service (NaaS) Cloud Service Provider (CSP). The NaaS CSP provides a virtual Content Delivery Network (vCDN) service. The XaaS CSP (Cloud Service Provider) receives content from the Content Provider (CSP) and delivers it to the CSUs through the vCDN. The diagram includes labels for CSC, NaaS CSP, XaaS CSP, CSP (content provider), CSU #1, CSU #2, vCDN, CSP services, and Content services. A reference Y.3512(14)_F11.2.2.1 is also present.
|
+| Pre-conditions (optional) | - Content provider acting as CSC stores the content in XaaS CSP data centres.
- Content provider acting as CSC monitors the use of content.
|
+| Post-conditions (optional) | - XaaS CSP offers the virtual CDN service using network resources of the NaaS CSP.
- Content provider acting as CSC decides to move content from the data centre to the virtual CDN for a defined period of time.
|
+| Derived requirements | - Performance (refer to clause 7.1)
- Operation and management (refer to clause 7.2)
- Service chain (refer to clause 7.3)
|
+
+### II.3 NaaS platform related use cases
+
+#### II.3.1 General use cases
+
+None.
+
+#### II.3.2 Detailed use cases
+
+##### II.3.2.1 NaaS platform use case for service chain
+
+| | |
+|-------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS platform use case for service chain |
+| Description | With CSC's tenants increasing requirements on the service diversity and complexity, CSP needs to deliver integrated network application services, such as deep packet inspection (DPI), intrusion detection, intrusion prevention, load balance, firewall, etc. Traditionally, the set of services are provided using dedicated physical network elements, which have limited network capacity and functionalities, complex configuration and update, and lengthy provision period. The situation, when the output of one service is used as input for the other service is called service chain. In traditional network the set-up of services chain, e.g., chain composed of intrusion protection |
+
+| | |
+|----------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | system (IPS), load balancer and DPI, needs dedicated configuration and is not flexible in case of e.g., growth of traffic, adding/removing services to/from the chain.
For the better service flexibility, it is recommended for NaaS CSP to provide programmable NaaS platform, on which NaaS applications such as vRouter, vCDN, vEPC, etc. can be deployed, in order to steer the CSC's traffic via customized NaaS applications sequence.
|
+| Roles | CSC (Tenant A, Tenant B), CSP |
+| Figure (optional) | Image: Diagram illustrating NaaS platform use case for platform provision. It shows two CSP data centres, each containing virtualized resources for Tenant A and Tenant B. Tenant A's resources include a VM and a routing instance. Tenant B's resources include a VM and a routing instance. A central NaaS CSP block contains five services (a, b, c, d, e) connected in a chain. Solid blue arrows represent Tenant A's network service chain, and dashed blue arrows represent Tenant B's network service chain. The diagram shows how traffic from both tenants is steered through the NaaS services.
Y.3512(14)_FII.3.2.1
|
+| Pre-conditions (optional) | - – CSP can deliver dedicated physical network appliances solutions for services, such as DPI, intrusion detection, intrusion prevention, load balance, firewall, etc.
|
+| Post-conditions (optional) | - – CSP can provide composed either virtual or physical network services or both, or services chains dynamically and flexibly according to the CSC's specific service logic in a shorter deployment, configuration, and update intervals, compared with dedicated physical network appliances solution.
|
+| Derived requirements | - – Programmable NaaS platform (refer to clause 8.1)
- – Dynamic and flexible network services composition and steering (refer to clause 8.2)
- – Isolation of service chains for tenants (refer to clause 8.3)
|
+
+##### II.3.2.2 NaaS platform use case for platform provision
+
+| | |
+|-------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS platform use case for platform provision |
+| Description | CSC-A is a network operator. CSC-A wants to build advanced traffic analysis system and multi-dimensional reporting using dynamically scaling DPI functionalities, opportunistic services at low risk, and in short time of implementation, multi-tenant CDN, etc., in mobile networks. However, classical proprietary hardware-based network appliances inhibit the rapid roll out of new converged network functionalities and revenue earning services. They neither scale on-demand nor are flexible enough.
CSC-A has the possibility to cope with its business innovation needs by developing necessary features and services using NaaS platform. Innovating using NaaS platform allows it to utilize CSP network services and combine them with the functionalities developed by CSC-A. All functionalities can be integrated by CSC-A on the basis of NaaS platform to build enhanced network services e.g., virtualized evolved packet core (EPC), software-based DPI platform, integrated development environments (IDEs). The capacity of NaaS platform needs to scale elastically according to the utilization of enhanced network services to secure the required performance. Solutions to support
|
+
+| | |
+|----------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | integration of the CSP network services with the CSC-A's developed software are also needed. |
+| Roles | CSP, CSC |
+| Figure (optional) | Image: Diagram illustrating the NaaS provider architecture. A purple oval labeled 'NaaS provider' contains a person at a desk and a list of software types: 'Independent vender supplied SW', 'CSC-A developed SW', and 'Open source SW'. Below this, a yellow circle with an upward arrow points to a box labeled 'Platform capabilities type service (e.g., virtualized EPC platform, DPI tool, IDE)'. This box sits above a blue cloud labeled 'Non-cloud network provider (CSC-A) network'. Inside this cloud are icons for 'Network appliances', 'OSS/BSS etc.', and 'New NW functionalities developed and integrated by CSC-A'. The diagram is labeled 'Y.3512(14)_FII.3.2.2' at the bottom right.
|
+| Pre-conditions (optional) | CSC-A needs to build enhanced network services using dedicated hardware equipment for each functionality and manage the whole network. |
+| Post-conditions (optional) | CSC-A used NaaS platform to combine CSP network services with self-developed functionalities and integrate them into enhanced network services. |
+| Derived requirement | - – Flexible scaling of NaaS platform (refer to clause 8.4)
- – Integration of software applications (refer to clause 8.5)
|
+
+### II.4 NaaS connectivity related use cases
+
+This clause provides description of use cases where NaaS CSC can provision and use network connectivity.
+
+#### II.4.1 General use cases
+
+##### II.4.1.1 General NaaS connectivity use case
+
+NOTE – The following use case is based on a use case provided in [ITU-T Y.3501].
+
+| | |
+|-------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Name | General NaaS connectivity use case |
+| Description | A NaaS CSP sets up, maintains and releases the network connectivity between CSCs and between the CSP and the CSC as a cloud service. This can include on-demand and semi-permanent connectivity. |
+| Roles | CSC, CSP |
+
+| | |
+|----------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure | Image: Diagram showing XaaS CSP X, XaaS CSP Y, and XaaS CSC A connected via NaaS CSP Connectivity.
The diagram illustrates a network topology where XaaS CSP X and XaaS CSP Y are connected to XaaS CSC A through a central NaaS CSP Connectivity hub. XaaS CSP X is represented by a blue oval at the top, XaaS CSP Y by a blue oval at the bottom right, and XaaS CSC A by a green oval on the left. A red oval labeled 'NaaS CSP Connectivity' is positioned in the center. Arrows indicate bidirectional communication between XaaS CSP X and the NaaS CSP Connectivity hub, and between XaaS CSP Y and the NaaS CSP Connectivity hub. A single arrow points from the NaaS CSP Connectivity hub to XaaS CSC A. The text 'Y.3512(14)_Fll.4.1.1' is located at the bottom right of the diagram area.
|
+| Pre-conditions (optional) | - – There is no connectivity between XaaS CSC A and XaaS CSP Y.
- – There is no connectivity between XaaS CSP X and XaaS CSP Y.
- – Either XaaS CSC A or XaaS CSP Y requests the connectivity between them with their end-point identifiers and associated characteristics (referring to QoS and security aspects) for the connectivity.
- – Either XaaS CSP X or XaaS CSP Y requests the connectivity between them with their end-point identifiers and associated characteristics (referring to QoS and security aspects) for the connectivity.
|
+| Post-conditions (optional) | - – XaaS CSC A and XaaS CSP Y can communicate with each other.
- – XaaS CSP X and XaaS CSP Y can communicate with each other.
|
+| Requirements | - – On-demand network configuration
- – Heterogeneous networks compatibility
- – QoS-guaranteed connectivity
- – Secured connectivity
- – Common control mechanism for NaaS connectivity (refer to clause 9.1)
NOTE – The first 4 requirements belong to general requirements of NaaS which are provided in [ITU-T Y.3501].
|
+
+#### II.4.2 Detailed use cases
+
+##### II.4.2.1 NaaS connectivity use case for dynamic transport network
+
+| | |
+|---------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS connectivity use case for dynamic transport network |
+| Description | CSC demands a geographically distributed connectivity service and dynamic traffic capacity which can accommodate cloud bursting (e.g., VM migration or the transfer of large data files across data centres which sit in different places) which brings a surge of traffic passing through the backbone of the CSP.
IP and transport networks of the CSP are separately managed and therefore cannot provide the common control mechanism for dynamic bandwidth adjustment. In order to guarantee the service continuity and consistent SLA to the CSC, such CSP would have to offer over-provisioning of links, most of which being not used effectively and thus causing resource waste.
The CSP is recommended to cope with the surge of transit traffic which traverses its backbone without making use of traditional over-provisioning approaches of the networking resources.
|
+| Roles | CSC, CSP |
+| Figure (optional) | |
+| Pre-conditions (optional) | |
+
+| | |
+|----------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Post-conditions (optional) | |
+| Derived requirements | - – Unified SLA for multiple optimized networks (refer to clause 9.2)
- – Leveraging transport networks dynamically (refer to clause 9.3)
- – Unified network control mechanism (refer to clause 9.4)
|
+
+##### II.4.2.2 NaaS connectivity use case for flexible and extended VPN
+
+| | |
+|---------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS connectivity use case for flexible and extended VPN |
+| Description | The different VPN sites are connected via BGP/MPLS IPVPN. The processing resources and the corresponding subnet are migrated from the CSC's data centre to the CSP's data centre, which is not yet involved in the VPN as a VPN site. In order to add this new site in the existing VPN, there is a need to provision a new subnet in the CSP's data centre and to set up a new virtual routing and forwarding (VRF) in its edge router. The migration of the corresponding subnet from the CSC's data centre to the CSP's data centre and the subnet removal from the CSC's data centre needs to be announced to the remaining edge routers. The concrete procedure is shown in the following figure.
- 1. Processing resources and the corresponding subnet migrate from the CSC's data centre to the CSP's data centre.
- 2. New VRF is configured in the edge router of the CSP's data centre.
- 3. The removal of the CSC's subnet is announced through MP-BGP update to all VPN sites.
- 4. CSP's new subnet is announced through MP-BGP update to all VPN sites.
Service continuity needs to be ensured during the whole migration and reconfiguration procedure. However, the existing VPN is a black box from the CSC's perspective, and as such it can't be provisioned and reconfigured by the CSC. In addition, the current VPN technology cannot support the dynamic addition and reduction of the VPN sites and bandwidth capacity.
|
+| Roles | CSC, CSP |
+| Figure (optional) | Image: Diagram illustrating the NaaS connectivity use case for flexible and extended VPN. The diagram shows three VPN sites (each with a server and a router) connected to a central VPN cloud. The CSP's data centre is shown as a new site being added to the VPN. The diagram is annotated with numbered steps: 1. Resource migration from CSC's data centre to CSP's data centre; 2. New VRF configuration in the CSP's edge router; 3. MP-BGP update to all VPN sites; 4. MP-BGP update to all VPN sites. The diagram is labeled Y.3512(14)_FII.4.2.2.
① Resource migration ② New VRF ③ MP-BGP update ④ MP-BGP update
|
+| Pre-conditions (optional) | |
+
+| | |
+|----------------------------|---------------------------------------------------------|
+| Post-conditions (optional) | |
+| Derived requirements | – Elastic network reconfiguration (refer to clause 9.5) |
+
+##### II.4.2.3 NaaS connectivity use case for BoD service
+
+| | |
+|----------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS connectivity use case for BoD service |
+| Description | In this scenario CSU access to cloud computing service offered by XaaS CSP is considered (e.g., virtual desktop infrastructure (VDI), video streaming). CSU accesses the service from a fixed location e.g., using a company local area network (LAN) or from mobile location e.g., mobile terminal. The XaaS CSP serves the services on the basis of own data centres and has no impact on the performance of particular connectivity between end users and the data centre where the service is hosted. From the perspective of CSU, quality of experience (QoE) of the service is dependent on a combination of data centre and network performance. The XaaS CSP is able to guarantee certain service quality limited to its own data centre. This quality could be downgraded on network performance on the connection between CSC and particular data centre. The XaaS CSP acting alone is not able to impact network performance without interaction with NaaS CSP.
As a solution to guarantee end-to-end service quality, bandwidth reservations can be applied in the network between the CSU and the data centre. This allows the guarantee of certain network performance and can be a basis for end-to-end SLA contract for the service between a CSU and the XaaS CSP. To fulfil these needs, XaaS CSP interacts with NaaS CSP. NaaS CSP can be any actor that has the ability to offer connectivity between XaaS CSP and the CSC, to which CSU belongs.
|
+| Roles | CSC, CSC, CSP |
+| Figure (optional) | Image: Network diagram showing the NaaS connectivity use case for BoD service. The diagram is divided into three sections: CSC, NaaS CSP, and XaaS CSP. In the CSC section, two laptops labeled CSU #1 and CSU #2 are connected to a central blue router. In the NaaS CSP section, there is a mesh of blue routers. A red line connects the central router in CSC to a router in NaaS CSP, representing the BoD service (bandwidth reservation and provisioning). Black lines represent non-BoD services (network traffic congestion). In the XaaS CSP section, a server icon labeled 'CSP services' is connected to a router in NaaS CSP by a red line. A legend at the bottom indicates that red lines are for BoD service and black lines are for non-BoD service. The reference Y.3512(14)_F11.4.2.3 is at the bottom right.
Y.3512(14)_F11.4.2.3
|
+| Pre-conditions (optional) | – XaaS CSP has no impact on connectivity parameters between the service and the CSU. |
+| Post-conditions (optional) | – XaaS CSP offers end-to-end service quality or SLA to the CSC, on the basis of cooperation with NaaS CSP. |
+| Derived requirements | - – Seamless and end-to-end solution of bandwidth allocation (refer to clause 9.6)
- – Symmetric or asymmetric capacity (refer to clause 9.7)
|
+
+##### II.4.2.4 NaaS connectivity use case for optimized traffic engineering
+
+| | |
+|----------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS connectivity use case for optimized traffic engineering |
+| Description | The CSP provides network connectivity services to a CSC in order for the CSC to inter-connect its own multiple geographically distributed data centres. With the increase of cloud services deployed over the CSC's data centres, more and more traffic, e.g., for data mirroring, redundancy, database synchronization, VM migration, active-active storage replication, is traversing the CSP's backbone network due to the CSC's increasing distributed services.
Currently, CSP typically provides the CSC with static connectivity services resulting in either over-provisioned, under-utilized service capacity or under-provisioned, capacity-capped services.
In order to make a more efficient use of its connectivity resources, a solution for the CSP is to support a central decision-making function for the backbone traffic engineering. At the minimum, such solution has to coexist with other legacy network solutions used by the CSP for the support of other services.
|
+| Roles | CSC, CSP |
+| Figure (optional) | Image: Network diagram showing a centralized traffic engineering solution for a CSP's backbone network connecting multiple CSC data centres.
The diagram illustrates a network architecture for optimized traffic engineering. At the top center, a green box labeled 'Centralized traffic engineering' is connected via dashed orange lines to several network devices. These devices are part of the 'CSP's backbone network', which is represented by a cloud. The backbone network includes 'CSP's backbone edge devices' (blue circular icons with four ports) and 'CSP's backbone core/aggregation devices' (grey square icons with a cross). Three 'CSC's data centre' clusters (each containing server racks and a database icon) are connected to the backbone network. The data centres are distributed geographically. A legend at the bottom identifies the icons: a blue circle for 'CSP's backbone edge device' and a grey square for 'CSP's backbone core/aggregation device'. The text 'Y.3512(14)_FII.4.2.4' is visible in the bottom right corner of the diagram area.
|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements | - – Optimized and fine-grained traffic engineering (refer to clause 9.8)
- – Coexistence with legacy network services and functions (refer to clause 9.9)
- – Centralized control view and abstraction view of resources (refer to clause 9.10)
|
+
+##### II.4.2.5 NaaS connectivity use case for performance on demand
+
+| | |
+|----------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS connectivity use case for performance on demand |
+| Description | CSC requests CSP to provide on-demand network performance (such as bandwidth quantities, maximum latencies and other QoS parameters), which includes dynamic establishment, change and resized capacity of links. However, traditional solution based on human intervention lacks automation capabilities which make it difficult to deliver self-provisioned services and respond to time-sensitive changes in network performance requirements. Additionally, frequent changes sometimes result in congestion and instability because traffic, which comes from multiple sources, shares the same network link.
CSP provides CSC the appropriate control in order to request services through a portal and to shield the underlying physical network to the CSC.
|
+| Roles | CSC, CSP |
+| Figure (optional) | Image: Diagram illustrating the NaaS connectivity use case for performance on demand. A Customer Service Center (CSC) is shown on the left, connected to a CSP's backbone network. The CSP's backbone network consists of edge devices and core/aggregation devices. A 'Performance on-demand' box is connected to the core devices. The network is also connected to CSC's data centre and the Internet. A legend identifies the CSP's backbone edge device and core/aggregation device.
The diagram shows a Customer Service Center (CSC) on the left, represented by a person at a computer. It is connected to a CSP's backbone network. The backbone network includes several edge devices (represented by blue routers) and core/aggregation devices (represented by grey boxes with a 'V' symbol). A green box labeled 'Performance on-demand' is connected to the core devices via dashed orange lines. The backbone network is also connected to CSC's data centre (represented by server racks) and the Internet (represented by a cloud). A legend at the bottom identifies the CSP's backbone edge device and core/aggregation device. The reference Y.3512(14)_FII.4.2.5 is noted at the bottom right.
|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements | - – Centralized control view and abstraction view of resources (refer to clause 9.10)
- – CSC limited control of services (refer to clause 9.11)
|
+
+##### II.4.2.6 NaaS connectivity use case for virtual router
+
+| | |
+|-------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS connectivity use case for virtual router |
+| Description | According to [ITU-T Y.3500], multi-tenancy is a key characteristic of the cloud service, which requires the CSP to provide the CSC either shared physical or virtual resources or both, such that multiple tenants and their resources and data are isolated from and inaccessible to each other. These tenants share the same underlay physical resources, including physical servers, physical storage and physical networks and each tenant is assigned its own logical resources, including VMs, virtual storage and virtual networks. These logical resources need to be isolated from each other and the virtual compute, storage and network resources need to be integrated and matched in a fine granularity.
However, the legacy underlay physical routers and switches of CSP's transport network don't contain each tenant's state, including tenant's medium access control (MAC) and IP addresses and the network policies attached to the VM that belongs to the tenant. In other words, the forwarding tables of the underlay physical routers and switches only contain the IP prefixes or MAC addresses of the physical servers.
|
+
+| | |
+|----------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | The virtual router is software implemented router and can be implemented within the virtualization infrastructure. The virtual router provides connectivity among virtual machines, virtual switches, etc., and contains per tenant state and a separate forwarding table for a virtual network. The forwarding table includes the IP prefixes (in the case of a layer 3 overlay network) or the MAC addresses (in the case of a layer 2 overlay network) of VMs. In addition, no single virtual router needs to contain all IP prefixes or all MAC addresses for all virtual machines in the CSP's data centre. A given virtual router only needs to contain those routing instances that are locally installed on the same server.
|
+| Roles | CSC, CSP |
+| Figure (optional) | Image: Diagram illustrating NaaS connectivity use case for private IP addresses and VPNs. It shows two CSP data centres connected via a central transport network. Each data centre contains virtualized resources (VMs) connected to a virtual router, which is connected to a gateway router. The gateway routers are connected to the transport network, which includes an overlay network. The diagram uses different line styles to represent physical and virtual networks for different tenants.
Y.3512(14)_F11.4.2.6
|
+| Pre-conditions (optional) | - – CSP's IP carrier network support overlay network mechanism.
|
+| Post-conditions (optional) | - – CSC's VMs that run in different CSP's data centres can communicate with each other.
|
+| Derived requirements | - – Logically isolated network partition (refer to clause 9.12)
- – Overlay network mechanism (refer to clause 9.13)
|
+
+##### II.4.2.7 NaaS connectivity use case for private IP addresses and VPNs
+
+| | |
+|-------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | NaaS connectivity use case for private IP addresses and VPNs |
+| Description | Case I: Public cloud site multi-tenant VPN gateway (GW) with overlapping private IP addresses
Multi-tenant VPN GW in a public cloud site is shared by CSC-I-A and CSC-I-B. Both of them are interested to use the same private IP address pool for their end points. Both of CSCs are connected to the public cloud VPN GW through a given public IP address of it. The cloud VPN GW should be able to switch the traffic from each CSC to a proper subnet.
Case II: Interworking support for different types of VPNs
CSC-II has site-to-site proprietary MPLS-VPN connection between its headquarter (HQ) and private data centre. According to the company progress, CSC-II is interested to establish new site-to-site and site-to-client secure VPN connections (e.g., IP security (IPsec) VPN and secure socket layer (SSL) VPN). New VPN connections are planned between their globally distributed branch offices and mobile users, while keeping the CSC-II existing VPN investments. NaaS CSP should be able to provide interworking between the CSC owned existing VPN and different types of new VPNs.
|
+
+| | |
+|-------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | Case III: On-demand network support for the distributed end points
CSC-III requires a solution of delivering reliable, predictable and on-demand network connections for all their locations. This service should be able to be changed dynamically according to the CSC-III's needs. The CSC-III is interested in elastic request parameters for connectivity to their location over the existing links. The connectivity should be established to one or more of the NaaS CSP's points of presence (PoPs) with minimum efforts for deploying additional equipment.
|
+| Roles | CSP, CSC |
+| Figure (optional) | Image: Figure 1: Case I: Public Cloud site multi-tenant VPN GW with overlapping private IP addresses. The diagram shows a central 'NaaS Public IP address space' cloud. On the left, 'CSC-I-A' has an enterprise HQ, a branch office, and a remote office, all with private IP subnets (10.1.x.x/16 or 10.1.1.x/24). A 'Mobile network' connects to a 'CSC-I-A mobile user'. On the right, a 'Public cloud data centre' contains 'CSC-I-A's resources' and 'CSC-I-B's resources', both with private IP subnets (10.1.x.x/16). A 'Multi-tenant VPN GW' (100.1.1.1) is connected to the NaaS cloud. Various gateways (GW) are shown at the edges of the NaaS cloud and connecting to the external networks.
Figure 1 – Case I: Public Cloud site multi-tenant VPN GW with overlapping private IP addresses
Image: Figure 2: Case II: Interworking support for different types of VPNs. The diagram is divided into 'Site-to-site' and 'Site-to-client' sections. In the 'Site-to-site' section, 'CSC-II enterprise HQ' and 'CSC-II private data centre' are connected via a 'Proprietary MPLS-VPN' using 'CE' and 'PE' routers. In the 'Site-to-client' section, a 'NaaS' cloud is connected to 'CSC-II new branch office', 'CSC-II new mobile user', and 'CSC-II new remote office'. The NaaS cloud is connected to the MPLS-VPN via 'IPSec to MPLS interworking' and 'SSL to MPLS interworking' gateways (GW). A 'Mobile network' is also shown. A legend indicates 'SSL VPN' in pink and 'IPSec VPN' in cyan.
Figure 2 – Case II: Interworking support for different types of VPNs
|
+
+
+
+Figure 3 – Case III: On-demand network support for the distributed end points. The diagram illustrates a network architecture where a central NaaS (Network as a Service) cloud connects various distributed endpoints. At the top, 'CSC-III enterprise HQ' is connected to a 'GW' (Gateway) which links to the NaaS cloud. On the left, 'CSC-III branch office' and 'CSC-III remote office' are connected to their own 'GW' units, which also link to the NaaS cloud. On the right, another 'CSC-III branch office' is connected to the NaaS cloud. A 'Mobile network' is shown at the bottom, with a 'CSC-III mobile user' (represented by a mobile phone) connected to it. Red lines indicate the network paths connecting all these elements through the central NaaS cloud. A small reference code 'Y.3512(14)\_F11.4.2.7c' is visible in the bottom right corner of the diagram area.
+
+**Figure 3 – Case III: On-demand network support for the distributed end points**
+
+| | |
+|----------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Pre-conditions (optional) | It is assumed that multi-tenant VPN GW in public cloud site is provided by the NaaS CSP. |
+| Post-conditions (optional) | |
+| Derived requirement | - – Overlapped private IP addresses (refer to clause 9.14)
- – Interworking among different VPN solutions (refer to clause 9.15)
- – VPN connection in mobile environment (refer to clause 9.16)
- – Connection to NaaS CSP's network through public Internet (refer to clause 9.17)
|
+
+## Appendix III
+
+## Considerations on CSP's network related activities
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix provides considerations on CSP's network related activities.
+
+Each individual service of the NaaS category can be specified by a set of terms including:
+
+- Service interface – It is offered to the CSC and defines the functionality which is implemented by the CSP. Service interface can include functionality related to demarcation points for the interconnection of the CSP and the CSC, topology and route related functionality to share topologies, discovery related functionality to perform other services needed by inter-cloud related activities, and other functionalities related to monitoring, protection, verification, etc. Route related functionality requires information on ingress and egress end points and optionally intermediate points of a network segment. Attributes of a network segment can include edge point attributes, QoS parameters, performance attributes, time attributes, user attributes, service requester identifier, etc.
+- Service demarcation point – This is a boundary point between NaaS CSP and NaaS CSC. It is used as a reference point to identify the responsibilities and obligations of all involved entities. For IP/MPLS networks, the demarcation point user-to-network interface (UNI) is a pair of customer edge and provider edge. For other transport networks, UNI and network-to-network interface (NNI) are defined as demarcation points. For example, UNI defined by Metro Ethernet Forum (MEF) is physically implemented over a bi-directional Ethernet link that provides the various data, control and management plane capabilities required by the metro Ethernet network (MEN) service provider to clearly demarcate the two different network domains involved in the operational, administrative, maintenance and provisioning aspects of the service. Often software abstraction layer (SAL) or network operating system (NOS) is used for the demarcation point for network platforms, and TCP/UDP sockets for network applications.
+- Service capabilities – This is what NaaS delivers to the CSC via service interfaces as network connectivity and networking related service capabilities. While transport network connectivity capabilities include IP/MPLS network, transmission networks, IP multimedia subsystem (IMS), software defined networking (SDN) and CDN, virtual network connectivity capabilities include pseudo-wire, virtual private LAN service (VPLS), L3 VPN and VLAN. Networking related service capabilities can include WAN optimization, load balancing, domain name system (DNS), firewall, IPS/IDS, telecommunication services and network applications such as peer-to-peer (P2P) based file transfer, etc.
+
+Although infrastructure capability type NaaS can provide such network as a whole, a CSC relies on CSP for the integration and customizing of software, reconfiguring and expanding functionalities of network elements, as well as management and administration of the network. When CSC leverages NaaS platforms to build its own network, the responsibility of CSP is up to the service demarcation point of the platform. CSC is responsible for managing, administering and operating the network as well as network functions and services implemented up on the demarcation point.
+
+The composite services provisioned in cloud environments need SLA support in the following areas [b-EC SLA]:
+
+- SLA specifications capturing the dependencies and interactions between the services. The dependencies should be parametric and express the overall service context (e.g., data movements, relationships between providers, orchestration rules).
+- Convergence in SLA management to handle dependencies (e.g., joint management) while retaining the autonomy in resource management for each provider.
+
+Enhanced SLA specification and management approaches should take into consideration that composition may be performed as either centralized (e.g., an entity managing the composition and the corresponding service offerings) or distributed (e.g., achieved through consecutive SLA establishments) approaches. SLA specifications in cross-service scenarios should either include the common terms (limiting however end-to-end quality provision to these terms) or be implemented through links between SLAs (e.g., one SLA for each service with enriched specification to include links to the SLAs of other services), as a protocol to enable interaction between different layers and entities.
+
+SLAs identify, in a clear and precise way, the responsibilities and obligations of all involved entities, as well as their boundaries and limits.
+
+NaaS can be used to support other cloud service CSP's network related activities (e.g., provide network connectivity, deliver network services and provide network management services), where a logically isolated CSC cloud in the CSP's data centre allows a CSC to provision a private, isolated partition of the cloud where the CSC can use cloud capabilities in a virtual network, often using CSC-defined IP address ranges. A CSC cloud can have multiple subnets in a data centre. Network connectivity between the remote CSC and CSC cloud, for example, may include the following:
+
+- IPsec VPN connection over public Internet (CSP edge VPN gateway – CSC premises VPN gateway);
+- Dedicated network connection over private lines (CSP edge VPN gateway – customer premises equipment (CPE));
+- IPsec VPN connection over private lines (CSP edge VPN gateway – CSC premises VPN gateway);
+- VPN connection with a software appliance over public Internet (software VPN appliance – CSP edge Internet gateway - CSC premises VPN gateway, where Internet gateway only routes VPN connection over public Internet);
+- Multi-protocol label switching (MPLS) VPN connections.
+
+Cloud services needs interconnecting multiple CSC clouds into a contiguous virtual network as well as to meet this requirement NaaS may provide followings:
+
+- Software VPN appliance based connections between CSC clouds for intra-cloud and inter-cloud (software VPN appliance at CSC cloud-1 – Internet gateway – Internet gateway – software VPN appliance at CSC cloud-2, where Internet gateway only routes VPN connection, over public Internet for inter-cloud case);
+- Software VPN appliance to physical VPN connection between CSC clouds (VPN gateway at CSC cloud-1 – Internet gateway – software VPN appliance at CSC cloud-2, where Internet gateway only routes VPN connection);
+- CSC managed CSC cloud-to-CSC cloud routing over physical IPsec VPN connections using CSC equipment and public Internet or private lines (VPN gateway at CSC cloud-1 – CSC equipment – VPN gateway at CSC cloud-2).
+
+## Bibliography
+
+- [b-IETF RFC 4364] IETF RFC 4364 (2006), *BGP/MPLS IP Virtual Private Networks (VPNs)*.
+- [b-EC SLA] European Commission Directorate General Communications Networks, Content and Technology Unit E2 – Software and Services, Cloud, (Brussels, June 2013), *Cloud Computing Service Level Agreements – Exploitation of Research Results*.
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|--------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | General tariff principles |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Terminals and subjective and objective assessment methods |
+| Series Q | Switching and signalling |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects and next-generation networks |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+I n t e r n a t i o n a l T e l e c o m m u n i c a t i o n U n i o n
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+# Y.3526
+
+(11/2021)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Cloud Computing
+
+# --- **Cloud computing – Functional requirements of edge cloud management**
+
+Recommendation ITU-T Y.3526
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Computing power networks | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+Y.3000–Y.3499
+
+### CLOUD COMPUTING
+
+Y.3500–Y.3599
+
+### BIG DATA
+
+Y.3600–Y.3799
+
+### QUANTUM KEY DISTRIBUTION NETWORKS
+
+Y.3800–Y.3999
+
+### INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|---------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+For further details, please refer to the list of ITU-T Recommendations.
+
+## Recommendation ITU-T Y.3526
+
+# Cloud computing – Functional requirements of edge cloud management
+
+## Summary
+
+Recommendation ITU-T Y.3526 provides requirements for edge cloud management. It presents an overview of edge cloud management including advantages of edge cloud management and the relationship with global management in a distributed cloud. It describes the edge cloud management local functions and mode. Additionally, this Recommendation provides edge cloud management functional requirements derived from use cases.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.3526 | 2021-11-06 | 13 | 11.1002/1000/14759 |
+
+## Keywords
+
+Distributed cloud, edge cloud, functional requirements, management mode.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2021
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|----|---------------------------------------------------------------------------------------------|-------------|
+| 1 | Scope..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 2 |
+| | 3.1 Terms defined elsewhere..... | 2 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 3 |
+| 5 | Conventions ..... | 3 |
+| 6 | Overview of edge cloud management ..... | 4 |
+| | 6.1 Challenges for management of distributed cloud..... | 4 |
+| | 6.2 Advantages of introducing edge cloud management..... | 5 |
+| | 6.3 Relationship of edge cloud management with edge node ..... | 5 |
+| | 6.4 Relationship of edge cloud management with global management in distributed cloud ..... | 6 |
+| 7 | Edge cloud management mode in configuration models..... | 7 |
+| | 7.1 Edge cloud management in configuration models of distributed cloud ..... | 7 |
+| | 7.2 Edge cloud management modes ..... | 8 |
+| 8 | Edge cloud local management functions ..... | 10 |
+| 9 | Functional requirements of edge cloud management ..... | 11 |
+| | 9.1 Resource requirements ..... | 11 |
+| | 9.2 Service requirements ..... | 12 |
+| 10 | Security considerations..... | 13 |
+| | Appendix I – Use case of edge cloud management in distributed cloud ..... | 14 |
+| | I.1 Use case template ..... | 14 |
+| | I.2 Service image management in distributed AI service deployment ..... | 14 |
+| | I.3 Alarm format management..... | 15 |
+| | I.4 Edge cloud service to a stationary CSC ..... | 16 |
+| | I.5 Edge cloud service seamlessly to mobile CSC..... | 18 |
+| | I.6 Edge cloud service offloading ..... | 21 |
+| | I.7 Edge cloud management as a service broker with microservices ..... | 22 |
+| | I.8 Remote management for edge nodes..... | 23 |
+| | I.9 Customized service management ..... | 24 |
+| | Bibliography..... | 26 |
+
+
+
+## Recommendation ITU-T Y.3526
+
+# Cloud computing – Functional requirements of edge cloud management
+
+# 1 Scope
+
+This Recommendation provides an overview and requirements of edge cloud management. It addresses the following subjects:
+
+- Overview of edge cloud management
+ - Challenges for management of a distributed cloud;
+ - Advantages of introducing edge cloud management;
+ - Relationships with edge cloud and edge node; and
+ - Relationships with global management in a distributed cloud.
+- Edge cloud management mode
+- Edge cloud local management functions
+- Functional requirements of edge cloud management
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- | | |
+|----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| [ITU-T J.1301] | Recommendation ITU-T J.1301 (2021), Specification of cloud-based converged media service to support Internet protocol and broadcast cable television – Requirements. |
+| [ITU-T X.1361] | Recommendation ITU-T X.1361 (2018), Security framework for the Internet of things based on the gateway model. |
+| [ITU-T X.1601] | Recommendation ITU-T X.1601 (2015), Security framework for cloud computing. |
+| [ITU-T X.1642] | Recommendation ITU-T X.1642 (2016), Guidelines for the operational security of cloud computing. |
+| [ITU-T Y.3500] | Recommendation ITU-T Y.3500 (2014), Cloud computing – Overview and vocabulary. |
+| [ITU-T Y.3502] | Recommendation ITU-T Y.3502 (2014), Information technology – Cloud computing – Reference architecture. |
+| [ITU-T Y.3508] | Recommendation ITU-T Y.3508 (2019), Cloud computing – Overview and high-level requirements of distributed cloud. |
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 cloud computing** [ITU-T Y.3500]: Paradigm for enabling network access to a scalable and elastic pool of shareable physical or virtual resources with self-service provisioning and administration on-demand.
+
+NOTE – Examples of resources include servers, operating systems, networks, software, applications, and storage equipment.
+
+**3.1.2 cloud service** [ITU-T Y.3500]: One or more capabilities offered via cloud computing invoked using a defined interface.
+
+**3.1.3 cloud service customer** [ITU-T Y.3500]: Party which is in a business relationship for the purpose of using cloud services.
+
+NOTE – A business relationship does not necessarily imply financial agreements.
+
+**3.1.4 cloud service provider** [ITU-T Y.3500]: Party which makes cloud services available.
+
+**3.1.5 core cloud** [ITU-T Y.3508]: A cloud computing, which manages resource pools including resources in the edge of the network and enables cloud service.
+
+NOTE – Enabled cloud service on the core cloud is provided by a cloud service provider (CSP).
+
+**3.1.6 distributed cloud** [ITU-T Y.3508]: Distribution of cloud capabilities types to the edge of the network for enabling cloud services with low latency and real time processing on limited bandwidth by interworking among pools of physical or virtual resources.
+
+**3.1.7 edge cloud** [ITU-T Y.3508]: A cloud computing deployed to the edge of the network accessed by cloud service customers (CSCs) with small capacity resources enabling cloud service.
+
+NOTE 1 – Enabled cloud service on the edge cloud is lightweight cloud service provided by a cloud service provider (CSP) depending on cloud service category.
+
+NOTE 2 – Lightweight cloud service refers to a portion of cloud service to reconfigure the functionality of cloud service to fit on edge cloud such as base station and gateway with small capacity resource.
+
+**3.1.8 regional cloud** [ITU-T Y.3508]: A cloud computing hosted from core cloud to particular geographical regions.
+
+NOTE – Enabled cloud service on the regional cloud is entire or partial cloud service of core cloud provided by a cloud service provider (CSP).
+
+**3.1.9 microservice** [ITU-T J.1301]: An architectural and organizational approach to software development where software is composed of small independent microservices that communicate over well-defined application programming interfaces. Microservices architecture makes applications easier to scale and faster to develop, enabling innovation and accelerating time-to-market for new features.
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 edge cloud management:** An efficient and effective way to provide management of resources, data, services, applications, operation and maintenance and risks of edge cloud.
+
+NOTE 1 – The scope of edge cloud management is within an edge cloud. Each edge cloud has one edge cloud management.
+
+NOTE 2 – Edge cloud management coordinates with global management and other edge cloud managements.
+
+**3.2.2 edge node:** Resource pool with limited computing, storage, network and other software and tools within one edge cloud.
+
+NOTE 1 – Each edge node belongs to only one edge cloud. Each edge cloud has at least one edge node.
+
+NOTE 2 – Edge node uses edge cloud management to expose its abilities and achieve coordination with other edge nodes.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-------|---------------------------------------------------------|
+| AI | Artificial Intelligence |
+| API | Application Programming Interface |
+| AR | Augmented Reality |
+| CC | Core Cloud |
+| CDN | Content Delivery Network |
+| CSC | Cloud Service Customer |
+| CSN | Cloud Service Partner |
+| CSP | Cloud Service Provider |
+| EC | Edge Cloud |
+| FCAPS | Fault, Configuration, Accounting, Performance, Security |
+| ICT | Information and Communication Technology |
+| IoT | Internet of Things |
+| ML | Machine Learning |
+| NFV | Network Function Virtualization |
+| NFVO | Network Function Virtualization Orchestrator |
+| RC | Regional Cloud |
+| SLA | Service Level Agreement |
+| VR | Virtual Reality |
+| V2X | Vehicle to Everything |
+
+# **5 Conventions**
+
+In this Recommendation:
+
+The keywords "**is required to**" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+
+The keywords "**is recommended**" indicate a requirement which is recommended but which is not absolutely required. Thus this requirement need not be present to claim conformance.
+
+# 6 Overview of edge cloud management
+
+## 6.1 Challenges for management of distributed cloud
+
+Services in Internet of things (IoT), augmented reality/virtual reality (AR/VR), artificial intelligence (AI) and 5G application domains, which require low network latency between a cloud service provider (CSP) and cloud service customer (CSC) and wide bandwidth, need a new cloud computing concept of distributed cloud, which is the distribution of cloud capabilities types to the edge of the network for enabling cloud service with low latency and real-time processing on limited bandwidth by interworking among pool of physical or virtualized resources [ITU-T Y.3508].
+
+According to the concept and structure of distributed cloud, refer to Figure 6-1 of [ITU-T Y.3508], global management in core cloud (CC) provides cloud resource management for distributed cloud, which mainly refers to CC, regional cloud (RC) and edge cloud (EC). However, as 5G and edge computing technologies are widely used on the edge side, the number and type of ECs will increase remarkably. Using global management alone to manage distributed cloud with a large amount of ECs will face the following challenges:
+
+- **Heavy operation and management burden:** With the rapid growth of the number of ECs, global management will handle a huge amount of fault, configuration, accounting, performance and security (FCAPS) data coming from the distributed cloud system. Processing all those data will place a heavy burden on global management. The transmission of FCAPS data from ECs to a centralized global management will occupy a wide bandwidth of the transmission network.
+- **Edge autonomy management:** Global management has difficulty in maintaining autonomy management on the edge side. Firstly, ECs are far away from global management, which might lead to insecure and inefficient operation and management if ECs lose connection with centralized global management. Secondly, EC services have regional characteristics. Different areas might have diversified edge services, not all services need to be controlled by global management, e.g., some IoT or some local vertical industry services. Global management cannot achieve the flexibility and efficiency of edge autonomy management in location-based edge services.
+- **Heterogeneous edge resources:** EC resources have two major types: One is a general type which carries edge services that have general resource requirements such as vehicle to everything (V2X), content delivery network (CDN), cloud games, etc. The other is a customized type which carries typical vertical industry services that have special resource requirements and are only used by certain industries, such as IoT. Different use cases have different resource requirements such as virtual machines, containers, physical servers, and all-in-one solutions. It is difficult for centralized global management to cover all of the different features and requirements with resource diversification at edge side. In addition cloud resources and services on edge nodes are provided by multiple vendors and in different versions. It is hard for global management to hide the heterogeneity of the underlying resources and offer unified services to CSCs.
+- **Wide fault domain:** Upgrading, updating, breakdown or any other transient offline of global management would leave the whole distributed cloud unmanaged. So in order to ensure manageability of distributed cloud and make sure that faults in different edge regions do not affect each other, distributed cloud needs isolation from faults in the domain of local edge management.
+- **Information and communication technology (ICT) united management:** To ensure low latency and wide bandwidth on edge side, the telecommunication user plane functions provided by telco-operators and cloud services provided by CSP should be deployed in the same EC. Telecommunication user plane functions are managed and orchestrated by network function virtualization orchestrator (NFVO) in a network function virtualization
+
+(NFV) structure, which is defined in [b-ETSI NFV]. While general cloud services are managed by global management, the merging of NFVO functions and global management is complicated and should receive careful consideration in edge cloud (EC).
+
+- **Edge coordination:** EC is limited in abilities and resources. Consequently the applications use abilities and resources from multiple ECs, and may also be deployed or migrated between multiple ECs or edge nodes. These cases require tight coordination and flexible dispatching between ECs or edge nodes. It is a challenge for global management to achieve in-time operations.
+
+## 6.2 Advantages of introducing edge cloud management
+
+To solve the challenges faced by global management to manage distributed cloud, edge cloud management is introduced into distributed cloud to manage edge cloud and support global management.
+
+Advantages of introducing edge cloud management are as follows:
+
+- **Relieve operation and maintenance pressure:** Edge cloud management can help transfer information between ECs and global management. It collects FCAPS data, filters important information (such as resource capacity, resource usage, faults, etc.) and reports to global management. This can help global management obtain a global view of distributed cloud, and relieve the pressure on the transmission network from global management.
+- **Provide edge autonomy management:** Edge cloud management provides local management for ECs to reduce the unreliability and inflexibility of remote management.
+- **Shield differences of edge cloud services:** Edge cloud management ensures unified application programming interfaces (APIs), unified services and cloud resources dispatch for CSCs by shielding the differences of edge nodes, such as different APIs, software versions, data formats, etc.
+- **Support flexible ICT management:** Edge cloud management provides APIs and abilities to CSCs and other management systems such as NFVO, global management, etc. It integrates abilities required by different ICT management systems, and maintains coordination between them. This helps to merge different requirements of ICT management.
+- **Promote edge coordination:** Edge cloud management provides coordination for a limited number of edge nodes to balance the flexibility and efficiency by using different ECs.
+- **Cooperate with global management:** Edge cloud management cooperates with global management to achieve coordination between ECs and core cloud (CC), ECs and regional cloud (RC).
+
+## 6.3 Relationship of edge cloud management with edge node
+
+Edge cloud is a kind of cloud computing deployed to the edge of the network accessed by CSCs with small capacity resources enabling cloud service as defined in [ITU-T Y.3508]. It can be managed by edge cloud management and includes several edge nodes. The relationships between edge cloud management and edge nodes, shown in Figure 6-1, are described as follows:
+
+- Edge cloud management is focused on offloading the operation and maintenance pressure from global management, executing edge autonomy management, shielding differences of EC services, supporting flexible ICT management and promoting edge coordination between EC to RC and CC.
+- Edge nodes include different resources, such as computing, networking, storage and other special industry resources.
+
+
+
+Figure 6-1: Conceptual relationships between edge cloud management and edge nodes. The diagram shows an 'Edge cloud' container. Inside, there is a box for 'Edge cloud management' at the top. Below it, a horizontal line connects to three ovals: 'Edge node 1', an ellipsis '...', and 'Edge node n'. The reference 'Y.3526(21)' is at the bottom right.
+
+**Figure 6-1 – Conceptual relationships between edge cloud management and edge nodes**
+
+Physically, edge cloud management can be deployed into a single node or several nodes as a set of functions by an administrator. Physical relationships of edge cloud management with edge nodes are shown in Figure 6-2 and Figure 6-3. Edge cloud management is deployed in single edge node with a set of functions as shown in Figure 6-2. Edge cloud management can be divided into several functions and deployed to multiple edge nodes as shown in Figure 6-3.
+
+
+
+Figure 6-2: Edge cloud management deployed in a single edge node. The diagram shows an 'Edge cloud' container. Inside, a horizontal line connects to four ovals: 'Edge node 1', 'Edge node 2', an ellipsis '...', and 'Edge node n'. Inside the 'Edge node 1' oval, there is a box labeled 'Edge cloud management'. The reference 'Y.3526(21)' is at the bottom right.
+
+**Figure 6-2 – Edge cloud management deployed in a single edge node**
+
+
+
+Figure 6-3: Edge cloud management deployed in multiple nodes with a set of functions. The diagram shows an 'Edge cloud' container. Inside, a horizontal line connects to five ovals: 'Edge node 1', 'Edge node 2', 'Edge node 3', an ellipsis '...', and 'Edge node n'. Inside 'Edge node 1', there are two stacked boxes: 'ECM function1' and 'ECM function2'. Inside 'Edge node 2', there is a box labeled 'ECM function3'. The reference 'Y.3526(21)' is at the bottom right.
+
+**Figure 6-3 – Edge cloud management deployed in multiple nodes with a set of functions**
+
+## 6.4 Relationship of edge cloud management with global management in distributed cloud
+
+In [ITU-T Y.3508], distributed cloud has a global view and local view of operations and administration management for distributed cloud resources and services. Global management works in coordination with CC, RC as well as EC from a global view. However from the local view edge cloud management is necessary to execute autonomy management, different edge nodes management, and also to interact with global management or other systems.
+
+This Recommendation focuses on edge cloud management which provides local management for cloud resources and service in ECs, and will cooperate with global management to achieve hierarchical and automatic management of a distributed cloud.
+
+
+
+Figure 6-4: Concept of edge cloud management in distributed cloud. The diagram is divided into three sections: Primary data centre, Regional data centre, and The edge of the network, all under the CSP umbrella. The Primary data centre contains a Core cloud. The Regional data centre contains a Regional cloud. The edge of the network contains multiple Edge clouds. Global management is connected to the Core cloud and the Regional cloud. Edge cloud management (Edge cloud management\_1 and Edge cloud management\_n) is connected to the Edge clouds. Each cloud type (Core, Regional, and Edge) has a stack of Computing, Network, and Storage components. The Edge cloud stacks are labeled as Edge nodes. A resource capacity bar at the bottom shows the relationship between the data centres: Primary data centre (≥) and Regional data centre (>). A legend indicates that double-headed arrows represent 'Distributing and interworking'. The reference Y.3526(21) is noted in the bottom right corner.
+
+**Figure 6-4 – Concept of edge cloud management in distributed cloud**
+
+Figure 6-4 shows the concept of edge cloud management in a distributed cloud. The ECs can be grouped according to different characteristics such as industry, features, locations, etc. Each group contains one or several edge nodes, and is managed by edge cloud management. Edge cloud management can manage EC independently, and can also cooperate with global management.
+
+Relationships between global management and edge cloud management can be described as follows:
+
+- Global management is responsible for managing the overall distributed cloud, including CC, RC and EC, which manages EC indirectly through edge cloud management.
+- Edge cloud management is responsible for managing EC, and mainly focuses on management of coordination between edge nodes within one EC, and between different ECs. Edge cloud management manages EC directly.
+
+NOTE 1 – Global management subscribes to edge cloud management to collect data of EC.
+
+NOTE 2 – Instructions of global management given to EC will be illustrated by edge cloud management firstly and then send to target edge node for execution.
+
+# 7 Edge cloud management mode in configuration models
+
+The term "model" used here specifies structures of management. Distributed cloud configuration models are used to indicate different combinations of CC, RC, and EC, refer to Figure 6-3 of [ITU-T Y.3508]. It can be used to instruct deployment and construction. The term "mode" used here specifies the method of management. Management mode of edge cloud management is used to indicate different kinds of management method in EC. Different management modes will be abstracted from the configuration models, and different management and interactions will be defined. This clause mainly describes the edge cloud management mode.
+
+## 7.1 Edge cloud management in configuration models of distributed cloud
+
+There are four configuration models of distributed cloud defined in Figure 6-3 and Table 6-1 of [ITU-T Y.3508]. Specifically, only model 2 (Edge-Core) and model 3 (Edge-Regional-Core) which includes EC have interactions with edge cloud management as shown in Figure 7-1.
+
+
+
+The diagram illustrates two distributed cloud models: Model 2 and Model 3, plotted against vertical and horizontal distribution axes.
+ **Distributed cloud model 2:** Under a CSP, it shows a 'Core cloud' connected vertically to an 'Edge cloud', which is then connected to an 'End device' (CSC). Management is handled by 'Global management' (connected to Core cloud) and 'Edge cloud management' (connected to Edge cloud).
+ **Distributed cloud model 3:** Under a CSP, it shows a 'Core cloud' connected to two 'Regional clouds', which are in turn connected to multiple 'Edge clouds'. These Edge clouds connect to an 'End device' (CSC). Management involves 'Global management' and multiple 'Edge cloud management' units.
+ Legend: Solid arrows with double heads indicate 'Distributing and interworking'. Dashed arrows with single heads indicate 'Use cloud service'.
+
+**Figure 7-1 – Edge cloud management in configuration models of distributed cloud**
+
+Figure 7-1 – Edge cloud management in configuration models of distributed cloud
+
+Distributed cloud model 2 is a type of distributed cloud in which the EC and the CC are configured together. In this model, edge cloud management manages the EC, while global management manages the CC. Cloud service in this model is executed on both edge and core clouds by interworking between edge cloud management and global management.
+
+Distributed cloud model 3 is a type of distributed cloud in which edge, regional and core clouds are configured together. In this model, edge cloud management manages the EC while global management manages the CC and RC. As cloud service in this model is deployed on edge, regional and core clouds, edge cloud management interacts with global management to support coordination among edge, regional and core clouds, and edge cloud management supports coordination between RC and CC.
+
+### 7.2 Edge cloud management modes
+
+Interactions between edge nodes, EC, and CC or RC are frequent. Therefore, edge cloud management should interact with global management in a distributed cloud. According to the illustration of edge cloud management in configuration model 2 and model 3 of a distributed cloud, there are three management modes of edge cloud management. As shown in Figure 7-2, the three management modes of edge cloud management are:
+
+- EC local management mode,
+- EC vertical management mode,
+- EC horizontal management mode.
+
+8 Rec. ITU-T Y.3526 (11/2021)
+
+
+
+Figure 7-2: Edge cloud management modes. The diagram illustrates the management architecture. At the top is 'Global management'. Below it is a large 'Edge cloud' containing 'EC vertical management', 'EC local management', and 'EC horizontal management'. Two 'Edge node' ovals are connected to 'EC local management'. To the right is a smaller 'Edge cloud' containing 'EC horizontal management'. Arrows show connections: Global management to EC vertical management; EC vertical management to EC local management; EC local management to EC horizontal management; EC horizontal management to the other Edge cloud; and both Edge nodes to EC local management.
+
+Y.3626(21)
+
+**Figure 7-2 – Edge cloud management modes**
+
+- **EC local management:** EC local management manages edge nodes within a given EC under local management mode, which includes the following objects:
+ - **Resource:** Infrastructures of the EC within the jurisdiction of edge cloud management, including physical and virtualized resources.
+ - **Service:** Cloud services and functionalities to deliver cloud services of an EC within the jurisdiction of edge cloud management. Local management on services supports life cycle management of services deployed on an EC.
+ - **Product:** Cloud service products defined in [ITU-T Y.3502] and functionalities to support product delivery of an EC within the jurisdiction of edge cloud management. EC local management of edge cloud management on products maintains the existing product catalogue defined in [ITU-T Y.3502] of a managed EC.
+ - **Customer:** The customer purchases resource/service/products both in an EC and a distributed cloud. For both situations, global management has a global view of customer information while edge cloud management only focuses on customers' information and requirements on EC.
+- **EC vertical management:** EC vertical management supports interactions between edge cloud management and global management. Objects managed under vertical management mode include interactions of services and customers existing across CC, RC and EC. Distributed cloud model 2 and model 3 need the vertical management mode because edge cloud management should interact with global management to support coordination among EC, CC and RC.
+- **EC horizontal management:** Edge cloud management supports cooperation with between ECs. Objects managed under horizontal management mode include interactions of services, products and customers existing cross ECs, such as data exchanging, service continuity guarantees, etc. Distributed cloud model 3 needs horizontal management mode because edge cloud management should interact with other edge cloud management objects to support coordination among ECs.
+
+To provide complete management, the three management modes should cooperate under different scenarios. Table 7-1 presents four scenarios of management modes.
+
+**Table 7-1 – Scenarios of management modes**
+
+| Scenario | Description | Calling sequence |
+|-------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------|
+| Scenario 1:
Local management | If CSC only orders services in a specific EC, edge cloud management should possess local management mode to provide local EC service. | — |
+| Scenario 2:
Vertical management +
Local management | If CSC orders services in core/regional cloud and a specific EC, only vertical interaction would exist between the core/regional cloud and EC. Edge cloud management possess vertical management mode to support vertical interaction, and local management mode to support any modification on EC in the vertical interaction. | Vertical -> Local |
+| Scenario 3:
Vertical management +
Horizontal management +
Local management | If CSC orders services in core/regional cloud and multiple ECs, vertical interaction would exist while horizontal interaction would exist among multiple ECs. Edge cloud management possess vertical management mode to support vertical interaction, horizontal management mode to support horizontal interaction, and local management to support any resource or service change on EC in the vertical interaction and horizontal interaction. | Vertical -> Horizontal/Local
-> Local/Horizontal |
+| Scenario 4:
Horizontal management +
Local management | If CSC orders services among multiple ECs, only horizontal interaction would exist among ECs. Edge cloud management possess horizontal management mode to support horizontal management, and local management mode to support any resource or service change on ECs in horizontal interaction. | Local -> Horizontal ->
Local |
+
+# 8 Edge cloud local management functions
+
+Edge cloud local management consists of the following functions:
+
+- Service awareness: The function is derived from the "context awareness" requirement in clause 7.2 of [ITU-T Y.3508] and aims to inspect the requested cloud service by CSC based on context information described in clause 6.2 of [ITU-T Y.3508]. If the requested cloud service is inspected and exists in EC, the requested service is deployed and provided directly from an edge node to support low-latency. If not, the request is passed and executed to RC or CC.
+- Service discovery: The function aims to search, trace, and maintain the service information of cloud services to deliver the CSC's request to the available endpoint. The service discovery function assigns the endpoint of the cloud service.
+- Service deployment: The function aims to configure and deploy cloud services to one or multiple edge nodes to meet service requirements (e.g., low-latency, high speed network, etc.).
+- Offloading: The function aims to divide the task of the cloud service into multiple sub-tasks and offload them to multiple edge nodes. Since edge nodes in EC have limited resources, the requested cloud services may be too heavy to handle and provide with low-latency to CSC. Edge cloud management transfers sub-tasks of the cloud services to one or multiple edge nodes dynamically or statically in EC. The tasks are partitioned unequally or equally according to the resource status of edge nodes dynamically in running time or statically based on the predefined policy.
+
+- Edge node monitoring: The function aims to observe the status of edge nodes in EC such as temperature, computing resources utilization, network resources bandwidth, and services status, etc. Edge cloud management uses the monitored information to adjust unhealthy cloud services and edge nodes efficiently.
+- Service integration: The function aims to integrate the completed tasks of the offloaded cloud service to deliver to the CSC. Edge cloud management maintains all sub-tasks carried on multiple edge nodes and merges them into the target of the cloud service.
+- Remote backup and recovery: The function aims to backup and recover data of the edge node remotely. As EC has limited resources, edge cloud management needs to provide a remote backup and recovery mechanism by using regional or core cloud with enough resources. Edge cloud management supports set policies and triggers them to backup or recover data based on the CSC's demand.
+- Software version management: The function includes delivery, deletion, and querying of the software package and aims to manage the software version of edge nodes. Since the total number of edge nodes is huge in a distributed cloud, direct software management from core to edge node is difficult. A software version update of edge nodes is controlled remotely by edge cloud management and pushed from CC by global management.
+- Scaling: The function aims to scale in or out the edge nodes in EC by reducing or adding resources to ensure better utilization depending on traffic balance. If resources in EC are limited to meet the service level agreement (SLA) requirements of CSCs, edge cloud management interacts with global cloud management for scaling out.
+- Service migration: The function aims to migrate cloud services running on one edge node to another edge node by copying the status of the process of the cloud service. Edge cloud management resumes the copied image of the cloud service online or offline.
+- Edge node provisioning: The function aims to authenticate and authorize resources of edge nodes, and configure environment variables and system resources to be accessed by cloud services at any time. Edge cloud management provides scalable resource pools in EC. This function needs to support unified, flexible, and secure interfaces for unregistered edge nodes to involve the resource pool in EC.
+- Service mash-up: The function aims to compose a cloud service from multiple microservices provided by CSPs. The cloud service has limitations to be deployed as one cloud service due to the lesser capacity of the edge node. Edge cloud management supports cloud services composed by microservices running on multiple edge nodes.
+- Service customization: The function aims to configure, register, and publish the cloud services in EC according to specific CSC's requests. Cloud services on EC are not diverse enough to fulfil different requirements subscribed by various CSCs. Thus, edge cloud management supports CSCs to load customized services such as customized monitoring service, customized load balancing, etc. and instantiates them.
+
+# **9 Functional requirements of edge cloud management**
+
+## **9.1 Resource requirements**
+
+### **9.1.1 Image transmission**
+
+It is recommended that CSP supports remote service image repository by edge cloud management.
+
+NOTE – Service image includes AI reasoning model images, AI training model images, etc.
+
+It is recommended that CSP monitors service image transmission status and progress by edge cloud management when pushing service images to an edge node.
+
+It is recommended that CSP resumes service image transmission at break-point by edge cloud management if the transmission is interrupted due to a bad network connection on an edge node.
+
+### **9.1.2 Remote software version management**
+
+It is recommended that CSP manages software versions and packages on edge node remotely by edge cloud management.
+
+It is required that CSP supports software upgrading and rollback by edge cloud management.
+
+NOTE – Software on edge node includes edge management software and service software, etc.
+
+### **9.1.3 Remote scaling**
+
+It is recommended that CSP supports remote scaling based on edge node resources by edge cloud management to adapt to traffic workflow and improve resource usage rate.
+
+#### **9.1.4 Resource alarm format**
+
+It is recommended that CSP provides alarm format templates by edge cloud management to unify the alarm format.
+
+It is recommended that CSP supports CSC or CSN to subscribe alarm reports in customized format by edge cloud management.
+
+#### **9.1.5 Remote health check and resume**
+
+It is required that CSP supports checking health status of edge nodes remotely and resuming service in healthy edge nodes by edge cloud management once the original nodes are unreachable.
+
+#### **9.1.6 Remote backup and recovery**
+
+It is recommended that CSP provides a remote backup and recovery mechanism to support EC resources and data backup and to recover services in resource-sufficient edge nodes or other clouds by edge cloud management.
+
+#### **9.1.7 Heterogeneous resource management**
+
+It is recommended that CSP hides heterogeneous hardware differences and provides unified services by edge cloud management.
+
+## **9.2 Service requirements**
+
+### **9.2.1 Service inspection**
+
+It is required that CSP inspects the CSC's service request context for deploying cloud services to edge nodes by edge cloud management.
+
+### **9.2.2 Service location information maintenance**
+
+It is required that CSP maintains location and access information of cloud services by edge cloud management to assign endpoints for the CSC's requests.
+
+### **9.2.3 Deployment of latency sensitive service**
+
+It is recommended that CSP deploys latency sensitive cloud services by edge cloud management based on EC availability to meet SLAs.
+
+NOTE – Examples of latency sensitive cloud service include an augmented reality (AR) service, a virtual reality (VR) service, a massive disaster alert service, and a self-driving public transportation service.
+
+### **9.2.4 Context information based service offloading**
+
+It is recommended that CSP offloads the CSC's service by edge cloud management based on context information from a CC, RC, or neighbour EC to meet SLAs.
+
+### **9.2.5 Delegation of service authority**
+
+It is required that CSP obtains delegation of a CSC's service authority by edge cloud management to access cloud services used by the CSC in a neighbour EC.
+
+### **9.2.6 Task based service integration**
+
+It is required that CSP integrates tasks of offloaded services based on context information by edge cloud management to provide the CSC's requested cloud service.
+
+NOTE – An example of task of offloaded services is machine learning model generation.
+
+#### **9.2.7 Service mash-up**
+
+It is recommended that CSP composes a cloud service by edge cloud management using multiple microservices.
+
+#### **9.2.8 Simplified and customizable management process**
+
+It is recommended that CSP provides a simplified and customizable management process by edge cloud management to satisfy a CSC's customized requests.
+
+#### **9.2.9 Customized service**
+
+It is recommended that CSP supports a CSC to request, to load and instantiate customized services by edge cloud management.
+
+It is recommended that CSP supports a CSC to publish customized services and makes these customized services available for other CSC by edge cloud management.
+
+# **10 Security considerations**
+
+It is recommended that the security framework for cloud computing described in [ITU-T X.1601] be considered for the EC. [ITU-T X.1601] analyses security threats and challenges in the cloud computing environment and describes security capabilities that could mitigate these threats and meet security challenges.
+
+It is recommended that the guidelines for the operational security of cloud computing described in [ITU-T X.1642] be considered for the EC. [ITU-T X.1642] clarifies the security responsibilities between CSPs and CSCs, and analyses the requirements and categories of security metrics of operational security for cloud computing.
+
+It is recommended that the security framework for the IoT based on the gateway model described in [ITU-T X.1361] be considered for ECs. In particular, [ITU-T X.1361] analyses security threats to the IoT gateway and to the network and describes security capabilities for gateways and the network that address and mitigate these security threats and challenges.
+
+# Appendix I
+
+## Use case of edge cloud management in distributed cloud
+
+(This appendix does not form an integral part of this Recommendation.)
+
+### I.1 Use case template
+
+The use cases developed in Appendix I should adopt the unified format presented in Table I.1 for better readability and convenient material organization.
+
+**Table I.1 – Use case template**
+
+| | |
+|----------------------------|-----------------------------------------------------------------------------------------------------------------|
+| Title | Note: The title of the use case |
+| Description | Note: Scenario description of the use case |
+| Roles | Note: Roles involved in the use case |
+| Figure (optional) | Note: Figure to explain the use case, but not mandatory |
+| Pre-conditions (optional) | Note: The necessary pre-conditions that should be achieved before starting the use case. |
+| Post-conditions (optional) | Note: The post-condition that will be carried out after the termination of current use case. |
+| Derived requirements | Note: Requirements derived from the use cases, whose detailed description is presented in the dedicated chapter |
+
+## I.2 Service image management in distributed AI service deployment
+
+**Table I.2 – Service image management in distributed AI service deployment**
+
+| | |
+|-------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Service image management in distributed AI service deployment |
+| Description | This use case describes the edge cloud management to provide image management when deploying distributed AI service.
Distributed AI service for distributed cloud is a kind of separated service combined with CC and EC. In Figure I.1 AI service – CC is in charge of CPU-costing model training, and AI service – EC is in charge of data collection and data cleaning and reasoning, which requires less compute resources.
The process of CSC requesting distributed AI service to CC and edge is as follows:
- – Global management checks service image status in CC, edge cloud management checks service image status in service image repository on edge cloud management (step 2.1, 2.2, 2.3 in Figure I.1)
- – Trigger service deployment (step 3.1, 3.2 in Figure I.1)
- – CC picks AI service –CC created by image from service image repository on CC (step 4.1 in Figure I.1). Edge cloud management triggers service image cache to edge node (step 4.2 in Figure I.2). AI service –EC image is pushed to edge node form remote service image repository on EC and create AI service in EC (step 4.3 in Figure I.1).
- – After AI service has been created in core and edge cloud, service status and IP address would be reported to global management and edge cloud management for service connection. (step 5.1, 5.2, 5.3, 6 in Figure I.1)
Report the whole AI service status and IP address to CSC (step 7 in Figure I.1)
In this use case, edge cloud management is required to support remote service image repository as edge node is limited in resources. When pushing service image to edge node for cache, edge cloud management is required to monitor service image
|
+
+**Table I.2 – Service image management in distributed AI service deployment**
+
+| | |
+|----------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | transmission status and support transmission resuming at break-point when bad network connection causes transmission interruption. After AI service – CC/EC has been created, edge cloud management is required to maintain service access information (e.g., IP address) so that AI service – EC can push structured data to AI service – core for model training. |
+| Roles | CSC, CSP |
+| Figure (optional) |
Y.3526(21)
Figure I.1 – Service image management in distributed AI service deployment
|
+| Pre-conditions (optional) | AI service is packaged into related service images and stored separately in CC image repository and EC image repository. |
+| Post-conditions (optional) | |
+| Derived requirements | Image transmission (refer to clause 9.1.1)
Service location information maintenance (refer to clause 9.2.2) |
+
+### I.3 Alarm format management
+
+**Table I.3 – Alarm format management**
+
+| | |
+|-------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Alarm format management |
+| Description | This use case, shown in Figure I.2, describes the alarm format management requirements of EC.
Edge cloud management manages edge nodes from different hardware devices, of which alarm format are different. To implement unified alarm display and storage, it is recommended edge cloud management to provide alarm format template, which contains device-specific format rules and can reformat alarms into unified format.
As edge cloud management connects with other management systems including global management, NFVO, etc., it is recommended edge cloud management support customized alarm report format, through which other management systems can subscribe alarms based on their formats, and edge cloud management will package and report alarms in customized format.
|
+| Roles | CSC, CSP |
+
+| | |
+|----------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional) | Image: Figure I.2 – Alarm format management in EC. The diagram illustrates the process of alarm normalization and reporting. At the top, three entities exist: Global management, NFVO, and Other systems. Below them is the Edge cloud, which contains Edge cloud management. Inside Edge cloud management, there is an Alarm format template containing Format rules_A and Format rules_B, and a box for Customized alarm report format. At the bottom are Edge node (Device type A) and Edge node (Device type B). The flow is as follows: 1. Alarms in diverse formats are collected from edge nodes (formed by different hardware) and sent to the Alarm format template. 2. The template converts these into a unified format sent to the Edge cloud management. 3. External systems (Global management, NFVO, Other systems) subscribe to alarm reports in a customized format from the Edge cloud management.
graph TD subgraph External_Systems [External Systems] GM[Global management] NFVO[NFVO] OS[Other systems] end subgraph Edge_cloud [Edge cloud] subgraph Edge_cloud_management [Edge cloud management] ECM[Edge cloud management] CARF[Customized alarm report format] subgraph Alarm_format_template [Alarm format template] FRA[Format rules_A] FRB[Format rules_B] end end subgraph Edge_nodes [Edge nodes] ENA[Edge node Device type A] ENB[Edge node Device type B] end end ENA -- "1. Alarm in diverse format" --> FRA ENB -- "1. Alarm in diverse format" --> FRB Alarm_format_template -- "2. Alarm in unified format" --> ECM ECM --> CARF CARF -- "3. Subscribe alarm report in customized format" --> GM CARF -- "3. Subscribe alarm report in customized format" --> NFVO CARF -- "3. Subscribe alarm report in customized format" --> OS
Y.3526(21)
Figure I.2 – Alarm format management in EC
|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements | – Alarm format (refer to clause 9.1.4) |
+
+### I.4 Edge cloud service to a stationary CSC
+
+**Table I.4 – Edge cloud service to a stationary CSC**
+
+| Title | Edge cloud service to a stationary CSC |
+|-------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | This use case describes the edge cloud management to provide a cloud service to a stationary CSC. When a stationary CSC requests a cloud service to EC, the edge cloud management in EC handles the CSC's request based on service awareness, service discovery, and service deployment functions. Service awareness function inspects the requested cloud service by CSC. Service discovery function tracks and maintains the service information of cloud services (e.g., the service endpoint) to deliver the CSC's request to the available endpoint. Service discovery function assigns the endpoint of the cloud service. Service deployment function configures and deploys a cloud service to EC which supports low-latency. There are several options as follows.
<Option 1: The cloud service provided directly from CC> (See Figure I.3)
If the requested cloud service by CSC does not exist in EC, the service discovery function delivers the service request to CC and provides the cloud service.
<Option 2: The cloud service provided directly in EC> (See Figure I.4)
If the requested cloud service by CSC exists in EC, then the service discovery function delivers the cloud service request to edge node in EC. The edge node provides the cloud service.
<Option 3: The cloud service deployed in CC, displaced to EC and provided from EC > (See Figure I.5)
If the requested cloud service by CSC does not exist in EC, the service deployment function deploys the cloud service to edge node in EC. The edge node provides the cloud service with low-latency.
|
+
+**Table I.4 – Edge cloud service to a stationary CSC**
+
+| | |
+|--------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | NOTE 1 – Service awareness is derived from "context awareness" requirement in [ITU-T Y.3508] clause 7.2.
NOTE 2 – This use case is derived from use case II.1 in [ITU-T Y.3508].
|
+| Roles | CSP, CSC |
+| Figure |
Figure I.3 – An example of providing service directly from CC
Non-existing cloud service
Existing cloud service
CC: Core cloud
EC: Edge cloud
ED: End device
CSC: Cloud service customer
CSP: Cloud service provider
Y.3526(21)
|
+| |
Figure I.4 – An example of providing service directly in EC
Non-existing cloud service
Existing cloud service
CC: Core cloud
EC: Edge cloud
ED: End device
CSC: Cloud service customer
CSP: Cloud service provider
Y.3526(21)
|
+
+**Table I.4 – Edge cloud service to a stationary CSC**
+
+
+
+**Figure I.5 – An example of providing service by deployment from CC to EC**
+
+Legend:
+
+- Non-existing cloud service (dashed box)
+- Existing cloud service (solid box)
+- CC: Core cloud
+- EC: Edge cloud
+- ED: End device
+- CSC: Cloud service customer
+- CSP: Cloud service provider
+
+Option 3 – The cloud service C deployed in CC, displaced to EC and provided from EC
+
+Figure I.5: An example of providing service by deployment from CC to EC. The diagram shows a Stationary CSC (ED) connected to a CSP. The CSP contains a Core Cloud (CC) and an Edge Cloud (EC). The EC is managed by Edge cloud management, which includes Service awareness, Service discovery, and Service deployment. Service deployment leads to Edge nodes (Edge node 1 and Edge node 2). Edge node 1 contains Cloud service B, and Edge node 2 contains Cloud service C (Latency sensitive). A dashed arrow indicates the deployment of Cloud service C from CC to EC. A legend defines non-existing and existing cloud services, and abbreviations for CC, EC, ED, CSC, and CSP.
+
+**Figure I.5 – An example of providing service by deployment from CC to EC**
+
+| | |
+|----------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements | - – Service inspection (refer to clause 9.2.1)
- – Service location information maintenance (refer to clause 9.2.2)
- – Deployment of latency sensitive service (refer to clause 9.2.3)
|
+
+### I.5 Edge cloud service seamlessly to mobile CSC
+
+**Table I.5 – Edge cloud service seamlessly to mobile CSC**
+
+| | |
+|-------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Edge cloud service seamlessly to mobile CSC |
+| Description | This use case describes the edge cloud management to provide a cloud service seamlessly to mobile CSC. The mobile CSC connected to EC 1 moves and connects to EC 2. The edge cloud management in EC 2 authorizes the CSC to delegate authority of the cloud service, is aware service context of the used cloud service, and then provides the cloud service. The several workflow options are as follows.
<Option 1: The cloud service provided directly from CC> (See Figure I.6)
If the requested cloud service by CSC does not exist in EC 2, the edge cloud management delivers the service request to CC and CC provides the cloud service.
<Option 2: The cloud service provided directly in EC 2> (See Figure I.7)
If the requested cloud service by CSC exists in EC 2, then the edge cloud management delivers the service request to edge node 1 in EC 2. The edge node 1 provides the cloud service.
<Option 3: The cloud service deployed in CC, displaced to EC 2 and provided from EC 2> (See Figure I.8)
|
+
+**Table I.5 – Edge cloud service seamlessly to mobile CSC**
+
+**Table I.5 – Edge cloud service seamlessly to mobile CSC**
+
+
+
+| | |
+|-----------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | Figure I.8 – An example of providing service by deployment from CC to EC 2
Legend:
- Non-existing cloud service (dashed box)
- Existing cloud service (solid box)
- CC: Core cloud
- EC: Edge cloud
- ED: End device
- CSC: Cloud service customer
- CSP: Cloud service provider
Y.3526(21)
|
+| | Figure I.9 – An example of providing service in EC 1
Legend:
- Non-existing cloud service (dashed box)
- Existing cloud service (solid box)
- CC: Core cloud
- EC: Edge cloud
- ED: End device
- CSC: Cloud service customer
- CSP: Cloud service provider
Y.3526(21)
|
+| Pre-conditions (optional)
| A CSP maintains information of CSC's authority for delegation.
NOTE – Information of CSC's authority refers to information of access rights and privileges.
|
+| Post-conditions (optional)
| |
+| Derived requirements
| - – Service inspection (refer to clause 9.2.1)
- – Service location information maintenance (refer to clause 9.2.2)
- – Deployment of latency sensitive service (refer to clause 9.2.3)
- – Context information based service offloading (refer to clause 9.2.4)
- – Delegation of service authority (refer to clause 9.2.5)
|
+
+Figure I.8: An example of providing service by deployment from CC to EC 2. The diagram shows a CSC (Mobile) with an ED moving from a non-existing cloud service F to an existing cloud service F. The CSP contains EC 1, EC 2, and CC. EC 1 initially uses service F, but after the CSC moves, it uses service F provided by EC 2. The Edge cloud management process involves service awareness, discovery, and deployment, leading to the service being provided by EC 2. Option 3 states that the cloud service F deployed in CC is displaced to EC 2 and provided from EC 2. Figure I.9: An example of providing service in EC 1. The diagram shows a CSC (Mobile) with an ED moving from a non-existing cloud service G to an existing cloud service G. The CSP contains EC 1, EC 2, and CC. EC 1 initially uses service G, but after the CSC moves, it uses service G provided by EC 1. The Edge cloud management process involves context information, service awareness, discovery, and deployment, leading to the service being provided by EC 1. Option 4 states that the cloud service G provided in EC 1.
+
+### I.6 Edge cloud service offloading
+
+**Table I.6 – Edge cloud service offloading**
+
+| | |
+|----------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Edge cloud service offloading |
+| Description | This use case, shown in Figure I.10, describes the edge cloud management to provide a cloud service with service offloading. When CSC requests a cloud service to EC, the edge cloud management handles the CSC's request. Service awareness function in the edge cloud management inspects the CSC's service based on context information. The tasks of the offloaded cloud service are executed in each edge node. When the executions are done, service integration function in edge cloud management integrates the tasks of the offloaded cloud service and provides the cloud service to CSC.
An example of the cloud service provided with offloading is machine learning (ML) model training. ML model training service is offloaded to edge nodes with divided data. When each offloaded service is done, then the edge cloud management integrates each trained model and provides a global trained model to CSC.
|
+| Roles | CSP, CSC |
+| Figure | Image: Figure I.10: Process of edge cloud management service offloading. The diagram shows the interaction between a Core Cloud (CC) and an Edge Cloud (EC) within a Cloud Service Provider (CSP). The EC includes Edge cloud management, Service integration, and Cloud service E. Cloud service E is divided into three tasks (E-1, E-2, E-3) which are offloaded to Edge node 1, Edge node 2, and Edge node 3 respectively. The tasks are executed and then integrated by the Service integration function, which provides the Cloud service E to the Edge cloud management. The Edge cloud management then provides the Cloud service E to the Core Cloud (CC). The Core Cloud (CC) is connected to the Edge Cloud (EC) via a dashed line. The Edge Cloud (EC) is connected to the End Device (ED) via a solid line. The End Device (ED) is connected to the Cloud Service Customer (CSC) via a solid line. The process is numbered 1 to 5: 1. Request cloud service E, 2. Cloud service E is divided into three tasks, 3. Offload the cloud service E into three edge nodes, 4. Each task of cloud service E is integrated by edge cloud management, 5. Cloud service E provided by EC.
CC: Core cloud
EC: Edge cloud
ED: End device
CSC: Cloud service customer
CSP: Cloud service provider
Figure I.10 – Process of edge cloud management service offloading
|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+
+**Table I.6 – Edge cloud service offloading**
+
+| | |
+|----------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Derived requirements | - – Service inspection (refer to clause 9.2.1)
- – Service location information maintenance (refer to clause 9.2.2)
- – Context information based service offloading (refer to clause 9.2.4)
- – Task based service integration (refer to clause 9.2.6)
|
+|----------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+
+### **I.7 Edge cloud management as a service broker with microservices**
+
+**Table I.7 – Edge cloud management as a service broker with microservices**
+
+| | |
+|-------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Edge cloud management as a service broker with microservices |
+| Description | This use case, shown in Figure I.11 describes the edge cloud management as a service broker. When CSC requests the cloud service consisting of microservices, the edge cloud management handles the CSC's request with service mash-up function. If the requested cloud service is composed of several microservices, then the CSC's request delivered to the edge nodes that the microservices are deployed. Service mash-up function composes the microservices to produce the cloud service. Figure I.11 shows the splitting mechanism of cloud service by service mash-up as service broker in edge cloud management.
For example, the video editing cloud service consists of three microservices such as format conversion, caption design, and speed control.
|
+| Roles | CSP, CSC |
+| Figure | Image: Figure I.11: Service mash-up as a service broker. The diagram shows the interaction between a Cloud Service Customer (CSC) and a Cloud Service Provider (CSP). The CSC contains an End Device (ED). The CSP contains a Core Cloud (CC) connected to an Edge Cloud (EC). The EC includes an Edge cloud management block with a Service mash-up function, and four Edge nodes (1-4). Edge node 1 has Microservice B, Edge node 2 has Microservice C, Edge node 3 has Microservice D, and Edge node 4 has Cloud service A. The process flow is: 1. Request cloud service A from CSC to Edge cloud management; 2. Inspect that cloud service A consists of three microservices B, C, and D; 3. Mash-up and compose cloud service A with microservice B, C, and D; 4. Cloud service A provided by EC back to CSC's ED.
CC: Core cloud CSC: Cloud service customer
EC: Edge cloud CSP: Cloud service provider
ED: End device
Y.3526(21)
Figure I.11 – Service mash-up as a service broker
|
+
+**Table I.7 – Edge cloud management as a service broker with microservices**
+
+| | |
+|----------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements | - – Service inspection (refer to clause 9.2.1)
- – Service location information maintenance (refer to clause 9.2.2)
- – Service mash-up (refer to clause 9.2.7)
|
+
+### I.8 Remote management for edge nodes
+
+**Table I.8 – Remote management for edge nodes**
+
+| | |
+|-------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Remote management for edge nodes |
+| Description | This use case, shown in Figure I.12, describes the edge cloud management to manage edge nodes remotely. Six examples have been provided to derive requirements.
Example 1:
Edge nodes of EC are usually large in number and widely distributed. This makes direct software management on edge node impossible, which recommends edge cloud management to manage edge nodes software remotely within stable and remote management network. All the software packages can be delivered, deleted, queried remotely. And the software upgrading and rollback in edge nodes can be controlled remotely by edge cloud management.
Example 2:
The business traffic on EC of single edge node may change suddenly or regularly on different locations, such as during World Cup period, workday, weekend. To deal with traffic growth and ensure service quality, edge cloud management should scale out edge node remotely by adding resources. To ensure better utilization of resources during period with less traffic, edge cloud management should scale in edge node remotely by releasing idle resources. These resources can come from other edge nodes in the same edge, etc.
Example 3:
Edge cloud is usually located in harsh environment instead of in data centre, for example high-temperature and dusty environment. It is recommended that edge cloud management to support remote health check on edge nodes. Once the edge node is in unknown status and application is unreachable, edge cloud management should pick another edge node to resume the application.
Example 4:
Edge cloud has limited resources, it is recommended to reserve more resources for CSC's service and local backup is not suggested. Edge cloud management is recommended to provide remote backup and recovery mechanism. Edge cloud management supports to set backup policies for edge nodes and trigger them to backup data on demand. Edge nodes resource or data could be backup to RC or CC with enough resources.
Example 5:
CC and RC have huge amount of resources to serve multiple CSCs, for which complementary and unified process is easier to maintain. However, EC has limited resources, sometimes can only serve one CSC in local industry environment like private cloud. It is recommended that edge cloud management could support simplified and customizable management process to fulfil different CSC and various CSC's service requirements on demand.
|
+
+**Table I.8 – Remote management for edge nodes**
+
+| | |
+|----------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | Example 6:
The CSC's service could use different type of cloud resource in EC. Taking one AI service for example, web service module needs VM or container, but video codec module needs GPU. So different edge nodes might have diversified device type. It is recommended that edge cloud management hides heterogeneous hardware differences and provide unified services.
|
+| Roles | CSP, CSC |
+| Figure | Image: Figure I.12 – Remote management for edge nodes. The diagram shows 'Edge cloud management' at the top with five sub-functions: Software version management, Scaling, Health check and resume, Backup and recovery, and Heterogeneous resource management. Arrows point from these functions to five corresponding scenarios below. 1. Software version management: shows an 'Edge node' with 'Version v0.1' being updated to 'Version v1.0'. 2. Scale out: shows an 'Edge node' with a plus sign and an arrow pointing to another 'Edge node'. 3. Health check: shows an 'Edge node' with 'Unknown status' being checked against a 'VM' icon. 4. Backup: shows an 'Edge node' with 'Backup data 1' and 'Backup data n' being sent to a 'Cloud'. 5. Heterogeneous resource: shows an 'Edge node' with 'X86' and 'GPU' resources. A small reference 'Y.3526(21)' is at the bottom right.
Figure I.12 – Remote management for edge nodes
|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements | - – Remote software version management (refer to clause 9.1.2)
- – Remote scaling (refer to clause 9.1.3)
- – Remote health check and resume (refer to clause 9.1.5).
- – Remote backup and recovery (refer to clause 9.1.6)
- – Heterogeneous resource management (refer to clause 9.1.7)
- – Simplified and customizable management process (refer to clause 9.2.8)
|
+
+### I.9 Customized service management
+
+**Table I.9 – Customized service management**
+
+| | |
+|-------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Customized service management |
+| Description | This use case describes the edge cloud management to provide customized service management.
Example 1:
As EC has limited resources, and CSC requirements on EC are not universal, services on EC may not be diverse enough to fulfil different CSCs requirements. To balance between limited service types in EC and non-universal edge service requirements of CSC, it is recommended that edge cloud management supports CSC to load customized services and instantiates them. These customized services could be provided by CSC, for example customized monitoring service, customized load balancer, etc., used to support multiple CSC's service designing, running, monitoring, management, etc. (see Figure I.13)
|
+
+**Table I.9 – Customized service management**
+
+| | |
+|----------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | Example 2:
Following Example 1, if the customized service loaded by one CSC ("CSC_A" in Figure I.14) can represent requirements of a group of CSCs ("other CSC" in Figure I.14), then CSC_A can choose to make its customized service publicly available (step ① in Figure I.14), and let other CSC to subscribe and use this service (step ③ in Figure I.14). In step ②, CSP should authenticate CSC_A as a legal customized service provider, so that CSC_A could load and publish customized service. Edge cloud management authenticates the published service as a legal and public available service on EC, and authorize other CSC to subscribe this service. This example recommends edge cloud management to support customized service publishing.
|
+| Roles | CSP, CSC |
+| Figure | Image: Figure I.13: Edge cloud management supports CSC to load customized service. The diagram shows a 'CSC' entity at the top with two arrows pointing down to an 'Edge cloud management' box: 'Onboard' and 'Instantiate'. The 'Edge cloud management' box contains three colored bars (blue, grey, blue) and one yellow bar. Below it are three cloud icons: 'Edge cloud', 'Core cloud', and 'Edge cloud', each containing three colored bars (blue, grey, blue). A dashed line connects the 'Edge cloud management' box to each cloud icon. A legend on the right shows a dashed box with three colored bars and the text 'Various cloud services' and 'Y.3526(21)'.
Figure I.13 – Edge cloud management supports CSC to load customized service
Image: Figure I.14: Edge cloud management supports CSC to publish customized service. The diagram shows a 'CSC_A' entity at the top with an arrow pointing down to an 'Edge cloud management' box labeled '1 Onboard publish'. A 'CSP' entity is in the middle with an arrow pointing to the 'Edge cloud management' box labeled '2 Authorize'. An 'Other CSC' entity is at the top right with an arrow pointing to the 'Edge cloud management' box labeled '3 Subscribe'. The 'Edge cloud management' box contains three colored bars (blue, grey, blue) and one yellow bar. Below it are three cloud icons: 'Edge cloud', 'Core cloud', and 'Edge cloud', each containing three colored bars (blue, grey, blue). A dashed line connects the 'Edge cloud management' box to each cloud icon. A legend on the right shows a dashed box with three colored bars and the text 'Various cloud services' and 'Y.3526(21)'.
Figure I.14 – Edge cloud management supports CSC to publish customized service
|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements | – Customized service (refer to clause 9.2.9) |
+
+## **Bibliography**
+
+[b-ETSI NFV]
+
+ETSI NFV White Paper 2: Network Functions Virtualisation –
+Introductory White Paper
+
+[https://portal.etsi.org/NFV/NFV\\_White\\_Paper2.pdf](https://portal.etsi.org/NFV/NFV_White_Paper2.pdf)
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+## Y.3527
+
+(09/2021)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Cloud Computing
+
+# --- **Cloud computing – End-to-end fault and performance management framework of network services in inter-cloud**
+
+Recommendation ITU-T Y.3527
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Computing power networks | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+| | |
+|------------------------|----------------------|
+| CLOUD COMPUTING | Y.3500–Y.3599 |
+|------------------------|----------------------|
+
+| | |
+|----------|---------------|
+| BIG DATA | Y.3600–Y.3799 |
+|----------|---------------|
+
+| | |
+|-----------------------------------|---------------|
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800–Y.3999 |
+|-----------------------------------|---------------|
+
+## INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|---------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+For further details, please refer to the list of ITU-T Recommendations.
+
+## Recommendation ITU-T Y.3527
+
+# Cloud computing – End-to-end fault and performance management framework of network services in inter-cloud
+
+## Summary
+
+Recommendation ITU-T Y.3527 provides framework and functional requirements of end-to-end (E2E) fault and performance management of network services (NSs) in inter-cloud. The functional requirements are derived from the corresponding typical use cases. In particular, a predictive model for fault and performance issue detection and localization is presented.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.3527 | 2021-09-13 | 13 | 11.1002/1000/14760 |
+
+## Keywords
+
+End-to-end, fault, framework, inter-cloud, management, network service, performance.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+### NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2021
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|---|--------------------------------------------------------------------------------------------------------------|------|
+| 1 | Scope ..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 3 |
+| 6 | Overview of E2E fault and performance management of NSs in inter-cloud..... | 3 |
+| | 6.1 NSs in the virtualized environment ..... | 3 |
+| | 6.2 Background..... | 4 |
+| | 6.3 Challenges of E2E fault and performance management for NSs in inter-cloud ..... | 5 |
+| | 6.4 Goals of E2E fault and performance management of NSs in inter-cloud ..... | 5 |
+| | 6.5 Framework of E2E fault and performance management of NSs in inter-cloud ..... | 5 |
+| 7 | Functional requirements for E2E fault and performance management of NSs in inter-cloud..... | 7 |
+| | 7.1 Fault and performance data collection ..... | 7 |
+| | 7.2 Fault and performance problem detection ..... | 7 |
+| | 7.3 Fault and performance problem localization ..... | 8 |
+| | 7.4 Fault and performance problem correlation ..... | 8 |
+| | 7.5 Fault handling in inter-cloud ..... | 8 |
+| 8 | Security consideration ..... | 8 |
+| | Appendix I – Use case of end-to-end fault and performance management of network services in inter-cloud..... | 9 |
+| | I.1 Use case template ..... | 9 |
+| | I.2 Virtual broadband service..... | 9 |
+| | I.3 Fault recovery in inter-cloud ..... | 10 |
+| | I.4 Fault prediction and handling in inter-cloud ..... | 11 |
+| | Appendix II – A predictive model for fault and performance issues detection and localization..... | 13 |
+| | II.1 Problem statement ..... | 13 |
+| | II.2 A model for fault and performance issues detection and localization..... | 13 |
+| | II.3 Markers and metrics for fault and performance issue detection and localization ..... | 14 |
+| | Bibliography..... | 15 |
+
+
+
+## Recommendation ITU-T Y.3527
+
+# Cloud computing – End-to-end fault and performance management framework of network services in inter-cloud
+
+# 1 Scope
+
+This Recommendation specifies framework and functional requirements for end-to-end (E2E) fault and performance management of network services (NSs) in inter-cloud. The scope of this Recommendation includes:
+
+- an overview of E2E fault and performance management of NSs in inter-cloud;
+- functional requirements for E2E fault and performance management of NSs in inter-cloud;
+- typical use cases for E2E fault and performance management of NSs in inter-cloud;
+- a predictive model for fault and performance issues detection and localization.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- | | |
+|----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| [ITU-T M.3010] | Recommendation ITU-T M.3010 (2000), Principles for a telecommunications management network . |
+| [ITU-T X.711] | Recommendation ITU-T X.711 (1997), Information technology – Open Systems Interconnection – Common management information protocol: Specification . |
+| [ITU-T X.1601] | Recommendation ITU-T X.1601 (2015), Security framework for cloud computing . |
+| [ITU-T Y.3502] | Recommendation ITU-T Y.3502 (2014) ISO/IEC 17789:2014, Information technology – Cloud computing – Reference architecture . |
+| [ITU-T Y.3515] | Recommendation ITU-T Y.3515 (2017), Cloud computing – Functional architecture of Network as a Service . |
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+- 3.1.1 cloud service customer** [b-ITU-T Y.3500]: Party which is in a business relationship for the purpose of using cloud services.
+- 3.1.2 cloud service provider** [b-ITU-T Y.3500]: Party which makes cloud services available.
+- 3.1.3 inter-cloud computing** [b-ITU-T Y.3511]: The paradigm for enabling the interworking between two or more cloud service providers.
+
+**3.1.4 network as a service (NaaS)** [b-ITU-T Y.3500]: Cloud service category in which the capability provided to the cloud service customer is transport connectivity and related network capabilities.
+
+NOTE – NaaS can provide any of the three cloud capabilities types.
+
+**3.1.5 network function** [ITU-T Y.3515]: A function of a network infrastructure whose external interfaces and functional behaviour are well specified.
+
+NOTE – Examples of network functions include network switches and network routers.
+
+**3.1.6 network service** [ITU-T Y.3515]: A collection of network functions with a well specified behaviour.
+
+NOTE – Examples of network services include content delivery networks (CDNs) and IP multimedia subsystem (IMS).
+
+**3.1.7 physical network function** [ITU-T Y.3515]: A network function implemented via a tightly coupled software and hardware system.
+
+**3.1.8 service function chain** [b-ITU-T Y.Suppl. 41]: A chain that defines an ordered set of abstract service functions and ordering constraints that must be applied to packets and/or frames and/or flows selected as a result of classification and/or policy.
+
+**3.1.9 virtualized network function** [ITU-T Y.3515]: A network function that can be deployed as a software on a NaaS cloud service provider infrastructure.
+
+NOTE – Examples of virtualized network functions include virtual switches and virtual routers.
+
+## **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following terms:
+
+**3.2.1 cloud service:** One or more capabilities offered via cloud computing invoked using a defined interface. It may comprise the hardware and hypervisor layers delivering individual servers, border routers, firewalls, load balancers & switches.
+
+NOTE – Expanded version of definition in [b-ITU-T Y.3500].
+
+**3.2.2 network function virtualization (NFV):** Principle of separating network functions from the hardware they run on by using virtual hardware abstraction.
+
+NOTE – Based on [b-ETSI GR NFV 003].
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-------|------------------------------------------------------------|
+| CCS | Cloud Compute and Storage |
+| CDN | Content Delivery Network |
+| CMIP | Common Management Information Protocol |
+| CSC | Cloud Service Customer |
+| CSP | Cloud Service Provider |
+| E2E | End to End |
+| FCAPS | Fault, Configuration, Accounting, Performance and Security |
+| IMS | IP Multimedia Subsystem |
+| IP | Internet Protocol |
+| NaaS | Network as a Service |
+
+| | |
+|-----|--------------------------------------|
+| NC | Network Connectivity |
+| NF | Network Function |
+| NFV | Network Function Virtualization |
+| NS | Network Service |
+| OSS | Operations Support System |
+| PNF | Physical Network Function |
+| PM | Physical Machine |
+| PR | Physical Resources |
+| QoS | Quality of Service |
+| SFC | Service Function Chain |
+| SLA | Service Level Agreement |
+| TMN | Telecommunication Management Network |
+| VM | Virtual Machine |
+| VNF | Virtualized Network Function |
+
+# 5 Conventions
+
+In this Recommendation:
+
+The phrase "**is required to**" indicates a requirement that must be strictly followed and from which no deviation is permitted if conformity to this Recommendation is to be claimed.
+
+The phrase "**is recommended**" indicates a requirement that is recommended but which is not absolutely required. Thus this requirement need not be present to claim conformity.
+
+# 6 Overview of E2E fault and performance management of NSs in inter-cloud
+
+## 6.1 NSs in the virtualized environment
+
+According to [ITU-T Y.3515], an NS is a collection of network functions (NFs) with a well specified behaviour, examples of NSs include CDNs and IMSs. An NS can also be made up of NF(s) or component NS(s), characterized by its functional and behavioural specification (see [b-ETSI GR NFV 003]). The NS contributes to the behaviour of the higher layer service, which is characterized by at least performance, dependability and security specifications. E2E NS behaviour is the result of the combination of the behaviours of individual NFs, as well as the network infrastructure composition mechanism.
+
+When supporting NaaS connectivity services, an NS can be described as an abstracted transport connectivity between two endpoints in a virtualized environment where the endpoints may be located in one or more clouds. The virtualization hierarchy of NS is shown in Figure 6-1.
+
+
+
+Figure 6-1: Virtualization hierarchy of NS. The diagram shows a stack of layers. At the top, two 'NS' (Network Service) boxes are shown, each containing 'NF' (Network Function) blocks. The second NS box is labeled 'SFC' (Service Function Chain) with a bracket under its NF blocks. Below the NS boxes is a box for 'Virtualized resources (Compute, storage and networking)', and at the bottom is a box for 'Physical resources'. A legend on the right defines NS as Network service, NF as Network function, and SFC as Service function chain. The reference Y.3527(21) is at the bottom.
+
+**Figure 6-1 – Virtualization hierarchy of NS**
+
+An NS can be described as an E2E implementation using a service function chain (SFC), interconnecting the virtual network resources. An SFC is an ordered set of virtualized network functions (VNFs) in the virtualized environment that represents functions like routers and broadband network gateways or middle-boxes like load balancers and firewalls, which act on the traffic in the sequence they appear in the chain. Such VNFs are hosted on virtual machines (VMs) instantiated over physical data centre and network resources. An example of an E2E NS in inter-cloud is shown in Figure 6-2. This NS is composed of VNF1 to VNF5, which belong to different cloud service providers (CSPs).
+
+
+
+Figure 6-2: An E2E NS in inter-cloud. The diagram shows three CSPs (Cloud Service Providers) in boxes. CSP 1 contains VNF1 and 'Physical and virtual resources'. CSP 2 contains VNF2, VNF3, and 'Physical and virtual resources'. CSP 3 contains VNF4, VNF5, and 'Physical and virtual resources'. A 'CSC' (Cloud Service Chain) circle on the left connects to VNF1. VNF1 connects to VNF2 and VNF3. VNF2 connects to VNF4. VNF3 connects to VNF4. VNF4 connects to VNF5. VNF5 connects to a 'CSC' circle on the right. The reference Y.3527(21) is at the bottom right.
+
+**Figure 6-2 – An E2E NS in inter-cloud**
+
+## 6.2 Background
+
+The traditional telecommunication network deployment largely involves use of physical network appliances like routers, switches, broadband remote access servers, as well as middle-boxes like firewalls, deep packet inspectors or load balancers. These integrated hardware and software solutions are normally closed and proprietary leading to vendor lock-in, thereby making expansions and deployment of new services difficult and time consuming. Such equipment is also not amenable to easy scaling or redeployment of resources. The power and space requirements, as well as the total cost of operation, are higher in physical element-based networks.
+
+In traditional networks, time-tested standards relating to fault, configuration, accounting, performance and security (FCAPS) are embodied in the common management information protocol (CMIP) specified in [ITU-T X.711] and telecommunication management network (TMN) specified in [ITU-T M.3010]. Network management based on relevant Recommendations provides five nines (99.999%) availability and carrier grade reliability.
+
+Inter-cloud computing, coupled with the deployment of NFV, provides numerous advantages to CSPs including ease of deployment, ease of scaling, ease of introducing and switching off services, and reduced cost of operation. Therefore, NSs in inter-cloud need a strong fault and performance management system to replace traditional networks. For carrier grade availability and reliability of up to 99.999% for NS inter-cloud, there is a need for standardization of the framework for fault and
+
+performance management to deal with complexity in such networks, as the anomalous behaviour could be in the hardware, VMs, VNFs, SFCs or at the service levels.
+
+## **6.3 Challenges of E2E fault and performance management for NSs in inter-cloud**
+
+Telecommunication networks have been traditionally designed to provide high availability and standards-based quality of service (QoS). In inter-cloud, NS deployment over multiple clouds identifies new challenges to equip inter-cloud management systems to deal with management issues. Especially, those NSs relay over underlying both physical and software infrastructure. Therefore, E2E management is related to the physical, virtual layer or the VNFs of inter-cloud environments where VMs are instantiated, on which particular VNFs are hosted.
+
+For NSs in inter-cloud, faults may occur for many more reasons compared to traditional physical telecommunication networks. The virtual resources are created on shared physical resources like servers or network equipment, using virtualization software. One reason why virtual resources may fail is because of the failure of physical resources. Even if the physical resources are healthy, virtual resources may fail. Furthermore, even if both physical and virtual resources are healthy, the VNFs instantiated on these virtual resources may have problems causing NSs to malfunction or totally break down. The myriad levels of malfunctions make handling of fault and performance issues in inter-cloud more complex.
+
+Some of the key challenges for E2E fault and performance management for NSs in inter-cloud are as follows:
+
+- absence of a standardized framework;
+- non-applicability of traditional rule-based techniques when used in inter-cloud;
+- multiple layers of implementation including physical infrastructure, virtual resource, NFs and NSs;
+- massive distribution of NFs and underlying resources over different clouds.
+
+## **6.4 Goals of E2E fault and performance management of NSs in inter-cloud**
+
+The goals of E2E fault and performance management of NSs in inter-cloud can be summarized as follows.
+
+- Detection of any condition that has already led to or could lead to degraded performance or failure, which could be caused by manifested faults, hidden faults or inconspicuous deviations. The goal of fault and performance issue detection is to sense and notify impending or actual fault and performance issues.
+- Identification and localization of manifested and impending faults. The goal of fault and performance issue localization is to determine the root cause of the problem by identifying the resources that are malfunctioning or the severity with which the resources may malfunction in the future.
+
+## **6.5 Framework of E2E fault and performance management of NSs in inter-cloud**
+
+The fault and performance management of NSs in inter-cloud is a collaborative process among the elements constituting the service and the management functional components involved. The fault and performance management-related responsibilities are jointly implemented by some functional components of the operations support systems (OSSs) defined in the multi-layer functions of cloud-computing reference architecture [ITU-T Y.3502]. These functional components include OSS-NS, OSS-NF, OSS-cloud compute and storage (OSS-CCS), OSS-network connectivity (OSS NC) and OSS- OSS-physical resources (PR). Their interrelationship in the context of NSs is illustrated in Figure 6-3. For more information about these functional components, please see clauses 7.8 and 8.3 of [ITU-T Y.3515].
+
+
+
+Figure 6-3: OSS functionalities and reference points for fault and performance management of NSs. The diagram shows a layered architecture. On the left, the 'User layer' and 'Access layer' are at the top. Below them is the 'Service layer' containing multiple 'NaaS service' blocks. The 'Resource layer' contains two 'NS' blocks, each with multiple 'NF' blocks. Below the NS blocks is a dashed box containing 'Virtualized compute, storage and network connectivity resources' and 'Physical resources'. On the right, the 'Multi-layer functions' block contains 'Operation support systems' and a stack of OSS components: 'OSS-network services (OSS-NS)', 'OSS-network functions (OSS-NF)', 'OSS-cloud compute and storage (OSS-CCS)', 'OSS-network connectivity (OSS-NC)', and 'OSS-physical resources (OSS-PR)'. Reference points are indicated by lines with labels: 'Ns-Ons' between NS and OSS-NS; 'Nf-Onf' between NF and OSS-NF; 'Res-Ores' between the Resource layer and the OSS-CCS/OSS-NC/OSS-PR stack; 'Onf-Ons' between OSS-NS and OSS-NF; 'Ores-Onf' between the OSS-CCS/OSS-NC/OSS-PR stack and OSS-NF; and 'Ores-Ons' between the OSS-NS and the OSS-CCS/OSS-NC/OSS-PR stack.
+
+**Figure 6-3 – OSS functionalities and reference points for fault and performance management of NSs**
+
+The responsibilities of functional components related to fault and performance management of NSs are as follows.
+
+- **OSS-NS:** which is responsible for managing the lifecycle of NSs and using available resources or requesting additional resources to maintain the required performance. For handling fault and performance issues, it monitors NSs and resources, and detects anomalous conditions. It gets NF level alarms from OSS-NF and resource level alarms from OSS-CCS, OSS-NC and OSS-PR. It correlates alarms from various sources to localize faults and performance conditions.
+- **OSS-NF:** which is responsible for managing the lifecycle of NFs. For handling fault and performance issues, it interacts with NF instances to obtain NF-related fault and performance information. It also collects NF instance-related resource information and sends it to OSS-NS for fault detection and localization.
+- **OSS-CCS, OSS-NC and OSS-PR:** which are responsible for collecting alarms related to physical and virtual resources. They forward fault and performance alarms to OSS-NS and OSS-NF for broader correlation and root cause analysis. The fault information may include VM crashes, virtual port malfunction, storage failure and resource unavailability.
+
+The reference points related to fault and performance management of NSs are as follows.
+
+- **Res-Ores:** This reference point covers the interactions between the virtual and physical resources, and the functional components about virtual and physical resource management, i.e., OSS-CCS, OSS-NC and OSS-PR. It includes the interaction related to reporting resource level fault and performance issues.
+- **Nf-Onf:** This reference point covers the interactions between the NFs and OSS-NF. It includes the interaction related to reporting NF level fault and performance issues.
+
+- **Ns-Ons:** This reference point covers the interactions between the NSs and OSS-NS. It includes the interaction related to reporting NS level fault and performance issues.
+- **Onf-Ons:** This reference point covers the interactions between the OSS-NF and OSS-NS. It includes the interaction related to exchanging information about the creation and modification of NFs, and forwarding fault and performance issues related to NFs.
+- **Ores-Onf:** This reference point covers the interactions between the OSS-NF and the functional components for virtual and physical resource management. It includes the interaction related to exchanging information about resource level fault and performance issues.
+- **Ores-Ons:** This reference point covers the interactions between the OSS-NS and the functional components for virtual and physical resource management. It includes the interaction related to exchanging information about resource level fault and performance issues.
+
+Figure 6-3 presents the OSS functionalities and reference points for fault and performance management of NSs based on the cloud-computing reference architecture [ITU-T Y.3502] in one CSP. In an inter-cloud environment, the framework of E2E fault and performance management of NSs is presented as Figure 6-4. It is based on fault and performance management chains including the cloud service customer (CSC) and one or more CSPs.
+
+
+
+Figure 6-4: Framework of E2E fault and performance management of NSs in inter-cloud. The diagram shows a Cloud Service Customer (CSC) on the left and two Cloud Service Providers (CSP1 and CSP2) on the right. The CSC has a 'User layer'. CSP1 and CSP2 each have an 'Access layer', 'Service layer', and 'Resource layer'. Inside each CSP, there are 'Multi-layer functions' including 'Operation support systems' (OSS-NS, OSS-NF, OSS-CCS) and 'Fault and performance management' (OSS-NS, OSS-NF, OSS-CCS). A 'Use network service' arrow points from the CSC to CSP1. An 'Inter-cloud' double-headed arrow connects CSP1 and CSP2. A long arrow at the bottom, labeled 'End-to-end fault and performance management of network services in inter-cloud', spans from the CSC to CSP2. The reference Y.3527(21) is at the bottom right.
+
+**Figure 6-4 – Framework of E2E fault and performance management of NSs in inter-cloud**
+
+# 7 Functional requirements for E2E fault and performance management of NSs in inter-cloud
+
+This clause identifies functional requirements applicable for E2E fault and performance management of NSs in inter-cloud.
+
+## 7.1 Fault and performance data collection
+
+It is required that a CSP support collection of fault and performance data from all resources even in different CSPs that support the implementation of the NS.
+
+## 7.2 Fault and performance problem detection
+
+It is required that a CSP support detection of the unavailability and failures of physical and virtual resources that might cause fault or performance problems in NFs running on top of them.
+
+It is required that a CSP support filtering out dependent and routine operational events.
+
+It is recommended that a CSP support classification of detected faults into manifested or impending so that further action can accordingly be taken.
+
+## **7.3 Fault and performance problem localization**
+
+It is required that a CSP support determination of the root cause of a manifest fault by identification of the resources that are malfunctioning.
+
+It is recommended that a CSP support determination of the severity of an impending fault with which the resources may malfunction in the future.
+
+## **7.4 Fault and performance problem correlation**
+
+It is required that a CSP support mapping each fault to the impacted components of the NS.
+
+It is required that a CSP identify unavailability of virtual resources that are or will be affected by failures on the physical resources under them, or identifies VNF instances that are or will be affected by failures of the virtual resources.
+
+## **7.5 Fault handling in inter-cloud**
+
+It is recommended that a CSP support recovery of a manifest fault using an active-standby configuration.
+
+It is recommended that a CSP support handling of an impending fault using an active-standby configuration or VM migration.
+
+# **8 Security consideration**
+
+Security aspects for consideration within the cloud-computing environment are described in [ITU-T X.1601], which analyses security threats and challenges and describes security capabilities that could mitigate these threats and meet security challenges.
+
+# Appendix I
+
+## Use case of end-to-end fault and performance management of network services in inter-cloud
+
+(This appendix does not form an integral part of this Recommendation.)
+
+## I.1 Use case template
+
+The use cases developed in this appendix should adopt the unified format in Table I.1 for better readability and convenient material organization.
+
+**Table I.1 – Unified format**
+
+| | |
+|----------------------------|---------------------------------------------------------------------------------------------------------|
+| Title | The title of the use case |
+| Description | Scenario description of the use case |
+| Roles | Roles involved in the use case |
+| Figure (optional) | Figure to explain the use case, not mandatory |
+| Pre-conditions (optional) | The necessary pre-conditions that should be achieved before starting the use case. |
+| Post-conditions (optional) | The post-condition that will be carried out after the termination of current use case. |
+| Derived requirements | Requirements derived from the use cases, whose detailed description is presented in the relevant clause |
+
+### I.2 Virtual broadband service
+
+This use case illustrates fault and performance management for a virtual broadband service in inter-cloud.
+
+**Table I.2 – Virtual broadband service**
+
+| | |
+|-------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Virtual broadband service |
+| Description | CSP1 provides broadband service to CSC. The broadband service is an NS that is composed of VNFs realized as VNF1 to VNF3 and physical network functions (PNFs) realized as PNF1 to PNF2. VNF1, VNF2 and PNF1 are deployed in CSP1, VNF3 and PNF2 are deployed in CSP2. CSP1 is the primary CSP in the inter-cloud intermediary pattern.
As the operator of this NS, CSP1 should have the comprehensive topology of the NS and the relationship between of the elements, e.g., the virtual resources and their supporting physical resources, and the VNF instances and their supporting virtual resources.
During the operation of this NS, large volumes of high dimensional data in the form of markers like alarms, notifications, warnings and measurement of performance indicators are produced from both CSP1 and CSP2.
As the operator of this NS, CSP1 has the responsibility for managing the fault and performance issues to meet service level agreements (SLAs). To achieve this, CSP1 should collect all markers from CSP1 and CSP2 related to the fault and performance problems of the NS. Based on these data, CSP1 should detect any condition that has already led to or could lead to degraded performance or failure, and identify and localize manifested and impending faults.
|
+| Roles | CSC, CSP |
+
+**Table I.2 – Virtual broadband service**
+
+| | |
+|----------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional) |
Y.3527(21)
|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements | - – Fault and performance data collection (see clause 7.1)
- – Fault and performance problem detection (see clause 7.2)
- – Fault and performance problem localization (see clause 7.3)
|
+
+### I.3 Fault recovery in inter-cloud
+
+This use case illustrates the process of recovering a fault of an NS in inter-cloud.
+
+**Table I.3 – Fault recovery in inter-cloud**
+
+| | |
+|-------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Fault recovery in inter-cloud |
+| Description | CSP1 provides an NS to CSC. The NS is composed of VNFs realized as VNF1 to VNF3. VNF1 and VNF2 are deployed in CSP1, VNF3 is deployed in CSP2 with an active-standby mode. VNF3 (active) is deployed on VM5 that launched in physical machine 3 (PM3), VNF3 (standby) is deployed on VM8 that launched in PM4. CSP1 is the primary CSP in the inter-cloud intermediary pattern.
As the operator of this NS, CSP1 needs to detect faults in physical resources that can affect proper functioning of virtual resources. Once such a fault is detected, CSP1 shall find out which virtual resources and VNFs are affected by this fault, and decide how to handle it.
In this use case, VM5 and VM6 are affected by a fault in PM3. VNF3 (active) is out of function because it is deployed on VM5. To keep the availability of the NS, CSP1 shall switch the VNF3 (standby) to active state and change the access path of the NS. Then CSP1 needs to find another VM that is not hosted in PM4 to deploy VNF3 as the new standby node.
|
+| Roles | CSC, CSP |
+
+**Table I.3 – Fault recovery in inter-cloud**
+
+| | |
+|----------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional) | Image: Diagram of fault recovery in inter-cloud. It shows two Cloud Service Providers (CSP 1 and CSP 2) connected to a Central Service Controller (CSC). CSP 1 contains VNF1 and VNF2, which are connected to VM1, VM2 and VM3, VM4 respectively, all running on Physical Machines (PM1 and PM2). CSP 2 contains VNF3 (Active) and VNF3 (Standby), connected to VM5, VM6 and VM7, VM8 respectively, running on PM3 and PM4. A red 'X' is marked over PM3, indicating a hardware fault. A dashed line shows the connection from VNF3 (Active) to VNF3 (Standby). A legend at the bottom defines PM as Physical machine, VM as Virtual machine, and VNF as Virtual network function.
PM Physical machine VM Virtual machine VNF Virtual network function
Y.3527(21)
|
+| Pre-conditions (optional) | A VNF is deployed in active-standby mode and the active node is affected by a hardware fault. |
+| Post-conditions (optional) | The standby node is switched to active node. |
+| Derived requirements | - – Fault and performance problems correlation (see clause 7.4)
- – Fault handling in inter-cloud (see clause 7.5)
|
+
+### I.4 Fault prediction and handling in inter-cloud
+
+This use case illustrates the process of predicting and handling an impending fault of an NS in inter-cloud.
+
+**Table I.4 – Fault prediction and handling in inter-cloud**
+
+| | |
+|-------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Title | Fault prediction and handling in inter-cloud |
+| Description | CSP1 provides an NS to CSC. The NS is composed of VNFs realized as VNF1 to VNF3. VNF1 and VNF2 are deployed in CSP1, VNF3 is deployed in CSP2. CSP1 is the primary CSP in the inter-cloud intermediary pattern.
As the operator of this NS, CSP1 could predict some impending faults based on the data collected from the physical resources. For example, the CSP1 may find that the central processing unit temperature of PM3 is rising, then exceeding a threshold value, which may trigger a restart of the PM. In this case, CSP1 can predict an impending fault for PM3.
As VNF3 is deployed on VM5 that launched in PM3, this impending fault will affect VNF3. To keep the availability of the NS, CSP1 shall handle this impending fault. If VNF3 is configured with active-standby mode as in the use case in clause I.3, CSP1 will switch the standby node to active state and change the access path of the NS. If VNF3 is not configured in active-standby mode, CSP1 will select a healthy PM (in this use case PM4 is the healthy PM) to migrate the VNF3 to a new VM in that PM and change the access path of the NS.
|
+| Roles | CSC, CSP |
+
+**Table I.4 – Fault prediction and handling in inter-cloud**
+
+| | |
+|-----------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional)
| Image: Diagram of inter-cloud fault prediction and handling. It shows two Cloud Service Providers (CSP 1 and CSP 2) connected via a Cloud Service Center (CSC). CSP 1 contains VNF1 and VNF2, which are hosted on PM1 and PM2 respectively. VNF1 is connected to VM1 and VM2. VNF2 is connected to VM3 and VM4. CSP 2 contains VNF3 and VNF3', which are hosted on PM3 and PM4 respectively. VNF3 is connected to VM5 and VM6. VNF3' is connected to VM7 and VM8. A red question mark is placed next to PM3. A dashed arrow points from VNF3 to VNF3'. A legend at the bottom defines PM as Physical machine, VM as Virtual machine, and VNF as Virtual network function. The reference Y.3527(21) is also present.
PM Physical machine VM Virtual machine VNF Virtual network function
Y.3527(21)
|
+| Pre-conditions (optional)
| |
+| Post-conditions (optional)
| |
+| Derived requirements
| - – Fault and performance problems correlation (see clause 7.4)
- – Fault handling in inter-cloud (see clause 7.5)
|
+
+# Appendix II
+
+## A predictive model for fault and performance issues detection and localization
+
+(This appendix does not form an integral part of this Recommendation.)
+
+## II.1 Problem statement
+
+For NSs in inter-cloud, fault and performance issues can have complex origins within virtual resources, including computation, storage, networking, and VNFs. In such case, it would be very difficult to capture the intricate relationships among the features (e.g., the location of the fault, resources involved, and markers produced) and the corresponding labels (fault, no fault, impending fault, manifested fault, fault-severity, etc.) through traditional deterministic methods.
+
+Traditional failure detection methods depend on probing or running tests on hardware, which are not accessible to the NSs deployed on virtual resources. Too much probing or software testing may overload the VMs that have been optimized for the NF hosted on them. Attempts to apply other traditional methods, like rule-based approaches involving direct correlation of the markers with the faults, get mired in complexity and prove to be inadequate.
+
+The traditional deterministic methods fail to deliver in virtualized environments in which virtual resources can be dynamically scaled, migrated or destroyed. Predictive techniques are needed to identify and resolve management issues before or after they have occurred.
+
+This Recommendation provides a model based on a judicious combination of shallow as well as deep structures in machine learning to ensure carrier grade availability and reliability.
+
+### II.2 A model for fault and performance issues detection and localization
+
+The model approach has predictive and deductive properties to meet fault and performance management requirements. Run time monitoring and measurements, alarms, notifications and warnings, configuration changes, measurements and environmental factors are all used along with models trained with historical data to draw inferences about manifest fault and performance issues. Additionally, decisions about impending faults are taken using these inputs and the predictive properties of machine-learning models.
+
+
+
+```
+graph LR
+ Markers[Markers e.g., alarms, notifications] --> PreProc[Data pre-processing]
+ PreProc --> Detection
+ PreProc --> Localization
+ subgraph Detection_Box [Detection]
+ L1[Level 1 fault detection] -- Fault --> L2[Level 2 fault classification]
+ L1 -- No fault --> NoAction[No action]
+ L2 -- Impending fault --> Localization_Box
+ L2 -- Manifest fault --> Reports[Detection reports]
+ end
+ subgraph Localization_Box [Localization]
+ Deep[Deep learning model for analysing impending faults] --> Reports
+ subgraph MultiLayer [Trained multi-layer model for localization of manifest faults]
+ L1c[Level 1 coarse grain localization] --> L2f[Level 2 fine grain localization]
+ L2f --> Reports
+ end
+ end
+ L2 -- "(Elective localization)" --> Localization_Box
+ L2 -- "(Priority localization)" --> MultiLayer
+ Reports --> Impending[Impending fault reports]
+```
+
+The diagram illustrates a model for fault and performance issues detection and localization. It starts with 'Markers e.g., alarms, notifications' which feed into 'Data pre-processing'. The processed data then splits into two main paths: 'Detection' and 'Localization'. The 'Detection' path involves 'Level 1 fault detection'. If a 'Fault' is detected, it proceeds to 'Level 2 fault classification'. From here, an 'Impending fault' leads to the 'Localization' path, while a 'Manifest fault' leads to 'Detection reports'. The 'Localization' path includes a 'Deep learning model for analysing impending faults' which also leads to 'Impending fault reports'. Additionally, there is a 'Trained multi-layer model for localization of manifest faults' which consists of 'Level 1 coarse grain localization' and 'Level 2 fine grain localization', both leading to 'Localization reports'. The 'Localization' path also receives input from 'Level 2 fault classification' via '(Elective localization)' and '(Priority localization)'.
+
+Flowchart of the model for fault and performance issues detection and localization.
+
+Figure II.1 – Model for fault and performance issues detection and localization
+
+The model shown in Figure II.1 consists of three main sub-systems: data pre-processing, detection and localization. Data pre-processing involves collation and normalization of the dataset to remove biases. The pre-processing policy may also involve the reduction of features based on some criterion like correlation with the labels.
+
+The detection sub-system decides whether there is a manifest or an impending fault or a performance issue. Detection is essentially a two-stage binary classification. Firstly, it classifies the outcome into "normal performance" and "abnormal performance" or "fault" and "no fault" categories. Then for the "fault" or "abnormal performance" cases, it decides whether the problem is manifest, i.e., it has already occurred somewhere in the network in some form, or impending, i.e., it might happen in the near future.
+
+The localization sub-system fulfils the localization of the detected faults. Localization of manifested faults is taken up on priority while for the impending faults it is elective, nevertheless important. For the manifested faults, the model uses a multi-layered localization strategy using machine-learning classification models. At localization layer 1, the broad category of the manifested fault is determined, e.g., network performance problem. At localization layer 2, the system makes a finer identification of the problem to assist in the identification of its root cause, i.e., malfunctioning resources or resources subject to performance degradation. For the impending faults, a deep learning strategy uses the markers to predict the severity and location of faults.
+
+## **II.3 Markers and metrics for fault and performance issue detection and localization**
+
+During the operation, CSP networks produce large volumes of high dimensional data in the form of markers like alarms, notifications, observed behaviour, warnings, counter values and measurement of performance indicators. The markers used by CSPs are predominantly at the service and NF level.
+
+There are a large number of markers that are directly or indirectly related to the occurrence of a fault and performance issue. Events produce the markers related to communication, QoS, processing, equipment and environment. Not only do each fault and performance issue usually have multiple markers, but also many markers appear in more than one type of issue. This means that when using machine learning for fault detection and localization, feature engineering, i.e., selection of appropriate markers is required to get better results.
+
+The metrics used by CSPs to measure the health of the network provide important information about fault and performance problems at the macro level. Use of these as features in the training dataset will help learning algorithms to narrow down the scope of the localization effort.
+
+# Bibliography
+
+- [b-ITU-T Y.3500] Recommendation ITU-T Y.3500 (2014) | ISO/IEC 17788:2014, *Information technology – Cloud computing – Overview and vocabulary*.
+- [b-ITU-T Y.3511] Recommendation ITU-T Y.3511 (2014), *Framework of inter-cloud computing*.
+- [b-ITU-T Y.Suppl. 41] Recommendation ITU-T Y.Suppl. 41 (2016), *ITU-T Y.2200-series - Deployment models of service function chaining*.
+- [b-ETSI GR NFV 003] ETSI Group Report NFV 003 V1.5.1 (2020), *Network functions virtualisation (NFV); Terminology for main concepts in NFV*.
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+## Y.3531
+
+(09/2020)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Cloud Computing
+
+# --- **Cloud computing – Functional requirements for machine learning as a service**
+
+Recommendation ITU-T Y.3531
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+# GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Network control architectures and protocols | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+| | |
+|------------------------|----------------------|
+| CLOUD COMPUTING | Y.3500–Y.3599 |
+|------------------------|----------------------|
+
+| | |
+|----------|---------------|
+| BIG DATA | Y.3600–Y.3799 |
+|----------|---------------|
+
+| | |
+|-----------------------------------|---------------|
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800–Y.3999 |
+|-----------------------------------|---------------|
+
+## INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|---------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+## Recommendation ITU-T Y.3531
+
+# Cloud computing – Functional requirements for machine learning as a service
+
+## Summary
+
+Recommendation ITU-T Y.3531 provides cloud computing requirements for machine learning as a service (MLaaS), which addresses requirements from use cases. MLaaS is a cloud service category in which the capability provided to the cloud service customer is the provision and use of a machine learning (ML) framework, which is a set of functionalities for provisioning ML data, as well as training, deployment and management of an ML model.
+
+From the perspective of cloud computing service provision, Recommendation ITU-T Y.3531 provides the functional requirements for MLaaS to identify functionalities such as ML data pre-processing, ML model training and ML model testing. Also, Recommendation ITU-T Y.3531 is aligned with the cloud computing reference architecture specified in Recommendation ITU-T Y.3502.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.3531 | 2020-09-29 | 13 | 11.1002/1000/14405 |
+
+## Keywords
+
+BdaaS, big data, big data as a service, cloud computing, MlaaS, machine learning, machine learning as a service.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2020
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|---|----------------------------------------------------------------------------------------|------|
+| 1 | Scope ..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 3 |
+| 6 | Overview of machine learning..... | 3 |
+| | 6.1 Introduction to machine learning..... | 3 |
+| | 6.2 Generic process of machine learning ..... | 4 |
+| | 6.3 Machine learning ecosystem ..... | 5 |
+| 7 | Machine learning as a service..... | 7 |
+| | 7.1 System context of MLaaS ..... | 7 |
+| | 7.2 CSN:machine learning data provider ..... | 8 |
+| | 7.3 CSN:machine learning model developer..... | 9 |
+| | 7.4 CSP:machine learning service provider ..... | 9 |
+| | 7.5 CSC:machine learning service user..... | 11 |
+| 8 | Functional requirements of MLaaS ..... | 11 |
+| | 8.1 ML data collection and storage requirements ..... | 11 |
+| | 8.2 ML data labelling requirements..... | 12 |
+| | 8.3 ML data pre-processing requirements ..... | 12 |
+| | 8.4 ML data analysis and feature engineering requirements..... | 12 |
+| | 8.5 ML model training requirements..... | 13 |
+| | 8.6 ML model monitoring requirements ..... | 14 |
+| | 8.7 Trained ML model deployment and retraining requirements..... | 14 |
+| 9 | Security considerations..... | 15 |
+| | Appendix I – Use case of MLaaS for operation perspectives..... | 16 |
+| | I.1 ML data annotation and labelling management ..... | 16 |
+| | I.2 Model training with user configuration..... | 17 |
+| | I.3 Report learning result and re-training ML model..... | 18 |
+| | I.4 Distributed training with multiple worker nodes..... | 19 |
+| | I.5 Model testing and optimizing the model quality includes hyperparameter tuning..... | 21 |
+| | I.6 Model monitoring to issue alerts of abnormal or unsuspected learning process..... | 22 |
+| | I.7 Model deployment and monitoring ..... | 23 |
+| | I.8 Automated machine learning in cloud computing..... | 24 |
+
+| | Page |
+|-----------------------------------------------------------------------------------------|-------------|
+| Appendix II – Use case of MLaaS for application perspectives..... | 25 |
+| II.1 Object recognition model development in the cloud computing
environment..... | 25 |
+| II.2 Traffic speed prediction and monitoring service..... | 26 |
+| II.3 Image recognition..... | 27 |
+| II.4 Face recognition ..... | 28 |
+| II.5 Image segmentation model development ..... | 29 |
+| II.6 Generative adversarial model development ..... | 30 |
+| Bibliography..... | 32 |
+
+# Recommendation ITU-T Y.3531
+
+# Cloud computing – Functional requirements for machine learning as a service
+
+# 1 Scope
+
+This Recommendation provides system context, functional requirements and use cases for machine learning as a service (MLaaS).
+
+In particular, the scope of this Recommendation includes:
+
+- an overview of machine learning (ML);
+- an introduction to MLaaS;
+- functional requirements of MLaaS.
+
+The use cases of MLaaS are developed to derive its functional requirements.
+
+NOTE – Development of ML algorithms and methodologies lie outside the scope of this Recommendation.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- | | |
+|----------------|----------------------------------------------------------------------------------------------------------------|
+| [ITU-T Y.2201] | Recommendation ITU-T Y.2201 (2011), Requirements and capabilities for ITU-T NGN . |
+| [ITU-T Y.2701] | Recommendation ITU-T Y.2701 (2007), Security requirements for NGN release 1 . |
+| [ITU-T Y.3502] | Recommendation ITU-T Y.3502 (2014), Information technology – Cloud computing – Reference architecture . |
+| [ITU-T Y.3600] | Recommendation ITU-T Y.3600 (2015), Big data – Cloud computing based requirements and capabilities . |
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 activity** [ITU-T Y.3502]: A specified pursuit or set of tasks.
+
+**3.1.2 cloud computing** [b-ITU-T Y.3500]: Paradigm for enabling network access to a scalable and elastic pool of shareable physical or virtual resources with self-service provisioning and administration on-demand.
+
+NOTE – Examples of resources include servers, operating systems, networks, software, applications, and storage equipment.
+
+**3.1.3 cloud service** [b-ITU-T Y.3500]: One or more capabilities offered via cloud computing (3.1.2) invoked using a defined interface.
+
+**3.1.4 cloud service customer** [b-ITU-T Y.3500]: Party which is in a business relationship for the purpose of using cloud services.
+
+NOTE – A business relationship does not necessarily imply financial agreements.
+
+**3.1.5 cloud service partner** [b-ITU-T Y.3500]: Party which is engaged in support of, or auxiliary to, activities of either the cloud service provider or the cloud service customer, or both.
+
+**3.1.6 cloud service provider** [ITU-T Y.3500]: Party which makes cloud services available.
+
+**3.1.7 machine learning** [b-ITU-T Y.3172]: Processes that enable computational systems to understand data and gain knowledge from it without necessarily being explicitly programmed.
+
+NOTE 1 – This definition is adapted from [b-ETSI GR ENI 004].
+
+NOTE 2 – Supervised machine learning and unsupervised machine learning are two examples of machine learning types.
+
+**3.1.8 machine learning model** [b-ITU-T Y.3172]: Model created by applying machine learning techniques to data to learn from.
+
+NOTE 1 – A machine learning model is used to generate predictions (e.g., regression, classification, clustering) on new (untrained) data.
+
+NOTE 2 – A machine learning model may be encapsulated in a deployable fashion in the form of a software (e.g., virtual machine, container) or hardware component (e.g., IoT device).
+
+NOTE 3 – Machine learning techniques include learning algorithms (e.g., learning the function that maps input data attributes to output data).
+
+**3.1.9 metadata** [b-ITU-T H.752]: Structured, encoded data that describe characteristics of information-bearing entities to aid in the identification, discovery, assessment and management of the described entities.
+
+**3.1.10 role** [ITU-T Y.3502]: A set of activities that serves a common purpose.
+
+**3.1.11 sub-role** [ITU-T Y.3502]: A subset of the activities of a given role.
+
+## **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following terms:
+
+**3.2.1 machine learning as a service (MLaaS)**: A cloud service category in which the capabilities provided to a cloud service customer are the provision and use of a machine learning framework.
+
+**3.2.2 machine learning framework**: A set of functionalities for provisioning machine learning data, as well as training, deployment and management of a machine learning model.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-------|--------------------------------|
+| CPU | Central Processing Unit |
+| CSC | Cloud Service Customer |
+| CSN | Cloud Service partner |
+| CSP | Cloud Service Provider |
+| GAN | Generative Adversarial Network |
+| GPU | Graphics Processing Unit |
+| ML | Machine Learning |
+| MLaaS | Machine Learning as a Service |
+| MLDP | Machine Learning Data Provider |
+
+| | |
+|------|-----------------------------------|
+| MLMD | Machine Learning Model Developer |
+| MLSP | Machine Learning Service Provider |
+| MLSU | Machine Learning Service User |
+
+# 5 Conventions
+
+The following conventions are used in this Recommendation:
+
+- The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted, if conformance to this Recommendation is to be claimed.
+- The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+- The keywords "can optionally" indicate an optional requirement which is permissible, without implying any sense of being recommended. This term is not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with this Recommendation.
+
+# 6 Overview of machine learning
+
+## 6.1 Introduction to machine learning
+
+Machine learning (ML) is a technique in computer science to enable machines or computers to learn how to perform tasks without being explicitly programmed. According to the definition, the mechanism of ML is distinct from explicit programming, which applies if-then statements to make decisions. The goal of ML is to improve their ability to solve tasks automatically through data.
+
+The development of ML involves ML models, learning algorithms and training data. An ML model consists of mathematical representations for performing tasks with input data. The learning algorithm trains an ML model using training data for the task.
+
+The ML developer configures the ML model and learning algorithm, and gathers training data based on setting up tasks. The tasks are designed to solve problems by performance evaluation metrics based on computational methods. An evaluation metric is a criterion for the measurement of the performance of an ML model. Examples of general tasks for ML are prediction, classification, clustering and sample generation.
+
+ML tasks are classified according to the characteristics of the learning algorithm, such as the necessity for training data or feedback. Categories of ML task include: supervised learning; unsupervised learning; semi-supervised learning; and reinforcement learning.
+
+- **Supervised learning:** a learning task with labelled data, which maps input data to desired output data.
+- **Unsupervised learning:** a learning task with unlabelled data, which finds structures or patterns in the data.
+- **Semi-supervised learning:** a task of learning with both labelled and unlabelled data, where there is a small amount of labelled data.
+- **Reinforcement learning:** a task of learning in which an agent uses environment data to perform a task and then provides feedback.
+
+## 6.2 Generic process of machine learning
+
+The process is implemented by ML data acquisition, ML data processing, ML model development and ML model deployment. Figure 6-1 shows the generic process of ML.
+
+
+
+```
+graph LR; A[ML data acquisition] --> B[ML data processing]; B --> C[ML model development]; C --> D[ML model deployment]; subgraph A [ML data acquisition]; A1[Data collection]; A2[Data labelling (Optional)]; end; subgraph B [ML data processing]; B1[Data pre-processing]; B2[Feature engineering]; end; subgraph C [ML model development]; C1[Model training]; C2[Model validation]; C3[Hyperparameter tuning]; C4[Model testing]; end; subgraph D [ML model deployment]; D1[Model deployment]; D2[Manage model]; end;
+```
+
+The diagram illustrates the generic process of machine learning as a four-stage flowchart. Stage 1, 'ML data acquisition', includes 'Data collection' and 'Data labelling (Optional)'. Stage 2, 'ML data processing', includes 'Data pre-processing' and 'Feature engineering'. Stage 3, 'ML model development', includes 'Model training', 'Model validation', 'Hyperparameter tuning', and 'Model testing'. Stage 4, 'ML model deployment', includes 'Model deployment' and 'Manage model'. Arrows indicate the sequential flow from one stage to the next. A reference code 'Y.3531(20)\_F6-1' is located at the bottom right of the diagram.
+
+Figure 6-1: Generic process of machine learning flowchart.
+
+**Figure 6-1 – Generic process of machine learning**
+
+- **ML data acquisition** collects data for training. The collected data are grouped into datasets for training, validation and test before ML model development.
+ - **Data collection** gathers raw data, including that which is structured, unstructured and semi-structured. Within all types, data can exist in formats such as text, spreadsheet, video, audio, image and map. [ITU-T Y.3600].
+ - **Data labelling** optionally generates labelled data for supervised learning or semi-supervised learning. Human resources and labelling tools are required to annotate data. The tools use tagging units, e.g., image data use a tagging unit of a bounding box to indicate a target object and video data use a tagging unit of 5 s videos for labelling.
+- **ML data processing** handles data to improve learning performance or create meaningful information from data.
+ - **Data pre-processing** transforms data to resolve inaccurate, incomplete or outlier data. Noise and bias in raw data are removed or mitigated for training data.
+ - **Feature engineering** finds and determines the useful features for an ML model from the data. Feature engineering algorithms to implement ML include: feature selection; scaling; and extraction.
+ - **Feature selection** obtains a subset from the original features of those with the same or similar analytical results. Examples of feature selection are: genetic algorithm; greedy forward selection; and correlation feature selection.
+ - **Feature scaling** normalizes the range of data in the original features. Examples of feature scaling are: mean normalization; and min-max normalization.
+ - **Feature extraction** derives new from original features by set reduction. Examples of feature extraction are: principal component analysis; and dimensionality reduction.
+- **ML model development** trains and optimizes the ML model. Model training, model validation, model testing and hyperparameter tuning are iteratively performed to meet the purpose of the ML model.
+ - **Model training** fits the parameters of the ML model to the training dataset. Training algorithms are implemented to update parameters such as backpropagation and gradient descent. The parameters are adjusted or optimized automatically by feeding in a training dataset.
+ - **Model validation** verifies the performance of the ML model with a validation dataset. The model validation process gives the opportunity to optimize hyperparameters before ML training is completed.
+
+- **Model testing** measures the performance of the final trained ML model with the test dataset. Model testing gives the final performance report to deploy the trained ML model. Model testing prevents re-learning when the ML model performs poorly after the ML model is deployed.
+- **Hyperparameter tuning** adjusts the hyperparameters of ML model training. The hyperparameters are adjustable values for controlling ML model training. The hyperparameters include: iteration time; batch size; and epoch.
+- **ML model deployment** utilizes the model to perform tasks in applications. ML model deployment involves deployment and management of the model, including retraining performance monitoring and management.
+ - **Model deployment** loads the trained ML model into the application or hardware. The ML developer uses the trained model to develop ML applications.
+ - **Manage models** updates or monitors the ML model. In addition, manage models requests model retraining.
+
+Figure 6-2 shows an example of trained ML model development that includes the life cycle following the generic process of ML.
+
+
+
+```
+
+graph LR
+ RD1[Raw data] --> FE[Feature engineering]
+ RD2[Raw data] --> FE
+ FE --> MD[ML dataset]
+ subgraph MD [ML dataset]
+ TD[Training dataset]
+ VD[Validation dataset]
+ TeD[Test dataset]
+ end
+ MD --> MT[Model training]
+ MT --> MV[Model validation]
+ MV --> HT[Hyperparameter tuning]
+ HT --> MT
+ MV --> TeD
+ TeD --> MTest[Model testing]
+ MTest --> TMLM[Trained ML model]
+ TMLM -.->|Request retraining| FE
+
+```
+
+The diagram illustrates the generic ML process. It begins with 'Raw data' (represented by two database icons) feeding into 'Feature engineering'. The output of feature engineering is the 'ML dataset', which is divided into three sections: 'Training dataset', 'Validation dataset', and 'Test dataset'. The 'Training dataset' is used for 'Model training'. The output of model training is 'Model validation'. 'Model validation' leads to 'Hyperparameter tuning', which then feeds back into 'Model training'. 'Model validation' also leads to 'Model testing' via the 'Test dataset'. The output of 'Model testing' is the 'Trained ML model', represented by a gear icon. A dashed feedback loop labeled 'Request retraining' connects the 'Trained ML model' back to the 'Feature engineering' stage.
+
+Flowchart of the generic ML process showing the cycle from raw data to a trained ML model, including feedback loops for retraining and hyperparameter tuning.
+
+**Figure 6-2 – Example of generic ML process**
+
+In Figure 6-2, the final output of a ML process is a trained ML model that has the ability to perform tasks on devices. If a deployed trained ML model falls below acceptable performance, then the model needs to be retrained or reengineered. The deployed model is retrained using a new dataset to meet the performance required for a given purpose.
+
+To achieve its goal, ML requires well-designed models and learning algorithms, as well as an amount of data for training. Several learning algorithms and ML models have been developed to improve task-solving performance.
+
+## 6.3 Machine learning ecosystem
+
+The ML ecosystem consists of stakeholders that provide ML data, the ML model and ML framework. In this ecosystem, developers can effectively build their own ML or application.
+
+This clause describes an ML ecosystem through stakeholder roles and sub-roles. It describes the activities required for the ML roles to provide and consume ML, as well as the relationships among the roles.
+
+The ML ecosystem includes the following roles:
+
+- data provider;
+- ML model provider;
+- ML framework provider;
+- ML framework customer.
+
+The ML ecosystem is shown in Figure 6-3.
+
+
+
+The diagram illustrates the high-level machine learning ecosystem. It features four main components: a Data provider, an ML model provider, an ML framework provider, and an ML framework customer. The Data provider is a large rounded rectangle containing two sub-roles: a Data supplier (hexagon) and an ML data provider (hexagon). The Data supplier sends 'Data' to the ML data provider. The ML data provider sends 'ML data' to the ML framework provider. The ML model provider sends an 'ML model' to the ML framework provider, and the ML framework provider sends an 'ML model request/report' back to the ML model provider. The ML framework provider sends 'ML functionality' to the ML framework customer. The ML framework customer sends 'Use ML functionality' back to the ML framework provider. The ML framework provider sends a 'Data request/report' back to the ML data provider. A reference code 'Y.3531(20)\_F6-3' is located at the bottom right of the diagram.
+
+Figure 6-3 – High-level machine learning ecosystem diagram
+
+**Figure 6-3 – High-level machine learning ecosystem**
+
+### 6.3.1 Data provider
+
+The data provider (DP) role consists of two sub-roles:
+
+- data supplier;
+- ML data provider.
+
+#### 6.3.1.1 Data supplier
+
+A data supplier provides data from different sources and performs activities specified in [ITU-T Y.3600]. The data supplier's activities include:
+
+- data generation;
+- creation of metadata information describing data source(s) and relevant attributes;
+- publication of metadata information to access metadata.
+
+#### 6.3.1.2 ML data provider
+
+An ML data provider acquires data and performs data processing for ML processing. It receives data from a data supplier [ITU-T Y.3600], then sends data for ML processing to an ML framework provider. The ML data provider supports various kinds of data, e.g., structured, unstructured and streaming.
+
+The ML data provider's activities include:
+
+- analysis of features of data;
+- dataset generation for ML.
+
+NOTE 1 – Activities such as analysing data and pre-processing are described in [ITU-T Y.3600].
+
+NOTE 2 – Analysis of features from data includes labelling tasks by human resources. This activity is optional if the ML model requires labelled data for training.
+
+### **6.3.2 ML model provider**
+
+An ML model provider provides an ML model to an ML framework provider. Developing an ML model involves ML algorithms for handling data, learning models and evaluating models in the process, as well as designing the schema of the ML model.
+
+The ML model provider's activities include:
+
+- ML model development;
+- ML model provision.
+
+### **6.3.3 ML framework provider**
+
+An ML framework provider provides ML functionalities to an ML framework customer. The ML framework includes an interface for using ML functionalities. The ML framework provider also manages and reports activities to an ML framework customer to develop an ML model.
+
+The ML framework provider's activities include:
+
+- training an ML model with ML data;
+- ML model management and reporting;
+- ML model deployment for an ML application;
+- ML functionality provision to an ML framework customer.
+
+### **6.3.4 ML framework customer**
+
+An ML framework customer uses ML functionalities from an ML framework provider for business, e.g., decision making, business process automation and customer interaction. The ML framework can be an end-user or a system that performs ML-enabled applications.
+
+The ML framework customer's activities include:
+
+- ML framework access and utilization.
+
+# **7 Machine learning as a service**
+
+## **7.1 System context of MLaaS**
+
+MLaaS is a cloud service category in which the capabilities provided to a cloud service customer (CSC) are the provision and use of an ML framework. ML processing needs a large amount of computing power and resources for ML model training due to the large amount of training data and the highly complex computation involved in ML model training. MLaaS resolves the problem by providing elastic computing capabilities and resources in cloud environments based on CSC requests.
+
+The system context of MLaaS provides additional sub-roles and activities based on the architectural user viewpoint established in [ITU-T Y.3502]. This clause describes how cloud computing supports the four main roles in an ML ecosystem: ML data provider, ML model provider, ML framework provider and ML framework customer.
+
+Cloud computing sub-roles can be mapped to ML roles as shown in Table 7-1. The sub-roles of a cloud service provider (CSP), cloud service partner (CSN) and CSC mapped to the roles and sub-roles of an ML ecosystem.
+
+**Table 7-1 – Mapping of a machine learning ecosystem to an MLaaS system context**
+
+| Machine learning ecosystem | MLaaS system context |
+|----------------------------|----------------------------------------------|
+| ML data provider | CSN:MLDP (machine learning data provider) |
+| ML model provider | CSN:MLMD (machine learning model developer) |
+| ML framework provider | CSP:MLSP (machine learning service provider) |
+| ML framework customer | CSC:MLSU (machine learning service user) |
+
+Figure 7-1 illustrates the cloud computing sub-roles in MLaaS. Figure 7-1 also identifies activities specific to ML and assigns them to cloud computing sub-roles. MLaaS utilizes other sub-roles of CSP and CSN.
+
+
+
+ML ecosystem
+
+MLaaS
+
+Cloud service partner (CSN)
+
+CSN: MLDP
+
+Provide data labelling
+
+CSN: MLMD
+
+Develop ML model
+
+Register ML model
+
+Cloud service provider (CSP)
+
+CSP: MLSP
+
+Provide audit ML data
+
+Provide data feature engineering
+
+Perform ML model training
+
+Perform ML model testing
+
+Monitor and report ML model training
+
+Manage ML model deployment
+
+Manage retraining policy
+
+Cloud service customer (CSC)
+
+CSC: MLSU
+
+Use ML service
+
+MLDP: Machine learning data provider
+MLMD: Machine learning model developer
+MLSP: Machine learning service provider
+MLSU: Machine learning service user
+
+Y.3531(20)\_F7-1
+
+Figure 7-1 – MLaaS system context diagram. The diagram is divided into two main sections: 'ML ecosystem' and 'MLaaS'. The 'ML ecosystem' section shows three roles: 'ML data provider', 'ML model provider', and 'ML framework customer'. The 'MLaaS' section is further divided into three main components: 'Cloud service partner (CSN)', 'Cloud service provider (CSP)', and 'Cloud service customer (CSC)'. The 'CSN' component contains two sub-roles: 'CSN: MLDP' (with activity 'Provide data labelling') and 'CSN: MLMD' (with activities 'Develop ML model' and 'Register ML model'). The 'CSP' component contains one sub-role: 'CSP: MLSP' (with activities 'Provide audit ML data', 'Provide data feature engineering', 'Perform ML model training', 'Perform ML model testing', 'Monitor and report ML model training', 'Manage ML model deployment', and 'Manage retraining policy'). The 'CSC' component contains one sub-role: 'CSC: MLSU' (with activity 'Use ML service'). A legend at the bottom identifies the shapes: a rectangle for 'Role', a hexagon for 'Sub-role', and an oval for 'Activity'. A reference code 'Y.3531(20)\_F7-1' is located at the bottom right.
+
+**Figure 7-1 – MLaaS system context**
+
+## 7.2 CSN:machine learning data provider
+
+CSN:MLDP is a sub-role of the CSN, which provides data labelling and activities of CSN:DP as specified in [ITU-T Y.3600]. The activities of CSN:DP for data include generation, publication and brokerage. Additional activities of CSN:MLDP include:
+
+- data labelling provision.
+
+### 7.2.1 Data labelling provision
+
+Data labelling provision involves the generation of labelling information with the tools for this purpose. Human labellers manually annotate data in accordance with guidelines given by the tools. This activity involves:
+
+- labelling generation in accordance with guidelines from the CSP:MLSP;
+
+- metadata provision for labelled data;
+- CSN:DP catalogue updating for a CSP:MLSP to search ML data.
+
+## **7.3 CSN:machine learning model developer**
+
+CSN:MLMD is a sub-role of a CSN, which supports an ML model in the solution of various learning tasks. A CSN:MLMD generates an ML model catalogue for discovery and utilization of a ML model. An ML model catalogue includes ML model metadata, such as scheme, version, usage and evaluation metric.
+
+NOTE – ML model usage include the applicable learning task of an ML model.
+
+The activities of an CSN:MLMD for an ML model include:
+
+- development;
+- registration.
+
+### **7.3.1 ML model development**
+
+ML model development involves developing and updating ML models, and publication of the ML model with its information. This activity involves:
+
+- ML model development by setting initial values of a parameter;
+- ML model updating with feedback and reporting information;
+- hyperparameter configuration provision for ML model training;
+- ML model metadata generation including its usage, input/output data format and expected performance.
+
+### **7.3.2 ML model registration**
+
+ML model registration is the provision of an ML model catalogue to a CSP:MLSP. The ML model catalogue includes ML model information with metadata.
+
+NOTE – The ML model can be provided with a structured format established by ML frameworks.
+
+This activity involves:
+
+- ML model access information provision to the CSP:MLSP;
+- catalogue provision for the CSP:MLSP to search an appropriate ML model.
+
+## **7.4 CSP:machine learning service provider**
+
+CSP:MLSP is a sub-role of the CSP, which provides MLaaS including infrastructures and tools for ML model training, deployment and management. In addition, a CSP:MLSP supports the collection and auditing of ML data.
+
+NOTE – CSP:MLSP can provide the activities of CSP:BDIP specified in [ITU-T Y.3600]. The related activities of CSP:BDIP are data collection, data storage, data pre-processing and data integration.
+
+The additional activities of CSP:MLSP include:
+
+- ML data audit;
+- data feature engineering;
+- ML model training;
+- ML model testing;
+- ML model training monitoring and reporting;
+- ML model deployment management;
+- retraining policy management.
+
+### **7.4.1 ML data audit**
+
+ML data audit supports labelling tasks by providing universalized and managed tools for them. This activity encourages improvement in labelling quality and reliability of the ML dataset. This activity involves:
+
+- providing labelling environments and tools for a CSN:MLDP;
+- auditing ML data for labelling quality;
+- reporting feedback to the CSN:MLDP.
+
+### **7.4.2 Data feature engineering**
+
+Data feature engineering employs methods, such as selection, scaling and extraction from ML data, for features. Feature engineering supports expedition of the training process and manages the risk of an underperforming ML model.
+
+NOTE – The overfitting problem is an example of an underperforming ML model. Overfitting occurs when the model fits the data too closely, and fails to generalize for prediction.
+
+### **7.4.3 ML model training**
+
+ML model training executes the training process for an ML model, including its validation. This activity involves:
+
+- creation of a virtual machine and storage for ML model training;
+- triggering and operation of ML model training with input for training relevant information, such as hyperparameter configuration;
+- provision of configurations for partitioning the ML data into datasets for training, validation and test;
+- ML model performance validation;
+- registration and storage of the results of ML model training.
+
+### **7.4.4 ML model testing**
+
+ML model testing evaluates a trained ML model before it is deployed, ensuring that its performance and quality target the tasks.
+
+### **7.4.5 ML model training monitoring and reporting**
+
+ML model training monitoring and reporting support the model training process by providing functionalities such as measuring resource utilization, alerting abnormalities and automatic stopping. The report history can be utilized to detect errors in the ML model scheme and determination of retraining policy. This activity involves:
+
+- measurement and monitoring resource utilizations during ML model training;
+- reporting a problem if ML model training cannot be maintained with the ML model provided;
+- reporting the performance of the ML model during ML model training;
+- automatic stoppage if the configured threshold is exceeded.
+
+NOTE – A CSC:MLSU configures threshold values for automatic stopping, such as resource utilization overloads.
+
+### **7.4.6 ML model deployment management**
+
+ML model deployment management supports export of the trained ML model for deployment in the target computing environment. A CSP:MLSP supports transformation into multiple formats of an ML model for various computing environments. In addition, the exported models are registered for retraining and updating of the ML model catalogue.
+
+NOTE 1 – The trained ML model can be updated in the catalogue and provided to service an ML model for transfer learning.
+
+NOTE 2 – Transfer learning is a technique of application of a pre-trained ML model to a related learning task.
+
+### **7.4.7 Retraining policy management**
+
+Retraining policy management determines the process of retraining for a CSC:MLSU. Retraining ensures and maintains the performance of an ML model or improves its performance. Retraining policy considers the expected performance of a deployed model, monitoring time period, subsequent following actions, etc.
+
+## **7.5 CSC:machine learning service user**
+
+CSC:MLSU is a sub-role of the CSC, which utilizes an ML framework and cloud services to develop ML applications according to the user's intention.
+
+CSC:MLSU activity includes:
+
+- ML service use.
+
+### **7.5.1 ML service use**
+
+ML service use involves invoking and using a ML framework and cloud service to develop ML applications.
+
+# **8 Functional requirements of MLaaS**
+
+## **8.1 ML data collection and storage requirements**
+
+[ITU-T Y.3600] provides data collection and storage functional requirements in terms of big data. The functionalities of MLaaS also involve data collection and storage, and several functional requirements of these ML activities do not differ from those of big data specified in [ITU-T Y.3600].
+
+The following functional requirements are inherited from those for big data specified in [ITU-T Y.3600] by changing the role from big data to ML, such as CSP:BDIP to CSP:MLSP and CSN:DP to CSN:MLDP.
+
+The data collection and storage requirements include the following.
+
+- 1) It is required that a CSP:MLSP support the collection of data from multiple CSN:MLDPs in parallel.
+- 2) It is recommended that a CSN:MLDP expose data to the CSP:MLSP by publication of metadata.
+- 3) It is recommended that a CSP:MLSP support data collection from different CSN:MLDPs with different modes.
+
+NOTE 1 – Data can be collected in different modes, such as pull mode in which the data collection process is initiated by CSP:MLSP or push mode in which the data collection process is initiated by the CSN:MLDP.
+- 4) It is recommended that a CSN:MLDP provide a brokerage service to the CSP:MLSP for searching accessible data.
+
+NOTE 2 – Brokerage provides a data catalogue that has data information such as data specification, data instructions, electronic access methods, licence policy and data quality.
+- 5) It is required that a CSP:MLSP support different data types with sufficient storage space, elastic storage capacity and efficient control methods.
+- 6) It is required that a CSP:MLSP support storage for different data formats and data models.
+
+NOTE 3 – Data formats include text, spreadsheet, video, audio, image and map. Data models include relational models, document models, key-value models and graph models (as described in clause 6.1 of [ITU-T Y.3600]).
+
+## **8.2 ML data labelling requirements**
+
+The ML data labelling requirements include the following.
+
+- 1) It is required that a CSP:MLSP provide tools for labelling tasks for CSN:MLMD.
+NOTE 1 – The tools of labelling tasks provide different types of tagging unit for data formats such as image, video and text.
+- 2) It is required that a CSP:MLSP provide audit data for labelled ML data.
+NOTE 2 – The audit data for labelling are utilized to enhance data labelling quality such as accuracy of labelling and consistency of labelling.
+NOTE 3 – The audit data is reported to a CSN:MLDP as feedback when the request arrives or when the labelling quality is poor for developing ML model.
+- 3) It is required that a CSN:MLDP provide information about data labelling tasks.
+NOTE 4 – Information about data labelling tasks includes data type, unit of labelling and consensus majorities of labellers.
+
+## **8.3 ML data pre-processing requirements**
+
+As in clause 8.1, the following requirements are partially inherited from big data functional requirements in [ITU-T Y.3600], derived by changing the role from big data to ML such as CSP:BDIP to CSP:MLSP.
+
+The ML data pre-processing requirements include the following.
+
+- 1) It is required that a CSP:MLSP support data aggregation.
+NOTE 1 – Data from different sources can be organized in the same model or data format, as described in clause 6.1 of [ITU-T Y.3600].
+- 2) It is recommended that a CSP:MLSP support unification of data collected in different formats.
+NOTE 2 – Unification of data is used for example to unify data about persons, locations or dates extracted from web pages, pictures, videos, SNS data and calling logs to text format.
+- 3) It is recommended that a CSP:MLSP support extraction of data from unstructured data or semi-structured data into structured data.
+NOTE 3 – This requirement can be applied also to data storage.
+
+The additional requirements of ML data pre-processing not described in [ITU-T Y.3600] include the following.
+
+- 4) It is required that a CSP:MLSP provide a configuration for splitting ML data into datasets for training, validation and test.
+NOTE 4 – The training, validation and test datasets are divided completely independently.
+
+## **8.4 ML data analysis and feature engineering requirements**
+
+As in clause 8.1, the following requirements are inherited from big data functional requirements in [ITU-T Y.3600], derived by changing the role from big data to ML such as CSP:BDIP to CSP:MLSP.
+
+The ML data analysis requirements include the following.
+
+- 1) It is required that a CSP:MLSP support analysis of various data types and formats.
+- 2) It is required that a CSP:MLSP support association analysis.
+NOTE 1 – Association analysis is the task of uncovering relationships among data.
+
+- 3) it is required that a CSP:MLSP support different data analysis algorithms.
+NOTE 2 – Data analysis algorithms include those for classification, clustering, regression, association and ranking.
+
+In addition, preferences for ML data feature engineering not described in [ITU-T Y.3600] include the following.
+
+- 4) It is recommended that a CSP:MLSP provide feature selection to determine a subset of relevant features of ML data.
+- 5) It is recommended that a CSP:MLSP provide feature scaling to normalize the range of features of ML data.
+- 6) It is recommended that a CSP:MLSP provide feature extraction to generate new improved features from the original features of ML data.
+
+## 8.5 ML model training requirements
+
+The ML model training requirements include the following.
+
+- 1) It is required that a CSN:MLMD provide a registry of the ML model and catalogue to CSP:MLSP.
+- 2) It is recommended that a CSP:MLSP provide feedback on ML model usage to CSP:MLMD.
+NOTE 1 – The feedback includes applied learning tasks with high performance experienced by a CSC:MLSU. The CSP:MLMD use the feedback to update the ML model.
+- 3) It is required that a CSP:MLSP configure hyperparameter values.
+- 4) It is recommended that a CSN:MLMD provide default configuration hyperparameter values.
+- 5) It is recommended that a CSN:MLMD provide a restricted range of values for hyperparameter adjustments.
+NOTE 2 – The values in a restricted range are the adoptable hyperparameter values for the ML model.
+- 6) It is recommended that a CSP:MLSP provide a visualization of learning results.
+NOTE 3 – Examples of visualization are a chart, table, distribution plo, and graph, which show analytic information about a learning result.
+- 7) It is required that a CSP:MLSP provide ML model training operations.
+NOTE 4 – ML model training operations include initiate, stop and resume ML model training.
+- 8) It is required that a CSP:MLSP provide an ML model validation process with a validation dataset.
+- 9) It is recommended that a CSP:MLSP provide learning status monitoring during ML model training.
+NOTE 5 – Learning status includes expected learning time, applied hyperparameter set and memory usage.
+- 10) It is required that a CSP:MLSP provide performance evaluation for a trained ML model.
+- 11) It is required that a CSP:MLSP store evaluation results of trained ML models with an applied hyperparameter set.
+- 12) It is recommended that a CSP:MLSP provide hyperparameter optimization methods.
+NOTE 6 – Hyperparameter optimization involves choosing a set of optimal hyperparameters for ML model training. Examples of hyperparameter optimization methods are grid search, Bayesian optimization and evolutionary optimization.
+- 13) It is recommended that a CSP:MLSP provide automated ML model search methods.
+NOTE 7 – Automated ML model search finds the design of an ML model so as to increase the performance for the target learning task.
+
+- 14) It is recommended that a CSP:MLSP provide a transformation of ML models for use in other ML frameworks.
+- 15) It is recommended that a CSP:MLSP provide distributed ML model training.
+NOTE 8 – Distributed ML model training is the training of an ML model in multiple worker nodes to accelerate production of results.
+
+## 8.6 ML model monitoring requirements
+
+ML model monitoring requirements include the following.
+
+- 1) It is required that a CSP:MLSP provide monitoring of resource utilization during ML model training.
+NOTE 1 – Resource utilization includes a processing unit (such as a central processing unit (CPU) or graphics processing unit (GPU)), memory, storage and network utilization.
+- 2) It is recommended that a CSP:MLSP issue resource utilization overload alerts during ML model training.
+- 3) It is required that a CSP:MLSP report the history of resource utilization with timestamps.
+- 4) It is required that a CSP:MLSP provide the automatic stoppage by detecting learning failure or measuring unpromising model performance.
+NOTE 2 – Detection of learning failure includes ML parameter update failures.
+- 5) It is recommended that a CSP:MLSP set threshold values for automatic stoppage.
+NOTE 3 – Automatic stoppage is executed with user-defined threshold values to avoid unwanted early results. Unwanted results include overtraining and decreasing performance.
+- 6) It is recommended that a CSN:MLMD provide the default threshold values for automatic stoppage.
+- 7) It is required that a CSP:MLSP store the history of learning failure during ML model training.
+NOTE 4 – The history includes a log of resource utilization, performance measurement and execution of automatic stoppage.
+
+## 8.7 Trained ML model deployment and retraining requirements
+
+The trained ML model deployment and retraining requirements include the following.
+
+- 1) It is required that a CSP:MLSP provide a registry of a trained ML model.
+NOTE 1 – A trained ML model is registered with a schema including applied input/output data and ML model structures of.
+- 2) It is required that a CSP:MLSP provide trained ML model metadata.
+NOTE 2 – Trained ML model metadata includes the evaluated performance and applied hyperparameter set.
+- 3) It is required that a CSP:MLSP export a trained ML model with a format applicable to target hardware deployment.
+- 4) A CSP:MLSP can optionally provide performance monitoring for the ML model deployed.
+- 5) It is required that a CSP:MLSP provide retraining policy to manage the performance of a trained ML model.
+NOTE 3 – The retraining policy includes reset learning parameter, add new data for learning to optimize the ML model.
+- 6) It is recommended that a CSP:MLSP provide ML model retraining according to measured ML model performance.
+
+# **9 Security considerations**
+
+It is recommended that the security framework for cloud computing described in [b-ITU-T X.1601] be considered for the MLaaS. [b-ITU-T X.1601] analyses security threats and challenges in the cloud computing environment and describes security capabilities that could mitigate these threats and meet security challenges.
+
+[b-ITU-T X.1631] provides guidelines supporting the implementation of information security controls for CSCs and CSPs. Many guidelines aid CSPs to assist CSCs in implementing the controls and guide them to implement such controls. Selection of appropriate information security controls and the application of the implementation guidance provided depends on a risk assessment, as well as any legal, contractual, regulatory or other cloud-sector specific information security requirements.
+
+Relevant security requirements of [ITU-T Y.2201], [ITU-T Y.2701] and applicable ITU-T X, ITU-T Y and ITU-T M series of Recommendations need to be taken into consideration, including access control, authentication, data confidentiality, data retention policy, network security, data integrity, availability and privacy.
+
+# Appendix I
+
+## Use case of MLaaS for operation perspectives
+
+(This appendix does not form an integral part of this Recommendation.)
+
+The use cases in this appendix provide examples of operating MLaaS functionalities and related functional requirements of MLaaS.
+
+### I.1 ML data annotation and labelling management
+
+| Title | ML data annotation and labelling management |
+|----------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | This use case describes the management procedure for ML data, which includes assigning data, generating annotation, reporting result and merging ML data. The following are specific steps for managing ML data with annotators.
- 1) CSP:MLSP sets the ML data server and collects raw data from CSN:DP.
- 2) CSP:MLSP requests annotation to be assigned to raw data.
- 3) CSN:MLDP annotates raw data using the annotation method provided by CSP:MLSP.
- 4) CSN:MLDP provides the annotated dataset to CSP:MLSP.
- 5) CSP:MLSP applies the decision policy to the annotated data.
- A. CSP:MLSP decides 'accept' or 'reject' for annotated data from each annotator.
- B. CSP:MLSP saves or reports the results of quality of annotated data.
- C. CSP:MLSP merges the accepted data into the ML dataset
|
+| Role or sub-role | CSN:MLDP |
+| Figure (optional) | Image: Diagram illustrating the ML data annotation and labelling management process. The process starts with CSN:MLDP (Data #1, Data #2, ..., Data #N) sending data to CSP:MLSP (ML data set). CSP:MLSP then requests annotation from multiple CSN:MLDP (Annotator #1, ..., Annotator #K). Each CSN:MLDP (Annotator) performs an 'Annotate' action on the data, resulting in ML data #1, ML data #2, ..., ML data #N. The annotated data is then sent back to CSP:MLSP. A box below CSP:MLSP lists the steps: 1) Accept or reject annotated data, 2) Report annotated results from annotator, 3) Merge accepted data into ML data set. Dashed lines indicate the flow of data from the annotated datasets back to the ML data set.
Y.3531(20)_Fl.1
|
+| Pre-conditions (optional) | CSN:MLDP operates ML data server to schedule or assign data resources to annotators.
CSN:MLDP searches and requests raw data for annotation from CSN:DP
|
+| Post-conditions (optional) | CSN:MLDP provides an interface for reporting ML results and learning progress to CSC:MLSU. |
+
+| Title | ML data annotation and labelling management |
+|-----------------------------------------|----------------------------------------------------------------------------------------------------------------------------|
+| | CSN:MLSP stores the trained or optimized ML model for developing ML applications |
+| Derived requirements or recommendations | - – Clause 8.2 items 1), 2), 3)
- – Clause 8.1 items 1) ,3) ,5), 6)
|
+
+### I.2 Model training with user configuration
+
+| Title | Model training with user configuration |
+|-------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | This use case describes the model training procedure in cloud computing. A single machine for training is considered as default training. The following are general steps for model training in this use case.
- 1) CSP:MLSP installs a virtual machine with a machine learning engine that has an interface for model training with the user.
- 2) CSN:MLMD provides an ML model for ML training to CSP:MLSP.
- 3) CSN:MLMD provides appropriate ML data for ML model to CSP:MLSP.
NOTE – For the preparation of an ML model and data pair, CSC:MLSU requests the ML model and appropriate ML data for the model, or CSP:MLSP provides pair of ML model an ML data for CSC:MLSU. This preparation scenario lies outside the scope of this use case. - 4) CSC:MLSU configures and sets the learning policy and parameters for machine learning training.
- 5) CSP:MLSP trains the ML model and tracks the performance of the training result for reporting to CSC:MLSU.
- 6) CSP:MLSP saves the trained model and training result in the designated source
|
+| Role or sub-role | CSN:MLMD
CSN:MLDP
CSP:MLSP
CSC:MLSU |
+| Figure (optional) | Image: Diagram of the model training process showing the flow from user configuration to model training and saving results.
The diagram illustrates the model training process. At the bottom, a user icon labeled 'CSN: MLSU' sends a request (4) to a central server labeled 'CSP: MLSP'. The request includes learning policy and parameters. The server then interacts with two data sources: 'CSN: MLMD' (providing an ML model, step 2) and 'CSN: MLDP' (providing ML data, step 3). The data is fed into a virtual machine (step 1) where training occurs. The results (step 5) are saved as a 'Trained-ML model' and a 'Result data set (e.g., learning history)'. The diagram is labeled Y.3531(20)_F1.2.
|
+
+| Title | Model training with user configuration |
+|-----------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Pre-conditions (optional) | CSC:MLSU installs virtual machine with CSP to build an ML model.
CSP provides an ML framework or platform tools to build an ML model.
CSN:MLSU searches and requests ML data and model from CSN:MLDP and CSN:MLMD |
+| Post-conditions (optional) | CSP:MLSP provides the interface for reporting ML results and learning progress to CSC:MLSU.
CSP:MLSP stores the trained or optimized ML model for developing ML applications |
+| Derived requirements or recommendations | - – Clause 8.1 items 1), 2), 4)
- – Clause 8.3 items 1), 2), 3), 4)
- – Clause 8.5 items 1), 3), 6), 7), 9), 10), 11)
|
+
+### I.3 Report learning result and re-training ML model
+
+| Title | Report learning result and re-training ML model |
+|---------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | This use case describes the reporting of learning results from CSP:MLSP to CSC:MLSU, and re-training an ML model. The objective of reporting learning results is generally to give information about handling and managing an ML training configuration for CSC:MLSU. CSC:MLSU can optimize ML learning parameters and allow manual modification of ML learning policy; in addition, CSC:MLSU can request a re-training option. The following are general steps for this use case.
- 1) CSC:MLSU requests a learning report from CSP:MLSP.
- 2) CSP:MLSP transforms and visualizes the learning report on appropriate interfaces.
NOTE 1 – Visualization options can be provided to CSC:MLSU from CSP:MLSP. The raw data of the training result is the default option. - 3) CSP:MLSP reports the learning result to CSC:MLSU
- 4) CSC:MLSU analyses the learning report and manages and optimizes the learning policies.
NOTE 2 – The reset and re-training steps are the same as those in 'model training with user configuration' use case (clause I.2)
|
+| Role or sub-role | CSP:MLSP
CSC:MLSU |
+| Figure (optional) | Image: Diagram illustrating the process of reporting learning results and re-training an ML model. The diagram shows a cycle between CSP:MLSP and CSC:MLSU. CSP:MLSP is represented by a computer icon and a 'Virtual machine for ML' box. CSC:MLSU is represented by a person icon. A 'Result data set' box is shown. Step 1: CSC:MLSU requests learning results from CSP:MLSP. Step 2: CSP:MLSP visualizes the result data set, shown as a scatter plot with 'Stochastic', 'Mini-batch', and 'Batch' learning curves. Step 3: CSP:MLSP reports learning results to CSC:MLSU. Step 4: CSC:MLSU resets parameter/policy and requests re-training, which feeds back into CSP:MLSP.
The diagram illustrates the process of reporting learning results and re-training an ML model. It shows a cycle between CSP:MLSP and CSC:MLSU. CSP:MLSP is represented by a computer icon and a 'Virtual machine for ML' box. CSC:MLSU is represented by a person icon. A 'Result data set' box is shown. Step 1: CSC:MLSU requests learning results from CSP:MLSP. Step 2: CSP:MLSP visualizes the result data set, shown as a scatter plot with 'Stochastic', 'Mini-batch', and 'Batch' learning curves. Step 3: CSP:MLSP reports learning results to CSC:MLSU. Step 4: CSC:MLSU resets parameter/policy and requests re-training, which feeds back into CSP:MLSP.
Y.3531(20)_FI.3
|
+| Pre-conditions (optional) | CSN:MLSP already performs ML learning and stores backup result data for ML model |
+| Post-conditions | |
+
+| Title | Report learning result and re-training ML model |
+|-----------------------------------------|-------------------------------------------------------------------------------------------------------------------|
+| (optional) | |
+| Derived requirements or recommendations | - – Clause 8.6 items 1), 2), 3), 7)
- – Clause 8.7 item 5)
|
+
+### I.4 Distributed training with multiple worker nodes
+
+| Title | Distributed training with multiple worker nodes |
+|------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | This use case describes model training with multiple worker nodes to support parallel and distributed learning. CSC:MLSU can organize multiple worker nodes for ML training. This option has many advantages such as reductions in data size for each worker node and division of data into private and public. The following are general steps for distributed training.
- 1) CSC:MLSU designs or organizes the architecture of ML worker nodes.
- 2) CSP:MLSP provides ML management for distributed training to CSC:MLSU.
- 3) CSC:MLSU sets the distribution policy for an ML model or data and schedules policy for assigning resources and ML parameters.
- 4) CSP:MLSP assigns resources and parameters using the configured policy from CSC:MLSU.
- 5) CSP:MLSP requests ML training from each virtual or local worker node and collects the training results.
- 6) CSP:MLSP iterates steps 4) and 5) until training is completed
|
+| Role or sub-role | CSP:MLSP
CSC:MLSU |
+
+| Title | Distributed training with multiple worker nodes |
+|-----------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional) | Image: Diagram illustrating distributed training with multiple worker nodes. The top part shows '1) Allocation of learning data to multiple worker nodes' where a central 'CSC: MLSU' (represented by a person icon) distributes data (Data #1 to Data #N) to worker nodes across 'Cloud 1', 'Cloud 2', and a 'Local worker node'. The bottom part shows '2) Distributed learning and updating parameter to ML management' where worker nodes send 'Learning parameter' and 'Parameter update' information to a central 'CSP: MLSP' server.
1) Set learning parameter scheduling
2) Set connection topology
1) Allocation of learning data to multiple worker nodes
2) Distributed learning and updating parameter to ML management
Y.3531(20)_F1.4
|
+| Pre-conditions (optional) | CSP provides virtual server to manage ML parameters and control distributed learning policy.
CSP provides network connection with multiple worker nodes on other cloud and local environment |
+| Post-conditions (optional) | |
+| Derived requirements or recommendations | – Clause 8.5 items 3), 6), 7), 8), 9), 10), 15) |
+
+### I.5 Model testing and optimizing the model quality includes hyperparameter tuning
+
+| Title | Model testing and optimizing the model quality includes hyperparameter tuning |
+|-----------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | This use case describes the model testing procedure in cloud computing. The model testing or validation process is usually performed to optimize or generalize a model's performance and quality. The testing may require an iterative process to tune some model perspective resources and hyperparameters. Generally, the poor performance of an ML model results from: 1) lack of feature prediction; 2) non-optimal hyperparameters; and 3) abnormal learning data. The purpose of model testing is usually related to the resolution of problems 1) and 2). In that context, this use case mainly targets resolution of problems 1) and 2) experimentally.
The following are general steps for model testing in this use case.
- 1) CSN:MLMD requests learning result from CSP:MLSP.
- 2) CSP:MLSP reports the initial or previous learning result to CSN:MLMD.
NOTE – The model testing process can be performed iteratively. - 3) CSN:MLMD optimizes the ML model with a given dataset.
- a) CSN:MLMD tunes the hyperparameters of an ML model.
- b) CSN:MLMD adds features for ML data.
- 4) CSN:MLMD tests the ML model until the performance of ML model is qualified
|
+| Role or sub-role | CSN:MLMD
CSP:MLSP
CSC:MLSU
CSN:MLDP |
+| Figure (optional) |
Y.3531(20)_F1.5
|
+| Pre-conditions (optional) | CSP:MLSP installs a virtual machine and builds an ML model for testing.
CSP provides an ML framework or /platform tools for testing the ML model |
+| Post-conditions (optional) | CSN:MLDP provides the ML dataset for learning and testing.
CSP:MLSP stores the testing history of ML model for debugging ML.
If CSN:MLMD fails to optimize the ML model, then CSN:MLMD requests testing ML data from CSN:MLDP |
+| Derived requirements or recommendations | – Clause 8.5 items 2), 3), 4), 5), 6), 12) |
+
+### I.6 Model monitoring to issue alerts of abnormal or unsuspected learning process
+
+| Title | Model monitoring to issue alerts of abnormal or unsuspected learning process |
+|-----------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | This use case describes the function of monitoring services in MLaaS. Abnormalities during learning may be caused by many aspects that can result in failure to learn, so the CSC:MLSU or CSN:MLMD should be able to recognize an abnormal state of learning by monitoring its systems. Abnormalities during the learning process can be detected through resource overload in the hardware, such as CPU and GPU, excessively abnormal prediction results and synchronization errors of parameters. The following are general steps for model testing in this use case.
- 1) CSC:MLSU or CSN:MLMD requests job details for learning process.
- 2) CSP:MLSP reports the job details which shows current job statuses.
NOTE – Job statuses include CPU or GPU utilization, memory usage and parameter update or synchronization status. - 3) CSC:MLSU sends a request to stop the learning procedure to CSP:MLSP.
CSN:MLMD can also set an automatic stop when a learning abnormality is clearly detected. In that case, CSN:MLMD can set the values that are served by CSP:MLSP or customized by CSN:MLMD
|
+| Role or sub-role | CSN:MLMD
CSP:MLSP
CSC:MLSU
CSN:MLDP |
+| Figure (optional) |
The diagram illustrates the monitoring operations. On the left, a person icon represents CSC:MLSU. In the center, a box labeled 'CSP: MLSP' contains a section titled 'Monitoring operations' with four sub-processes: 'Resource utilization', 'Measurement of performance', 'Alert learning failure', and 'Automatic stopping'. Arrows show the flow of data: 'Request monitoring' from CSC:MLSU to CSP:MLSP, 'Provide monitoring data' from CSP:MLSP to CSC:MLSU, and an 'Alert' from CSP:MLSP to CSC:MLSU. All four sub-processes in the 'Monitoring operations' box have arrows pointing to a 'Stack log file for monitoring' represented by a cylinder icon on the right. The identifier 'Y.3531(20)_FI.6' is located at the bottom right of the diagram area.
|
+| Pre-conditions (optional) | CSP:MLSP installs virtual machine and builds ML model for testing |
+| Post-conditions (optional) | CSP:MLSP provides the interface for reporting the testing result to CSN:MLMD.
CSN:MLDP provides the ML dataset for learning and testing.
CSP:MLSP stores the testing history of ML model for debugging ML.
If CSN:MLMD fails to optimize the ML model, then CSN:MLMD requests testing ML data to CSN:MLDP |
+| Derived requirements or recommendations | - – Clause 8.5 item 10)
- – Clause 8.6 items 1), 2), 3), 4), 5), 6), 7)
|
+
+### I.7 Model deployment and monitoring
+
+| Title | Model deployment and monitoring |
+|------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | This use case describes model deployment and monitoring procedures in the cloud computing environment. Once a model has been trained, then it is deployed in production. A model-monitoring process is also needed to maintain the performance of a deployed model. In a broad sense, model deployment and monitoring in this use case includes registering, managing and monitoring stages in the cloud computing environment.
The following are general steps for model deployment and monitoring described in this use case.
- 1) CSP:MLSP registers a trained model after a training stage.
- 2) CSP:MLSP provides information about the trained model used by CSP:MLSP to develop an application service.
- 3) CSP:MLSP provides an application service using the deployed model, and monitors its performance continuously.
- 4) CSP:MLSP requests model retraining or reengineering according to the measured performance of the model and predefined policy.
- 5) CSP:MLSP retrains or reengineers a model when asked.
- 6) CSP:MLSP notifies CSP:MLSP using the model for an application service when it is retrained or reengineered.
- 7) CSC:MLSU uses the application service using the deployed model
|
+| Role or sub-role | CSP:MLSP
CSC:MLSU |
+| Figure (optional) | Image: Two flowcharts illustrating model monitoring and retraining/reengineering processes. The top flowchart, labeled 'Model monitoring and retraining a model' (Y.3531(20)_F1.7a), shows CSP:MLSP managing ML data, retraining/testing, and deploying a model. It then shows a loop where CSP:MLSP monitors the model's performance (step 1), requests retraining when needed, and updates the model (step 4). The bottom flowchart, labeled 'Model monitoring and reengineering a model' (Y.3531(20)_F1.7b), shows a similar process but with a 'Request for model reengineering' leading to a 'Manage ML data' step (step 2) before retraining/testing (step 3). Both flowcharts show CSC:MLSU using the ML service and providing results back to CSP:MLSP for monitoring.
The figure consists of two flowcharts illustrating model monitoring and retraining/reengineering processes.
Top Flowchart: Model monitoring and retraining a model (Y.3531(20)_F1.7a)
- CSP: MLSP:
- Manage ML data (white box) feeds into Retrain/test ML model (orange box, step 2).
- Retrain/test ML model feeds into Deploy ML model (orange box, step 3).
- Deploy ML model feeds into Update the model and information (blue arrow).
- CSP: MLSP (Monitoring Loop):
- Monitor ML model's performance (orange box, step 1) receives Results from CSC:MLSU.
- Monitor ML model's performance feeds into Request for model retraining when needed (red arrow).
- Request for model retraining when needed feeds into Retrain/test ML model (step 2).
- Update the model and information (blue arrow) feeds into Use updated ML model (orange box, step 4).
- CSC: MLSU:
- Use ML service (white box) receives Results from Use updated ML model (step 4).
- Use ML service feeds into Results (blue arrow) which feeds back into Monitor ML model's performance (step 1).
Bottom Flowchart: Model monitoring and reengineering a model (Y.3531(20)_F1.7b)
- CSP: MLSP:
- Manage ML data (orange box, step 2) feeds into Retrain/test ML model (orange box, step 3).
- Retrain/test ML model feeds into Deploy ML model (orange box, step 4).
- Deploy ML model feeds into Update the model and information (blue arrow).
- CSP: MLSP (Monitoring Loop):
- Monitor ML model's performance (orange box, step 1) receives Results from CSC:MLSU.
- Monitor ML model's performance feeds into Request for model reengineering (red arrow).
- Request for model reengineering feeds into Manage ML data (step 2).
- Update the model and information (blue arrow) feeds into Use updated ML model (orange box, step 5).
- CSC: MLSU:
- Use ML service (white box) receives Results from Use updated ML model (step 5).
- Use ML service feeds into Results (blue arrow) which feeds back into Monitor ML model's performance (step 1).
|
+| Pre-conditions (optional) | CSP:MLSP provides a trained model to be deployed to develop an application service |
+| Post-conditions (optional) | CSC:MLSU uses an ML application service provided by CSP:MLSP |
+| Derived requirements and recommendations | – Clause 8.7 items 1), 2), 3), 4), 5), 6) |
+
+### I.8 Automated machine learning in cloud computing
+
+| Title | Automated machine learning in cloud computing |
+|------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description
| This use case describes automated machine learning procedures in the cloud computing environment. Automated machine learning supports three main functionalities of algorithms, namely automated feature engineering, ML model search and hyperparameter optimization. To execute automated machine learning, CSC:MLSU just configures the learning task and input data. Then, automated feature engineering algorithms construct features of ML data for automatic ML model training. After feature construction, ML model search algorithms are implemented to find an ML model design by exploring the ML model catalogue. Finally, hyperparameter optimization algorithms tune hyperparameter values to maximize ML model performance.
The following are general steps for the model deployment in this use case.
- 1) CSC:MLSU sets the learning task and input data.
- 2) CSP:MLSP executes feature engineering algorithms with input data.
- 3) CSP:MLSP executes ML model search and hyperparameter optimization algorithms iteratively.
NOTE 1 – ML model search and hyperparameter optimization algorithms can be combined.
NOTE 2 – Validation of an ML model is performed during step 3).
- 4) CSP:MLSP tests the ML model output from step 3).
- a) If test performance is evaluated under target performance, then repeat step 3).
- b) Otherwise, export the trained ml model.
|
+| Role or sub-role
| CSP:MLSP
CSC:MLSU
|
+| Figure (optional)
| Image: Diagram of the Automated Machine Learning (AML) system architecture. The diagram shows the flow from input (Learning task and Data) through the Automated ML system (Feature engineering, Hyperparameter optimization, ML model search) to the output (Trained ML model). The system is managed by CSP:MLSP and CSC:MLSU. A legend indicates Input (light blue oval), Functionalities (white rectangle), and Output (dark blue rectangle).
The diagram illustrates the Automated Machine Learning (AML) system architecture. It shows the flow from input (Learning task and Data) through the Automated ML system (Feature engineering, Hyperparameter optimization, ML model search) to the output (Trained ML model). The system is managed by CSP:MLSP and CSC:MLSU. A legend indicates Input (light blue oval), Functionalities (white rectangle), and Output (dark blue rectangle).
Y.3531(20)_F1.8
|
+| Pre-conditions (optional)
| |
+| Post-conditions (optional)
| |
+| Derived requirements or recommendations
| - – Clause 8.5 items 12), 13), 14)
- – Clause 8.6 items 4), 5), 6)
|
+
+# Appendix II
+
+## Use case of MLaaS for application perspectives
+
+(This appendix does not form an integral part of this Recommendation.)
+
+The use cases in this appendix provide scenarios for operating ML applications using MLaaS and related functional requirements of MLaaS.
+
+### II.1 Object recognition model development in the cloud computing environment
+
+| Title | Object recognition model development in the cloud computing environment |
+|------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | An AI software engineer wants to concentrate on developing and testing ML models for object recognition. However, the size of the labelled dataset is not sufficient to develop and test the model. In the cloud computing environment, the engineer can access a validated ML dataset for object recognition from other engineers or companies. With the data from the cloud, engineers can build, train and manage their own recognition model by testing the performance of the model.
In this use case, the engineer who is represented as CSN:MLMD can develop an ML model in cloud computing systems with validated data from the CSN:MLDP. The following steps show the process of developing an ML model.
- 1) CSN:MLMD registers the ML model with CSP:MLSP.
- 2) CSN:MLDP prepares an ML dataset with data labelling.
- 2-1) CSN:MLDP requests raw data from CSN:DP.
- 2-2) CSN:MLDP labels the data with an object detection algorithm.
NOTE 1 – A different detection algorithm can be adopted. An example of a detection algorithm is rectangle detection and face detection with a facial landmark.
- 3) CSP:MLSP requests ML data with the information from the detection algorithm adopted.
- 4) CSP:MLSP iteratively trains the ML model with the ML dataset until it is optimized.
- a) 4-1) CSP:MLSP trains the ML model with the ML dataset with default parameter.
- b) 4-2) CSP:MLSP evaluates the trained ML model with a validation dataset.
- c) 4-3) CSP:MLSP changes the model parameter and repeats a) and b) until the model is optimized.
NOTE 2 – The ML model parameter can be different among ML models. An example of an ML model parameter is the Euclidean distance between the labelled data and validation data.
- 5) CSP:MLSP reports the performance evaluation to CSN:MLMD
|
+| Role or sub-role | CSN:MLMD
CSN:DP
CSN:MLDP
CSP:MLSP
|
+
+| Title | Object recognition model development in the cloud computing environment |
+|------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional) | Image: Diagram of Object recognition model development in the cloud computing environment. The process involves two main components: CSN:MLDP and CSP:MLSP. CSN:MLDP (top) receives raw data from CSN:DP and performs object detection (with detection algorithm*) and data labelling (e.g., Cat, Burger). CSP:MLSP (bottom) receives ML data and adopted detection algorithm from CSN:MLDP, performs training with ML data and ML model, and stores the trained ML model. CSN:MLMD (bottom left) provides ML models to CSP:MLSP. The process is numbered 1) to 5).
NOTE – Detection algorithm* = ex) Rectangle detection, and face detection with facial landmark
NOTE – Model parameter* = ex) Euclidean distance threshold between the labelled and validation data
Y.3531(20)_F11.1
|
+| Pre-conditions (optional) | CSN:MLDP searches data and requests data from CSN:DP |
+| Post-conditions (optional) | CSP:MLSP stores the trained or optimized ML model to develop ML applications |
+| Derived requirements and recommendations | - – Clause 8.2 items 1), 3), 4)
- – Clause 8.4 items 1), 3), 4)
- – Clause 8.5 items 1), 2)
|
+
+### II.2 Traffic speed prediction and monitoring service
+
+| Title | Traffic speed prediction and monitoring service |
+|------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | Traffic speed information on city roads are gathered from sensors. Traffic speed on each road after a given period, e.g., 15 min, is predicted, and the predictions used to solve traffic congestion in the city. The following is a procedure of this use case.
- 1) Raw data such as traffic speed on city roads are gathered by CSN:DP.
- 2) The gathered raw data are featured and pre-processed by CSP:MLSP, and the data used for training and validating a model.
- 3) Some machine learning models developed by CSN:MLMD are provided, and those models are used to train models by CSP:MLSP.
- 4) A prediction model is trained and validated using a training dataset.
- 5) The trained model is deployed and used to develop an application.
- 6) Data for prediction are fed into the trained model or application, and predictions are returned to the service user. The service user can use the predictions, e.g., predicted traffic speed on each road, to solve traffic congestion by controlling traffic signals
|
+| Role or sub-role | CSN:DP
CSN:MLMD
CSP:MLSP
CSU:MLSU |
+
+| Title | Traffic speed prediction and monitoring service |
+|------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional) | Image: A flowchart titled 'Traffic speed prediction and monitoring service' showing the process from data gathering to prediction. It involves roles CSN:DP, CSP:MLSP, CSN:MLMD, CSU:MLSU, and CSP:MLSP. Steps include: 1. Gathering raw data (CSN:DP), 2. Preprocessing raw data and generating training data (CSP:MLSP), 3. Developing ML models used for training (CSN:MLMD), 4. Training and validating ML model, managing and deploying trained model (CSP:MLSP), 5. Developing traffic speed prediction application and providing the service with the trained/deployed prediction model (CSP:MLSP), and 6. Using the prediction result for monitoring traffic speed and controlling traffic signals if needed (CSU:MLSU). Data flows include raw data input, training data, data input for prediction, and providing prediction results.
Y.3531(20)_F11.2
|
+| Pre-conditions (optional) | CSN:MLSP can transform raw data used for predicting traffic speed. The transformed data are fed into a trained prediction model.
The sensors for traffic observation are installed on city roads or in each vehicle to gather speed and location data from traffic using the roads
|
+| Derived requirements and recommendations | - – Clause 8.1 items 1), 3), 5)
- – Clause 8.3 items 1), 3), 4)
- – Clause 8.4 items 2), 6)
- – Clause 8.5 items 1), 3), 6), 7), 8), 9), 10), 11)
- – Clause 8.7 items 1), 2), 3), 4)
|
+
+### II.3 Image recognition
+
+| Title | Image recognition |
+|------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | CSC:MLSU who is an application developer wants to provide image recognition in applications, e.g., animal recognition. In order to improve development efficiency, CSC:MLSU can just focus on user interface interactions, and use MLaaS to implement the image recognition function. The process would include the following steps.
- 1) CSP:MLSP collects animal images with different formats from different CSP:MLDPs and stores those images.
- 2) CSP:MLSP does some pre-process work on the images like: image classification by species (e.g., cats, dogs, pigs); image conversion into the same format (e.g., convert jpg, jpeg or bmp to png); image ranking by resolution.
- 3) CSP:MLSP sends pre-processed images to CSN:MLMD to develop an ML model and uses multiple worker nodes to get training acceleration.
- 4) After training, CSN:MLMD registers an image recognition model with the CSP:MLSP.
- 5) CSP:MLSP recognizes images from those submitted using the model registered by the CSN:MLMD.
- 6) CSP:MLSP displays the results of image recognition to the CSC:MLSU.
- 7) CSC:MLSP provides accuracy, CPU usage and time cost of image recognition as feedback to CSP:MLMD
|
+| Role or sub-role | CSC:MLSU
CSP:MLSP
CSN:MLMD
CSN:MLDP
|
+
+| Title | Image recognition |
+|------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional) | Image: Sequence diagram for Image recognition process involving CSC: MLSU, CSP: MLSP, CSN: MLMD, and CSN: MLDP.
sequenceDiagram participant CSC as CSC: MLSU participant CSP as CSP: MLSP participant CSN as CSN: MLMD participant CSN as CSN: MLDP CSP->>CSN: 1. Account opening CSN-->>CSP: 3. Image recognition service selection CSP->>CSC: 4. Provide an image that needs to be recognized CSP->>CSN: 5. An image needs to be recognized CSN->>CSN: 2. Authentication and authorization CSN->>CSN: 6. Image recognizing based on ML model CSN-->>CSP: 7. Return image recognition result: "Cat" CSP->>CSC: 8. Display image recognition result: "Cat" CSN->>CSN: 9. Record usage of image recognition service for billing
The diagram illustrates the image recognition process. It involves four entities: CSC: MLSU, CSP: MLSP, CSN: MLMD, and CSN: MLDP. The process starts with '1. Account opening' from CSP: MLSP to CSN: MLMD. Then, '3. Image recognition service selection' is sent from CSN: MLMD to CSP: MLSP. CSP: MLSP then sends '4. Provide an image that needs to be recognized' to CSC: MLSU, accompanied by a cat image. Next, '5. An image needs to be recognized' is sent from CSP: MLSP to CSN: MLMD, also with the cat image. CSN: MLMD performs '2. Authentication and authorization' and '6. Image recognizing based on ML model'. It then returns '7. Return image recognition result: "Cat"' to CSP: MLSP. CSP: MLSP displays '8. Display image recognition result: "Cat"' to CSC: MLSU. Finally, CSN: MLMD records '9. Record usage of image recognition service for billing'.
|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements and recommendations | - – Clause 8.1 items 1), 3), 5), 6)
- – Clause 8.3 items 1), 2), 4)
- – Clause 8.4 items 4), 5)
- – Clause 8.5 items 1), 2)
- – Clause 8.7 item 1)
|
+
+Y.3531(20)\_F11.3
+
+### II.4 Face recognition
+
+| Title | Face recognition |
+|-------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | CSC:MLSU who is a door control system developer for a company needs to use face recognition for employee and visitor authentication. The most convenient way for the developer is to implement a face recognition function using MLaaS. The process would include the following steps.
- 1) CSP:MLSU uses a camera to collect videos taken from different angles of employees. In order to detect live, videos with spoofed faces on a screen are also collected.
- 2) CSP:MLSU uploads those videos to CSP:MLSP and splits them into a real face training set, a fake face training set and testing set through the configuration reference point of CSP:MLSP.
- 3) CSP:MLSP marks the position of face and eyes in the training sets.
- 4) CSP:MLSP sends training sets to CSN:MLMD and configures hyperparameter values to start developing an ML model. During development, CSP:MLSP can obtain the learning status from CSN:MLMD.
- 5) After the learning process, CSN:MLSP validates the trained ML models with the testing set. If the validation results meet expectations, ML models will be registered and deployed.
- 6) When a visitor comes to the company, CSP:MLSU captures a video of the visitor. Then CSP:MLSP performs face recognition for the captured video using the model deployed.
- 7) The CSP:MLSP displays the result of face recognition to the CSC:MLSU and the visitor is authenticated based on the result
|
+
+| Title | Face recognition |
+|------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Role or sub-role | CSC: MLSU
CSP: MLSP |
+| Figure (optional) | Image: Sequence diagram for Face recognition process involving CSC: MLSU, CSP: MLSP, and CSN: MLMD.
sequenceDiagram participant CSC as CSC: MLSU participant CSP as CSP: MLSP participant CSN as CSN: MLMD CSC->>CSC: 1. Collect videos taken from different angles of employees CSC->>CSP: 2. Upload videos and split them into different sets CSP->>CSP: 3. Mark face and eyes in the videos CSP->>CSN: 4. Configure hyperparameter values and start ML model development CSN-->>CSP: 5. Validate and deploy ML model CSP->>CSC: 6. Get face videos through camera for the purpose of authentication Note over CSP: 6. Two faces that need to be judged whether they are from the same person Note over CSP: Face for authentication (elderly woman icon) Note over CSP: Face for authenticated user (man icon) Note over CSP: ? (red question mark icon) CSP-->>CSC: 7. Return face recognition result: "Fail"
Y.3531(20)_F11.4
|
+| Pre-conditions (optional) | |
+| Post-conditions (optional) | |
+| Derived requirements and recommendations | - – Clause 8.2 items 1)
- – Clause 8.3 items 1), 4)
- – Clause 8.4 items 2), 6)
- – Clause 8.5 items 1), 2), 3), 4), 5), 7), 8), 11)
- – Clause 8.6 item 1)
- – Clause 8.7 item 1)
|
+
+### II.5 Image segmentation model development
+
+| Title | Image segmentation model development |
+|-------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | Image segmentation is a fundamental task for high level vision tasks such as driving a vehicle and robot navigation. Recently developed deep neural networks can perform with a large amount of training data and powerful computation resources. Thus, it is a good choice for CSN:MLMD to train and deploy a model in cloud computing environments. This use case includes the following key steps.
- 1) CSN:MLMD designs specific model parameters, such as network architecture and training loss function.
- 2) CSP:MLSP establishes the training data format and requests training data from CSN:MLDP.
- 3) CSN:MLMD requests CSP:MLSP to prepare resources with the necessary library installed (such as an ML library) for model training.
- 4) CSP:MLSP runs a training process for the model committed by CSN:MLMD and reports training status including training and validation errors.
- 5) After convergence, the trained model is registered and deployed in the cloud
|
+
+| Title | Image segmentation model development |
+|------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Role or sub-role | CSN:MLMD
CSN:MLDP
CSP:MLSP |
+| Figure (optional) | Image: Flowchart of Image Segmentation Model Development process
graph TD subgraph CSN_MLDP [CSN: MLDP] A[2. Provide training data (Labelled)] end subgraph CSN_MLMD [CSN: MLMD] B[1. Define the model structure and parameters] end subgraph CSP_MLSP [CSP: MLSP] C[3. Provides infrastructure and training environments] D[4. Run training process] E[Model file] end subgraph CSC_MLSU [CSC: MLSU] F[ ] end A -- Training data --> B B -- Model definition --> CSP_MLSP CSP_MLSP -- Model access service --> F
The diagram illustrates the workflow for image segmentation model development. It involves three main entities: CSN:MLDP, CSN:MLMD, and CSP:MLSP. CSN:MLDP provides training data (labeled) to CSN:MLMD. CSN:MLMD defines the model structure and parameters, which are then used by CSP:MLSP to provide infrastructure and training environments. CSP:MLSP runs the training process and produces a model file. Finally, the model access service is provided to CSC:MLSU. The identifier Y.3531(20)_F11.5 is noted at the bottom right of the diagram area.
|
+| Pre-conditions (optional) | |
+| Derived requirements and recommendations | - – Clause 8.1 items 1), 3), 4)
- – Clause 8.5 items 1), 2), 3), 4), 6), 9), 11), 12)
- – Clause 8.6 items 1), 3), 4)
- – Clause 8.7 item 1)
|
+
+### II.6 Generative adversarial model development
+
+| Title | Generative adversarial model development |
+|------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Description | Generative adversarial models can generate new images whose appearance is consistent with those in the training dataset, e.g., generate the image of an animal or a building. A simple generative model can be trained in an unsupervised manner, i.e., no labels are required. Neural network-based generative adversarial network (GAN) models are one effective method for image generation. However, training a GAN is usually tedious and requires lots of tuning skills. It would be convenient if the CSP can provide a training and deployment service for a CSN:MLMD. Such a use case can be fulfilled with the following steps.
- 1) CSN:MLMD requests specific training data from CSN:MLDP according to the task. For instance, if the model is to generate animals, then the training data should only contain a large number of various animals.
- 2) CSN:MLMD establishes the network architectures of generative and discriminative modules with corresponding loss functions.
- 3) CSN:MLSP prepares computation resources and starts model training. A training process will stop if the convergence condition is satisfied or the maximum number of iterations has been reached. Retraining can be executed if necessary.
- 4) After convergence, the model access method is returned to CSN:MLMD
|
+| Role or sub-role | CSN:MLDP
CSN:MLMD
CSP:MLSP |
+
+| Title | Generative adversarial model development |
+|------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Figure (optional) |
graph TD subgraph CSN_MLDP [CSN: MLDP] A[2. Provide training data (Unlabelled)] end subgraph CSN_MLMD [CSN: MLMD] B[1. Define the model structure and parameters] end subgraph CSP_MLSP [CSP: MLSP] C[3. Provides infrastructure and training environments] D[4. Run training process] E[Model file] end subgraph CSC_MLSU [CSC: MLSU] F[Model access service] end A -- Training data --> B B -- Model definition --> CSP_MLSP CSP_MLSP -- Model access service --> F
Y.3531(20)_FII.6
|
+| Pre-conditions (optional) | |
+| Derived requirements and recommendations | - – Clause 8.1 items 1), 3), 4)
- – Clause 8.5 items 1), 4), 5), 6), 7), 9)
- – Clause 8.6 items 5), 6)
- – Clause 8.7 items 1), 5)
|
+
+# Bibliography
+
+- [b-ITU-T H.752] Recommendation ITU-T H.752 (2015), *Multimedia content provisioning interface for IPTV services*.
+- [b-ITU-T X.1601] Recommendation ITU-T X.1601 (2015), *Security framework for cloud computing*.
+- [b-ITU-T X.1631] Recommendation ITU-T X.1631 (2015), *Information technology – Security techniques – Code of practice for information security controls based on ISO/IEC 27002 for cloud services*.
+- [b-ITU-T Y.3172] Recommendation ITU-T Y.3172 (2019), *Architectural framework for machine learning in future networks including IMT-2020*.
+- [b-ITU-T Y.3500] Recommendation ITU-T Y.3500 (2014), *Information technology – Cloud computing – Overview and vocabulary*.
+- [b-ETSI GR ENI 004] ETSI GR ENI 004 V2.1.1 (2019), *Experiential networked intelligence (ENI); Terminology for main concepts in ENI*.
+- [b-Han] Han, J., Kamber, M., Pei, J.. (2012), *Data mining: Concepts and techniques*, third edition., Burlington. MA: Morgan Kaufmann. 703 pp.
+- [b-He] He, X., Zhao, K., Chu, X. (2019), *AutoML: A Survey of the state-of-the-art*, arXiv preprint arXiv:1908.00709v5.
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+I n t e r n a t i o n a l T e l e c o m m u n i c a t i o n U n i o n
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+# Y.3654
+
+(02/2022)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Big Data
+
+# --- **Big data driven networking – Machine learning mechanism**
+
+Recommendation ITU-T Y.3654
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Computing power networks | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+Y.3000–Y.3499
+
+### CLOUD COMPUTING
+
+Y.3500–Y.3599
+
+### **BIG DATA**
+
+**Y.3600–Y.3799**
+
+### QUANTUM KEY DISTRIBUTION NETWORKS
+
+Y.3800–Y.3999
+
+### INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|---------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.3654
+
+# Big data driven networking – Machine learning mechanism
+
+## Summary
+
+Recommendation ITU-T Y.3654 specifies the mechanisms of machine learning in big data driven networking (bDDN). A set of related aspects of machine learning in bDDN are presented, these aspects include: overview, learning procedure, deployment, interfaces, learning path and control path, security considerations.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.3654 | 2022-02-13 | 13 | 11.1002/1000/14862 |
+
+## Keywords
+
+bDDN, machine learning.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2022
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|----|--------------------------------------------------------------------------------|-------------|
+| 1 | Scope ..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 2 |
+| 6 | Overview of mechanisms of machine learning in big data driven networking ..... | 2 |
+| 7 | The learning procedure of machine learning in bDDN ..... | 3 |
+| | 7.1 Data collection..... | 3 |
+| | 7.2 Data pre-processing ..... | 4 |
+| | 7.3 Model training ..... | 4 |
+| | 7.4 Model evaluation ..... | 4 |
+| 8 | The deployment of machine learning in bDDN ..... | 4 |
+| | 8.1 Overview of deployment of machine learning in bDDN ..... | 4 |
+| | 8.2 Deploying machine learning in network plane..... | 5 |
+| | 8.3 Deploying machine learning in big data plane ..... | 6 |
+| | 8.4 Deploying machine learning in management plane ..... | 6 |
+| | 8.5 Hybrid deploying machine learning ..... | 7 |
+| 9 | The interfaces related to machine learning in bDDN ..... | 8 |
+| 10 | The learning and control path based on machine learning in bDDN ..... | 9 |
+| 11 | Security considerations..... | 9 |
+| | Bibliography..... | 10 |
+
+
+
+# Recommendation ITU-T Y.3654
+
+# Big data driven networking – Machine learning mechanism
+
+# 1 Scope
+
+This Recommendation specifies the mechanisms of machine learning in big data driven networking, its scope includes the following aspects:
+
+- Overview
+- Learning procedure
+- Deployment
+- Related interfaces
+- Learning and control path
+- Security considerations
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- [ITU-T Y.2704] Recommendation ITU-T Y.2704 (2010), *Security mechanisms and procedures for NGN*.
+- [ITU-T Y.3172] Recommendation ITU-T Y.3172 (2019), *Architectural framework for machine learning in future networks including IMT-2020*.
+- [ITU-T Y.3180] Recommendation ITU-T Y.3180 (2022), *Mechanism of traffic awareness for application-descriptor-agnostic traffic based on machine learning*.
+- [ITU-T Y.3531] Recommendation ITU-T Y.3531 (2020), *Cloud computing – Functional requirements for machine learning as a service*.
+- [ITU-T Y.3650] Recommendation ITU-T Y.3650 (2018), *Framework of big-data-driven networking*.
+- [ITU-T Y.3652] Recommendation ITU-T Y.3652 (2020), *Big data driven networking - requirements*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 big data** [b-ITU-T Y.3600]: A paradigm for enabling the collection, storage, management, analysis and visualization, potentially under real-time constraints, of extensive datasets with heterogeneous characteristics.
+
+**3.1.2 big data driven networking (bDDN)** [ITU-T Y.3650]: Big-data-driven networking (bDDN) is a type of future network framework that collects big data from networks and
+
+applications, and generates big data intelligence based on the big data; it then provides big data intelligence to facilitate smarter and autonomous network management, operation, control, optimization and security, etc.
+
+**3.1.3 machine learning (ML)** [ITU-T Y.3172]: Processes that enable computational systems to understand data and gain knowledge from it without necessarily being explicitly programmed.
+
+**3.1.4 machine learning sandbox** [ITU-T Y.3172]: An environment in which machine learning models can be trained, tested and their effects on the network evaluated.
+
+**3.1.5 machine learning model** [ITU-T Y.3172]: Model created by applying machine learning techniques to data to learn from.
+
+## **3.2 Terms defined in this Recommendation**
+
+None.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|------|------------------------------------|
+| API | Application Programming Interface |
+| bDDN | Big Data Driven Networking |
+| C | Collector |
+| CPU | Central Processing Unit |
+| FTP | File Transfer Protocol |
+| GPU | Graphic Processing Unit |
+| HTTP | Hyper-Text Transfer Protocol |
+| INF | Interface |
+| L-ML | Local Machine Learning |
+| M | Model |
+| ML | Machine Learning |
+| PP | Pre-Processing |
+| R-ML | Remote Machine Learning |
+| SNMP | Simple Network Management Protocol |
+| SRC | Source |
+
+# **5 Conventions**
+
+In the body of this Recommendation, the words shall, should and may sometimes appear, in which case they are to be interpreted, respectively, as is required to, is recommended to, and can optionally. The appearance of such phrases or keywords in an appendix or in material explicitly marked as informative are to be interpreted as having no normative intent.
+
+# **6 Overview of mechanisms of machine learning in big data driven networking**
+
+Big-data-driven networking (bDDN) is a type of future network framework that collects big data from networks and applications, and generates big data intelligence based on the big data; it then provides big data intelligence to facilitate smarter and autonomous network management, operation, control, optimization and security, etc. In [ITU-T Y.3650], the bDDN framework is made up of three planes – big data plane, management plane and network plane. Additionally, each plane in bDDN has sub-layers.
+
+Machine learning (ML) provides a way to teach a computational system to learn knowledge using data without necessarily being explicitly programmed in order to realize complicated tasks such as characteristic detection or behaviour prediction. ML has become an important technical trend, networks operators are trying to find a way to utilize ML for better network performance. In [ITU-T Y.3531], machine learning is classified as: supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning, according to the characteristics of the learning algorithm. To integrate ML into a network, it should be noted that,
+
+- i ML builds a mathematical model based on sample data known as training data, data is the basis of ML,
+- ii the purpose of incorporating ML into a network is for a better network performance by using the output of ML to control or operate the network.
+
+The framework of bDDN is a good fit for using ML in a network, the big data plane collects various data from the network which can be used for model training, the output of the ML can be used on the network plane and the management plane. As described in [ITU-T Y.3650], ML can be efficient in many cases, such as troubleshooting of network problems, network traffic prediction, traffic optimization adjustment, network security auditing, etc. When ML cooperates with bDDN, it can be applied to everywhere in bDDN, for example in the big data sensing layer of the big data plane, ML can be used for application-descriptor-agnostic traffic awareness [ITU-T Y.3180], in the network control layer of the network plane ML can be used for cellular network traffic scheduling.
+
+# 7 The learning procedure of machine learning in bDDN
+
+When applying ML in bDDN, the learning procedure is mainly mapping to the big data plane of bDDN which is composed of four layers: network big data sensing, network big data repository, network big data analyser and network intelligence and service. Figure 7-1 shows the general procedure of machine learning in bDDN. (The ellipse in Figure 7-1 maps the procedure to the big data plane of bDDN.)
+
+
+
+Figure 7-1: The learning procedure of ML in bDDN. The diagram shows a flowchart within a dashed box. On the left, a vertical stack of four boxes represents the 'Big data plane': 'Network intelligence and service', 'Network big data analyser', 'Network big data repository', and 'Network big data sensing'. On the right, a vertical stack of four boxes represents the ML process: 'Data collection', 'Data pre-processing', 'Model training', and 'Model evolution'. Arrows indicate the flow: 'Data collection' feeds into 'Data pre-processing', which feeds into 'Model training', which feeds into 'Model evolution'. A feedback loop arrow goes from 'Model evolution' back to 'Model training'. A dashed line connects 'Model evolution' to 'Network intelligence and service'. Another dashed line connects 'Network big data sensing' to 'Data collection'.
+
+**Figure 7-1 – The learning procedure of ML in bDDN**
+
+## 7.1 Data collection
+
+Machine learning in bDDN relies on the data collected from the network, it requires specified data for a given networking problem. In general, data collection can be achieved in two phases – offline and online. Offline data collection allows a large amount of historical data for model training and testing to be gathered. Real-time network data collected in the online phase can be used as feedback to the model, or as input for re-training the model. The data sensing layer of the big data plane in bDDN supports multiple methods and data collection interfaces, such as simple network
+
+management protocol (SNMP), file transfer protocol (FTP), hyper-text transfer protocol (HTTP), Restful service, etc. [ITU-T Y.3652], and collects various data from the network including the traffic data, network device performance data, network management data and network operation data. In addition, the big data plane also collects some external circumstance data that may have an impact on networks. The data collected in the big data plane contains lots of information about the true status of the network and is very helpful for network operation, maintenance and optimization.
+
+## **7.2 Data pre-processing**
+
+The ML learns by using large amounts of training data to adjust its internal parameters until it can reliably discriminate similar patterns in data it has not seen before. By its very nature, ML is acutely sensitive to the quality of the data, high quality datasets are essential for developing machine learning models. While the raw data collected in the big data plane of bDDN usually occurs with low quality, so it is necessary to pre-process the data before training. The main pre-processing includes handling null values, data standardization, handling categorical variables, etc. Feature engineering is also a vital part. With feature engineering the performance of a certain ML algorithm may be improved significantly. Feature engineering includes feature selection, feature scaling and feature extraction [ITU-T Y.3531]. Furthermore, data labelling is necessary for supervised learning and semi-supervised learning.
+
+## **7.3 Model training**
+
+There are many models that have been created over the years, while different algorithms are for different tasks. For a certain task, choosing the suitable model will have a significant impact on the effect. Then moving on to the model training, the pre-processed data is divided into two parts, training data and testing data. The model learns specific parameters over the training data, such parameters will minimize the loss or how badly it performs on the training dataset. The big data analyser layer usually has sufficient available computing resources, such as central processing unit (CPU) and graphic processing unit (GPU), which can accelerate ML model training.
+
+## **7.4 Model evaluation**
+
+Once the ML model has been built, it is crucial to gauge the performance of the ML model. The performance metrics can be used to measure the different aspects of the model, such as reliability, robustness, accuracy and complexity. The model tries to perform on the testing dataset using the knowledge gained from the training dataset. The performance of the model can further be improved on the training dataset and the testing dataset using various techniques, or by trying multiple machines learning algorithms and using the one that performs best.
+
+NOTE – The aforementioned procedure is the common procedure of ML in bDDN. In the case of reinforcement learning, the pre-preparation of training dataset and testing dataset, in which the intelligent agent learns by maximizing the reward, is not very necessary.
+
+# **8 The deployment of machine learning in bDDN**
+
+## **8.1 Overview of deployment of machine learning in bDDN**
+
+After the ML model is trained, it shall be deployed in bDDN to solve specified problems. To minimize the impact on the live network, the ML model could be performed in a machine learning sandbox [ITU-T Y.3172] before deploying.
+
+When deploying the ML model in bDDN, the data collected through collector (C) from the source node (SRC) is taken as the input of the trained ML model (M) after optional pre-processing (PP), and the output of the ML model is applied to the target node (SINK). In most use case, the ML is deployed in a remote machine learning system (R-ML) in which the C, PP M node will be implemented in the big data plane, the ML model is deployed in the big data analyser layer, and acts
+
+on the SINK through restful application programming interface (API) or other interfaces (INF) powered by the network intelligence and service layer. In R-ML, it takes full advantage of bDDN which integrates the big data capability and computing resources, the underlying network nodes will need no or only need slight modifications.
+
+For the cases that require a real-time control, the R-ML will not fit well, and the ML shall be deployed in a local machine learning system (L-ML) in which the ML will be deployed as near to the target node as possible to minimize the time delay. In L-ML the underlying network nodes may need be updated for computing and storage resources to deploy the ML.
+
+Figure 8-1 shows the R-ML and L-ML deployment in bDDN.
+
+
+
+Figure 8-1: R-ML and L-ML deployment in bDDN. The diagram illustrates two deployment models: R-ML (Remote Machine Learning) and L-ML (Local Machine Learning) within a bDDN architecture. A legend indicates that red squares represent 'Service for egress (Producer)' and green squares represent 'Service for ingress (Consumer)'. The 'Big data plane' on the left contains four layers: 'Data intelligence and service' (INF), 'Network big data analyser' (M), 'Network big data repository' (PP), and 'Network big data sensing' (C). The 'Network and management plane' on the right contains three layers: 'SINK', 'M' (Machine Learning), and 'PP' (Policy and Control), with a 'SRC' (Source) at the bottom. In the R-ML model, data flows from SRC to SINK, then to INF, M, PP, and C in the Big data plane. In the L-ML model, data flows from SRC to SINK, then to M, PP, and C in the Network and management plane. The diagram is labeled Y.3654(22) at the bottom right.
+
+**Figure 8-1 – R-ML and L-ML deployment in bDDN**
+
+According to the location of the data source and the target node in bDDN, the deployment of ML in bDDN can be classified into four types presented in clauses 8.2 to 8.5.
+
+## 8.2 Deploying machine learning in network plane
+
+Generally, machine learning functions can be realized in the network control layer or application layer of the network plane. Controller in the control layer is usually extensible and a lot of high-level functions including machine learning can be realized in the controller. In the meantime, application components in the application layer can also be designed to support machine learning functions. For example, the ML can be used for radio resource management [b-ITU-T Y-Sup.55].
+
+Figure 8-2 describes such an approach. In Figure 8-2 the dash line between SRC and SINK node means there may be other ML functions between SRC and SINK node.
+
+
+
+Y.3654(22)
+
+Figure 8-2: Deploying machine learning in network plane of bDDN. The diagram shows a 'Network plane' box containing three stacked components: 'Application', 'Network controller', and 'Network infrastructure'. To the right of these components are two blue boxes labeled 'SINK' (top) and 'SRC' (bottom). Each box has a small red square on its left and a small green square on its right. A dashed blue line connects the green square of the SRC box to the red square of the SINK box, passing through the 'Network controller' component.
+
+**Figure 8-2 – Deploying machine learning in network plane of bDDN**
+
+## 8.3 Deploying machine learning in big data plane
+
+Generally, the ML model is training in the big data plane, and it can also be deployed in the big data plane. For example, it can be used in the network big data sensing layer for application-descriptor-agnostic traffic awareness [ITU-T Y.3180] and for traffic classification, and it can be used to estimate the data volume so that the big data repository can be expanded in time.
+
+Figure 8-3 illustrates the approach to deploy ML in the big data plane.
+
+
+
+Y.3654(22)
+
+Figure 8-3: Deploying machine learning in big-data plane of bDDN. The diagram shows a 'Big data plane' box containing four stacked components: 'Data intelligence and service', 'Network big data analyser', 'Network big data repository', and 'Network big data sensing'. To the right of these components are two blue boxes labeled 'SINK' (top) and 'SRC' (bottom). Each box has a small red square on its left and a small green square on its right. A dashed blue line connects the green square of the SRC box to the red square of the SINK box, passing through the 'Network big data sensing' and 'Network big data repository' components.
+
+**Figure 8-3 – Deploying machine learning in big-data plane of bDDN**
+
+## 8.4 Deploying machine learning in management plane
+
+The ML model can also be deployed in the management plane. Under such circumstances, it is proper to realize machine learning functions in the network marketing and operation layer. The ML can be used for automatic network maintenance.
+
+Figure 8-4 illustrates the approach to deploy ML in the management plane.
+
+
+
+Y.3654(22)
+
+Figure 8-4: Deploying machine learning in management plane of bDDN. The diagram shows a single 'Management plane' box containing three stacked components: 'Network maintenance', 'Network administration', and 'Network marketing and operation'. To the right of these components are two blue boxes labeled 'SINK' (top) and 'SRC' (bottom). Each box has a small red square on its top-left and a small green square on its top-right. A dashed blue line connects the green square of the top 'SINK' to the green square of the bottom 'SRC', and another dashed blue line connects the red square of the bottom 'SRC' to the red square of the top 'SINK', forming a loop.
+
+**Figure 8-4 – Deploying machine learning in management plane of bDDN**
+
+## 8.5 Hybrid deploying machine learning
+
+In other cases, the ML model is not deployed in a single plane. The SRC node and the SINK node are in different planes. ML can be used for power management by estimating the usage of the network according to the user data collected from the network plane, and the corresponding network devices can be turned off to save energy.
+
+Figure 8-5 illustrates the approach to deploy ML by cooperating different components.
+
+
+
+Y.3654(22)
+
+Figure 8-5: Hybrid deploying machine learning in bDDN. The diagram is divided into two main sections: 'Network plane' (top) and 'Management plane' (bottom). The 'Network plane' contains 'Application', 'Network controller', and 'Network infrastructure' components. It features a 'SRC' node (blue box with red and green squares) and a 'SINK' node (blue box with red and green squares). The 'Management plane' contains 'Network maintenance', 'Network administration', and 'Network marketing and operation' components. It also features a 'SINK' node (blue box with red and green squares) and a 'SRC' node (blue box with red and green squares). A dashed blue line connects the green square of the 'SRC' in the Network plane to the green square of the 'SINK' in the Management plane. A dashed yellow line connects the red square of the 'SINK' in the Network plane to the red square of the 'SRC' in the Management plane.
+
+**Figure 8-5 – Hybrid deploying machine learning in bDDN**
+
+
+
+Y.3654(22)
+
+Figure 9-1: Interfaces related to ML in bDDN. The diagram shows a central 'Machine learning module' (blue box) connected to three planes: 'Big data plane', 'Network plane', and 'Management plane'. The 'Big data plane' contains 'Data intelligence and service', 'Network big data analyser', 'Network big data repository', and 'Network big data sensing'. The 'Network plane' contains 'Application', 'Network controller', and 'Network infrastructure'. The 'Management plane' contains 'Network maintenance', 'Network administration', and 'Network marketing and operation'. The interfaces are labeled: 'iMB' connects the Machine learning module to the Big data plane; 'iMN' connects the Machine learning module to the Network plane; and 'iMM' connects the Machine learning module to the Management plane.
+
+**Figure 9-1 – Interfaces related to ML in bDDN**
+
+Figure 9-1 shows the interfaces related to ML in bDDN. In the bDDN framework, the learning procedure of ML refers to the big data sensing layer, the big data repository layer and the big data analyser layer of the big data plane. The deployment of ML in bDDN refers to all three planes. The machine learning module interacts with big data plane via interface iMB, interacts with network plane via interface iMN, and interacts with management plane via interface iMM.
+
+NOTE – the machine learning module is a logical module that contains the functions related to the learning procedure and deployment of ML in bDDN.
+
+- iMB: the interface between the machine learning module and big data plane of bDDN. In the learning procedure the big data plane collects, or pre-processes the training and testing datasets, and provides the computing resources for model training and model evaluation via iMB. In the deployment of ML, firstly the output of machine learning can be applied to the big data plane (deploying machine learning in big data plane) via iMB. Secondly in R-ML deployment, the network intelligence and service layer delivers the output of ML to the target nodes in the network plane and the management plane via iMB.
+- iMN: the interface between machine learning module and network plane of bDDN. In L-ML deployment the network plane provides the pre-processed source data via iMN, and the output of ML applied to the network plane via iMN. In R-ML deployment the output of the machine learning module is applied to the network plane through iMN, the interface between the big data plane and network plane [ITU-T Y.3650].
+- iMM: the interface between machine learning module and manage plane of bDDN. In L-ML deployment the management plane provides the pre-processed source data via iMM, and the output of ML applied to the management plane via iMM. In R-ML deployment the output of the machine learning module is applied to the network plane through the iMB, the interface between big data plane and management plane [ITU-T Y.3650].
+
+# **10 The learning and control path based on machine learning in bDDN**
+
+## **The learning path**
+
+The learning path is to learn the machine learning model from the big data generated in bDDN. The learning path starts from the big data sensing layer and goes through the big data plane. It refers to the data collection, data pre-processing, model training and model evolution steps in clause 7.
+
+## **The control path**
+
+When the machine learning model is ready, it can be deployed to bDDN for control to achieve a better network performance. As described in clause 8, the ML model can be deployed in all the three planes of bDDN.
+
+In general, the learning path and control path is looped, the model, as the output of the learning path is the input of the control path and is deployed to the network in the control path. In addition, the control effect can react to the learning path to update the model, which can keep the model adaptive to the complex network environment.
+
+# **11 Security considerations**
+
+When applying machine learning for big data driven networking, security best practices should be adopted such as authentication, authorization and access control as described in [ITU-T Y.2704]. The big data used for machine learning applying to big data driven networking should be protected in order to avoid leaking and being destroyed.
+
+# Bibliography
+
+- [b-ITU-T Y.3600] Recommendation ITU-T Y.3600 (2015), *Big data – Cloud computing based requirements and capabilities*.
+- [b-ITU-T Y-Sup.55] ITU-T Supplement 55 to Y.3170-series (2019), *Machine learning in future networks including IMT-2020: use cases*.
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation
+
+## **ITU-T Y.3657 (12/2023)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Big Data
+
+## --- **Big data driven networking – Requirements and capabilities of network visibility**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+### Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+| | |
+|--------------------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | Y.100-Y.999 |
+| General | Y.100-Y.199 |
+| Services, applications and middleware | Y.200-Y.299 |
+| Network aspects | Y.300-Y.399 |
+| Interfaces and protocols | Y.400-Y.499 |
+| Numbering, addressing and naming | Y.500-Y.599 |
+| Operation, administration and maintenance | Y.600-Y.699 |
+| Security | Y.700-Y.799 |
+| Performances | Y.800-Y.899 |
+| INTERNET PROTOCOL ASPECTS | Y.1000-Y.1999 |
+| General | Y.1000-Y.1099 |
+| Services and applications | Y.1100-Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200-Y.1299 |
+| Transport | Y.1300-Y.1399 |
+| Interworking | Y.1400-Y.1499 |
+| Quality of service and network performance | Y.1500-Y.1599 |
+| Signalling | Y.1600-Y.1699 |
+| Operation, administration and maintenance | Y.1700-Y.1799 |
+| Charging | Y.1800-Y.1899 |
+| IPTV over NGN | Y.1900-Y.1999 |
+| NEXT GENERATION NETWORKS | Y.2000-Y.2999 |
+| Frameworks and functional architecture models | Y.2000-Y.2099 |
+| Quality of Service and performance | Y.2100-Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200-Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250-Y.2299 |
+| Enhancements to NGN | Y.2300-Y.2399 |
+| Network management | Y.2400-Y.2499 |
+| Computing power networks | Y.2500-Y.2599 |
+| Packet-based Networks | Y.2600-Y.2699 |
+| Security | Y.2700-Y.2799 |
+| Generalized mobility | Y.2800-Y.2899 |
+| Carrier grade open environment | Y.2900-Y.2999 |
+| FUTURE NETWORKS | Y.3000-Y.3499 |
+| CLOUD COMPUTING | Y.3500-Y.3599 |
+| BIG DATA | Y.3600-Y.3799 |
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800-Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | Y.4000-Y.4999 |
+| General | Y.4000-Y.4049 |
+| Definitions and terminologies | Y.4050-Y.4099 |
+| Requirements and use cases | Y.4100-Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250-Y.4399 |
+| Frameworks, architectures and protocols | Y.4400-Y.4549 |
+| Services, applications, computation and data processing | Y.4550-Y.4699 |
+| Management, control and performance | Y.4700-Y.4799 |
+| Identification and security | Y.4800-Y.4899 |
+| Evaluation and assessment | Y.4900-Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.3657
+
+## Big data driven networking – Requirements and capabilities of network visibility
+
+## Summary
+
+Recommendation ITU-T Y.3657 specifies requirements and capabilities of network visibility for big-data-driven networking (bDDN). It focuses on the scenario where network infrastructure layer of bDDN corresponds to Internet protocol (IP) bearer network.
+
+The scope of this Recommendation includes the following aspects of network visibility of bDDN: overview for network visibility of big-data-driven networking, requirements and capabilities for network visibility of the control aspect, requirements and capabilities for network visibility of the forwarding aspect, requirements and capabilities for network visibility of the management aspect, interface requirements for network visibility and security considerations.
+
+## History \*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T Y.3657 | 2023-12-14 | 13 | 11.1002/1000/15748 |
+
+## Keywords
+
+Big-data-driven networking (bDDN), capabilities, IP bearer network, network visibility, requirements.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+### NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2024
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|----|--------------------------------------------------------------------------------------------|-------------|
+| 1 | Scope..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 4 |
+| 6 | Introduction..... | 4 |
+| 7 | Overview for network visibility of bDDN..... | 4 |
+| | 7.1 Network telemetry ..... | 4 |
+| | 7.2 Overview of network visibility based on bDDN..... | 5 |
+| 8 | Requirements and capabilities for network visibility of control aspect of bDDN ..... | 7 |
+| | 8.1 Requirements for network visibility of the control aspect of bDDN ..... | 7 |
+| | 8.2 Capabilities for network visibility of the control aspect of bDDN ..... | 15 |
+| 9 | Requirements and capabilities for network visibility of the forwarding aspect of bDDN..... | 15 |
+| | 9.1 Requirements for network visibility of the forwarding aspect of bDDN..... | 15 |
+| | 9.2 Capabilities for network visibility of the forwarding aspect of bDDN..... | 20 |
+| 10 | Requirements and capabilities for network visibility of the management aspect of bDDN..... | 20 |
+| | 10.1 Requirements for network visibility of the management aspect of bDDN .... | 21 |
+| | 10.2 Capabilities for network visibility of the management aspect of bDDN ..... | 23 |
+| 11 | Interface requirements for network visibility of bDDN ..... | 23 |
+| | 11.1 NETCONF..... | 24 |
+| | 11.2 gRPC network management interface (gNMI)..... | 25 |
+| | 11.3 UDP based publication channel (UPC) ..... | 27 |
+| | 11.4 BGP-LS ..... | 27 |
+| | 11.5 BMP..... | 28 |
+| | 11.6 Other interfaces ..... | 28 |
+| 12 | Requirements for network visibility of other aspects ..... | 29 |
+| | 12.1 Requirements for the visibility of real-time congestion ..... | 29 |
+| | 12.2 Requirements for the visibility of real-time link quality ..... | 31 |
+| 13 | Security considerations ..... | 33 |
+| | Bibliography..... | 34 |
+
+
+
+# Recommendation ITU-T Y.3657
+
+## Big data driven networking – Requirements and capabilities of network visibility
+
+# 1 Scope
+
+This Recommendation studies requirements and capabilities for network visibility of big-data-driven networking, which focuses on network visibility for bDDN in the scenario where the network infrastructure layer of big data driven networking (bDDN) corresponds to the Internet protocol (IP) bearer network.
+
+The scope of this Recommendation includes:
+
+- Overview for network visibility of bDDN;
+- Requirements and capabilities for network visibility of the control aspect of bDDN;
+- Requirements and capabilities for network visibility of the forwarding aspect of bDDN;
+- Requirements and capabilities for network visibility of the management aspect of bDDN;
+- Interface requirements for network visibility of bDDN;
+- Security considerations.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- [ITU-T Y.2704] Recommendation ITU-T Y.2704 (2007), *Security mechanisms and procedures for NGN*.
+- [ITU-T Y.3600] Recommendation ITU-T Y.3600 (2015), *Big data – Cloud computing based requirements and capabilities*.
+- [ITU-T Y.3650] Recommendation ITU-T Y.3650 (2018), *Framework of big-data-driven networking*.
+- [ITU-T Y.3652] Recommendation ITU-T Y.3652 (2020), *Big data driven networking – requirements*.
+
+# 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following term defined elsewhere:
+
+**3.1.1 big data driven networking (bDDN)** [ITU-T Y.3650]: A type of future network framework that collects big data from networks and applications, and generates big data intelligence based on the big data; it then provides big data intelligence to facilitate smarter and autonomous network management, operation, control, optimization and security, etc.
+
+### 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following term:
+
+**3.2.1 network visibility:** The ability for the network management and control entity to sense the state and behaviour of a network by collecting comprehensive network data.
+
+NOTE – Network visibility is essential and beneficial to network operation, maintenance and management.
+
+## 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-------|-----------------------------------------------------|
+| ACL | Access Control List |
+| AI | Artificial Intelligence |
+| ARP | Address Resolution Protocol |
+| bDDN | big Data Driven Networking |
+| BFD | Bidirectional Forwarding Detection |
+| BGP | Border Gateway Protocol |
+| BMP | BGP Monitoring Protocol |
+| BSID | Binding Segment Identification |
+| CLI | Command-Line Interface |
+| CRC | Cyclic Redundancy Check |
+| CPU | Central Processing Unit |
+| EVPN | Ethernet Virtual Private Network |
+| GR | Graceful Restart |
+| gRPC | Google Remote Procedure Calls |
+| IFIT | In-situ Flow Information Telemetry |
+| IGP | Interior Gateway Protocol |
+| IGMP | Internet Group Management Protocol |
+| IOAM | In-situ Operations, Administration, and Maintenance |
+| IP | Internet Protocol |
+| IPFIX | IP Flow Information Export |
+| IS-IS | Intermediate System-to-Intermediate System |
+| ISP | Internet Service Provider |
+| LDP | Label Distribution Protocol |
+| LLDP | Link Layer Discovery Protocol |
+| L2VPN | Layer 2 Virtual Private Network |
+| L3VPN | Layer 3 Virtual Private Network |
+| LSA | Link-State Advertisement |
+| LSDB | Link-State Data Base |
+| LSP | Label Switching Path |
+
+| | |
+|---------|----------------------------------------------------|
+| LSR | Label Switching Router |
+| MAC | Media Access Control |
+| MIB | Management Information Base |
+| ML | Machine learning |
+| MLD | Multicast Listener Discover |
+| MPLS | Multi-Protocol Label Switching |
+| MPLS-TE | Multi-Protocol Label Switching-Traffic Engineering |
+| MTU | Maximum Transmission Unit |
+| NBMA | Non-Broadcast Multiple Access |
+| NDP | Neighbour Discovery Protocol |
+| NETCONF | Network Configuration protocol |
+| NMS | Network Management System |
+| NSSA | Not-So-Stubby Area |
+| OAM | Operation, Administration and Maintenance |
+| OSPF | Open Shortest Path First |
+| PIM | Protocol Independent Multicast |
+| PW | Pseudo Wire |
+| QoE | Quality of Experience |
+| QoS | Quality of Service |
+| RIB | Routing Information Base |
+| RPC | Remote Process Call |
+| RPF | Reverse Path Forwarding |
+| RSVP | Resource Reservation Protocol |
+| SLA | Service Level Agreement |
+| SNMP | Simple Network Management Protocol |
+| SR | Segment Routing |
+| SRv6 | Segment Routing over IPv6 |
+| STAMP | Simple Two-way Active Measurement Protocol |
+| TCP | Transfer Control Protocol |
+| TWAMP | Tow-Way Active Measurement Protocol |
+| VC | Virtual Circuit |
+| UPC | UDP based Publication Channel |
+| VPN | Virtual Private Network |
+| VRF | Virtual Routing and Forwarding |
+| XML | Extensible Markup Language |
+| YANG | Yet Another Next Generation |
+
+# **5 Conventions**
+
+In this Recommendation:
+
+The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted, if conformance to this Recommendation is to be claimed.
+
+The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required.
+
+The keywords "can optionally" indicate an optional requirement which is permissible, without implying any sense of being recommended. This term is not intended to imply that the vendor's implementation must provide the option, and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with this Recommendation.
+
+# **6 Introduction**
+
+The future network should no longer be a vehicle only for best effort connectivity, but a programmable infrastructure of connectivity and applications supporting vital and high precision services that require low latency and extremely high reliability communications. How to guarantee the quality of service (QoS) and improve user quality of experience (QoE) will be a major challenge for IP bearer networks, widely adopted by telecom operators to carry telecommunication services. The conventional network management system (NMS) cannot provide real-time network visibility and traffic visibility. Network visibility is the ability of management tools to see the state and behaviour of a network. It is essential for successful network operation, management and maintenance. The future autonomous networks will require a holistic view on network visibility. A holistic view on network visibility needs comprehensive data. Network telemetry, as one of network data collection techniques, can gain network insight and facilitate efficient and automated network management.
+
+Conventional operation, administration and maintenance (OAM) only covers a narrow range of data, and those data are insufficient to gain network visibility. Compared with the conventional OAM, network telemetry is an ideal tool to gain sufficient network visibility with better flexibility, scalability, accuracy, coverage and performance.
+
+[ITU-T Y.3650] specifies a framework for big-data-driven networking (bDDN) – A type of future network framework that collects big data from networks and applications, and generates big data intelligence based on the big data. It then provides big data intelligence to facilitate smarter and autonomous network management, operation, control, optimization, security, etc. [ITU-T Y.3652] specifies requirements of big data driven networking. All these Recommendations provide the specification for high-level aspects of bDDN.
+
+Network visibility is a fundamental requirement and capability for big data-driven networks, which exploit the bDDN architecture to achieve massive network data collection, storage, analysis and visual presentation. Moreover, when bDDN is applied in an IP bearer network, those requirements and capabilities are more important and urgent.
+
+## **7 Overview for network visibility of bDDN**
+
+It can be learned from clause 6 that network visibility is essential and that beneficial functional features for bDDN and network telemetry is a proper method for network visibility.
+
+### **7.1 Network telemetry**
+
+For a long time, network operators have relied upon simple network management protocol (SNMP), command-line interface (CLI), or Syslog to monitor the network. These conventional techniques are
+
+not sufficient to support operations and maintenance of the future networks, such as security anomaly detection, policy and intent compliance, service level agreement (SLA) compliance, root cause analysis (RCA), event tracking and prediction, network optimization, etc. The reason is as follows:
+
+- Most use cases need to continuously monitor the network and dynamically refine the data collection in real-time. The conventional poll-based low-frequency data collection is not appropriate for these applications. Comprehensive data is needed from all aspects of a network device. Conventional OAM only covers a narrow range of data (e.g., SNMP only handles data from the management information base (MIB)).
+- Many application scenarios need to correlate network-wide data from multiple sources (i.e., from distributed network devices, different components of a network device, or different network planes).
+- Some of the conventional OAM techniques (e.g., CLI and Syslog) lack a formal data model. The unstructured data hinder the tool automation and application extensibility. Standardized data models are essential to support the programmable networks.
+- The conventional measurement techniques can interfere with the user traffic and their results are indirect. Techniques that can collect direct and on-demand data from user traffic are more favourable (e.g., in-situ OAM).
+
+Network telemetry [b-IETF RFC 9232] has emerged as a mainstream network data collection and consumption technique, and it covers the conventional network OAM. Hence, network telemetry can directly trigger automated network operation, while in contrast some conventional OAM tools are designed and used to help human operators to monitor and diagnose the networks and guide manual network operations. It is expected that network telemetry can provide the necessary network insight for autonomous networks and address the shortcomings of conventional OAM techniques.
+
+Network telemetry is expected to hold the following characteristics:
+
+- Push and streaming: Instead of polling data from network devices, telemetry collectors subscribe to streaming data pushed from data sources.
+- Volume and velocity: The data volume can be huge, and the processing is optimized for the needs of automation in real-time.
+- Normalization and unification: Telemetry aims to address the overall network automation needs. Efforts are made to normalize data representation and unify the protocols, so as to simplify data analysis and provide integrated analysis across heterogeneous devices and data sources across a network.
+- Model-based: Telemetry data are modelled in advance, which allows applications to configure and consume data with ease.
+- Dynamic and interactive: Since network telemetry is meant to be used in a closed control loop for network automation, it needs to run continuously and adapt to the dynamic and interactive queries from the network management system or the controller.
+
+### **7.2 Overview of network visibility based on bDDN**
+
+As described in [ITU-T Y.3650], bDDN is composed of three planes, and each plane is composed of several layers. Figure 7-1 depicts the architecture of network visibility based on bDDN.
+
+The big data plane is composed of four layers, and the bottom layer is the data sensing layer which collects various data from the network infrastructure layer of the network plane. To gain a holistic view on network visibility, it is necessary to collect comprehensive data from network control components, network forwarding components and network management components in real time. The telemetry of control aspect refers to the health condition monitoring of different network control protocols covering Layer 2 to Layer 7. Keeping track of the running status of these
+
+protocols is beneficial for detecting, localizing, and even predicting various network issues, as well as network optimization in real time and in fine granularity. An effective telemetry of the forwarding aspect relies on the data that the network device can expose. The quality, quantity and timeliness of data must meet some stringent requirements. The data plane programmability of network elements is essential to support network telemetry. The management plane of network elements interacts with the NMS, and provides information such as performance data, network logging data, network warning and defects data, and network statistics and state data. The management plane includes many protocols, including some that are considered "legacy", such as SNMP and Syslog.
+
+
+
+The diagram illustrates the architecture of network visibility based on bDDN, organized into three main planes: Network plane, Big data plane, and Management plane.
+
+- Network plane:** Contains a "Network application" and a "Network controller". It is associated with "Network intelligence" and "Big-data-driven control".
+- Big data plane:** Contains a "Network big data analyser", a "Network big data repository", and a "Network big data sensing layer". It is associated with "Network intelligence" and "Network big data intelligence and service".
+- Management plane:** Contains "Network operation", "Network administration", and "Network maintenance". It is associated with "Network intelligence" and "Big-data-driven OAM".
+
+Telemetry data flows from the Network plane and Management plane into the Big data plane. This data is categorized into three aspects: "Control aspect", "Forwarding aspect", and "Management aspect".
+
+The Network infrastructure is shown at the bottom, consisting of three layers:
+
+- Access layer:** Includes AR (Access Router) and Leaf nodes.
+- Convergence layer:** Includes Leaf and Spine nodes.
+- Backbone layer:** Includes Spine and CR (Core Router) nodes.
+
+Yellow arrows indicate the flow of data and control from the Network and Management planes through the Big data plane to the Network infrastructure. The diagram is labeled Y.3657(23) in the bottom right corner.
+
+Architecture of network visibility based on bDDN diagram
+
+**Figure 7-1 – Architecture of network visibility based on bDDN**
+
+The collected telemetry data is stored in a data storage repository. Meanwhile, some data pre-processing is required in accordance with several pre-set rules, including data filtering and cleaning, data labelling, data aggregating, data normalizing, etc. All these pre-processed data are saved to the corresponding database.
+
+The network big data analysing layer utilizes traditional data analysis methods (e.g., statistical analytical method, visualization analytical method, correlation analytical method) as well as the advanced big-data and machine learning techniques to process and analyse data.
+
+The network big data intelligence and service layer needs to further transform the processed data into valuable information and instructions and provide data intelligence to the other two planes in the form of services.
+
+The network plane consists of three layers: network infrastructure layer, network controller layer and network application layer. The network infrastructure layer includes all kinds of network devices implementing packet forwarding. The network controller layer includes network controllers, responsible for policy decision and real-time control of traffic flows, such as distribution of flow table, preferential path calculation, dynamic modification of configuration and so on. The application layer includes different kinds of network applications, such as path optimization, load balancing, service function chain (SFC), etc.
+
+With the aid of the big data plane, network visibility and data intelligence make the network plane capture network behaviour and network status quickly and accurately, so that network parameters can be autonomously updated for achieving optimal performance and best SLA guarantee.
+
+The management plane is also composed of three aspects: network operation aspect, network administration aspect and network maintenance aspect. Taking advantage of data analysis results and network intelligence in the big data plane, the management plane realizes a series of network management functions, including troubleshooting, configuration and optimization. Other functions such as expanding network capacity based on timely traffic prediction, and implementing security reinforcement based on the indicated potential risks, can also be supported.
+
+By introducing the big data plane, which concentrates on the collection, processing, analysis and visualization of multi-dimensional network data, the burden of control plane and management plane of the network can be greatly unloaded. This novel architecture of bDDN can fulfil hierarchization and decoupling of traditional network, and is beneficial to accelerate network reconstruction. Furthermore, data intelligence generated from the big data plane helps to implement network automation.
+
+# **8 Requirements and capabilities for network visibility of control aspect of bDDN**
+
+Network visibility of the control aspect of bDDN is of great significance for monitoring the network running state. To gain the visibility of the control aspect, it is necessary collect running status data of main network control protocols and keep tracking the running status of those protocols. Network visibility of control aspect of bDDN is beneficial for detecting, localizing and even predicting various network issues.
+
+### **8.1 Requirements for network visibility of the control aspect of bDDN**
+
+- It is required to support the visibility of border gateway protocol (BGP) running status, including BGP routing table, BGP route statistics, threshold alarm, BGP neighbour status, BGP neighbour flapping, the causes of BGP peering disconnections, etc.
+- It is required to support the visibility of routing information base (RIB), i.e., IP routing table.
+- It is required to support the visibility of intermediate system-to-intermediate system (IS-IS) running status, including IS-IS memory overload, IS-IS adjacency establishment failed, IS-IS adjacency status changed, IS-IS neighbour flapping, routing loop detected, etc.
+- It is required to support the visibility of open shortest path first (OSPF) running status, including the introduced external routes overrun, adjacency status changed, interface status changed, configuration error for the neighbour interface detected, OSPF neighbour flapping, routing loop detected, etc.
+- It is recommended to support the visibility of IP multicast protocol running status, including IGMP/MLD and protocol independent multicast (PIM).
+- It is recommended to support the visibility of label distribution protocol (LDP) running status, including LDP session state changed, LDP session deleted.
+
+- It is recommended to support the visibility of multi-protocol label switching-traffic engineering (MPLS-TE) running status, including resource reservation protocol (RSVP) status, MPLS-TE master and standby tunnel switching status.
+- It is required to support the visibility of SR/SRv6 policy running status.
+- It is required to support the visibility of Ethernet virtual private network (EVPN) running status, including EVPN routes, media access control (MAC) address routes suppressed, loop detected, routes discarded, EVPN instance status changed, etc.
+- It is required to support the visibility of multi-protocol label switching (MPLS) Layer 2 virtual private network (L2VPN) running status, including pseudo wire (PW) status changed, PW protection switching, etc.
+- It is required to support the visibility of MPLS Layer 3 virtual private network (L3VPN) running status, including virtual private network (VPN) tunnel status, virtual routing and forwarding (VRF) binding interface status, the number of routes exceeded, etc.
+- It is recommended to support the visibility of address resolution protocol (ARP) table.
+- It is recommended to support the visibility of neighbour discovery protocol (NDP) table.
+- It is recommended to support the visibility of bidirectional forwarding detection (BFD) session status.
+
+In order to achieve network visibility of the control aspect of bDDN, telemetry data collection of key control protocols is necessary. Table 8-1 presents relevant telemetry data collection of the control aspect.
+
+**Table 8-1 – Relevant telemetry data collection of the control aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|------------|----------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------|
+| BGP | BGP routing table | BGP RIB, including the following parameters: - – BGP table version
- – Origin
- – Destination prefix/subnet mask
- – Next hop
- – Metric
- – Local preference
- – AS PATH
| | On-change |
+| | BGP route statistics | - 1. Total number of public IPv4 routes
- 2. Total number of public IPv6 routes
- 3. Number of VPN IPv4 instance routes
- 4. Number of VPN IPv6 instance routes
- 5. Number of prefixes rejected by inbound policy
- 6. Total number of BGP updates invalidated
- 7. Number of updates invalidated due to AS_PATH loop
| ≤ 60 | Periodic |
+| | Threshold alarm | - 1. An alarm is generated when the total number of global routes reaches the overload threshold
- 2. An alarm is generated when the total number of VPN routes reaches the overload threshold
- 3. An alarm is generated when the number of routes received from BGP neighbour reaches the preset threshold
- 4. An alarm is generated when the number of BGP peering sessions reaches the preset threshold.
| | Event-triggered |
+| | BGP neighbour status | - 1. IDLE
- 2. CONNECT
| | On-change |
+
+**Table 8-1 – Relevant telemetry data collection of the control aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|------------|----------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------|
+| | | 3. ACTIVE
4. OPENSENT
5. OPENCONFIRM
6. ESTABLISHED | | |
+| | The causes of BGP peering disconnected | 1. Configuration error
2. Notification message received
3. Received BGP message including one or more error fields
4. Hold timer timeout.
5. Neighbour unreachable
6. Connected interface down | | Event-triggered |
+| | BGP neighbour security | 1. BGP session authentication failed | | Event-triggered |
+| RIB | IP routing table | 1. Global routing table
2. VRF routing table
IP routing table includes the following parameters:
– Destination prefix/subnet mask
– Next hop
– Protocol type
– Preference
– Metric
– Outbound interface | $\leq 300$ | Periodic |
+| IS-IS | IS-IS memory overload | 1. Number of label switching paths (LSPs) reaches the overload threshold
2. Link-state data base (LSDB) size is overloaded
3. LSDB size exits overload state
4. New adjacency is rejected due to memory overload | | Event-triggered |
+| | IS-IS adjacency establishment failed | Fails to establish adjacency with the neighbour when receiving Hello message, possible reasons include:
– Configured local system ID is the same as the neighbour system ID
– Interface authentication fails due to the configured authentication mode or password problem
– The IS-IS level-1 neighbours connected to the same link have different area addresses configured
– The IS-IS neighbours connected to the same link have different Level class configured
– In a broadcast network, the local interface receives a hello message with network field values different from the local interface
– In a P2P network, the local interface receives a hello message with network field values different from the local interface
– The neighbour interfaces connected directly have different maximum transmission units (MTUs) configured | | On-change |
+| | IS-IS adjacency status changed | IS-IS adjacency state changes to:
– DOWN | | On-change |
+
+**Table 8-1 – Relevant telemetry data collection of the control aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|------------|----------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------|
+| | | | | |
+| | IS-IS interface status changed | Possible causes for interface status change include: - The physical state of the interface changes
- The Protocol state of the interface changes
- Enable or disable IS-IS
- Reset IS-IS all command
| | On-change |
+| | IS-IS neighbour flapping suppression changed | IS-IS neighbour flapping suppression changes: - IS-IS interface is in the flapping suppression phase
- IS-IS interface exits the flapping suppression phase
| | On-change |
+| | System ID conflicted | IS-IS detects a system ID conflict. In the same topology, the system ID's configurations of two IS-IS devices are duplicate. | | On-change |
+| | Routing loop detected | The device detects a loop in the route | | Event-triggered |
+| | Prefix SID problems | 1. Prefix SID conflicts
2. The received prefix SID exceeds the range of the local SRGB | | Event-triggered |
+| OSPFv2/v3 | The introduced external routes overrun | 1. The number of AS external link-state advertisements (LSAs) introduced by OSPF is greater than the upper threshold
2. The number of not-so-stubby area (NSSA) LSAs introduced by OSPF is greater than the upper threshold | | Event-triggered |
+| | LSA aged | 1. One or more LSAs in LSDB have reached the aging time | | Event-triggered |
+| | Adjacency status changed | OSPF adjacency state changes to: - Down
- Attempt
- Init
- 2-Way
- ExStart
- Exchange
- Loading
- Full
| | On-change |
+| | Interface status changed | Possible causes for interface state change include: - The physical state of the interface changes
- The Protocol state of the interface changes
- Enable or disable OSPF
- Reset OSPF all command
| | On-change |
+| | Configuration error for the neighbour interface detected | The interface configuration to establish OSPF adjacency is inconsistent. the types of configuration errors include: - Inconsistent version number
- Area mismatch
- Unknown non-broadcast multiple access (NBMA) neighbour
- Unknown virtual neighbour.
| | On-change |
+
+**Table 8-1 – Relevant telemetry data collection of the control aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|--------------|---------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------|
+| | | - – Inconsistent type of authentication configured
- – Authentication fails
- – Inconsistent mask configured
- – Inconsistent Hello time configured
- – Inconsistent Dead time configured
- – Inconsistent Option field configured
- – Inconsistent MTU configured
- – RouterID configuration conflicts
- – Unknown error
| | |
+| | OSPF neighbour flapping suppression changed | OSPF neighbour flapping suppression changes: - – OSPF interface is in the flapping suppression phase
- – OSPF interface exits the flapping suppression phase
| | On-change |
+| | Routing loop detected | The device detects a loop in the route | | On-change |
+| | Prefix SID problems | 1. Prefix SID conflicts
2. The received prefix SID exceeds the range of the local SRGB | | Event-triggered |
+| IP multicast | IGMP/MLD | 1. The IGMP/MLD group memberships of the specified interface exceed the threshold, and discard the Report messages
2. The number of IGMP/MLD table entries of the specified interface reaches the upper threshold
3. Prompt on receiving IGMP/MLD group member Report message
4. Prompt on receiving IGMP/MLD group member Leave message
5. The IGMP version configured on the interface is inconsistent with the version of the Query message received | | Event-triggered |
+| | PIM | 1. The number of PIM neighbours reaches the upper limit of system capacity.
2. PIM neighbour lost
3. The number of the global PIM table entries reaches the limit
4. The number of PIM multicast table entries in the VPN instance reaches the limit
5. Reverse path forwarding (RPF) routes flap, causing an alarm | | Event-triggered |
+| LDP | LDP session state changed | 1. The LDP session state changes from UP to DOWN due to the receipt of wrong message or notification message: - – Receives the message with wrong LDP ID
- – Receives the message with wrong version number
- – Receives the message with wrong PDU length
- – Receives the message with wrong packet length
- – Receives the message with wrong TLV value.
- – Receives Notification message about hello timeout
- – Receives Notification message about keepalive timeout
| | On-change |
+
+**Table 8-1 – Relevant telemetry data collection of the control aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|----------------|---------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------|
+| | | - – Receives Notification message about shutdown
- 2. The LDP session state changes from UP to DOWN due to TCP disconnection
- 3. The Hello hold timer for LDP session timed out
- 4. The Keepalive hold timer for LDP session timed out
- 5. Restarts LDP command
- 6. Configures graceful restart (GR) attribute of LDP session
| | |
+| | The number of LDP labels exceeded | When the number of LDP labels exceeds the limit, an alarm will be generated. | | Event-triggered |
+| | LDP session deleted | An LDP session is deleted | | Event-triggered |
+| | LDP session security | The LDP session authentication fails | | Event-triggered |
+| MPLS-TE | RSVP status | - 1. RSVP is UP
- 2. RSVP is DOWN
Telemetry data SHOULD carry the following tunnel attributes: - – Tunnel ID
- – Tunnel ingress label switching router (LSR) ID
- – Tunnel Egress LSR ID
| | On-change |
+| | MPLS-TE master and standby tunnel switching | - 1. The traffic is switched from the master tunnel to the hot-standby LSP
- 2. The traffic is switched from the hot-standby LSP to the master tunnel
Telemetry data SHOULD carry the following tunnel attributes: - – Master tunnel ID
- – Master tunnel ingress LSR ID
- – Master tunnel egress LSR ID
- – Master LSP protocol status
- – Standby LSP ID
- – Standby LSP protocol status
- – Switch reason
| | Event-triggered |
+| SR/SRv6 POLICY | SR POLICY status changed | - 1. SR POLICY is UP
- 2. SR POLICY is DOWN
Telemetry data SHOULD carry the following SR POLICY attributes: - – SR POLICY name
- – SR POLICY endpoint address
- – SR POLICY colour
- – SR POLICY binding segment identification (BSID)
| | On-change |
+| | BSID allocation failed | An allocation failure for the binding SID of SR policy is detected. | | Event-triggered |
+| EVPN | Types of EVPN routes | - 1. RT-1, Ethernet auto-discovery route
- 2. RT-2, MAC/IP advertisement route
- 3. RT-3, multicast Ethernet tag route
- 4. RT-4, Ethernet segment route
- 5. RT-5, IP prefix route
| $\leq 300$ | Periodic |
+| | MAC address | Due to frequent MAC addresses migration in the | | Event-triggered |
+
+**Table 8-1 – Relevant telemetry data collection of the control aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|------------|----------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------|
+| | routes suppressed | specified EVPN instance, the routes corresponding to these MAC addresses are suppressed. | | |
+| | Loop detected | In the dual-homing scenario of EVPN E-Tree instance, the traffic loop occurs, due to the inconsistent leaf attribute configurations on the two dual-homing PEs. | | Event-triggered |
+| | Routes discarded | The newly learned MAC and MAC/IP routes are discarded in an EVPN instance | | Event-triggered |
+| | EVPN instance status changed | 1. An EVPN instance state is DOWN
2. An EVPN instance state is UP | | On-change |
+| | Number of MAC addresses exceeded | The number of MAC addresses in the EVPN instance reaches the maximum | | Event-triggered |
+| L2VPN | PW status changed | PW state changes to DOWN/UP. Telemetry data SHOULD carry the following PW attributes:
– Virtual circuit (VC) ID
– Remote peer address
– Type of PW encapsulation
– Local VC label
– Remote VC label
The causes of PW DOWN include:
– Local VC deleted
– LDP session disconnected
– LDP mapping interface parameters not matched
– LDP Withdrawn message received
– LDP Release message received
– Interface down
– Type of interface encapsulation changed
– MTU not matched
– Unknown cause | | On-change |
+| | Insufficient label blocks | 1. An alarm is generated when the VPLS label blocks are insufficient
2. An alarm is generated when the VPWS label blocks are insufficient | | Event-triggered |
+| | PW protecting group fault | An alarm is generated when the working PW or protecting PW fails in the PW protecting group, carrying the parameters including:
– VSI name
– PW ID
– Remote peer IP address
– Possible cause | | Event-triggered |
+| | PW protection switching | 1. The master PW switches to the standby PW
2. The standby PW switches to the master PW | | Event-triggered |
+| L3VPN | Number of routes exceeded | The number of IPv4/v6 routes in the VPN instance exceeds the configured maximum number of VPN routes | | Event-triggered |
+| | VRF binding interface status | The interface binding a VPN instance is DOWN | | Event-triggered |
+| | VPN tunnel status | An alarm is generated when the VPN tunnel is DOWN, carrying the following parameters: | | On-change |
+
+**Table 8-1 – Relevant telemetry data collection of the control aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|------------|----------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------|
+| | | - – VPN ID
- – Outer tunnel ID
- – Next hop
| | |
+| LLDP | Neighbour status | The neighbour status SHOULD include the following TLVs:
- – System name
- – System description
- – Chassis-id
- – Port-id
- – Time to live
- – Management address
| $\leq 60$ | Periodic |
+| ARP | ARP table | Number of ARP entries cached by the specified interface
Each ARP entry SHOULD contain the following parameters:
- – Interface name
- – MAC address
- – IPv4 address
- – Aging time of dynamic learning
| $\leq 300$ | Periodic |
+| NDP | ND table | Number of ND entries stored by the specified interface
Each ND entry SHOULD contain the following parameters:
- – Interface name
- – MAC address
- – IPv6 address
- – Aging time of dynamic learning
| $\leq 300$ | Periodic |
+| BFD | BFD session status changed | An alarm is generated when the BFD session state changes, carrying the following parameters:
- 1) My discriminator
- 2) Your discriminator
- 3) Session state:
- – AdminDown
- – Down
- – Initiation
- – Up
- 4) The possible causes for session state change (Diagnostic word) include:
- – No diagnostic
- – Control Detection time expired
- – Echo function failed
- – Neighbour signalled session down
- – Forwarding plane reset
- – Path down
- – Concatenated path down
- – Administratively down
- – Reverse concatenated path down
- – Application remove
| | On-change |
+
+### **8.2 Capabilities for network visibility of the control aspect of bDDN**
+
+Network visibility of the control aspect includes mainly the following functions:
+
+- Status data collecting: Collecting the running status data related to the main control protocols.
+- Status data transforming: Transforming the collected status data to the format that big data plane of bDDN can easily understand.
+- Running status visualizing: Visualizing the running status in the form of curves, tables, charts, etc.
+- Running status tracking: Continually tracking the running status of the main control protocols.
+- Running status predicting: Predicting the health trend of the running protocols based on the collected status data.
+
+## **9 Requirements and capabilities for network visibility of the forwarding aspect of bDDN**
+
+Network visibility of the forwarding aspect of bDDN is also significant for operating and controlling the network (e.g., network planning, network optimization, traffic prediction, congestion avoidance and packet loss localizing). As an effective network data collection technique, telemetry of the forwarding aspect relies on the data that the network device can expose. The quality, quantity and timeliness of data must meet some stringent requirements. In addition, bDDN needs to support relevant capabilities for network visibility of the forwarding aspect.
+
+### **9.1 Requirements for network visibility of the forwarding aspect of bDDN**
+
+- It is required to support the visibility of interface traffic statistics and status, including physical interface traffic statistics, sub-interface traffic statistics, interface status, sub-interface status, interface buffer/queue, interface packets discarded, etc.
+- It is required to support the visibility of optical module performance.
+- It is required to support the visibility of L2VPN traffic statistics.
+- It is required to support the visibility of L3VPN traffic statistics.
+- It is required to support the visibility of MPLS/SR-TE traffic statistics.
+- It is required to support the visibility of SR/SRv6-policy TE traffic statistics.
+- It is required to support the visibility of QoS queue information statistics.
+- It is recommended to support the visibility of access control list (ACL) rules statistics.
+- It is required to support the visibility of tow-way active measurement protocol (TWAMP) measured data.
+- It is recommended to support the visibility of in-situ flow information telemetry (iFIT) measured data.
+- It is recommended to support the visibility of in-situ operations, administration, and maintenance (IOAM) monitored data.
+
+In order to achieve network visibility of forwarding aspect of bDDN, telemetry data collection of key forwarding performance is necessary. Table 9-1 presents relevant telemetry data collection of the forwarding aspect.
+
+**Table 9-1 – Relevant telemetry data collection of the forwarding aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|-------------------|---------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------|-----------------------------------------------------------------------|
+| Interface | Physical interface traffic statistics | - 1. Number of inbound/outbound bytes
- 2. Number of in/out unicast packets
- 3. Number of in/out broadcast packets
- 4. Number of in/out multicast packets
- 5. Number of in/out discarded packets
- 6. Number of in/out error packets
- 7. Number of in/out packets
- 8. In/out utilization
- 9. In/out bit rate (Mbit/s)
- 10. In/out packet rate (kbit/s)
- 11. In/out IPv4 bytes
- 12. In/out IPv4 packets
- 13. In/out IPv4 bit rate (Mbit/s)
- 14. In/out IPv4 packet rate (kbit/s)
- 15. In/out IPv4 utilization
- 16. In/out IPv6 bytes
- 17. In/out IPv6 packets
- 18. In/out IPv6 bit rate (Mbit/s)
- 19. In/out IPv6 packets (kbit/s)
- 20. In/out IPv6 utilization
| $\leq 60$ | Periodic |
+| | Sub-interface traffic statistics | - 1. Number of in/out bytes
- 2. Number of in/out unicast packets
- 3. Number of in/out broadcast packets
- 4. Number of in/out multicast packets
- 5. Number of in/out discarded packets
- 6. Number of in/out error packets
- 7. Number of in/out packets
- 8. In/out utilization
- 9. In/out bit rate (Mbit/s)
- 10. In/out packet rate (kbit/s)
- 11. In/out IPv4 bytes
- 12. In/out IPv4 packets
- 13. In/out IPv4 bit rate (Mbit/s)
- 14. In/out IPv4 packet rate (kbit/s)
- 15. In/out IPv4 utilization
- 16. In/out IPv6 bytes
- 17. In/out IPv6 packets
- 18. In/out IPv6 bit rate (Mbit/s)
- 19. In/out IPv6 packets rate (kbit/s)
- 20. In/out IPv6 utilization
| $\leq 60$ | Periodic |
+| | Interface status | - 1. Type of interface encapsulation
- 2. Interface management state
- 3. Interface physical state
- 4. Interface layer 2 protocol state
- 5. Interface IPv4/v6 protocol state
- 6. Interface index
| | On-change |
+
+**Table 9-1 – Relevant telemetry data collection of the forwarding aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|-------------------|-----------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------|-----------------------------------------------------------------------|
+| | Sub-interface status | - 1. Type of interface encapsulation
- 2. Interface management state
- 3. Interface physical state
- 4. Interface layer 2 protocol state
- 5. Interface IPv4/v6 protocol state
- 6. Interface index
| | On-change |
+| | Interface buffer/queue | - 1. Current used buffers/depth
- 2. Queue threshold exceeded
| $\leq 60$ | Periodic
Event-triggered |
+| | Interface packets discarded | - 1. The time when packets are discarded
- 2. The causes of packets discarded:
- – due to queue overflow
- – due to cyclic redundancy check (CRC) error
- – due to forwarding failure (e.g., FIB match failed, ACL match failed, etc.).
| | Event-triggered |
+| Optical module | Performance | - 1. Transmitting optical power
- 2. Receiving optical power
- 3. Optical module current (mA)
- 4. Optical module voltage (mV)
- 5. Optical module temperature (C°)
| $\leq 60$ | Periodic |
+| | Performance abnormal | - 1. Transmitting optical power exceeds the limit
- 2. Receiving optical power exceeds the limit
- 3. Optical module current exceeds the limit
- 4. Optical module voltage exceeds the limit
- 5. Optical module temperature exceeds the limit
| | Event-triggered |
+| PW | PW traffic statistics | - 1. PW name
- 2. VC ID
- 3. Number of in/out bytes
- 4. Number of in/out unknown unicast bytes
- 5. Number of in/out unicast bytes
- 6. Number of in/out broadcast bytes
- 7. Number of in/out multicast bytes
- 8. Number of in/out discarded bytes
- 9. Number of in/out packets
- 10. Number of in/out unknown unicast packets
- 11. Number of in/out unicast packets
- 12. Number of in/out broadcast packets
- 13. Number of in/out multicast packets
- 14. Number of in/out discarded packets
- 15. In/out utilization
- 16. In/out bit rate (Mbit/s)
- 17. In/out packets rate (kbit/s)
| $\leq 60$ | Periodic |
+
+**Table 9-1 – Relevant telemetry data collection of the forwarding aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|----------------------------------|---------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------|-----------------------------------------------------------------------|
+| L3VPN | VPN instance traffic statistics | - 1. VRF name
- 2. Number of in/out bytes
- 3. Number of in/out packets
- 4. Number of in/out discarded bytes
- 5. Number of in/out discarded packets
- 6. In/out bit rate (Mbit/s)
- 7. In/out packets rate (kbit/s)
| $\leq 60$ | Periodic |
+| MPLS/SR-TE | TE traffic statistics | - 1. Tunnel ID
- 2. Number of Outbound bytes
- 3. Outbound packets
- 4. Outbound discarded bytes
- 5. Outbound discarded packets
- 6. Outbound bit rate (Mbit/s)
- 7. Outbound packets rate (kbit/s)
| $\leq 60$ | Periodic |
+| SR/SRv6-Policy [b-IETF RFC 9256] | TE traffic statistics | - 1. Policy name
- 2. Number of Outbound bytes
- 3. Outbound packets
- 4. Outbound discarded bytes
- 5. Outbound discarded packets
- 6. Outbound bit rate (Mbit/s)
- 7. Outbound packets rate (kbit/s)
| $\leq 60$ | Periodic |
+| QoS | Queue information statistics | - 1. Interface name
- 2. Queue ID
- 3. Committed information rate (CIR)
- 4. Peak information rate (PIR)
- 5. Maximum buffers
- 6. Current used buffers
- 7. Buffer utilization
- 8. Total packets passed
- 9. Total bytes passed
- 10. Discarded packets
- 11. Discarded bytes
- 12. Current bit rate passed (Mbit/s)
- 13. Current packets rate passed (kbit/s)
| $\leq 60$ | Periodic |
+| ACL | ACL rules statistics | - 1. Interface ID
- 2. Maximum number of configurable ACL rules supported
- 3. Current number of the used ACL rules configured
- 4. ACL rules table
| $\leq 300$ | Periodic |
+| STAMP/TWAMP [b-IETF RFC 5357] | Measured data | - 1. Connection ID
- 2. Measurement ID
- 3. Number of testing packets sent by client
- 4. Number of testing packets received by client
- 5. Discarded testing packets
- 6. Testing packet loss
- 7. Minimum bidirectional delay (ns)
- 8. Maximum bidirectional delay (ns)
| According to testing duration | Periodic |
+
+**Table 9-1 – Relevant telemetry data collection of the forwarding aspect**
+
+| Data class | Data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, on-change or event-triggered) |
+|-------------------------------------|---------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------|-----------------------------------------------------------------------|
+| | | 9. Average bidirectional delay (ns)
10. Minimum bidirectional delay jitter (ns)
11. Maximum bidirectional delay jitter (ns)
12. Average bidirectional delay jitter (ns)
13. Minimum forward delay (ns)
14. Maximum forward delay (ns)
15. Average forward delay (ns)
16. Minimum forward delay jitter (ns)
17. Maximum forward delay jitter (ns)
18. Average forward delay jitter (ns)
19. Minimum reverse delay (ns)
20. Maximum reverse delay (ns)
21. Average reverse delay (ns)
22. Minimum reverse delay jitter (ns)
23. Maximum reverse delay jitter (ns)
24. Average reverse delay jitter (ns) | | |
+| Alternate-Marking [b-IETF RFC 9341] | Measured data | 1. Flow ID
2. Testing duration ID
3. Node ID
4. Number of packets
5. Number of bytes
6. Timestamp | According to testing duration | Periodic |
+| IOAM | Measured data for passport mode [b-IETF RFC 9197] | 1. IOAM namespace ID
2. Node ID
3. TTL or Hop Limit
4. Ingress interface ID
5. Egress interface ID
6. Timestamp
7. Forwarding delay
8. Queue depth
9. Buffer occupation | According to testing duration | Periodic |
+| | Measured data for postcard mode [b-IETF RFC 9326] | 1. IOAM namespace ID
2. Flow ID
3. Sequence Number
4. TTL or Hop Limit
5. Node ID
6. Ingress interface ID
7. Egress interface ID
8. Timestamp
9. Forwarding delay
10. Queue depth
11. Buffer occupation | According to testing duration | Periodic |
+
+### 9.2 Capabilities for network visibility of the forwarding aspect of bDDN
+
+Network visibility of the forwarding aspect includes mainly the following functions:
+
+- Data collection configuring: Selecting, on-demand, which class of telemetry data should be collected.
+
+- Data collecting: Collecting the telemetry data related to the forwarding aspect.
+- Data transforming: Transforming the collected data to the format that the big data plane of bDDN can easily understand.
+- Data statistics and visualization: Making the statistics of traffic and performance data, and visualizing the statistical data in the form of curves, tables, charts, etc.
+- Traffic predicting: Predicting network traffic trend based on traffic statistics.
+- Congestion and link quality management: managing network congestion level and link quality level based on performance data statistics.
+
+## 10 Requirements and capabilities for network visibility of the management aspect of bDDN
+
+Network visibility of the management aspect of bDDN is beneficial to network OAM such as troubleshooting, root cause analysis and event tracking. The management plane should provide network performance data, network logging data, device status data, fault, security, etc. Therefore, the management entity needs to support relevant requirements and capabilities for network visibility.
+
+### 10.1 Requirements for network visibility of the management aspect of bDDN
+
+- It is required to support the visibility of device performance, including central processing unit (CPU), memory, power supply, fan, temperature, etc.
+- It is required to support the visibility of device fault alarms.
+- It is required to support the visibility of device security, including security management of user login, CPU safety protection.
+- It is recommended to support the visibility of telemetry dynamic subscription management.
+
+To achieve network visibility of management aspect of bDDN, telemetry data collection of key management indicators is necessary. Table 10-1 presents relevant telemetry data collection of the management aspect.
+
+**Table 10-1 – Relevant telemetry data collection of the management aspect**
+
+| Data class | data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, On-change or event-triggered) |
+|-------------|--------------|-------------------------------------------------------------------------------------------------------|--------------------------------------------------|----------------------------------------------------------------|
+| Performance | CPU | 1. CPU utilization
2. CPU utilization reaches overload threshold
3. CPU working status | $\leq 30$
$\leq 30$ | Periodic
Event-triggered
Event-triggered |
+| | Memory | 1. Memory utilization
2. Memory utilization reaches overload threshold
3. Memory working status | $\leq 30$
$\leq 30$ | Periodic
Event-triggered
Event-triggered |
+| | Power supply | 1. Power
2. Voltage
3. Current
4. Power working status | $\leq 30$
$\leq 30$
$\leq 30$
$\leq 30$ | Periodic
Periodic
Periodic
Event-triggered |
+| | Fan | 1. Fan speed
2. Fan working status | $\leq 30$
$\leq 30$ | Periodic
Event-triggered |
+| | Temperature | 1. CPU temperature
2. Fan temperature
3. Temperature reaches the threshold | $\leq 30$
$\leq 30$ | Periodic
Periodic
Event-triggered |
+| Fault | Fault alarm | 1. System restart
2. Device fault (CPU, memory, power supply, fan, etc.) | | Event-triggered |
+
+**Table 10-1 – Relevant telemetry data collection of the management aspect**
+
+| Data class | data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, On-change or event-triggered) |
+|------------|-----------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------|
+| | | 3. Board hardware fault
4. Operating system fault
5. Interface fault
6. Link fault
7. Licence expired
8. Protection switching | | |
+| Security | Security management of user login | 1. The number of login failures reaches the threshold within a period of time
2. Add a user, including parameters:
– Operator name
– Operator's IP address
– New username
3. Delete a user, including parameters:
– Operator name
– Operator's IP address
– User name deleted
4. The user password has expired, including parameters:
– Username
5. The user has been locked, including parameters:
– Number of consecutive login failures
– Statistical time of consecutive login failures
– Locked time
– Type of user access.
6. Locked user is released, including parameters:
– Username
– Unlocking mode (automatic or manual) | | Event-triggered |
+| | CPU safety protection | 1. An attack on the CPU is detected. The attack type includes:
– TCP
– UDP
– ICMP
– ARP
– NDP
– DHCP
– DNS
2. Number of the discarded packets generated by tackling CPU attack packets. | | Event-triggered |
+| Telemetry | Dynamic subscription management | 1. User login fails, including parameters:
– Username
– User's IP address
– Port number
– VPN instance name
– Cause of login failure
2. User login succeeds, including parameters:
– Username
– User's IP address
– Port number | | Event-triggered |
+
+**Table 10-1 – Relevant telemetry data collection of the management aspect**
+
+| Data class | data item | Contents of data collection | Sampling interval (second) | types of subscription (periodic, On-change or event-triggered) |
+|------------|-----------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|----------------------------------------------------------------|
+| | | - – VPN instance name
- 3. Dynamic subscription fails. the possible causes include:
- – Sampling nodes/group (filters) not supported
- – Subscription parameters not supported
- – Insufficient resources
- – Transport encoding not supported
- – QoS not supported
- 4. Dynamic subscription disconnects. The possible causes include:
- – Remote process call (RPC) execution error
- – Google remote procedure calls (GRPC) internal execution error
- – The submitted contents not recognized
- – GRPC fails to parse the submitted contents
| | |
+
+### 10.2 Capabilities for network visibility of the management aspect of bDDN
+
+Network visibility of management aspect mainly includes the following functions:
+
+- Management data collecting: Collecting the configuration, performance, fault alarms and security data related to management aspect.
+- Management data transforming: Transforming the collected management data to the format that the big data plane of bDDN can easily understand.
+- Management data visualizing: Visualizing the collected management data in the form of curves, tables, charts, etc.
+- Network device management: Managing the device running status based on the collected management data.
+- Network device security management: Managing device operating security based on the collected management data.
+
+## 11 Interface requirements for network visibility of bDDN
+
+According to the framework of bDDN [ITU-T Y.3650], there are several interfaces between different planes or between different layers. However, this Recommendation mainly specifies the requirements of interfaces between the data sensing layer of the big data plane and the network infrastructure layer of the network plane named as iBN, as shown in Figure 11-1. The iBN can be implemented network configuration protocol (NETCONF), gNMI, UDP-based publication channel (UPC), BGP monitoring protocol (BMP), BGP-LS, SNMP, Syslog, IP flow information export (IPFIX), etc. The requirements for these interfaces are described in clauses 11.1 to 11.6.
+
+
+
+```
+
+graph TD
+ subgraph Big_data_plane [Big data plane]
+ NBSL[Network big data sensing layer]
+ end
+ subgraph Network_plane [Network plane]
+ NIL[Network infrastructure layer]
+ end
+ NBSL <--> |"iBN (NETCONF, gNMI, UPC, BMP, BGP-LS, SNMP, Syslog, etc.)"| NIL
+
+```
+
+Y.3657(23)
+
+Diagram showing the interface between the Big data plane and the Network plane. The Big data plane contains the Network big data sensing layer. The Network plane contains the Network infrastructure layer. A bidirectional arrow connects the two layers, labeled with protocols: iBN (NETCONF, gNMI, UPC, BMP, BGP-LS, SNMP, Syslog, etc.).
+
+**Figure 11-1 – Interface between network sensing layer and network infrastructure layer**
+
+### 11.1 NETCONF
+
+The NETCONF [b-IETF RFC 6241] protocol defines a simple mechanism through which a network device can be managed, configuration data information can be retrieved, and notification data information can be subscribed. NETCONF uses a simple RPC-based mechanism to facilitate communication between a client and a server.
+
+- NETCONF is required to support dynamic subscriptions, where a subscriber initiates a subscription negotiation with a publisher via an RPC. If the publisher is able to serve this request, it accepts it and then starts pushing notification messages back to the subscriber. If the publisher is not able to serve it as requested, then an error response is returned. This response may include hints for subscription parameters that, had they been present, may have enabled the dynamic subscription request to be accepted. The lifetime of a dynamic subscription is bound by the transport session used to establish it, and the loss of the transport session will result in the immediate termination of any associated dynamic subscriptions.
+- NETCONF is required to support configured subscriptions, which allow the management of subscriptions via a configuration so that a publisher can send notification messages to a receiver. Configured subscriptions can be configured to persist across reboots and even when its publisher is fully disconnected from any network.
+- NETCONF is required to support the ability to create, renew, time out, and terminate a subscription.
+- NETCONF is required to support and independently track multiple subscription requests by the same Subscriber.
+- NETCONF is required to support subscriptions against operational datastores, configuration datastores, or both.
+- NETCONF may include Filters as defined within a subscription request, therefore the Subscription Service MUST publish only data nodes that meet the Filter criteria within a subscription.
+- NETCONF is required to support the ability to subscribe to periodic updates. The subscription period shall be configurable as part of the subscription request.
+- NETCONF is required to support the ability to subscribe to updates on-change, i.e., whenever values of subscribed data objects change.
+- For on-change updates, NETCONF is required to support a dampening period that needs to be passed before the subsequent on-change updates are sent. The dampening period should be configurable as part of the subscription request.
+
+- NETCONF is required to support the ability to subscribe to the adaptive updates for interface traffic collection. In order to capture the congestion state of interfaces, such as microburst, a (i.e., subscription period) sub-second level sampling interval, or even a millisecond level sampling interval is necessary. However, under normal network conditions, a minute-level sampling interval can satisfy the requirements for traffic visibility, thus reducing enormously resources occupancy.
+ - 1) The network device is required to support determining the interface traffic sampling interval based on the current output queue length, which is detected by a dedicated hardware chip in real time. The longer the output queue, the shorter the sampling interval is. When the output queue is less than the preset safety threshold, a minute-level sampling interval is adopted; otherwise, a sub-second level sampling interval or even a millisecond-level sampling interval is adopted, whose parameter is negatively correlated with the difference between the current output queue length and the safety threshold.
+ - 2) The network device is required to support determining the interface traffic sampling interval based on the current output packet drop, which is detected by the dedicated hardware chip in real time. As soon as packet drop occurs, the sampling interval must be adjusted to a sub-second or even millisecond level.
+ - 3) The network device is required to support determining the interface traffic sampling interval based on the current port utilization, which is detected (i.e., millisecond interval) by the dedicated hardware in real time. The higher the port utilization, the shorter the sampling interval is. When the port utilization is less than the preset safety threshold, a minute-level sampling interval adopted; otherwise, a sub-second level sampling interval or even a millisecond level sampling interval is adopted, whose parameter depends on the corresponding port utilization threshold.
+- NETCONF is required to support the termination of a subscription when requested by the subscriber.
+- NETCONF is required to support the ability to suspend and to resume a subscription on request of a client.
+- NETCONF may on self-determination to suspend an existing subscription. Reasons may include transitory resource limitation, credential expiry, failure to reconfirm a subscription, loss of connectivity with the receiver, etc. When this occurs, the subscription service must notify the subscriber and update the subscription status.
+- NETCONF is required to support subscription to yet another next generation (YANG) notifications defined in [b-IETF RFC 8639].
+- NETCONF is required to support subscription to YANG-push defined in [b-IETF RFC 8641].
+
+### 11.2 gRPC network management interface (gNMI)
+
+The gRPC network management interface (gNMI) [b-GNMI-SPEC] supports modification and retrieval of configuration, as well as telemetry streams from a network element to a data collection system. gNMI derives a number of benefits from being built on gRPC and HTTP/2, including modern security mechanisms, bidirectional streaming, binary framing and a wide variety of language bindings to simplify integration with management applications. With protobuf encoding, it also provides significant efficiency advantages over extensible markup language (XML) serialization with a 3 to 10 times reduction in data volume.
+
+The conceptual layers and requirements for gNMI serving as the collection and encapsulation of telemetry data are depicted as Table 11-1.
+
+**Table 11-1 – Conceptual layers and requirements for gNMI serving as the collection and encapsulation of telemetry data**
+
+| Layer | | Requirements |
+|-------------------------------|------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Data model | Service data | Must include the service data from the specified paths. |
+| | Telemetry header | Must include timestamp, the time when the device collects the service data, and the paths from which the service data originates. |
+| gRPC | | gRPC is required to provide the following RPCs: - • Capabilities, used by the client and target as an initial handshake to exchange capability information.
- • Get, used to retrieve snapshots of the data on the target by the client.
- • Set, used by the client to modify the state of the target.
- • Subscribe, used to control subscriptions to data on the target by the client.
|
+| HTTP/2 | | HTTP/2 is required to support header field compression and binary framing, allowing multiple concurrent exchanges on the same connection. |
+| Secure transport based on TCP | | gNMI connection is required to provide authentication, data integrity, confidentiality, and replay protection (e.g., Transport layer security (TLS) [b-IETF RFC 5246]). |
+
+- gNMI is required to support the ability to create, renew, time out, and terminate a subscription.
+- gNMI is required to support an add/change/deletion of subscriptions.
+- gNMI may include filters as defined within a subscription request, therefore the Subscription Service must publish only data nodes that meet the filter criteria within a subscription.
+- gNMI is required to support STREAM subscription, a long-lived subscription which continues to transmit updates relating to the set of paths that are covered within the subscription indefinitely. STREAM subscription includes one of the following modes:
+ - On change-data updates are only sent when the value of the data item changes. For all On-change subscription, the target must first generate updates for all paths that match the subscription path(s), and transmit them. Following this initial set of updates, updated values should only be transmitted when their value changes. A heartbeat interval may be specified along with an "on change" subscription. In this case, the value of the data item(s) must be re-sent once per heartbeat interval regardless of whether the value has changed or not.
+ - Sampled-the value of the data item(s) must be sent once per sample interval to the client. Optionally, the suppress\_redundant field of the Subscription message may be set for a sampled subscription. In the case, the target Should Not generate a telemetry update message unless the value of the specified path has changed.
+- gNMI is required to support POLL subscription, used for on-demand retrieval of data items via long-lived RPCs. On reception of such a "SubscribeRequest" message containing a poll field, the target MUST generate updates for all the corresponding paths.
+- gNMI is required to support the ability to subscribe to the adaptive updates for interface traffic collection. In order to capture the congestion state of interface such as microburst, a sampling interval (i.e., subscription period) of sub-second level, or even millisecond level is necessary. However, under normal network condition, the sampling interval of minute level can satisfy the requirements for the traffic visibility, thus reducing resources occupancy enormously.
+ - 1) The network device is required to support determining the interface traffic sampling interval based on the current output queue length, which is detected by the dedicated
+
+hardware chip in real time. The longer the output queue, the shorter the sampling interval is. When the output queue is less than the preset safety threshold, minute level sampling interval is adopted; otherwise, a sub-second level sampling interval or even a millisecond level sampling interval is adopted, whose parameter is negatively correlated with the difference between the current output queue length and the safety threshold.
+
+- 2) The network device is required to support determining the interface traffic sampling interval based on the current output packet drop, which is detected by the dedicated hardware in real time. As soon as packet drop occurs, the sampling interval must be adjusted to the sub-second or even the millisecond level according to the subscription period.
+- 3) The network device is required to leverage the dedicated hardware chip to detect interface traffic at millisecond interval periodically. Among the multiple traffic thresholds in ascending order and corresponding sampling intervals acquired from subscription configuration message by the dedicated hardware chip, the higher the traffic threshold, the shorter the sampling interval is. The minimal threshold (i.e., safety threshold) corresponds to a minute-level sampling interval, and other thresholds correspond to the second, sub-second and millisecond level sampling intervals. The dedicated hardware chip compares the interface traffic with the preset multiple traffic thresholds to determine the traffic sampling interval. When the interface traffic (bandwidth utilization) is less than the preset safety threshold, a minute-level sampling interval is adopted; otherwise, a second, sub-second or even millisecond level sampling interval is adopted, whose parameter depends on the corresponding preset traffic threshold when interface traffic reaches it for a specified time (i.e., time threshold acquired from subscription configuration message).
+
+- gNMI is required to support structured data sent by the client or the target in an Update message, which MUST be serialized according to one of the supported encodings.
+- gNMI is required to support Protobuf and JSON encoded, and ASCII encoded is optional.
+
+### 11.3 UDP based publication channel (UPC)
+
+NETCONF and gNMI are ultimately based on the transfer control protocol (TCP) and lack the efficiency needed to stream data continuously at high velocity. On the other hand, in the case of data originating from multiple line cards of a single device, the centralized data collection mechanism such as NETCONF or gNMI requires data to be internally forwarded from those line cards to the main controller board, which then combines the individual data items into a single consolidated stream, resulting in a performance bottleneck, especially when large amounts of data is needed. What is needed instead is the support for a distributed mechanism that allows to directly push multiple individual substreams, e.g., one from each line card, but still allowing those substreams to be managed and controlled via a single subscription. UPC [b-IETF UPC] natively supports the distributed data collection mechanism.
+
+For dynamic subscription, in the case that a receiver (subscriber) is associated with multiple data originators, and notification messages are pushed on separate channels, all publication channels must share the same subscription session.
+
+For a configured subscription, the subscription configuration for every publication channel must contain the receiver's IP address and port number as destination IP address and port number.
+
+### 11.4 BGP-LS
+
+BGP-LS [b-IETF RFC 7752] specifies a mechanism by which link-state and TE information can be collected from networks and shared with external components using the BGP routing protocol. This is achieved using a new BGP network layer reachability information (NLRI) encoding format. A
+
+router maintains one or more databases for storing link-state information about nodes and links in any given area. Link attributes stored in these databases include local/remote IP addresses, local/remote interface identifiers, link metric, and TE metric, link bandwidth, reservable bandwidth, per class-of-service (CoS) class reservation state, preemption, and shared risk link groups (SRLGs). A BGP speaker may distribute the real physical topology from the link state database (LSDB) or the traffic engineering database (TED). Also, it may create an abstracted topology such as network slice, where virtual nodes are connected by virtual paths.
+
+With the aid of BGP-LS, the big data plane can retrieve the complete topological visibility within a "domain" (such as an interior gateway protocol (IGP) area) or across multiple domains such as a multi-area autonomous system (AS) or multiple ASs. When the whole network topological visibility is transmitted to the network plane, the network controller can determine the end-to-end MPLS-TE path across IGP areas or ASs and can even select the right exit router such as area border router (ABR) or autonomous system border router (ASBR) for an optimal path. However, without the network controller, the source router could only compute the path for the first area because the router only has full topological visibility for the first area along the path.
+
+- bDDN is required to support BGP-LS for network topological visibility. Network devices (e.g., routers) from the network infrastructure layer act as BGP-LS producer, originating link-state information from their underlying link-state IGP protocols into BGP-LS. And the big data plane acts as BGP-LS consumer, handing off the BGP-LS information that they have collected to a consumer application; also, as BGP-LS propagator, propagating the BGP-LS information to the network controller layer of the network plane for path computation and so on.
+
+### 11.5 BMP
+
+The BGP monitoring protocol (BMP) [b-IETF RFC 7854] can be used to monitor BGP sessions and obtain BGP route views. BMP provides access to the Adj-RIB-In of a peer on an ongoing basis and a periodic dump of certain statistics the monitoring station can use for further analysis.
+
+- bDDN is required to support BMP for the visibility of BGP routes and BGP sessions state, including:
+ - Route monitoring: Used to provide an initial dump of all routes received from a peer, as well as an ongoing mechanism that sends the incremental routes advertised and withdrawn by a peer to the monitoring station.
+ - Route mirroring: A means of providing a full-fidelity view of all messages received from its peers, for the purpose of error reporting and diagnosis.
+ - Statistics reports: An ongoing dump of statistics that can be used by the monitoring station as a high-level indication, including the number of routes in Adj-RIBs-In, the number of routes in Loc-RIB, the number of prefixes rejected by inbound policy, the number of prefixes subjected to treat-as-withdraw treatment, the number of prefixes invalidated due to AS\_PATH loop, etc.
+ - Peer down notification: A message sent to indicate that a peering session has gone down, with information indicating the reason for the session disconnect.
+ - Peer up notification: A message sent to indicate that a peering session has come up.
+
+### 11.6 Other interfaces
+
+Several conventional techniques and protocols supporting network data collection (e.g., SNMP, Syslog, and IPFIX) have been widely deployed. Based on a large amount of OAM data obtained from these interfaces, network operators can monitor network health status, make troubleshooting, analyse network traffic flows, manage routine operation and maintenance, etc.
+
+The simple network management protocol (SNMP) [b-IETF RFC 3416] uses a polling-based method to periodically retrieve network data, such as interface traffic statistics. Also, SNMP employs event management information base (MIB) and alarm management information base (MIB) (i.e., SNMP trap) to push management plane warnings.
+
+- bDDN is required to support SNMP until it has been completely replaced by network telemetry techniques.
+
+The Syslog protocol [b-IETF RFC 5424] specifies the standard format for syslog messages and is used to convey event notification messages, including interface UP and DOWN, the running status of signalling and control protocol, abnormal login, hardware or software failure, etc. During the runtime of network devices, the log module in the host software will record various conditions, so as to form log information transmitted to a syslog server for analysis. It mainly provides convenience for operators to retrieve the running status of network devices, diagnose network fault and analyse the root causes of failures.
+
+- bDDN is required to support Syslog for log analysis.
+
+IP flow information export (IPFIX) [b-IETF RFC 7011] provides a means of transmitting traffic flow information for administrative or other purposes. IPFIX data enables numerous critical applications, such as usage-based accounting, traffic profiling, traffic engineering, network security, QoS monitoring, and so on. Hence its value is highly weighed by internet service providers (ISPs).
+
+- bDDN is required to support IPFIX for traffic flow visibility.
+
+## **12 Requirements for network visibility of other aspects**
+
+### **12.1 Requirements for the visibility of real-time congestion**
+
+Congestion is a common phenomenon in IP networks. Network congestion leads to the deterioration of network performance and increases the uncertainty of service delivery. In order to reduce the uncertain services caused by network congestion, it is necessary to monitor the status and trend of network congestion in real-time manner, evaluate network congestion level. And the visibility of real-time congestion will provide the accurate basis for network planning, capacity expansion and optimization.
+
+#### **1) Requirements for the network infrastructure layer**
+
+The network infrastructure layer includes all kinds of IP network devices implementing packet forwarding.
+
+- The network infrastructure layer is required to support dynamic subscription or configured subscription, serving as a publisher that can send notification messages to a receiver. It accepts subscription services from the big data plane and sends telemetry data according to the subscription requests.
+- The network infrastructure layer device is required to support sending interface congestion state data to the big data plane in real-time manner, including packet loss data caused by queue overflow or/and queue depth data, in the case of the congestion conditions satisfied.
+- The network infrastructure layer device is required to leverage built-in dedicated hardware chip to detect interface congestion state at millisecond interval periodically, including packet loss by queue overflow or/and queue depth., in the case of the congestion conditions satisfied, that is, when the number of dropped packets caused by queue overflow is greater than the preset threshold (e.g., 0), or queue depth is greater than the preset threshold, it must send the corresponding congestion state data to CPU of main control card or line card in real time, which encapsulates them as telemetry packets with the timestamp of congestion occurrence and then sends them to the big data plane. Also, the interface congestion state
+
+data must carry congestion location information including device ID, interface ID and queue ID.
+
+- The network infrastructure layer device is required to support sending the congestion state data via the dedicated hardware chip to management or control entity (CPU) in on-change mode, which encapsulates it as telemetry data to the big data plane. For on-change updates, it is required to support a dampening period that needs to be passed before the subsequent on-change updates are sent. The dampening period should be configurable as part of the subscription request. Compared with periodic updates, on-change updates can cut down data volume sent greatly.
+ - The network infrastructure layer device is also required to configure management or control entity (CPU) to collect interface traffic statistics at minute-level interval periodically.
+- 2) Requirements for the big data plane
+- The big data plane is required to support dynamic subscriptions or configured subscriptions, serving as a subscriber that can accept notification messages from a publisher.
+ - The network big data sensing layer is required to collect congestion state data from the network infrastructure layer in real-time manner. Also, it is required to collect interface traffic statistics at minute-level interval periodically.
+ - The network big data repository layer is recommended to store the aforementioned congestion state data and interface traffic statistics for at least a month.
+ - The network big data analyser layer is required to perform real-time computation and analysis of the collected data. Some data analysis methods such as statistical analytical method, visualization analytical method, correlation analytical method are necessary.
+ - The data intelligence and service layer is required to support the real-time visualization of interface congestion state data and traffic data. Visualization should exhibit interface congestion state and traffic data in the form of curves, tables, charts and topology maps, etc., so that network operators can see and understand it intuitively. Figure 12-1 is an example of interface packet loss chart, Figure 12-2 is an example of interface queue depth chart, and Figure 12-3 is an example of interface traffic curve. Figure 12-4 is an example of network topology map with the congested interface on real-time display in bright red colour.
+ - Data intelligence and service layer is required to provide the network plane with real-time congestion status and trend, so that those key traffic flows can be optimized promptly.
+ - Data intelligence and service layer is also required to provide the management plane with interface traffic statistics, so that the capacity expansion and optimization can be evaluated appropriately.
+
+
+
+Number of dropped packets
+
+Time (h:m:s:ms)
+
+Y.3657(23)
+
+Figure 12-1: An example of interface packet loss chart. The chart shows the number of dropped packets over time. The y-axis is labeled 'Number of dropped packets' and the x-axis is labeled 'Time (h:m:s:ms)'. The chart displays several vertical bars of varying heights, indicating periodic packet loss events. The reference Y.3657(23) is noted at the bottom right of the x-axis.
+
+**Figure 12-1 – An example of interface packet loss chart**
+
+
+
+Figure 12-2: An example of interface queue depth chart. The chart shows Queue depth on the Y-axis and Time (h:m:s:ms) on the X-axis. The data is represented by a series of vertical spikes of varying heights, indicating periodic queue depth increases over time. The source is Y.3657(23).
+
+**Figure 12-2 – An example of interface queue depth chart**
+
+
+
+Figure 12-3: An example of interface traffic curve. The chart shows Utilization on the Y-axis (ranging from 50% to 100%) and Time (h) on the X-axis. The data is represented by a smooth, wavy line that fluctuates between approximately 40% and 90% utilization. The source is Y.3657(23).
+
+**Figure 12-3 – An example of interface traffic curve**
+
+
+
+Figure 12-4: An example of network topology with the congested interface on real-time displayed in bright red colour. The diagram shows a network topology with nine routers (R1 to R9) connected in a mesh-like structure. The link between R2 and R3 is highlighted in bright red and labeled 'Congested interface'. A red star is placed on this link, with an arrow pointing to it from the text 'Packet loss at port 1'. The source is Y.3657(23).
+
+**Figure 12-4 – An example of network topology with the congested interface on real-time displayed in bright red colour**
+
+### 12.2 Requirements for the visibility of real-time link quality
+
+The link quality of IP bearer network plays a key role in network transmission performance. The degradation of link quality will lead to the increase of transmission bit error rate (BER), which will convert to cyclic redundancy check (CRC) error packets discarded by the network forwarding device. The increase of network packet loss rate will affect the quality of service, especially to applications with sensitivity of packet loss. It is necessary to monitor the status and degradation trend of link quality in real-time manner and evaluate the level of link quality. Furthermore, the visibility of real-time link quality will help network operators improve the efficiency of fault diagnosis and root cause analysis.
+
+#### 1) Requirements for the network infrastructure layer
+
+The network infrastructure layer includes all kinds of network devices performing packet forwarding.
+
+- The network infrastructure layer device is required to support dynamic subscriptions or configured subscriptions, serving as a publisher that can send notification messages to a receiver. It accepts subscriptions services from the big data plane and sends telemetry data according to the subscription requests.
+- The network infrastructure layer device is required to support sending port link quality data to the big data plane periodically, including the number of CRC error packets of interface, transmitting optical power of optical module, receiving optical power of optical module.
+
+Also, the `suppress_redundant` function is needed, so that it should not generate a telemetry update message unless the value of the subscribed data object has changed.
+
+- The network infrastructure layer device is required to support sending the corresponding telemetry data to the big data plane in on-change mode, i.e., whenever values of subscribed data objects change. For on-change updates, it is required to support a dampening period that needs to be passed before the subsequent on-change updates are sent. The dampening period should be configurable as part of the subscription request. Compared with periodic updates, on-change updates can cut down data volume sent greatly.
+- The network infrastructure layer device is required to support sending the corresponding telemetry data to the big data plane based on the threshold triggered. That is, when the number of CRC error packets, or the transmitting optical power, or the receiving optical power exceeds its preset threshold, respectively, a warning telemetry update must be generated. The update frequency should be configurable as part of the subscription request.
+- The network infrastructure layer device is required to encapsulate the aforementioned data as telemetry packets, which carry information including timestamp, device ID and interface ID.
+
+#### 2) Requirements for the big data plane
+
+- The big data plane is required to support dynamic subscriptions or configured subscriptions, serving as a subscriber that can accept notification messages from a publisher.
+- Network big data sensing layer is required to support the following three subscription modes for collecting link quality data from the network device:
+ - Periodic update.
+ - On-change update.
+ - Update based on the threshold triggered.
+- The network big data repository layer is recommended to store link quality data for at least a month.
+- The network big data analyser layer is required to perform real-time computation and analysis of the collected link quality data, including the number of CRC error packets, transmitting optical power and receiving optical power, to determine the port link quality. Some data analysis methods such as statistical analytical method, visualization analytical method, correlation analytical method are necessary.
+- The network big data analyser layer is required to make intelligent analysis of the collected link quality data as follows:
+ - If the collected data of receiving optical power of optical module deviates from the normal working range, susceptible to transmission BER, also, the number of CRC error packets is increasing, though not beyond the threshold (as shown in Figure 12-5 and Figure 12-6), this port link is determined to be abnormal due to an optical module problem.
+ - If both the collected data of receiving optical power of optical module and those of the number of CRC error packets are all warning data triggered by the respective threshold, this port link is determined to be abnormal due to optical power of optical module problem.
+ - If the number of CRC error packets is increasing, but the collected data of receiving optical power of optical module are in the normal working range, this port link is determined to be abnormal due to improper configuration or loose contact of interface.
+ - If the collected data of transmitting optical power of optical module deviates from the normal working range, or are warning data triggered by the threshold, it will have
+
+influence on packet receiving of the connected device, and this port link is determined to be abnormal due to transmitting optical power of optical module problem.
+
+- Data intelligence and service layer is required to support the visualization of link quality data. Visualization should exhibit link quality state and degradation trend in the form of curves, tables, charts and maps, etc., so that network operators can see and understand it intuitively. Figure 12-5 is an example of curve for the collected data of interface CRC error packets, Figure 12-6 is an example of curve for the collected data of receiving optical power of optical module, and Figure 12-7 is an example of network topology with the link quality on real-time display in bright red colour.
+- Data intelligence and service layer is required to provide the network plane with the real-time link quality status and trend, so that network operators can make traffic rerouting or optimization promptly.
+- Data intelligence and service layer is also required to provide the management plane with the real-time link quality status and trend, so that network operators can make fault diagnosis and troubleshooting rapidly.
+
+
+
+Figure 12-5 is a line graph showing the trend of CRC error packets over time. The vertical axis is labeled 'CRC error packets' and the horizontal axis is labeled 'Time (h:m:s:ms)'. A solid black curve starts at a low value and rises steadily, approaching a horizontal dashed line labeled 'Threshold'. The text 'Y.3657(23)' is at the bottom right.
+
+Figure 12-5: A line graph showing CRC error packets over time. The y-axis is labeled 'CRC error packets' and the x-axis is labeled 'Time (h:m:s:ms)'. A solid black curve starts at a low value and rises steadily, approaching a horizontal dashed line labeled 'Threshold'. The text 'Y.3657(23)' is at the bottom right.
+
+**Figure 12-5 – An example of curve for the collected data of interface CRC error packets**
+
+
+
+Figure 12-6 is a line graph showing the trend of receiving optical power over time. The vertical axis is labeled 'Receiving optical power' and the horizontal axis is labeled 'Time (h:m:s:ms)'. A solid black curve fluctuates between two horizontal dashed lines labeled 'Upper normal limit' and 'Lower normal limit'. The text 'Y.3657(23)' is at the bottom right.
+
+Figure 12-6: A line graph showing receiving optical power over time. The y-axis is labeled 'Receiving optical power' and the x-axis is labeled 'Time (h:m:s:ms)'. A solid black curve fluctuates between two horizontal dashed lines labeled 'Upper normal limit' and 'Lower normal limit'. The text 'Y.3657(23)' is at the bottom right.
+
+**Figure 12-6 – An example of curve for the collected data of receiving optical power of optical module**
+
+
+
+Figure 12-7 is a network topology diagram showing 9 routers (R1 to R9) connected in a mesh-like structure. The link between R2 and R3 is highlighted in bright red with a star icon and labeled 'CRC error' and 'Link quality abnormal'. The text 'Y.3657(23)' is at the bottom right.
+
+Figure 12-7: A network topology diagram with 9 routers (R1 to R9). The link between R2 and R3 is highlighted in bright red with a star icon and labeled 'CRC error' and 'Link quality abnormal'. The text 'Y.3657(23)' is at the bottom right.
+
+**Figure 12-7 – An example of network topology with the link quality on real-time display in bright red colour**
+
+# **13 Security considerations**
+
+When implementing network visibility in bDDN, security best practices should be adopted such as authentication, authorization and access control and described in [ITU-T Y.2704].
+
+## Bibliography
+
+- [b-IETF RFC 3416] IETF RFC 3416 (2002), *Version 2 of the Protocol Operations for the Simple Network Management Protocol (SNMP)*.
+- [b-IETF RFC 5246] IETF RFC 5246 (2008), *The Transport Layer Security (TLS) Protocol Version 1.2*.
+- [b-IETF RFC 5357] IETF RFC 5357 (2008), *A Two-Way Active Measurement Protocol (TWAMP)*.
+- [b-IETF RFC 5424] IETF RFC 5424 (2009), *The Syslog Protocol*.
+- [b-IETF RFC 6241] IETF RFC 6241 (2011), *Network Configuration Protocol (NETCONF)*.
+- [b-IETF RFC 7011] IETF RFC 7011 (2013), *Specification of the IP Flow Information Export (IPFIX) Protocol for the Exchange of Flow Information*.
+- [b-IETF RFC 7432] IETF RFC 7432 (2015), *BGP MPLS-Based Ethernet VPN*.
+- [b-IETF RFC 7752] IETF RFC 7752 (2016), *North-Bound Distribution of Link-State and Traffic Engineering (TE) Information Using BGP*.
+- [b-IETF RFC 7854] IETF RFC 7854 (2016), *BGP Monitoring Protocol (BMP)*.
+- [b-IETF RFC 8639] IETF RFC 8639 (2019), *Subscription to YANG Notifications*.
+- [b-IETF RFC 8641] IETF RFC 8641 (2019), *Subscription to YANG Notifications for Datastore Updates*.
+- [b-IETF RFC 9197] IETF RFC 9197 (2022), *Data Fields for In Situ Operations, Administration, and Maintenance (IOAM)*.
+- [b-IETF RFC 9232] IETF RFC 9232 (2022), *Network Telemetry Framework*.
+- [b-IETF RFC 9256] IETF RFC 9256 (2022), *Segment Routing Policy Architecture*.
+- [b-IETF RFC 9326] IETF RFC 9326 (2022), *In Situ Operations, Administration, and Maintenance (IOAM) Direct Exporting*.
+- [b-IETF RFC 9341] IETF RFC 9341 (2022), *Alternate-Marking Method*.
+- [b-IETF RFC 9343] IETF RFC 9343 (2022), *IPv6 Application of the Alternate-Marking Method*.
+- [b-GNMI-SPEC] GNMI-SPEC (2018), *OpenConfig operator working group, gRPC Network Management Interface (gNMI) v0.6.0*.
+- [b-IETF UPC] IETF UPC (2020), *UDP based Publication Channel for Streaming Telemetry. Work in progress*.
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation
+
+## **ITU-T Y.3824 (09/2024)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Quantum key distribution networks
+
+---
+
+## **Quantum key distribution network federation – Reference models**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+# Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+| | |
+|--------------------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | Y.100-Y.999 |
+| General | Y.100-Y.199 |
+| Services, applications and middleware | Y.200-Y.299 |
+| Network aspects | Y.300-Y.399 |
+| Interfaces and protocols | Y.400-Y.499 |
+| Numbering, addressing and naming | Y.500-Y.599 |
+| Operation, administration and maintenance | Y.600-Y.699 |
+| Security | Y.700-Y.799 |
+| Performances | Y.800-Y.899 |
+| INTERNET PROTOCOL ASPECTS | Y.1000-Y.1999 |
+| General | Y.1000-Y.1099 |
+| Services and applications | Y.1100-Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200-Y.1299 |
+| Transport | Y.1300-Y.1399 |
+| Interworking | Y.1400-Y.1499 |
+| Quality of service and network performance | Y.1500-Y.1599 |
+| Signalling | Y.1600-Y.1699 |
+| Operation, administration and maintenance | Y.1700-Y.1799 |
+| Charging | Y.1800-Y.1899 |
+| IPTV over NGN | Y.1900-Y.1999 |
+| NEXT GENERATION NETWORKS | Y.2000-Y.2999 |
+| Frameworks and functional architecture models | Y.2000-Y.2099 |
+| Quality of Service and performance | Y.2100-Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200-Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250-Y.2299 |
+| Enhancements to NGN | Y.2300-Y.2399 |
+| Network management | Y.2400-Y.2499 |
+| Computing power networks | Y.2500-Y.2599 |
+| Packet-based Networks | Y.2600-Y.2699 |
+| Security | Y.2700-Y.2799 |
+| Generalized mobility | Y.2800-Y.2899 |
+| Carrier grade open environment | Y.2900-Y.2999 |
+| FUTURE NETWORKS | Y.3000-Y.3499 |
+| CLOUD COMPUTING | Y.3500-Y.3599 |
+| BIG DATA | Y.3600-Y.3799 |
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800-Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | Y.4000-Y.4999 |
+| General | Y.4000-Y.4049 |
+| Definitions and terminologies | Y.4050-Y.4099 |
+| Requirements and use cases | Y.4100-Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250-Y.4399 |
+| Frameworks, architectures and protocols | Y.4400-Y.4549 |
+| Services, applications, computation and data processing | Y.4550-Y.4699 |
+| Management, control and performance | Y.4700-Y.4799 |
+| Identification and security | Y.4800-Y.4899 |
+| Evaluation and assessment | Y.4900-Y.4999 |
+
+For further details, please refer to the list of ITU-T Recommendations.
+
+# Recommendation ITU-T Y.3824
+
+# Quantum key distribution network federation – Reference models
+
+## Summary
+
+As quantum key distribution networks (QKDNs) are being deployed globally, further need for interoperability and interconnection arises. The starting of federations of QKDNs can facilitate the sharing of their resources and capabilities among them. Recommendation ITU-T Y.3824 specifies the reference models for QKDN federation (QKDNf).
+
+## History \*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T Y.3824 | 2024-09-13 | 13 | 11.1002/1000/16132 |
+
+## Keywords
+
+Quantum key distribution (QKD), QKD network (QKDN), QKDN federation (QKDNf), reference model.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+### NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2024
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|-----------------------------------------------------------|-------------|
+| 1 Scope ..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere..... | 1 |
+| 3.2 Terms defined in this Recommendation..... | 1 |
+| 4 Abbreviations and acronyms ..... | 1 |
+| 5 Conventions ..... | 2 |
+| 6 Overview of QKDNf ..... | 2 |
+| 6.1 Concept of QKDNf..... | 2 |
+| 6.2 Scenario of QKDNf..... | 2 |
+| 6.3 Considerations for QKDNf..... | 3 |
+| 7 Reference models for QKDNf..... | 3 |
+| 7.1 Reference model for QKDNf with direct interface ..... | 3 |
+| 7.2 Reference model for QKDNf with QKDNf broker ..... | 4 |
+| 8 Security considerations..... | 5 |
+| Appendix I – Use cases of QKDNf..... | 6 |
+| I.1 Use cases of QKDNf ..... | 6 |
+| Bibliography..... | 9 |
+
+
+
+# Recommendation ITU-T Y.3824
+
+## Quantum key distribution network federation – Reference models
+
+# 1 Scope
+
+This Recommendation specifies the reference models for QKDN federation (QKDNf).
+
+In particular, this Recommendation includes:
+
+- Overview of QKDNf
+- Reference models for QKDNf.
+
+Appendix I describes use cases of QKDNf.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T X.1710] Recommendation ITU-T X.1710 (2020), *Security framework for quantum key distribution networks*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 quantum key distribution (QKD)** [b-ETSI GR QKD 007]: Procedure or method for generating and distributing symmetrical cryptographic keys with information theoretical security based on quantum information theory.
+
+**3.1.2 quantum key distribution network (QKDN)** [b-ITU-T Y.3800]: A network comprised of two or more quantum key distribution (QKD) nodes connected through QKD links.
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 QKDN federation:** A functionality that ensures quantum key distribution network (QKDN) service continuity in multi-QKDN provider operation scenarios through resource sharing and coordinated service provision.
+
+**3.2.2 QKDN federation broker:** A functional entity designed to simplify the federation management of multiple quantum key distribution network (QKDN) providers.
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-----|-----------------------------------|
+| API | Application Programming Interface |
+| QKD | Quantum Key Distribution |
+
+| | |
+|-------|-----------------------------------------------|
+| QKDN | Quantum Key Distribution Network |
+| QKDNf | Quantum Key Distribution Network Federation |
+| QKDNI | Quantum Key Distribution Network Interworking |
+| QoS | Quality of Service |
+
+# 5 Conventions
+
+None.
+
+# 6 Overview of QKDNf
+
+For large-scale quantum key distribution networks (QKDNs) involving multiple providers, it is crucial to efficiently integrate resources to ensure consistent service delivery and to support the provision of quantum key distribution (QKD) services for end-to-end users across different providers. This can be achieved through cooperation among various QKDN providers, which is commonly referred to as QKDN federation (QKDNf).
+
+This Recommendation specifies reference models for QKDNf, enabling QKDN providers to share resources and capabilities for user service covering a large network area.
+
+## 6.1 Concept of QKDNf
+
+QKDNf is a functionality for the interaction and coordination among QKDN providers, supporting a multi-operator, -network, -vendor environment to provide consistent QKD service to the end users. If the end user wishes to maintain the same level of security which a QKDN provides when the end user moves to the region of another QKDN provider, then the end user needs to identify the service capability in that region. The relevant QKDN service discovery, network capability discovery, resource allocation and negotiation, and the subsequent service provisioning need to be performed. As QKD is being deployed globally, however, still limited coverage exists from a QKDN perspective as only some operators deploy them in parts of their networks. Therefore, it is crucial to have the mechanisms to have the same level of security service in the different regions where possible and to combine resources (e.g., keys and available key relay) among multiple providers. Furthermore, QKDN sharing can be considered where an operator lacks QKDN coverage in certain regions of a country.
+
+Figure 1 shows a conceptual model of QKDNf, where each federation involves QKDNs with authorized network resources or capabilities.
+
+
+
+Figure 1: Conceptual model of QKDNf. The diagram shows three QKDN federations. Federation 1 (top left) is connected to QKDN A and QKDN B. Federation 2 (top middle, dashed box) is connected to QKDN X and QKDN Y. Federation 3 (top right) is connected to QKDN Z. Dotted lines indicate connections between the federations and their respective QKDNs. An ellipsis (...) is shown between Federation 1 and Federation 2, and between Federation 3 and the right side of the diagram. The reference Y.3824(24) is at the bottom right.
+
+**Figure 1 – Conceptual model of QKDNf**
+
+## 6.2 Scenario of QKDNf
+
+The following describes a scenario similar to national roaming, where the end users of QKDN provider A can access the QKD service provided by QKDN provider B through a mutual agreement between the two providers. In this scenario, although the end user is a customer of QKDN provider
+
+A, the optimal location for receiving QKD service falls within the network coverage of QKDN provider B.
+
+When the end user initiates the QKD service on their device, the QKD network of QKDN provider A recognizes that the ideal location for service provision is within the network coverage of QKDN provider B, based on the established federation agreement. As a result, the QKD service of QKDN provider A redirects the service request to the QKD network of QKDN provider B, ensuring that the requested QKD service is provided to the end user consistently.
+
+Appendix I details two use cases of QKDNf that extends this scenario to specific applications.
+
+## 6.3 Considerations for QKDNf
+
+The primary advantage of QKDNf is to enable global access to QKD services across different geographical regions. QKDNf allows QKDN providers to offer their services to end users, even when these users move across various QKDNs. It is crucial that the QKD service consistently continues as the end user connects to different visited networks.
+
+Furthermore, QKDNf presents an opportunity to minimize capital expenditure (CAPEX) for QKDN providers while promoting the sharing of QKDN resources. It allows providers to leverage existing infrastructure and resources of other providers, enabling efficient utilization and avoiding unnecessary duplication of QKDN deployments. By sharing QKDN resources, providers can optimize their operations and expand their service coverage without significant additional investments.
+
+To establish QKDNf, effective communication and coordination among QKDN providers is essential. This involves exchanging information related to QKDNf discovery, resource negotiation and allocation, service provisioning, security aspects (such as authentication and authorization), charging, identity management, and monitoring. Federation agreements can be established directly between QKDN providers. However, QKDN providers may choose to utilize a federation broker if they intend to establish federation agreements with as many other providers as possible. The QKDN federation broker can have a pre-established list of agreements with a large number of QKDN providers, facilitating QKDNf operations.
+
+# 7 Reference models for QKDNf
+
+## 7.1 Reference model for QKDNf with direct interface
+
+
+
+QKDN federation function
+
+Ff
+
+QKDN federation function
+
+Fm
+
+QKDN management layer
+
+QKDN control layer
+
+Key management layer
+
+Quantum layer
+
+QKDN-A
+(QKDN provider-A)
+
+QKDN control layer
+
+Key management layer
+
+Quantum layer
+
+QKDN management layer
+
+QKDN-B
+(QKDN provider-B)
+
+Y.3824(24)
+
+Figure 2: Reference model for QKDNf with direct interface between QKDNf functions. The diagram shows two QKDN providers, QKDN-A and QKDN-B, connected via a direct interface labeled 'Ff'. Each provider has a 'QKDN federation function' block at the top. Below this, a dashed box represents the internal structure of each provider. Inside the dashed box, there is a vertical stack of three layers: 'QKDN management layer', 'Key management layer', and 'Quantum layer'. The 'QKDN federation function' block is connected to the 'QKDN management layer' via a line labeled 'Fm'. The 'QKDN management layer' is connected to the 'Key management layer', which is connected to the 'Quantum layer'. The diagram is labeled 'QKDN-A (QKDN provider-A)' and 'QKDN-B (QKDN provider-B)' at the bottom, with a reference 'Y.3824(24)' on the right.
+
+Figure 2 – Reference model for QKDNf with direct interface between QKDNf functions
+
+Figure 2 presents a reference model that outlines the framework for enabling QKDNf, featuring a direct interface between QKDNf functions. The goal is to establish end-to-end QKD services across different QKDN providers through QKDNf.
+
+NOTE 1 – QKDNf functions can be supported by quantum key distribution network interworking (QKDNi) functions. A unified policy on service provisioning ensures consistent end-to-end key supply among QKDN providers, with necessary QKDNi functions for key relay routing between providers. The specific functional supporting aspects are out of scope of this Recommendation.
+
+The QKDNf function is a functional entity designed to enable end-to-end QKD services among different QKDN providers. It achieves this by facilitating seamless coordination, communication, and integration of services across QKDNs with different providers. It includes the following functional aspects:
+
+- Service discovery: Identifying available QKD services across different providers.
+- Resource negotiation and allocation: Managing and negotiating the allocation of network resources to ensure efficient service delivery.
+- Charging: Handling the charging policies associated with the usage of QKD services.
+- Security aspects: Ensuring robust security measures including authentication, authorization, and identity management.
+- Service provisioning: Enabling the provisioning of QKD services by facilitating necessary configurations and setups.
+
+NOTE 2 – As illustrated in Appendix I, QKDNf can enhance service provision. This enhancement is complementary to the efficiency improvements in control and management aspects achieved by QKDN orchestration.
+
+In order to enable QKDNf, two reference points are identified within the reference model:
+
+- Ff: This reference point serves as the interface between QKDNf functions, facilitating QKDNf-related procedures such as service discovery, resource negotiation and allocation, charging, security aspects (including authentication and authorization), and identity management. Ff ensures seamless coordination and communication between QKDNf functions across different providers.
+- Fm: This reference point acts as the interface between QKDN manager and QKDNf functions. Fq supports QKDNf-related procedures including service discovery, resource negotiation and allocation, and service provisioning. It enables the exchange of information and capabilities between QKDN providers and QKDNf functions, ensuring the effective integration and utilization of QKD services within the QKDNf framework.
+
+These reference points play a crucial role in enabling the necessary communication and interaction between QKDNf functions, as well as between QKDNs and QKDNf functions, to establish a seamless QKDNf ecosystem.
+
+## 7.2 Reference model for QKDNf with QKDNf broker
+
+The introduction of the QKDNf broker is primarily aimed at simplifying the federation management of multiple providers. The QKDNf broker is a functional entity within the QKDNf ecosystem that acts as an intermediary to facilitate the establishment and management of QKD services between different QKDN providers. The broker helps to streamline interactions and negotiations, providing a centralized coordination point for service management. It includes the following functional aspects:
+
+- Service coordination: Managing the coordination of QKDN providers to ensure seamless delivery of QKD services.
+- Resource brokerage: Facilitating the negotiation and allocation of network resources across QKDN providers.
+
+- Security assurance: Ensuring that security policies are uniformly enforced across the federated QKDNs.
+
+Figure 3 shows a reference model for enabling QKDNf with QKDNf broker. Same reference points are identified as shown in Figure 2.
+
+
+
+The diagram illustrates a reference model for QKDNf with a broker. It shows two QKDN providers, QKDN-A (QKDN provider-A) and QKDN-B (QKDN provider-B), connected via a QKDN federation broker. Each provider consists of a QKDN federation function and a QKDN management layer. The QKDN management layer is further divided into three sub-layers: QKDN control layer, Key management layer, and Quantum layer. The QKDN federation function is connected to the QKDN management layer via reference point Fm. The QKDN federation broker is connected to the QKDN federation function of both providers via reference point Ff.
+
+Figure 3: Reference model for QKDNf with broker between QKDNf functions. The diagram shows two QKDN providers, QKDN-A and QKDN-B, connected via a QKDN federation broker. Each provider has a QKDN federation function and a QKDN management layer. The QKDN management layer is divided into three sub-layers: QKDN control layer, Key management layer, and Quantum layer. The QKDN federation function is connected to the QKDN management layer via reference point Fm. The QKDN federation broker is connected to the QKDN federation function of both providers via reference point Ff.
+
+**Figure 3 – Reference model for QKDNf with broker between QKDNf functions**
+
+# 8 Security considerations
+
+QKDNf may involve exchanging information at the management level, but there should be considerations for isolation security when handling information from different QKDNs. For detailed information, refer to [ITU-T X.1710].
+
+# Appendix I
+
+## Use cases of QKDNf
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix provides use cases of QKDNf.
+
+## I.1 Use cases of QKDNf
+
+### Use case 1 – QKDNf for end-to-end key supply with multiple QKDN providers
+
+The scenario described in clause 6.2 can be extended to a specific use case focusing on service consistency. In this context, providers can ensure consistent QKD services across different regions by leveraging shared resources and capabilities through the QKDN federation.
+
+
+
+The diagram illustrates a QKDN federation consisting of two providers, A and B. Each provider has a set of QKD nodes (A, B, C, D) and associated managers (QKDN manager, QKDN controller, Key manager, QKD module). A cryptographic application is shown at the top, connected to the QKDN managers of both providers. The diagram is labeled Y.3824(24).
+
+Legend:
+
+- Cryptographic application
+- QKDN manager
+- QKDN controller
+- Key manager
+- QKD module
+
+Y.3824(24)
+
+Diagram illustrating the use case of service consistency with multiple providers through QKDNf. The diagram shows two QKDN providers, A and B, connected via a QKDN federation. Each provider has its own QKD nodes (A, B, C, D) and associated managers (QKDN manager, QKDN controller, Key manager, QKD module). A cryptographic application is shown at the top, connected to the QKDN managers of both providers. The diagram is labeled Y.3824(24).
+
+**Figure I.1 – Use case of service consistency with multiple providers through QKDNf**
+
+As illustrated in Figure I.1, each region is served by different QKDN providers. For a QKD service spanning provider-A and -B, such as secure video conferencing and sensitive data exchange, it is necessary to maintain a consistent service level during communications across providers A and B.
+
+For a cryptographic application, the service continuity can be supported through the QKDNf functions:
+
+- Federation agreement: QKDN providers A and B establish a federation agreement that allows access to each other's status of QKD-service capability through QKDNf functions.
+- Service discovery and allocation: When a cryptographic application initiates secure communication from provider A, the local QKDN provider checks if the communication needs to connect to the cryptographic application of provider B. This is facilitated by the QKDNf function, which enables discovery of available services and resources across federated QKDNs.
+- Resource coordination: If the recipient is with provider B, provider A communicates with provider B through the federation framework, facilitated by the QKDNf function, to allocate
+
+necessary resources. This includes distributing an equal amount of KSA keys among KM-A, B, C and D, ensuring continuity of service.
+
+- Seamless service provisioning: The QKDNf function enables providers A and B to seamlessly provide a key relay route (A-B-C-D) between QKD nodes A-B, B-C, and C-D. This ensures that the communication remains secure across borders without requiring end users to manually switch services or experience interruptions.
+
+Based on the above steps, QKDNf can ensure a consistent key supply policy between QKDN providers A and B, while the specific key relay between QKD nodes B and C can be supported through quantum key distribution network interworking (QKDNi) functions.
+
+#### Use case 2 – QKDNf for resilience
+
+The scenario described in clause 6.2 can be extended to a specific use case focusing on resilience. In the context of resilience, providers in areas susceptible to network failures can ensure uninterrupted QKD services by leveraging shared resources across the federation.
+
+
+
+The diagram illustrates a QKDN federation for resilience. It shows two providers, QKDN provider-A and QKDN provider-B, each containing multiple QKD nodes (A, B, C, D). Each node is connected to a QKD manager, a QKD controller, and a QKD module. Cryptographic applications are connected to the QKD nodes via application links. The federation is managed by a central QKDN manager and controller. A legend identifies the components: Cryptographic application, QKDN manager, QKDN controller, Key manager, and QKD module. The diagram is labeled Y.3824(24).
+
+Figure I.2: Use case of resilience with shared resources among QKDN providers. The diagram illustrates a QKDN federation consisting of QKDN provider-A and QKDN provider-B. Each provider contains QKD nodes (A, B, C, D) and associated components like QKD managers, controllers, and modules. Cryptographic applications are connected to the QKD nodes via application links. A legend identifies the components: Cryptographic application, QKDN manager, QKDN controller, Key manager, and QKD module. The diagram is labeled Y.3824(24).
+
+**Figure I.2 – Use case of resilience with shared resources among QKDN providers**
+
+As illustrated in Figure I.2, QKDN providers located in regions prone to failures may need to maintain uninterrupted QKD services, even in cases of infrastructure damage. Resilience can be supported through the QKDNf functions:
+
+- Federation agreements: With a nearby provider-B that does not experience failures, a pre-established federation agreement exists for providing QKD services in case of failures. The QKDNf function facilitates the creation and maintenance of these agreements.
+- Automatic service recovery: When a failure occurs, the affected QKDN provider-A automatically redirects its QKD service requests to another unaffected federated QKDN-B. The QKDNf function facilitates the creation and maintenance of these agreements.
+- Resource allocation and service continuity: Federated QKDN provider-B allocates resources to handle the increased load from QKDN provider-A, ensuring continuous availability of QKD services without interruptions. The QKDNf function is responsible for coordinating this resource allocation.
+
+- Monitoring and adjustment: Continuous monitoring and dynamic resource allocation, managed by the QKDNf function, allows the federation to adjust resource sharing in real-time based on the situation and duration of the failure. This optimizes key supply and minimizes disruptions.
+
+Through the above steps, QKDNf ensures the sharing of key resources between provider A and B at nodes A, B, and C, D, while maintaining a consistent key supply policy. This coordination enhances resilience, thereby jointly supporting cryptographic applications seamlessly.
+
+# Bibliography
+
+- [b-ITU-T Y.3800] Recommendation ITU-T Y.3800 (2019), *Overview on networks supporting quantum key distribution*.
+- [b-ETSI GR QKD 007] ETSI GR QKD 007 (2018), *Quantum Key Distribution (QKD) – Vocabulary*.
+
+
+
+
+
+# SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation
+
+## **ITU-T Y.3829 (08/2025)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Quantum key distribution networks
+
+---
+
+**Quantum key distribution networks
+interworking – Functional architecture for
+quality-of-service assurance**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+| | |
+|--------------------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | Y.100-Y.999 |
+| General | Y.100-Y.199 |
+| Services, applications and middleware | Y.200-Y.299 |
+| Network aspects | Y.300-Y.399 |
+| Interfaces and protocols | Y.400-Y.499 |
+| Numbering, addressing and naming | Y.500-Y.599 |
+| Operation, administration and maintenance | Y.600-Y.699 |
+| Security | Y.700-Y.799 |
+| Performances | Y.800-Y.899 |
+| INTERNET PROTOCOL ASPECTS | Y.1000-Y.1999 |
+| General | Y.1000-Y.1099 |
+| Services and applications | Y.1100-Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200-Y.1299 |
+| Transport | Y.1300-Y.1399 |
+| Interworking | Y.1400-Y.1499 |
+| Quality of service and network performance | Y.1500-Y.1599 |
+| Signalling | Y.1600-Y.1699 |
+| Operation, administration and maintenance | Y.1700-Y.1799 |
+| Charging | Y.1800-Y.1899 |
+| IPTV over NGN | Y.1900-Y.1999 |
+| NEXT GENERATION NETWORKS | Y.2000-Y.2999 |
+| Frameworks and functional architecture models | Y.2000-Y.2099 |
+| Quality of Service and performance | Y.2100-Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200-Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250-Y.2299 |
+| Enhancements to NGN | Y.2300-Y.2399 |
+| Network management | Y.2400-Y.2499 |
+| Computing power networks | Y.2500-Y.2599 |
+| Packet-based Networks | Y.2600-Y.2699 |
+| Security | Y.2700-Y.2799 |
+| Generalized mobility | Y.2800-Y.2899 |
+| Carrier grade open environment | Y.2900-Y.2999 |
+| FUTURE NETWORKS | Y.3000-Y.3499 |
+| CLOUD COMPUTING | Y.3500-Y.3599 |
+| BIG DATA | Y.3600-Y.3799 |
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800-Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | Y.4000-Y.4999 |
+| General | Y.4000-Y.4049 |
+| Definitions and terminologies | Y.4050-Y.4099 |
+| Requirements and use cases | Y.4100-Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250-Y.4399 |
+| Frameworks, architectures and protocols | Y.4400-Y.4549 |
+| Services, applications, computation and data processing | Y.4550-Y.4699 |
+| Management, control and performance | Y.4700-Y.4799 |
+| Identification and security | Y.4800-Y.4899 |
+| Evaluation and assessment | Y.4900-Y.4999 |
+
+For further details, please refer to the list of ITU-T Recommendations.
+
+# Recommendation ITU-T Y.3829
+
+## Quantum key distribution networks interworking – Functional architecture for quality-of-service assurance
+
+## Summary
+
+The quantum key distribution network (QKDN) is able to cover a wide area by interworking multiple QKDNs. This is called QKDN interworking (QKDNi). One of the challenges of the QKDNi is to assure network interworking performance and that different quality of service (QoS)/quality of experience (QoE) requirements of different interworking application scenarios are met.
+
+The requirements of QoS assurance for QKDNi specified in Recommendation ITU-T Y.3817 address these challenges. Based on the requirements, Recommendation ITU-T Y.3829 specifies the functional architecture, associated functional entities and reference points and a basic operational procedure.
+
+## History \*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T Y.3829 | 2025-08-29 | 13 | 11.1002/1000/16452 |
+
+## Keywords
+
+Functional architecture, QKDN, QKDNi, QoS assurance.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2025
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|----------------------------------------------------------------|-------------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere ..... | 1 |
+| 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 3 |
+| 6 Overview..... | 3 |
+| 7 Functional architecture of QoS assurance for QKDNi ..... | 3 |
+| 7.1 Functional entities for QKDNi QoS assurance ..... | 5 |
+| 7.2 QKDN control layer QoS assurance functional entity ..... | 6 |
+| 7.3 Key management layer QoS assurance functional entity ..... | 6 |
+| 7.4 QKDN cross-layer QoS assurance functional entity ..... | 7 |
+| 8 Reference points of the functional architecture ..... | 7 |
+| 9 Basic operational procedure of QoS assurance for QKDNi ..... | 7 |
+| 10 Security considerations ..... | 9 |
+| Bibliography..... | 10 |
+
+
+
+# Recommendation ITU-T Y.3829
+
+## Quantum key distribution networks interworking – Functional architecture for quality-of-service assurance
+
+# 1 Scope
+
+This Recommendation specifies the functional architecture of quality of service (QoS) assurance for quantum key distribution network interworking (QKDNi). The scope of this Recommendation is as follows:
+
+- Overview of QoS assurance for QKDNi.
+- Functional architecture of QoS assurance for QKDNi.
+- Reference points of the functional architecture.
+- Basic operational procedure of QoS assurance for QKDNi.
+
+The functional components of QoS assurance for QKDNi are extended based on the functional architecture of QoS assurance for QKDN [ITU-T Y.3811].
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- [[ITU-T E.860](#)] Recommendation ITU-T E.860 (2002), *Framework of a service level agreement*.
+- [[ITU-T Y.3810](#)] Recommendation ITU-T Y.3810 (2024), *Quantum key distribution network interworking – Framework*.
+- [[ITU-T Y.3811](#)] Recommendation ITU-T Y.3811 (2022), *Quantum key distribution networks – Functional architecture for quality of service assurance*.
+- [[ITU-T Y.3813](#)] Recommendation ITU-T Y.3813 (2024), *Quantum key distribution network interworking - Functional requirements*.
+- [[ITU-T Y.3817](#)] Recommendation ITU-T Y.3817 (2024), *Quantum key distribution network interworking – Requirements for quality of service assurance*.
+- [[ITU-T Y.3818](#)] Recommendation ITU-T Y.3818 (2024), *Quantum key distribution network interworking – Architecture*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 network performance** [b-ITU-T E.417]: The performance of a portion of a telecommunications network that is measured between a pair of network-user or network-network interfaces using objectively defined and observed performance parameters.
+
+**3.1.2 quality of experience (QoE)** [b-ITU-T P.10]: The degree of delight or annoyance of the user of an application or service. [b-Qualinet 2013]
+
+NOTE – Recognizing on-going research on this topic, this is a working definition which is expected to evolve for some time. (This note is not part of the definition.)
+
+**3.1.3 quality of service** [b-ITU-T Q.1741.9]: The collective effect of service performances, which determine the degree of satisfaction of a user of a service. It is characterized by the combined aspects of performance factors applicable to all services, such as service operability performance, service accessibility performance, service retainability performance, service integrity performance and other factors specific to service.
+
+**3.1.4 quality of service assurance** [b-ITU-T Y.3109]: Functionalities or mechanisms that enable service providers to make statements with a degree of confidence that the service meets the quality characteristics or objectives specified elsewhere.
+
+## **3.2 Terms defined in this Recommendation**
+
+None.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-------|-----------------------------------------------|
+| CL | Control Layer |
+| CM | Control layer Management |
+| GWN | Gateway Node |
+| IWN | Inter-Working Node |
+| KM | Key management layer Management |
+| KMA | Key Management Agent |
+| KML | Key Management Layer |
+| KPI | Key Performance Indicator |
+| KQM | KML QoS Measurement |
+| KSA | Key Supply Agent |
+| QCL | Quantum Control Layer |
+| QCLQA | QKDN Control Layer QoS Assurance |
+| QCRQA | QKDN Cross-Layer QoS Assurance |
+| QDA | CL QoS Data Analysis |
+| QKD | Quantum Key Distribution |
+| QKDN | Quantum Key Distribution Network |
+| QKDNi | Quantum Key Distribution Network interworking |
+| QL | Quantum Layer |
+| QoE | Quality of Experience |
+| QoS | Quality of Service |
+| QM | Quantum Layer Management |
+| QPP | QoS Policy Provisioning |
+
+| | |
+|-------|------------------------------------|
+| QQCE | QKDN QoS Capabilities Exposure |
+| QQCLS | QKDN QoS Cross-Layer Support |
+| QQM | QL QoS Measurement |
+| QQPO | QKDN QoS Planning and Optimization |
+| SLA | Service Level Agreement |
+
+# 5 Conventions
+
+None.
+
+# 6 Overview
+
+Quantum key distribution network (QKDN) is a cryptographic infrastructure that provides secure symmetric keys to cryptographic applications in user networks. The QKDN can cover a wide area by interworking multiple QKDNs, which is called QKDN interworking (QKDNi).
+
+[ITU-T Y.3810] introduces an overview of interworking QKDNs, the reference models, and the functional models of gateway functions (GWFs) and interworking functions (IWFs). Moreover, QKDNi functional requirements are identified in [ITU-T Y.3813].
+
+[ITU-T Y.3818] specifies functional architectures for QKDNi, which includes a functional architecture model, functional entities, interworking architectural configurations and basic operational procedures for QKDNi.
+
+One of the challenges of the QKDNi is to assure the network interworking performance and that different quality of service (QoS)/quality of experience (QoE) requirements of different interworking application scenarios are met.
+
+The requirements of QoS assurance for QKDNi specified in [ITU-T Y.3817] address these challenges. Based on the requirements, this Recommendation specifies the functional architecture, associated functional entities and reference points and a basic operational procedure.
+
+# 7 Functional architecture of QoS assurance for QKDNi
+
+This clause specifies the QKDNi layered functional architecture and associated functional entities in accordance with [ITU-T Y.3818]. Two functional architectures for QKDNi with gateway nodes (GWNs) and interworking node (IWN) are illustrated in [ITU-T Y.3818]. This Recommendation extends the functional entities required for QoS assurance as shown in Figure 1 and Figure 2, where the QoS assurance functional entities are added in each layer management function. Each entity interacts with each layer's control and management function to fulfil the QoS key performance indicators (KPIs). This includes planning, monitoring, analysing, optimizing and provisioning, which are addressed in [ITU-T Y.3811].
+
+
+
+Service layer
+
+Cryptographic application (APP)
+
+Ma
+
+Ax
+
+User network management layer
+
+User network manager
+
+Mu
+
+QKDN control layer
+
+QKDN controller
+
+Routing control
+
+Session control
+
+Configuration control
+
+Access control
+
+Policy based control
+
+QKDN controller control and management
+
+Cx
+
+Cxi
+
+Ck
+
+Key management layer
+
+Key manager (KM)
+
+KSA
+
+Key supply
+
+Key combination
+
+KM control and management
+
+KMA
+
+Key relay
+
+Key storage
+
+Key life cycle management
+
+Kx-2
+
+Kxi-2
+
+Kx-1
+
+Kxi-1
+
+Kq-1
+
+Kq-2
+
+Cq
+
+Quantum layer
+
+QKD module
+
+Key distillation
+
+QKD-key supply
+
+QKD module control and management
+
+Quantum channel synchronization
+
+RNG
+
+Quantum communication
+
+Channel multiplexing
+
+Qdist
+
+Qsync
+
+Qqc
+
+Cqrp
+
+Cops
+
+Mqrp
+
+Mops
+
+QKDN management layer
+
+QKDN manager
+
+FCAPS functions\*
+
+Control layer management
+
+QoS assurance
+
+Key management layer management
+
+QoS assurance
+
+Quantum layer management
+
+QoS assurance
+
+Cross-layer management orchestration
+
+Mx
+
+Mk
+
+Mc
+
+Mxi
+
+Y.3829(25)
+
+Functional architecture extension of QoS assurance for QKDNI with GWN. The diagram shows four main layers: Service layer, User network management layer, QKDN control layer, and QKDN management layer. The Service layer contains a Cryptographic application (APP) with interfaces Ax and Ma. The User network management layer contains a User network manager with interface Mu. The QKDN control layer contains a QKDN controller with sub-components: Routing control, Session control, Configuration control, Access control, Policy based control, and QKDN controller control and management. It has interfaces Cx, Cxi, and Ck. The Key management layer contains a Key manager (KM) with sub-components: KSA (Key supply, Key combination), KM control and management, KMA (Key relay, Key storage, Key life cycle management), and interfaces Kx-1, Kxi-1, Kxi-2, Kx-2, Kq-1, Kq-2, and Cq. The Quantum layer contains a QKD module with sub-components: Key distillation, QKD-key supply, QKD module control and management, Quantum channel synchronization, RNG, Quantum communication, and Channel multiplexing. It has interfaces Qdist, Qsync, Qqc, Cqrp, Cops, Mqrp, and Mops. The QKDN management layer contains a QKDN manager with sub-components: FCAPS functions\*, Control layer management (QoS assurance), Key management layer management (QoS assurance), and Quantum layer management (QoS assurance). A vertical bar on the right indicates 'Cross-layer management orchestration'. Various interfaces (Mx, Mk, Mc, Mxi) connect the layers.
+
+Figure 1 – Functional architecture extension of QoS assurance for QKDNI with GWN
+
+
+
+Figure 2: Functional architecture extension of QoS assurance for QKDNI with IWN. The diagram shows a multi-layered architecture. The Service layer contains a Cryptographic application (APP) with inputs Ax and outputs Ma, Ak, and Cx. The QKDN control layer contains a QKDN controller with sub-modules: Routing control, Session control, Configuration control, Access control, Policy based control, and QKDN controller control and management. It has inputs Cxi' and Cx, and outputs Ck and Mc. The Key management layer contains a Key manager (KM) with sub-modules: KSA, Key supply, Key combination, KM control and management, KMA, Key transfer (highlighted in red), Key storage, and Key life cycle management. It has inputs Kxi-2', Kx-2, Kxi-1', and Kx-1, and outputs Kq-1, Kq-2, and Cq. The Quantum layer contains a QKD module with sub-modules: Key distillation, QKD-key supply, QKD module control and management, Quantum channel synchronization, RNG, Quantum communication, and Channel multiplexing. It has inputs Qdist, Qsync, and Qqc, and outputs Mq and Cqrp. The QKD link contains a Quantum relay point and Optical switching/splitting, with outputs Mqrp and Mops. The User network management layer contains a User network manager with input Mu. The QKDN management layer contains a QKDN manager with sub-modules: FCAPS functions\*, Control layer management (with QoS assurance), Key management layer management (with QoS assurance), and Quantum layer management (with QoS assurance). It also includes a vertical bar for Cross-layer management orchestration. Various interfaces (Ma, Mu, Mc, Ck, Kq-1, Kq-2, Cq, Mq, Cqrp, Cops, Mqrp, Mops) connect the layers.
+
+**Figure 2 – Functional architecture extension of QoS assurance for QKDNI with IWN**
+
+## 7.1 Functional entities for QKDNI QoS assurance
+
+The QoS assurance management functional entities for QKDNI are shown in Figure 3, which is extended from [ITU-T Y.3811]. The extended functional entities are represented with shadow rectangles in Figure 3.
+
+The QoS management and abstraction functional entity is a new QKDN control layer QoS assurance functional entities for QKDNI QoS assurance. The key management layer QoS assurance functional entities include the key management layer (KML) QoS transformation functional entity for QKDNI QoS assurance. Any quantum layer QoS assurance functional entity is not extended for QKDNI QoS assurance. The cross-layer management and orchestration QoS assurance functional entities include: QKDN QoS capability exposure to external management systems, QKDN service level agreement (SLA) support, QKDN QoS planning and optimization and QKDN QoS cross-layer support functions. Their functions are extended for QKDNI QoS assurance.
+
+
+
+Y.3829(25)
+
+Figure 3: QoS assurance functional entities for QKDNI. The diagram shows three layers of QoS assurance on the left, connected to a cross-layer assurance block on the right. The layers are: 1. QKDN control layer QoS assurance (containing QoS data analysis, QoS policy analysis, QoS policy provisioning, and QoS management and abstraction). 2. Key management layer QoS assurance (containing KML QoS measurement, KML QoS policy enforcement, KML QoS mapping and abstraction, and KML QoS transformation). 3. Quantum layer QoS assurance (containing QL QoS measurement, QL QoS policy enforcement, and QL QoS mapping and abstraction). The cross-layer assurance block on the right contains: QKDN QoS capability exposure, QKDN SLA support, QKDN QoS planning and optimization, and QKDN QoS cross-layer support. Arrows indicate connections from the management and abstraction entities of each layer to the cross-layer support entities.
+
+**Figure 3 – QoS assurance functional entities for QKDNI**
+
+## 7.2 QKDN control layer QoS assurance functional entity
+
+For QKDN control layer QoS assurance management, QoS management and abstraction functional entity is newly added for QKDNI.
+
+### QoS management and abstraction functional entity
+
+In general, the distribution of quantum key distribution (QKD) node information e.g., QoS, routing and topology, is restricted within a QKDN domain. It is therefore hard for a QKDN domain to know the QKD node information at different QKDN domains.
+
+The QoS management and abstraction functional entity is used to support QoS information transfer, QoS negotiation and QoS routing between QKDN domains, where QKDN interworking is required. The QoS information transfer is for sharing QoS information such as acceptable ranges for QoS values between QKDN domains. The QoS negotiation is for increasing success rate of QKDN interworking by handshaking their QoS capabilities. The QoS routing is to provision a transfer/relay route satisfying the requested KPIs between QKDN domains.
+
+Each QKDN control layer (e.g., QKDN controller) generates QKDN connections (e.g., quantum link connection, key management agent (KMA) link connection) within its QKDN domain. It is performed based on collected and analysed QoS related information from the QoS management and abstraction functional entity. Furthermore, within the GWN, a QKDN connection of a QKDN domain is concatenated with a QKDN connection of other QKDN domain based on the QoS related information for a quantum link connection. A KML transmitting a key supply agent (KSA)-key (e.g., transmitting KMA) subsequently selects an appropriate KML receiving the KSA-key (e.g., receiving KMA) within the GWN/IWN for a KMA link connection.
+
+## 7.3 Key management layer QoS assurance functional entity
+
+For key management layer QoS assurance management, KML QoS transformation functional entity is newly added for QKDNI.
+
+### KML QoS transformation functional entity
+
+The KML receives QKD-key(s) from one or more QKD modules, which may be produced by different vendors. It may lead to making the lengths of the acquired QKD-keys different. From the QoS assurance perspective, the KML QoS transformation is performed by considering QoS requirements of the QKD-key and of the cryptographic application. The cryptographic application may present QoS requirements with two types of QoS expressions: implicit and explicit
+
+[ITU-T Y.3817]. The KML QoS transformation may be more accurate if explicit QoS expression is applied.
+
+The KML, specifically KMA, combines, splits and formats the QKD-key, and generates the KSA-key according to the KML QoS transformation. The KML subsequently sends the KSA-key(s) to cryptographic applications.
+
+## **7.4 QKDN cross-layer QoS assurance functional entity**
+
+For QKDN cross-layer QoS assurance management, the QKDN cross-layer QoS assurance functional entity is extended for QKDNI.
+
+### **QKDN SLA support functional entity**
+
+The QKDN SLA support functional entity is also used for making an agreement about QKDNI QoS assurance management between the QKDN providers. The SLA may include statements about the QoS management and QoS transformation between the QKDN providers, which are described in clauses 7.2 and 7.3.
+
+### **QKDN QoS planning and optimization functional entity**
+
+For QKDNI QoS assurance, the QKDN QoS planning and optimization functional entity provides a concatenated QKDN connection within the GWN/IWN. It can update the QoS planning results to improve the overall QKDN quality and ensure that the QKDN resources are efficiently utilized. The update may result in removing the current concatenated QKDN connection and generating a new one.
+
+### **QKDN QoS cross-layer support functional entity**
+
+The QKDN QoS cross-layer support functional entity is also responsible for managing a concatenated QKDN connection within the GWN/IWN. This capability is applicable for QoS provisioning, QoS-based key relay or re-routing analysis and QoS related fault and security anomaly analysis for QKDNI QoS assurance.
+
+# **8 Reference points of the functional architecture**
+
+[ITU-T Y.3811] specifies the reference points between a QKDN manager and the quantum layer (QL), KML, and QKDN control layer for the purpose of QKDN QoS assurance. This clause only specifies the extended reference points [ITU-T Y.3818] for the purpose of QKDNI QoS assurance.
+
+- Mxi: A reference point connecting two QKDN managers between the QKDNI. Mxi enables the two QKDN managers to share QKDN management information. It is responsible for one QKDN manager to communicate management information with the other QKDN manager. For QKDNI QoS assurance, this reference point is extended to support QKDN cross-layer QoS assurance functional entity, specifically, QKDN SLA support, QKDN QoS planning and optimization, and QKDN QoS cross-layer support.
+- Mxi': A reference point connecting two QKDN managers in the IWN. Mxi' enables the two QKDN managers to share QKDNI management information. For QKDNI QoS assurance, this reference point is extended to support the QKDN cross-layer QoS assurance functional entity, specifically, QKDN SLA support, QKDN QoS planning and optimization, and QKDN QoS cross-layer support. It exists when two QKDN managers are accommodated within the IWN, allowing them to share information. Otherwise, Mxi can be used.
+
+# **9 Basic operational procedure of QoS assurance for QKDNI**
+
+The QKDNI QoS assurance lifecycle is also involved in the lifecycle of QKDNI services. This clause describes a basic operational QoS assurance lifecycle procedure in a QKDNI as shown in Figure 4.
+
+
+
+```
+
+sequenceDiagram
+ participant A as QKDN manager (Provider A)
+ participant QQCE as QCRQA-QQCE (Provider B)
+ participant QQPO as QCRQA-QQPO (Provider B)
+ participant QPP as QCLQA-QPP (Provider B)
+ participant QDA1 as QCLQA-QDA (KMLQA-KQM, QLQA-QQM)
+ participant QDA2 as QCLQA-QDA (QCRQA-QQCLS)
+ participant QM as QM/KM/CM
+
+ A->>QQCE: 1. QoS Prov Req
+ QQCE->>QQPO: 2. QoS Prov Req
+ Note over QQPO: 3-1. Determine an optimal QKDNi QoS provisioning plan based on available resources matching provider's request
+ QQPO->>QPP: 3-2. QoS Prov Req
+ Note over QPP: 4-1. Provision QKDNi QoS resource
+ QPP->>QQCE: 4-2. QoS Prov Resp
+ QQCE->>A: 5. QoS Prov Resp
+ QPP->>QQCE: 6. QoS Prov status
+ QQCE->>QDA1: 7. QoS Prov status
+ Note over QDA1: 8-1. Collect and analyse provisioned QKDNi QoS resources
+ QDA1->>QM: 8-2. Resource status
+ QM->>QDA1: 9. Resource status
+ QM->>QQCE: 10. Resource status update
+ Note over QQPO: 11-1. Update available resource status and determine if re-optimization is needed upon status updates
+ QQPO->>QPP: 11-2. Prov update Req
+ Note over QM: 12-1. Perform fault, configuration, performance, security and charging management of the provisioned QKDNi QoS resources. If any control or re-provisioning actions are required, request them to QCLQA-QPP
+ QM->>QPP: 12-2. Prov update Req
+ Note over QPP: 13-1. Re-provision the provisioned QoS resources with update request
+ QPP->>QQCE: 13-2. Prov status
+ QQCE->>QDA1: 14. Resource status update
+ QDA1->>QM: 15. Resource status update
+ QQCE->>A: 16. Resource status update
+
+```
+
+The diagram illustrates the sequence of operations for QKDNi QoS assurance between two providers. It details the flow of QoS provisioning requests, internal optimization processes, resource provisioning, status reporting, and management actions across various functional entities including QCRQA-QQCE, QCRQA-QQPO, QCLQA-QPP, QCLQA-QDA, and QM/KM/CM.
+
+Sequence diagram illustrating a basic operational procedure for QKDNi QoS assurance between QKDN provider A and QKDN provider B.
+
+Y.3829(25)
+
+**Figure 4 – A basic operational procedure for QKDNi QoS assurance**
+
+- 1) The QKDN manager of a QKDN provider (e.g., QKDN provider A) requests QKDNi resources to be provisioned with its specified service requirements based on the SLA between two QKDN providers (e.g., QKDN provider A and QKDN provider B). The QKDNi resources to be provisioned include a QoS-enabled interworking key relay route, KML resources to be provisioned with QoS requirements and QL resources to be provisioned with QoS requirements. The detailed provisioning process is supposed to be changeable according to QKDNi models (e.g., IWN and GWN). The QKDN QoS capabilities exposure (QQCE) functional element in the QKDN cross-layer QoS assurance (QCRQA) functional entity can open the QoS capabilities for third parties. Also, the QKDN SLA support functional element provides QoS information in the SLA template for QKDNi QoS provisioning which includes attributes about performance, billing and service delivery.
+- 2) The QCRQA-QQCE functional element receives the QKDN provider A's request and carries it to the QKDN QoS planning and optimization (QQPO) functional element in the QCRQA functional entity.
+- 3-1&2) After the decision of QoS planning and optimization, the QQPO then determines an optimal QoS resource provisioning plan based on the available resources which matches the QKDN
+
+provider A's request. Once the provisioning policy is determined, the QQPO requests provisioning to the QoS policy provisioning (QPP) functional element in the QKDN control layer QoS assurance (QCLQA) functional entity.
+
+- 4-1&2) QPP then performs the requested QoS provisioning task. It involves various sub-tasks including QoS related aspects: QoS provisioning, QoS policy enforcement, QoS mapping, etc.
+- 5) Upon completion of the provisioning process, QPP sends a provision response message to the QKDN provider A via QQCE.
+- 6) At the same time, a provisioning status is sent to the QL QoS measurement (QQM), KML QoS measurement (KQM), and CL QoS data analysis (QDA) functional elements to initiate the monitoring and analysis of the provisioned resources.
+- 7) The status update is also sent to QDA and the QKDN QoS cross-layer support (QQCLS) functional elements in the QCRQA functional entity to store the provisioned resource information. Both QDA and QQCLS have a resource repository to store resource status information for their analysis functions.
+- 8-1&2) QQM, KQM and QDA perform collection, monitoring, and analysis tasks of the provisioned resources. The QoS related data is also collected. Data and information collected and analysed are then stored in both QDA and QQCLS repositories for further processing.
+- 9&10) The QoS policy information is also stored in QDA and QQCLS repositories. When QDA and QQCLS receive resource status updates, the updates are stored in the repository and, at the same time, a notification is emitted to all functional elements that are listening to the status updates. In this case, an update notification is sent from QDA to QKDNi quantum layer management (QM), key management layer management (KM) and control layer management (CM) for fault, configuration, performance, security, and charging purposes, and finally to QQPO for cross-layer QoS management.
+- 11-1&2) When QQPO receives the notification, it updates the available resource status and determines if re-optimization is needed upon status updates.
+- 12-1&2) Also, when the QM/KM/CM in the QKDN management function receive the notification, they perform fault, configuration, performance, security and charging management of the provisioned resources and determine if any control or re-provisioning actions are required. If so, they send a request to QPP for provisioning update processes.
+- 13-1&2) QPP, upon receiving the provisioning update requests, performs re-provisioning tasks for the provisioned QKDNi QoS resources. When the re-provisioning tasks are done, QPP generates the provision status to QDA and QQCLS repositories.
+- 14&15) QDA and QQCLS further convey the notification to the QM/KM/CM and QQPO for resource status updates.
+- 16) QQPO finally sends the provisioning status update to the QKDN provider A.
+
+# **10 Security considerations**
+
+This Recommendation specifies the functional architecture of QoS assurance for the quantum key distribution network interworking (QKDNi), therefore, the security aspects of QKDNi functional architecture as described in [ITU-T Y.3811] should be applied. Details are outside the scope of this Recommendation.
+
+# Bibliography
+
+- [[b-ITU-T E.417](#)] Recommendation ITU-T E.417 (2005), *Framework for the network management of IP-based networks*.
+- [[b-ITU-T P.10](#)] Recommendation ITU-T P.10/G.100 (2017), *Vocabulary for performance, quality of service and quality of experience* .
+- [[b-ITU-T Q.1741.9](#)] Recommendation ITU-T Q.1741.9 (2015), *IMT-2000 references to Release 11 of GSM evolved UMTS core network*.
+- [[b-ITU-T Y.3109](#)] Recommendation ITU-T Y.3109 (2021), *Quality of service assurance-related requirements and framework for virtual reality delivery using mobile edge computing supported by IMT-2020*.
+- [b-Qualinet 2013] Qualinet *White Paper on Definitions of Quality of Experience* (2013), *Output from the fifth Qualinet meeting*, Novi Sad, March 12.
+[http://www.qualinet.eu/index.php?option=com\\_content&view=article&id=45&Itemid=52](http://www.qualinet.eu/index.php?option=com_content&view=article&id=45&Itemid=52)
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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new file mode 100644
index 0000000000000000000000000000000000000000..5a07acd17e7660083aca0476b870f6ac86cbaece
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@@ -0,0 +1,761 @@
+
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+## Y.4113
+
+(09/2016)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS
+AND NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Internet of things and smart cities and communities –
+Requirements and use cases
+
+# --- **Requirements of the network for the Internet of things**
+
+Recommendation ITU-T Y.4113
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+# GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS AND NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Network control architectures and protocols | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+| | |
+|-----------------|---------------|
+| CLOUD COMPUTING | Y.3000–Y.3499 |
+| Y.3500–Y.3999 | |
+
+## INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|----------------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4113
+
+# Requirements of the network for the Internet of things
+
+## Summary
+
+Recommendation ITU-T Y.4113 describes the requirements of the network for the Internet of things (IoT) that enhance the common requirements of the IoT identified in Recommendation ITU-T Y.4100/Y.2066. The requirements focus on the transport functions of the network, but also cover service support functions.
+
+The requirements described in this Recommendation are common requirements for core network, access network and IoT area network.
+
+There are a lot of use cases of the IoT with heterogeneous characteristics. Considering the current status of deployments in the IoT market, this Recommendation focuses on the requirements of the network for the IoT with smart meters and sensors as devices. Other use cases will be covered in the future revisions of this Recommendation.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.4113 | 2016-09-13 | 20 | 11.1002/1000/13025 |
+
+## Keywords
+
+Internet of Things, requirements of the network, sensor, smart meter.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2016
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|---|-----------------------------------------------------------------------------------|------|
+| 1 | Scope..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 2 |
+| | 3.1 Terms defined elsewhere..... | 2 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 3 |
+| 6 | General description of the network for the IoT ..... | 3 |
+| | 6.1 Basic model of the network for the IoT..... | 3 |
+| | 6.2 General characteristics of smart meters and sensors as devices for the IoT .. | 4 |
+| | 6.3 General issues of the network for the IoT ..... | 5 |
+| 7 | Requirements of the network for the IoT ..... | 6 |
+| | 7.1 General requirements..... | 6 |
+| | 7.2 Core network requirements ..... | 6 |
+| | 7.3 IoT area network requirements..... | 10 |
+| | Appendix I – Examples of use cases of smart meters and sensors ..... | 12 |
+| | I.1 Smart meters and sensors ..... | 12 |
+| | I.2 IoT area network..... | 15 |
+| | Appendix II – Access network and IoT area network technologies ..... | 18 |
+| | II.1 Access-specific aspects relating to core network requirements ..... | 18 |
+| | Bibliography..... | 20 |
+
+
+
+# Recommendation ITU-T Y.4113
+
+# Requirements of the network for the Internet of things
+
+# 1 Scope
+
+This Recommendation describes the requirements of the network for the Internet of things (IoT). The common requirements of the IoT described in [ITU-T Y.4100] are high-level; thus this Recommendation is complementary to [ITU-T Y.4100] in term of specific requirements of the network for the IoT.
+
+Because an increasing number of devices with heterogeneous characteristics will be connected to the network via varying access technologies depending on the specific deployment environment, it is important to consider the requirements of the network that are applicable to those various use cases of the IoT, and avoid case-by-case studies for each specific use case. This approach is expected to encourage IoT development.
+
+There are many use cases of the IoT with heterogeneous characteristics. Considering the current status of the deployments in the IoT market, this Recommendation focuses on the network for the IoT with smart meters and sensors as device for the IoT. Other use cases will be covered in future revisions of this Recommendation.
+
+The scope of this Recommendation includes:
+
+- general description of the network for the IoT, addressing respectively:
+ - basic model of the network for the IoT;
+ - general characteristics of smart meters and sensors;
+ - general issues of the network for the IoT.
+- requirements of the network for the IoT, addressing respectively:
+ - general requirements;
+ - core network requirements;
+ - IoT area network requirements.
+
+Examples of use cases with smart meters and sensors are described in Appendix I.
+
+Several access network and IoT area network technologies for the network supporting the IoT are identified in Appendix II.
+
+NOTE – The technologies listed in Appendix II are not meant to be exhaustive.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T Y.4000] Recommendation ITU-T Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+
+[ITU-T Y.4100] Recommendation ITU-T Y.4100/Y.2066 (2014), *Common requirements of the Internet of things*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 access network** [b-ITU-T Q.1742.11]: A network that connects access technologies (such as a radio access network) to the core network.
+
+**3.1.2 core network** [b-ITU-T Y.101]: A portion of the delivery system composed of networks, systems equipment and infrastructures, connecting the service providers to the access network.
+
+**3.1.3 device** [ITU-T Y.4000]: With regard to the Internet of things, this is a piece of equipment with the mandatory capabilities of communication and the optional capabilities of sensing, actuation, data capture, data storage and data processing.
+
+**3.1.4 Internet of things (IoT)** [ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.
+
+NOTE 1 – Through the exploitation of identification, data capture, processing and communication capabilities, the IoT makes full use of things to offer services to all kinds of applications, whilst ensuring that security and privacy requirements are fulfilled.
+
+NOTE 2 – From a broader perspective, the IoT can be perceived as a vision with technological and societal implications.
+
+**3.1.5 thing** [ITU-T Y.4000]: With regard to the Internet of things, this is an object of the physical world (physical things) or the information world (virtual things), which is capable of being identified and integrated into communication networks.
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 IoT area network:** A network of devices for the IoT and gateways interconnected through local connections.
+
+NOTE – This definition is based on "Overview of the Internet of things" [ITU-T Y.4000], where clause 6.2 states "devices can communicate with other devices using direct communication through a local network (i.e., a network providing local connectivity between devices and between devices and a gateway, such as an ad-hoc network)".
+
+**3.2.2 sensor:** (Based on the definition given in [b-ITU-T Y.2221]) An electronic device that senses a physical condition or chemical compound and delivers an electronic signal proportional to the observed characteristic.
+
+NOTE – Examples of usage of sensors include temperature monitoring, gas-leak alert, traffic congestion prediction, earthquake early warning, etc.
+
+**3.2.3 smart meter:** With regard to the Internet of things, a device for monitoring, measurement recording and control of utility usage.
+
+NOTE – Examples of utilities include electricity, gas and water.
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+2G Second Generation wireless telephony technology
+
+| | |
+|------|---------------------------------------------------|
+| 3G | Third Generation wireless telephony technology |
+| ADSL | Asymmetric Digital Subscriber Line |
+| API | Application Programming Interface |
+| DSL | Digital Subscriber Line |
+| FTTx | Fiber To The x |
+| IEEE | Institute of Electrical and Electronics Engineers |
+| IoT | Internet of Things |
+| LAN | Local Area Network |
+| LPWA | Low Power Wide Area |
+| LTE | Long Term Evolution |
+| MTBF | Mean Time Between Failures |
+| MTTR | Mean Time To Repair |
+| PSTN | Public Switched Telephone Network |
+| SDSL | Symmetric Digital Subscriber Line |
+| ULE | Ultra Low Energy |
+| xDSL | x Digital Subscriber Line |
+
+# 5 Conventions
+
+In this Recommendation:
+
+The keywords "**is required to**" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+
+The keywords "**is recommended**" indicate a requirement which is recommended but which is not absolutely required. Thus this requirement need not be present to claim conformance.
+
+The keywords "**can optionally**" and "**may**" indicate an optional requirement which is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator. Rather, it means the vendor may optionally provide the feature and still claim conformance with the specification.
+
+# 6 General description of the network for the IoT
+
+This clause introduces a basic model of the network for the IoT, general characteristics of smart meters and sensors, and general issues of the network for the IoT.
+
+## 6.1 Basic model of the network for the IoT
+
+The basic model of the network for the IoT consists of three parts as shown in Figure.1: core network, access network and IoT area network.
+
+
+
+Figure 1 – Basic model of the network for the IoT. The diagram illustrates the network architecture for IoT, divided into four main sections: IoT area network, Access network, Core network, and IoT application servers. In the IoT area network, two 'Device' boxes are connected to a 'Gateway' box. The Gateway connects to the Access network, which contains a cloud icon and a 'Device' box. The Access network connects to the Core network, which also contains a cloud icon. The Core network connects to two 'IoT application server' boxes, one of which is also connected to an 'IoT platform' box. Dashed lines delineate the boundaries of the IoT area network, Access network, and Core network.
+
+Y.4113(16)\_F01
+
+**Figure 1 – Basic model of the network for the IoT**
+
+The device is a piece of equipment with mandatory capabilities of communication, and optional capabilities of sensing, actuation, data capture, data storage and data processing with regard to the IoT [ITU-T Y.4000].
+
+The gateway is a unit with regard to the IoT which interconnects the devices with the core network. It performs the necessary translation between the protocols used in the core network and those used by devices [ITU-T Y.4101].
+
+The core network is a portion of the delivery system composed of networks, equipment and infrastructures, and connects the service provider domain with the access network.
+
+The access network connects the devices for the IoT and gateways to the core network. It can be implemented using different technologies such as fibre optics and radio access technologies.
+
+The IoT area network is a network of devices for the IoT and gateways that are interconnected. Connectivity is realized through local connections, typically using short-range communication technologies.
+
+The IoT platform is a technical infrastructure that provides integration of generic and specific capabilities [ITU-T Y.4000]. These capabilities, in conjunction with capabilities of the core network, may be exposed to one or more IoT application servers. The core network provides communication functionalities to support the data transfer to devices and gateways via access network. Some of those functionalities can be used by service providers.
+
+The IoT application server runs applications, and communicates with devices, gateways and IoT platform via the core network (or directly in case of communicate with the IoT platform) directly in order to deliver application services.
+
+## **6.2 General characteristics of smart meters and sensors as devices for the IoT**
+
+The general characteristics of smart meters and sensors as devices for the IoT are described in this clause.
+
+### **6.2.1 Small size data communication**
+
+Typical data handled by smart meters and sensors concern environmental information, usage of energy resources and status of communication availability of smart meters and sensors.
+
+Since most of these data are text based, not video or image based, the typical data handled by smart meters and sensors are, in general, of small size.
+
+### **6.2.2 Periodic data communication**
+
+One popular usage of smart meters and sensors is for environmental data measurements. Environmental data are in many use cases measured at fixed times and it is natural to send measured data at those same times; thus, periodic data communication is expected to occur.
+
+Another aspect of consider is the long lifetime of smart meters and sensors. Once these devices are deployed, they are expected to work for 10 years or more. Therefore, status monitoring of smart meters and sensors, i.e., checking they are working correctly, is needed. In some implementations, status monitoring data transmissions occur due to a pre-defined value of data transmission interval although this interval may vary depending on the specific implementations.
+
+NOTE – Appendix I.1 shows related use cases with smart meters.
+
+### **6.2.3 Huge number of deployed devices**
+
+The number of deployed smart meters and sensors is expected to be huge. The decreasing cost of these devices and the increasing number of related applications are both factors leading to the increasing scale of such deployments.
+
+NOTE 1 – Smart meters may be used for smart grids and for applications using environmental data collection. Houses, offices and commercial facilities are typical places where smart meters are deployed.
+
+NOTE 2 – Sensors may be used for public infrastructure (buildings, roads, trains, etc.). In addition, embedded sensors in smart phones, wearable devices and other devices are also in use.
+
+## **6.3 General issues of the network for the IoT**
+
+The large deployment of smart meters, sensors and related applications in the field may impose new challenges on the network due to the unique features of these devices. The following clauses describe general issues of the network due to the characteristics described in clause 6.2.
+
+### **6.3.1 Packet loss and higher latency due to simultaneous data transmission**
+
+Numerous IoT deployments concern devices, like smart meters, transmitting data containing readings at specific timings.
+
+A group of devices may upload their data at the same time (e.g., when a trigger event for data transmission occurs on these devices at the same time, or when simultaneous processing of these data by the remote application server is required). In such a case, the network may face the problem of simultaneous data transmissions (e.g., increasing the possibility of collisions of the random access channel) which may lead to packet loss and/or higher latency for these data transmissions.
+
+NOTE – Obviously, packet loss and higher latency are particularly relevant in case of a large number of simultaneous data transmissions.
+
+### **6.3.2 Unreliability of short-range radio communications in the IoT area network**
+
+Some critical applications may need particular consideration in terms of reliability. In the case of smart meters connected to an IoT area network using short-range radio communications, transmissions may not be reliable due to the instability of the short-range radio connections. There may be substantial loss of data in the data collection in this situation. If, for example, the collected data are intended to be used for monitoring of total power consumption and control of generation of electricity, the error-prone IoT system would not contribute to an improvement in level of the electricity system.
+
+### **6.3.3 Network overload due to large amount of traffic to be processed**
+
+With the increasing deployment of smart meters and sensors, the number of IoT area networks connected to the core network also increases accordingly. In such a case, even if the IoT area network has sufficient resources to process data from smart meters and sensors, issues in the core network may arise. One of the causes for such issue is that the amount of data received from IoT area networks may be too great to be processed in the core network. This may cause overload problems of the resources of the core network in term of links and network entities.
+
+Those issues may also arise in the access network. Even if the IoT area network operates without specific issues, congestion may be caused in the access network. One of the causes for such
+
+congestion is that the amount of data received from these IoT area networks may be too great to be processed in the specific area of the access network connecting these IoT area networks to the core network.
+
+# **7 Requirements of the network for the IoT**
+
+This clause describes the requirements of the network for the IoT, distinguished in general requirements, core network requirements and IoT area network requirements. The requirements of the access network for the IoT are not specified.
+
+Considering requirements for the IoT, technologies that may be applicable for use in the access network and IoT area network are provided in Appendix II.
+
+## **7.1 General requirements**
+
+This clause describes general requirements of the network for the IoT with smart meters and sensors which are potentially related to all three parts of the networks.
+
+NOTE – Each clause also identifies rational for the respective requirements, although this rational is not meant to be exhaustive.
+
+### **7.1.1 Support of a variety of devices for the IoT**
+
+Based on requirement C9 of [ITU-T Y.4100], the following general requirement is derived for this Recommendation:
+
+- the network is recommended to accommodate a variety of devices including devices with constrained capabilities.
+
+NOTE – Some devices such as environmental sensors have constrained capabilities with limited power, memory and processing resources in order to be ultra-low cost. The network should accommodate devices with constrained capabilities.
+
+### **7.1.2 Scalability**
+
+Based on clauses 6.2.3 and 6.3.3 of this Recommendation, the following general requirement is derived for this Recommendation:
+
+- the network is required to be scalable.
+
+NOTE – Decreasing cost of devices and increasing number of application demands are the main factors driving the increased number of deployed devices. The decreasing cost of devices allows new use cases, which are not profitable at higher device cost, to be deployed commercially. There is a clear trend that the number of deployed devices continues to increase. Therefore, the network ultimately needs to support a large number of devices.
+
+## **7.2 Core network requirements**
+
+This clause describes the requirements for the core network.
+
+### **7.2.1 Status monitoring**
+
+Based on clauses 6.3.2 and 6.3.3 of this Recommendation, the following core network requirements are derived for this Recommendation:
+
+- the core network is recommended to support status monitoring for gateways, devices and IoT area networks;
+- the core network is recommended to support status information request to gateways and/or devices according to the network management policies.
+
+The monitored status information includes, among other things: load status of gateways and devices, IoT data traffic routes, gateway and IoT area network topologies, and failure detection for critical devices and gateways which maintain IoT area network topologies. The network can request this
+
+information on-demand based on policies so that the network can leverage the latest information (independently from the status information autonomously provided to the network by devices and gateways).
+
+Supporting status monitoring can allow the core network to manage several IoT area networks in a unified manner. There may be several IoT area networks, each with its own resource capacity and connection reliability. For IoT service provisioning, communication between devices and service providers is needed; therefore, the connections between IoT area networks and core network should be as reliable as possible. Traffic volumes from IoT area networks toward the core network may be unbalanced, which may lead to network resource unavailability unless those IoT area networks are managed in a unified manner. Unified network management with status monitoring may be able to reduce resource unavailability due to traffic imbalance.
+
+It is not always required that the core network be involved in status monitoring, however the core network can assist the service providers by exposing monitored information if the core network supports status monitoring.
+
+### **7.2.2 Data transmission scheduling management**
+
+Based on clauses 6.2.2 and 6.3.1 of this Recommendation, the following core network requirement is derived for this Recommendation:
+
+- the core network is recommended to support data transmission scheduling management for gateways, devices and IoT area networks.
+
+The timing of the data transmission from gateways and/or devices is normally dependent on the application implementation by developers and can be configurable by the application user. If no specific considerations are applied with respect the data transmission timing, the impact of many devices transmitting data to the network at the same time may cause traffic congestion. Therefore, the network should exhibit robustness with respect to such situations by supporting mechanisms which manage the timing of data transmission from gateways and/or devices.
+
+In particular, data transmission scheduling management aims to coordinate the data transmission timing within a relevant group of gateways (e.g., a domain based group or an application based group) according to policies and load considerations. In case the devices are connected to the core network without gateways, the network may consider timing coordination among the devices according to the policies.
+
+NOTE – Coordination of the transmission times can be realized via either setting an explicit device transmission time or randomizing the device transmission time within a given interval.
+
+### **7.2.3 Topology calculation**
+
+Based on clauses 6.3.2 and 6.3.3 of this Recommendation, the following core network requirements are derived for this Recommendation:
+
+- the core network is recommended to support an IoT area network topology calculation with consideration of access network selection of devices and gateway by using monitored status information;
+- the core network is recommended to support notification actions such as requesting network topology recalculation based on the calculation results to critical devices and gateways those maintain the IoT area network topologies.
+
+In order to avoid congestion caused by unexpectedly heavy traffic for particular network entities, the network is required to manage the topologies of IoT area networks with consideration of access network selection of devices/gateway based on monitored information. The network will then be aware of which network entities unbalanced traffic comes from.
+
+For managing the topology of a given IoT area network, the network calculates an appropriate traffic topology for that particular IoT area network with appropriate access network selection of devices and gateway.
+
+Based on the result of such calculations, the core network requests the devices and/or gateways to re-calculate the network topology.
+
+NOTE – Appendix I.2.1 describes several issues and provides solutions for a use case involving smart meters.
+
+### **7.2.4 Traffic route calculation**
+
+Based on clauses 6.3.2 and 6.3.3 of this Recommendation, the following core network requirements are derived for this Recommendation:
+
+- the core network is recommended to support the calculation of an optimal traffic route within the IoT area network by using monitored status information;
+- the core network is recommended to support notification of actions such as requesting traffic route reformulation based on calculation results to critical devices and gateways that maintain the IoT area network topologies.
+
+The traffic route of devices/gateways toward the core network can be calculated by the core network in order to avoid congestion caused by unbalanced traffic. The network calculates a balanced traffic route for the particular IoT area network. The traffic route of devices and gateways can be reformulated based on a request from the network.
+
+Based on the results of such calculations, the core network requests the devices and gateways to recalculate the traffic route.
+
+NOTE – Appendix I.2.2 describes several issues and provides solutions for scenario involving smart meters.
+
+### **7.2.5 Access granted time**
+
+Based on clause 6.3.1 of this Recommendation, the following core network requirements are derived for this Recommendation:
+
+- the core network is recommended to support data communications triggered by devices only during the access granted time interval and the access time duration;
+- the core network is recommended to support termination of data communications after expiration of the access time duration of devices.
+
+The core network can avoid congestion by controlling the communication time of the devices and gateways. The conditions are implemented as time values which reflect network side requirements and/or service provider demands, e.g., application specific data requirements with cost effective time choice.
+
+The values of the granted access time interval (e.g., once every 12 hours) and access time duration (e.g., 10 minutes) can be pre-shared between network operators and service providers. These values are defined per device on a per application basis, and configured on both network and device sides.
+
+NOTE 1 – The requirements described in this clause do not affect the communications triggered by service providers, i.e., service providers are allowed to trigger IoT communications with devices at any timing if necessary.
+
+NOTE 2 – Appendix I.1 shows related use cases involving smart meters.
+
+### **7.2.6 Device recognition**
+
+Based on requirements C1 to C10 of [ITU-T Y.4100], the following core network requirements are derived for this Recommendation:
+
+- the core network is recommended to recognize the connected device as a device for the IoT, or not; in case of an IoT device, whether or not it is a smart meter or sensor;
+
+NOTE – Recognition is the process of differentiation of the connected device based on the knowledge of the network. However, the details of how to recognize whether a device is for the IoT and is a smart meter or sensor is out of scope of this Recommendation.
+
+- the core network is recommended to recognize the network functionalities for support of the set of services required for devices for the IoT and, specifically, for smart meters and sensors;
+- the core network is recommended to support activation/de-activation by the user of the network functionalities to support the set of services required for smart meters and sensors.
+
+If the network is able to recognize a connected device as a device for the IoT, and then additionally as a smart meter or sensor, the network is then able to recognize the network functionalities which can fulfil the requirements of the network for the IoT (including those described in clause 7).
+
+Not only IoT devices, but other devices as well, e.g., smartphones, may be connected to the core network. In such core network deployments, various network functionalities should be implemented to support services required for the IoT devices, specifically for smart meters and sensors, and services required for other devices. Some functionalities are specifically designed and dedicated for IoT services, but some others are not. The core network should be able to recognize which functionalities are applicable to the services required for the IoT devices, specifically smart meters and sensors, in order that it can deliver IoT services with the appropriate functionalities based on the specific connected devices.
+
+### **7.2.7 Group management**
+
+Based on clause 6.2.3 of this Recommendation and requirement A2 of [ITU-T Y.4100], the following core network requirements are derived for this Recommendation:
+
+- the core network is recommended to support IoT groups;
+- the core network is required to support join and leave of devices and gateways to/from an IoT group if group management is supported;
+- the core network is required to support the capability of data transmission to an IoT group if group management is supported.
+
+Group management [ITU-T Y.4100] is applied to devices and/or gateways. An IoT group may be constructed based on the service provider's preferences, e.g., on an application domain basis, or on a location basis. A device and/or gateway may belong to more than one IoT group if the policies of the different IoT groups are not conflicting. The core network is required to support the capability of data transmission to an IoT group by appropriate technologies, e.g., multicast.
+
+#### **7.2.8 API**
+
+In this clause, the requirements of application programming interface (API) exposure by the core network to the service provider domain are described.
+
+##### **7.2.8.1 Network status information exposure**
+
+Based on requirement A1 of [ITU-T Y.4100], the following core network requirement is derived for this Recommendation:
+
+- the core network is recommended to support the exposure of the network status information to the IoT platform through an API.
+
+NOTE – An IoT platform is able to use the network status information provided by the network through APIs for the efficient scheduling of IoT data backhaul transmission from gateways and devices, e.g., by arranging data collection time period and collection sequence.
+
+### 7.2.9 Access technology interface selection support
+
+Based on clauses 6.3.2 and 6.3.3 of this Recommendation, the following core network requirement is derived for this Recommendation:
+
+- the core network is recommended to support specific access network technology selection requests to devices and/or gateways.
+
+Devices or gateways are connected to the core network through the access network; see Figure 1. Even if the IoT area network and access network have sufficient capabilities and resources to process data from devices, the core network may be congested. For example, a gateway may have two interfaces toward the core network, one via long term evolution (LTE) access technology [b-GPP TS 36.300] and another via Wi-Fi access technology [b-IEEE 802.11]. In case where the LTE access technology is having issues while the Wi-Fi access technology is operating with sufficient resources, it is more efficient for the gateway to select the Wi-Fi access. If the core network has knowledge of the situation through network status information monitoring, the core network can request that devices or gateways select a suitable access network interface.
+
+### 7.2.10 Multi technology access network connection support
+
+Based on clauses 6.3.2 and 6.3.3 of this Recommendation, the following core network requirement is derived for this Recommendation:
+
+- the core network is required to support the connectivity with different kinds of access network technologies.
+
+There are use cases where a gateway connecting to the core network has multiple interfaces with different access technologies. For example, one interface can be a cellular based interface and another can be a fixed line based interface. Another use case is one of a gateway with two independent access network interfaces connected to the core network, one being a cellular based access network, and another being a fixed line access network.
+
+## 7.3 IoT area network requirements
+
+In this clause, the requirements for the IoT area network are described.
+
+### 7.3.1 Reliability
+
+Based on clauses 6.3.2 of this Recommendation and requirement N3 of [ITU-T Y.4100], the following IoT area network requirements are derived for this Recommendation:
+
+- the IoT area network is recommended to offer reliable data transmission;
+- a necessary measure to ensure high reliability of data transmission in the IoT area network is required in order to achieve end-to-end reliability.
+
+In a large number of IoT system implementations, the IoT area network utilizes short-range radio technologies. Such short-range radio technologies have higher packet and connection loss rates as compared with technologies used in the core network or the access network; therefore, they are not reliable in terms of data communications. In order to achieve high availability of data communications, high reliability should be ensured in the IoT area network.
+
+For core network and access network, there are several well-known measures for reliability and availability, for example mean time between failures (MTBF) and mean time to repair (MTTR). However, the IoT area network requires dedicated measures because of the infrequent data communications, as described in clause 6.2.2.
+
+### **7.3.2 Reaction to requests and notifications from the core network**
+
+Based on clauses 7.2.1, 7.2.2, 7.2.3 and 7.2.4, the following IoT area network requirement is derived:
+
+- the IoT area network is recommended to react to requests and notifications from the core network, specifically concerning status information, topology recalculation, topology information and traffic route information.
+
+The core network may send status information requests, topology recalculation requests and traffic recalculation requests to the IoT area network, or may notify topology or traffic route information. The IoT area network should react to these requests or notifications based on the IoT area network policies.
+
+# Appendix I
+
+## Examples of use cases of smart meters and sensors
+
+(This appendix does not form an integral part of this Recommendation.)
+
+## I.1 Smart meters and sensors
+
+This clause describes typical use cases and potential issues with the smart meters and sensors deployed as devices for the IoT. The use cases described in this clause may not be applicable to other devices.
+
+#### I.1.1 Communications between smart meters and network
+
+Figure I.1 shows typical data transmission from deployed smart meters in an IoT area network to the core network. There are two use cases; the first is the direct connection between smart meter and network, and the second is smart meter connection via a gateway. Data are transmitted towards the core network within periodic time interval, e.g., one transmission per hour.
+
+
+
+The diagram illustrates two communication paths from smart meters to a core network. At the top is a light blue rounded rectangle labeled 'Core network'. Below it is a larger light blue rounded rectangle labeled 'IoT area network'. Inside the IoT area network, there is a green rounded rectangle labeled 'Gateway' and three green rounded rectangles labeled 'Smart meter'. Two curved arrows originate from the first two 'Smart meter' boxes and point to the 'Gateway' box, with the label 'Data sent periodically' placed between them. A straight arrow originates from the third 'Smart meter' box and points directly to the 'Core network' box, also labeled 'Data sent periodically'. The identifier 'Y.4113(16)\_FI.1' is located at the bottom right of the diagram.
+
+Diagram illustrating typical data transmission from smart meters in an IoT area network to the core network.
+
+**Figure I.1 – Typical data transmission from deployed smart meters in IoT area network to the core network**
+
+Figure I.2 shows an example of data transmission within a dedicated time slot. Because of the increasing number of deployed smart meters, data transmission from a large number of smart meters may occur at the same time. This may cause congestion situations in the core network. In order to avoid such congestion, a dedicated time slot for each smart meter can be assigned in order to randomize each data transmission. In Figure I.2, a dedicated time slot (e.g., every 00:15-00:25) is assigned to smart meter A) for data transmission. A different dedicated time slot (e.g., every 00:35-00:45) is assigned to smart meter B) for data transmission. Transmissions are allowed only during the assigned dedicated time slot.
+
+
+
+Diagram illustrating data transmission within assigned dedicated time slots. The diagram shows a Core network at the top and an IoT area network below it. The IoT area network contains a Gateway and three Smart meters (Smart meter, Smart meter A, and Smart meter B). Arrows indicate data flow from Smart meter A to the Gateway and then to the Core network, labeled 'Data only sent during 00:15-00:25'. Similarly, an arrow indicates data flow from Smart meter B to the Gateway and then to the Core network, labeled 'Data only sent during 00:35-00:45'. Below the diagram, text specifies: 'Smart metre A) time slot for sending data is 00:15-00:25' and 'Smart metre B) time slot for sending data is 00:35-00:45'. The identifier Y.4113(16)\_Fl.2 is at the bottom right.
+
+**Figure I.2 – Data transmission within assigned dedicated time slot**
+
+Figure I.3 shows two cases of data communication initiated by the core network; one is the status information request and the other is the data retransmission request. When the core network realizes that part of the data communication is not completed for some reason, the core network may send a status information request to the smart meters in order to check their device health, or it may send a data retransmission request for data recovery. Even if it is outside the assigned dedicated time slot indicated in Figure I.2, the smart meters can communicate as a reaction upon receiving the request from the core network.
+
+
+
+Diagram illustrating data communication initiated by the core network. The diagram shows a Core network at the top and an IoT area network below it. The IoT area network contains a Gateway and three Smart meters (Smart meter, Smart meter, and Smart meter). Arrows indicate communication flow: a black arrow from the Core network to the Gateway labeled 'What is your status', a red arrow from the Gateway to the first Smart meter labeled 'Good', a black arrow from the Core network to the second Smart meter labeled 'Re-send request', and a red arrow from the second Smart meter to the Core network labeled 'Re-send'. The identifier Y.4113(16)\_Fl.3 is at the bottom right.
+
+**Figure I.3 – Data communication initiated by the core network
+(status request and re-send request)**
+
+Figure I.4 shows the case of data communication initiated by smart meters. Typical data concerns device health information, which is sent periodically. In terms of the device health check, a status report including device status of communication availability may be sent from smart meters toward the core network periodically.
+
+
+
+Figure I.4: Data communication initiated by smart meters. The diagram shows a Core network at the top and an IoT area network below it. The IoT area network contains a Gateway and three Smart meters (Smart meter, Smart meter A, and Smart meter B). Arrows labeled 'Periodic status report' point from the Gateway and Smart meter B to the Core network. The diagram is labeled Y.4113(16)\_FI.4.
+
+**Figure I.4 – Data communication initiated by smart meters**
+
+#### **I.1.2 Potential issues**
+
+This clause describes potential issues by deploying smart meters.
+
+##### **I.1.2.1 Data to/from devices for the IoT and data to/from other devices**
+
+Congestion in the network may potentially be caused by processing massive amounts of data from large numbers of devices for the IoT. Even if all of these data from IoT devices inside the network are prioritized as low, the issue may be unavoidable.
+
+For example, the processing of data from smart meters (data from IoT devices) in gateways and the network may not be guaranteed even if the priority of these data is set as low due to the huge amount of data from other devices that are not IoT devices. Neither may it be guaranteed even if the network can still have enough capacity of data processing when numerous data re-transmissions are triggered or a gateway fails causing unbalanced traffic, i.e., traffic originally assigned to the failed gateway which is re-routed to other gateways when the failure happens. Even if the data from smart meters are de-prioritized (see Figure I.5), the impact of the huge quantity of data from devices which are not part of the IoT may still cause the mentioned issue.
+
+
+
+Figure I.5: Data from smart meters and data from devices not for the IoT. The diagram shows a Core network at the top and an IoT area network below it. The IoT area network contains a Gateway and two Smart meters. A red arrow points from the Core network to the IoT area network, labeled 'Huge data from devices not part of IoT'. A black arrow points from the Gateway to the Core network, labeled 'Data from IoT devices is de-prioritized'. A red box in the Core network contains the text 'Still retain sufficient capacity for data processing?'. The diagram is labeled Y.4113(16)\_FI.5.
+
+**Figure I.5 – Data from smart meters and data from devices not for the IoT**
+
+##### **I.1.2.2 Unbalanced traffic within IoT area network**
+
+If the left side gateway in Figure I.6 fails, the data originally assigned to this failed gateway may be re-routed to the right side gateway in the Figure I.6. This can cause an overflow in the right side gateway, or at the connecting point of the network with the right side gateway.
+
+
+
+Figure I.6: Re-route provoking unbalanced traffic. The diagram shows a Core network at the top and an IoT area network below. In the IoT area network, there are two Gateways and three Smart meters. A 'Failure' is indicated on the left Gateway. Smart meters on the left are connected to the left Gateway. Smart meters on the right are connected to the right Gateway. A red arrow shows traffic from the left Gateway being rerouted to the right Gateway, which then sends it to the Core network. A red circle in the Core network is labeled 'Unexpected amount of traffic to handle'. The label 'Y.4113(16)\_Fl.6' is at the bottom right.
+
+**Figure I.6 – Re-route provoking unbalanced traffic**
+
+### I.2 IoT area network
+
+This clause describes typical use cases and potential issues with IoT area network.
+
+#### I.2.1 Topology modification
+
+When an IoT area network is established based on autonomous or distributed policy or any other policies, it may not be sufficiently balanced from a load point of view. Figure I.7 shows a case with five smart meters connected to the left side gateway and one smart meter connected to the right side gateway. In this case, the traffic from the IoT area network to the core network is unbalanced from the network point of view.
+
+
+
+Figure I.7: Unbalanced IoT area network from a load point of view. The diagram shows a Core network at the top and an IoT area network below. In the IoT area network, there are two Gateways. The left Gateway is connected to five Smart meters, and the right Gateway is connected to one Smart meter. Red arrows show traffic from both Gateways to the Core network. A double-headed arrow between the two red arrows is labeled 'Un-balanced traffic'. The label 'Y.4113(16)\_Fl.7' is at the bottom right.
+
+**Figure I.7 – Unbalanced IoT area network from a load point of view**
+
+From the core network point of view, even though the IoT area network load is managed by the IoT area network itself, the network load may be unbalanced, i.e., based on the required resources for the point of interconnect to the core network. Figure I.8 shows the case with traffic from smart meters connected to the left side gateway which is balanced from the IoT area network point of view, but still unbalanced from the network point of view.
+
+
+
+Y.4113(16)\_FI.8
+
+Figure I.8: Load optimization from the IoT area network point of view. The diagram shows a Core network at the top and an IoT area network below. The IoT area network contains two Gateways and seven Smart meters. A red arrow labeled 'Un-balanced traffic' points from the Core network to the left Gateway. Inside the IoT area network, a red arrow labeled 'Balanced traffic' points from the left Gateway to the right Gateway. Smart meters are connected to their respective Gateways via black arrows.
+
+**Figure I.8 – Load optimization from the IoT area network point of view**
+
+In order to mitigate the unbalanced traffic within the IoT area network and the point of interconnect between the IoT area network and the core network, by using the information obtained with status monitoring, the core network is capable of calculating the topology of the current IoT area network and also calculating the effective optimal topology. In addition, the core network is capable of providing appropriate actions, based on calculation results, to the devices and gateways which are critical to maintain the IoT area network topology in order to allow reformulation of the IoT area network topologies by themselves. Figure I.9 shows the case where, based on the request from the core network, the IoT area network reformulates the topology inside the IoT area network.
+
+
+
+Y.4113(16)\_FI.9
+
+Figure I.9: Balancing the topology from the core network point of view. The diagram shows a Core network at the top and an IoT area network below. The IoT area network contains two Gateways and seven Smart meters. A red arrow labeled 'Balanced traffic' points from the Core network to the left Gateway. Inside the IoT area network, a red arrow points from the right Gateway to the left Gateway, indicating a change in traffic flow. Smart meters are connected to their respective Gateways via black arrows.
+
+**Figure I.9 – Balancing the topology from the core network point of view**
+
+#### I.2.2 Traffic route diversion
+
+In the IoT area network, some factors may cause the unavailability of data transfer from devices and gateways. For example, a node may fail due to overload or hardware malfunctions. Devices may also have limited battery capacity, therefore affecting hardware capabilities. For example, a low battery may impact the radio power of the device. Figure I.10 shows the case with one smart meter having a low battery and getting loss of radio power to maintain connectivity with the gateway.
+
+
+
+The diagram shows a hierarchical network structure. At the top is the 'Core network'. Below it is the 'IoT area network'. Inside the IoT area network, there are two 'Gateway' nodes. The left gateway is connected to four 'Smart meter' nodes: one via dashed arrows (labeled 'Low battery') and three via solid arrows. The right gateway is connected to two 'Smart meter' nodes via solid arrows. All gateways have a solid arrow pointing up to the 'Core network'.
+
+Y.4113(16)\_FI.10
+
+Diagram illustrating low battery impact on radio power of devices. The IoT area network contains two gateways and six smart meters. One smart meter is highlighted with a red border and labeled 'Low battery'. Dashed arrows show its connection to the left gateway, while solid arrows show other smart meters connecting to their respective gateways. The gateways connect to the Core network.
+
+**Figure I.10 – Low battery may impact radio power of devices**
+
+In order to maintain correct traffic routing from the entire IoT system point of view, it may be efficient to request appropriate actions to devices and gateways, including appropriate neighbours, in order to regenerate the traffic routes based on consideration of the current status of the IoT area network. The status information monitored by the network can be used for this purpose. Figure I.11 shows the case where, based on the request from the core network to the IoT area network to regenerate the traffic routes inside the IoT area network, traffic diversion takes place.
+
+
+
+The diagram shows the same network structure as Figure I.10. In this scenario, the smart meter previously labeled 'Low battery' is now labeled 'Failure' and has a red border. A red arrow labeled 'Diversion to avoid specific device' originates from this failed smart meter and points to another smart meter in the same area. This other smart meter is then connected to the left gateway via a solid arrow. The other smart meters and gateways remain in their original states and connections. The gateways continue to connect to the 'Core network'.
+
+Y.4113(16)\_FI.11
+
+Diagram illustrating traffic diversion. The IoT area network contains two gateways and six smart meters. One smart meter is highlighted with a red border and labeled 'Failure'. A red arrow labeled 'Diversion to avoid specific device' shows traffic being rerouted from the failed smart meter to another smart meter. The gateways connect to the Core network.
+
+**Figure I.11 – Traffic diversion**
+
+# Appendix II
+
+## Access network and IoT area network technologies
+
+(This appendix does not form an integral part of this Recommendation.)
+
+### II.1 Access-specific aspects relating to core network requirements
+
+As shown in Figure 1, the network consists of three main parts, IoT area network, access network and core network.
+
+For the access network, a variety of technologies may be used. Clause II.1.1 lists some technologies which may be used for the access network.
+
+For the IoT area network, a variety of technologies may be used. Clause II.1.2 lists some technologies which may be used for the IoT area network.
+
+The technologies listed in both clauses II.1.1 and II.1.2 are not meant to be exhaustive.
+
+#### II.1.1 Technologies used for the access network
+
+Table II.1 lists some technologies which may be used for the access network.
+
+**Table II.1 – Some technologies used for access networks**
+
+| Technology | Description |
+|-----------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------|
+| Public switched telephone network (PSTN) technology | CCITT Signalling System No. 7 (SS7) technology. |
+| 2G/3G/LTE wireless technology | Second-generation wireless telephone technology (2G), third-generation wireless telephone technology (3G), LTE technologies. |
+| xDSL technology | Digital subscriber line (DSL) technologies, e.g., asymmetric DSL (ADSL), symmetric DSL (SDSL). |
+| FTTx technology | Fiber to the x (FTTx) technology (broadband network technologies using optical fiber). |
+| LPWA wireless technology | Low power wide area (LPWA) network technology. |
+
+#### II.1.2 Technologies used for IoT area network
+
+Table II.2 lists some technologies which may be used for the IoT area network.
+
+**Table II.2 – Some technologies used for IoT area networks**
+
+| Technology | Description |
+|-------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Controller area network (CAN) bus technology | A serial communication technology that supports distributed real-time control and multiplexing. |
+| ZigBee wireless technology | Wireless technology for short-range communication based on [b-IEEE 802.15.4]. |
+| Bluetooth wireless technology | Wireless technology for short-range communication [b-IEEE 802.15.1]. |
+| Wi-Fi wireless technology | Wireless local area network (LAN) technology (specifications known as IEEE 802.11 series specifications, e.g., 802.11, 802.11a, 802.11b, 802.11g, 802.11n and 802.11ac). |
+| Wireless smart utility network (Wi-SUN) wireless technology | Low-rate wireless personal area networks (LR-WPANs) (PHY is defined in [IEEE 802.15.4g], MAC is defined in [IEEE 802.15.4e]). |
+| Ultra low energy (ULE) technology | ULE technology ([b-ETSI TS 102 939-1]). |
+
+# Bibliography
+
+- [b-ITU-T Q.1742.11] Recommendation ITU-T Q.1742.11 (2014), *IMT 2000 references (approved as of 31st December 2012) to ANSI-41-evolved core network with cdma2000 access network*.
+- [b-ITU-T Y.101] Recommendation ITU-T Y.101 (2000), *Global Information Infrastructure terminology: Terms and definitions*.
+- [b-ITU-T Y.2221] Recommendation ITU-T Y.2221 (2010), *Requirements for support of ubiquitous sensor network (USN) applications and services in the NGN environment*.
+- [b-ETSI TS 102 939-1] ETSI TS 102 939-1 (2015), *Digital Enhanced Cordless Telecommunications (DECT); Ultra Low Energy (ULE); Machine to Machine Communications; Part 1: Home Automation Network (phase 1)*.
+- [b-3GPP TS 36.300] 3GPP specification TS 36.300, *Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall description; Stage 2*.
+- [b-IEEE 802.11] IEEE 802.11-2012, *Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications*.
+- [b-IEEE 802.15.1] IEEE 802.15.1-2005, *Wireless Medium Access Control (MAC) and Physical Layer (PHY) specifications for Wireless Personal Area Networks (WPANs)*.
+- [b-IEEE 802.15.4] IEEE 802.15.4-2003, *IEEE Standard for Information technology – Telecommunications and information exchange between systems – Local and metropolitan area networks – Specific requirements – Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs)*.
+- [b-IEEE 802.15.4e] IEEE 802.15.4e-2012, *IEEE Standard for Local and metropolitan area networks – Part 15.4: Low-Rate Wireless Personal Area Networks (LR-WPANs) Amendment 1: MAC sublayer*.
+- [b-IEEE 802.15.4g] IEEE 802.15.4g-2012, *IEEE Standard for Local and metropolitan area networks – Part 15.4: Low-Rate Wireless Personal Area Networks (LR-WPANs) Amendment 3: Physical Layer (PHY) Specifications for Low-Data-Rate, Wireless, Smart Metering Utility Networks*.
+
+
+
+# SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | General tariff principles |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Terminals and subjective and objective assessment methods |
+| Series Q | Switching and signalling |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects and next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+## Y.4208
+
+(01/2020)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Internet of things and smart cities and communities –
+Requirements and use cases
+
+# --- **Internet of things requirements for support of edge computing**
+
+Recommendation ITU-T Y.4208
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+# GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+| | |
+|--------------------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | |
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+| INTERNET PROTOCOL ASPECTS | |
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+| NEXT GENERATION NETWORKS | |
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Network control architectures and protocols | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+| FUTURE NETWORKS | Y.3000–Y.3499 |
+| CLOUD COMPUTING | Y.3500–Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | |
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4208
+
+# Internet of things requirements for support of edge computing
+
+## Summary
+
+Some of the capabilities offered by the Internet of thing (IoT), e.g., capabilities for computing, storage and analytics, are evolving in closer proximity to IoT data sources. Recommendation ITU-T Y.4208 provides an overview of related challenges faced by the IoT and describes how IoT-supporting edge computing (EC) may address these challenges. From the edge-computing deployment perspective, service requirements for support of EC capabilities in the IoT are identified, as well as related functional requirements. As an example, scenarios of EC deployment in different application domains, EC scenarios for vehicle-to-everything (V2X) and for smart manufacturing are provided in an appendix.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.4208 | 2020-01-13 | 20 | 11.1002/1000/14162 |
+
+## Keywords
+
+Edge computing, functional requirements, IoT requirements, service requirements.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2020
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|---|----------------------------------------------------------------------------------------------------------------------------|-------------|
+| 1 | Scope..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 3 |
+| 6 | Introduction of edge computing in the Internet of things ..... | 3 |
+| | 6.1 Concept of edge computing..... | 3 |
+| | 6.2 Internet of things challenges..... | 3 |
+| | 6.3 Addressing the Internet of things challenges..... | 5 |
+| 7 | Service requirements from an edge-computing deployment perspective..... | 5 |
+| | 7.1 Edge-computing deployment perspective ..... | 6 |
+| | 7.2 Service requirements for support of edge-computing capabilities in the Internet of things..... | 6 |
+| 8 | Functional requirements of the Internet of things to support edge computing..... | 7 |
+| | 8.1 Data management requirements ..... | 7 |
+| | 8.2 Functional requirements to support service provisioning ..... | 8 |
+| | 8.3 Application support requirements ..... | 8 |
+| | 8.4 Management requirements ..... | 8 |
+| | Appendix I – Detailed scenarios of edge computing in the Internet of things related to different application domains ..... | 10 |
+| | I.1 Edge-computing scenarios for vehicle-to-everything ..... | 10 |
+| | I.2 Edge-computing scenarios for smart manufacturing..... | 12 |
+| | Bibliography..... | 13 |
+
+
+
+# Recommendation ITU-T Y.4208
+
+# Internet of things requirements for support of edge computing
+
+# 1 Scope
+
+This Recommendation provides service requirements from an edge-computing (EC) deployment perspective. This Recommendation also specifies functional requirements of the Internet of things (IoT) for support of EC.
+
+The scope of this Recommendation includes:
+
+- introduction of EC into the IoT;
+- service requirements from an edge-computing deployment perspective;
+- functional requirements of the IoT for support of EC.
+
+Some detailed scenarios of EC in the IoT related to different application domains are provided in Appendix I.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- [ITU-T Q.1742.11] Recommendation ITU-T Q.1742.11 (2014), *IMT 2000 references (approved as of 31 December 2012) to ANSI-41-evolved core network with cdma2000 access network*.
+- [ITU-T Y.4000] Recommendation ITU-T Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+- [ITU-T Y.4100] Recommendation ITU-T Y.4100/Y.2066 (2014), *Common requirements of the Internet of things*.
+- [ITU-T Y.4101] Recommendation ITU-T Y.4101/Y.2067 (2017), *Common requirements and capabilities of a gateway for Internet of things applications*.
+- [ITU-T Y.4113] Recommendation ITU-T Y.4113 (2016), *Requirements of the network for the Internet of things*.
+- [ITU-T Y.4114] Recommendation ITU-T Y.4114 (2017), *Specific requirements and capabilities of the Internet of things for big data*.
+- [ITU-T Y.4401] Recommendation ITU-T Y.4401 (2015), *Functional framework and capabilities of the Internet of things*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 access network** [ITU-T Q.1742.11]: Network that connects access technologies (such as a radio access network) to the core network.
+
+**3.1.2 core network** [b-ITU-T Y.101]: A portion of the delivery system composed of networks, systems equipment and infrastructures, connecting the service providers to the access network.
+
+**3.1.3 device** [ITU-T Y.4000]: With regard to the Internet of things, this is a piece of equipment with the mandatory capabilities of communication and the optional capabilities of sensing, actuation, data capture, data storage and data processing.
+
+**3.1.4 gateway** [ITU-T Y.4101]: A unit in the Internet of things which interconnects the devices with the communication networks. It performs the necessary translation between the protocols used in the communication networks and those used by devices.
+
+**3.1.5 Internet of things (IoT)** [ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.
+
+NOTE 1 – Through the exploitation of identification, data capture, processing and communication capabilities, the IoT makes full use of things to offer services to all kinds of applications, whilst ensuring that security and privacy requirements are fulfilled.
+
+NOTE 2 – From a broader perspective, the IoT can be perceived as a vision with technological and societal implications.
+
+**3.1.6 IoT area network** [ITU-T Y.4113]: A network of devices for the IoT and gateways interconnected through local connections.
+
+NOTE – This definition is based on "Overview of the Internet of things" [ITU-T Y.4000], where clause 6.2 states "devices can communicate with other devices using direct communication through a local network (i.e., a network providing local connectivity between devices and between devices and a gateway, such as an ad-hoc network)".
+
+## **3.2 Terms defined in this Recommendation**
+
+None.
+
+# **4 Abbreviations and acronyms**
+
+| | |
+|-----|--------------------------------------------------|
+| EC | Edge Computing |
+| eNB | evolved Node Base |
+| EPC | Evolved Packet Core |
+| ETC | Electronic Toll Collection |
+| IoT | Internet of Things |
+| OPC | Object linking and embedding for Process Control |
+| QoS | Quality of Service |
+| RSU | Roadside Unit |
+| UE | User Equipment |
+| V2I | Vehicle-to-Infrastructure |
+| V2N | Vehicle-to-Network |
+| V2P | Vehicle-to-Pedestrian |
+| V2V | Vehicle-to-Vehicle |
+| V2X | Vehicle-to-Everything |
+
+# 5 Conventions
+
+In this Recommendation:
+
+The keywords **"is required to"** indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+
+The keywords **"is recommended"** indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+
+The keywords **"can optionally"** and **"may"** indicate an optional requirement which is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with the specification.
+
+# 6 Introduction of edge computing in the Internet of things
+
+## 6.1 Concept of edge computing
+
+Some of the capabilities offered by the IoT, e.g., for computing, storage and analytics, are evolving in close proximity to IoT data sources.
+
+For the purposes of this Recommendation, IoT data usually comes via devices and gateways. IoT devices or gateways may need to have computing, storage and intelligence support from IoT platform(s) or IoT application server(s). Compared to capabilities for computing, storage and intelligence accessed via the core network, EC enables deployment in proximity to IoT data sources and may provide IoT services with increased performance. Examples of increased performance include lower service response delay, higher service reliability and higher service access capacity.
+
+IoT requirements for support of EC may differ depending on context (e.g., applications and network technologies). EC is intended to offer flexibility (e.g., related to performance, deployment models and applications) with respect to identified needs. It is important to assess which service and functional requirements are needed in a given context. For example, not all IoT technical components may require capabilities related to support of EC.
+
+A number of efforts (and technical standards) are currently devoted to EC technical aspects from different perspectives, e.g., [b-ECC] [b-EdgeX] [b-IIC] [b-MEC] and [b-OECI].
+
+## 6.2 Internet of things challenges
+
+To identify the requirements of the IoT to support EC, the IoT challenges described in clauses 6.2.1 and 6.2.2 need to be investigated.
+
+#### 6.2.1 Challenges faced by the Internet of things network
+
+[ITU-T Y.4113] specifies a basic model of the network for the IoT, as shown in Figure 1. Multiple network technologies can be used as the IoT area network, access network and core network [ITU-T Y.4113].
+
+![Figure 1: Basic model of the network for the Internet of things [ITU-T Y.4113]. The diagram shows a flow from IoT devices through a Gateway, an Access network, a Core network, and finally to IoT platforms and application servers. The IoT area network is on the left, connected to the Gateway. The Access network and Core network are represented by cloud shapes. The IoT platform and application servers are on the right.](a5ee5c23b6dc52ec1d724b76d5a5f58f_img.jpg)
+
+The diagram illustrates the basic model of the network for the Internet of things. It is divided into three main sections: the IoT area network, the Access network, and the Core network. In the IoT area network, there are two IoT devices connected to a Gateway. The Gateway is connected to the Access network, which is represented by a cloud shape. The Access network is connected to the Core network, also represented by a cloud shape. The Core network is connected to two IoT application servers, one of which is also connected to an IoT platform. The diagram is labeled Y.4208(20)\_F01.
+
+Figure 1: Basic model of the network for the Internet of things [ITU-T Y.4113]. The diagram shows a flow from IoT devices through a Gateway, an Access network, a Core network, and finally to IoT platforms and application servers. The IoT area network is on the left, connected to the Gateway. The Access network and Core network are represented by cloud shapes. The IoT platform and application servers are on the right.
+
+**Figure 1 – Basic model of the network for the Internet of things [ITU-T Y.4113]**
+
+[ITU-T Y.4113] identifies general IoT network issues, including:
+
+- packet loss and higher latency due to simultaneous data transmission;
+- unreliability of short-range radio communications in the IoT area network;
+- network overload due to the large amount of traffic to be processed.
+
+In the basic model of the network for the IoT, heavy computing, storage and intelligence capabilities are typically deployed on IoT platforms or IoT application servers accessed via the core network, and light computing, storage and intelligence capabilities are typically deployed locally in the IoT device and the gateway, as shown in Figure 2.
+
+
+
+The diagram shows the typical deployment of computing, storage, and intelligence capabilities. It consists of four main components connected in a sequence: an oval labeled 'Computing, storage and intelligence', followed by a cloud labeled 'Access network', then another cloud labeled 'Core network', and finally another oval labeled 'Computing, storage and intelligence'. The diagram is labeled Y.4208(20)\_F02.
+
+Figure 2: Typical computing, storage and intelligence capabilities deployment under the basic model of the network for the Internet of things. The diagram shows a sequence of components: Computing, storage and intelligence (in an oval), Access network (cloud), Core network (cloud), and Computing, storage and intelligence (in an oval).
+
+**Figure 2 – Typical computing, storage and intelligence capabilities deployment under the basic model of the network for the Internet of things**
+
+To support EC, the IoT may need to be enhanced to support computing, storage and intelligence capabilities evolving in closer proximity to IoT data sources. With this support from the IoT, the computing, storage and intelligence capabilities distribution enables a new deployment model, as shown in Figure 3.
+
+
+
+The diagram illustrates a new deployment model for computing, storage, and intelligence capabilities. It consists of five main components connected in a sequence: an oval labeled 'Computing, storage and intelligence', followed by a cloud labeled 'Access network', then an oval labeled 'Computing, storage and intelligence', then a cloud labeled 'Core network', and finally an oval labeled 'Computing, storage and intelligence'. The diagram is labeled Y.4208(20)\_F03.
+
+Figure 3: New computing, storage and intelligence capabilities deployment model supported by enhanced Internet of things infrastructure. The diagram shows a sequence of components: Computing, storage and intelligence (in an oval), Access network (cloud), Computing, storage and intelligence (in an oval), Core network (cloud), and Computing, storage and intelligence (in an oval).
+
+**Figure 3 – New computing, storage and intelligence capabilities deployment model supported by enhanced Internet of things infrastructure**
+
+IoT infrastructure enhancement to support edge deployment may alleviate some IoT network issues identified in [ITU-T Y.4113], e.g., overload of network traffic at the core network may be decreased. However, new issues may appear, including, but not limited to:
+
+- how to improve the capabilities of IoT technical components in order to support different service requirements at the edge;
+
+- how to coordinate IoT technical components and assign related resources (e.g., computation, storage, network) to support EC.
+
+The existing IoT technical components may need additional capabilities to those identified in [ITU-T Y.4113], in order to handle these new challenges, separately or in cooperation, to support EC.
+
+### **6.2.2 Challenges faced by data processing in the Internet of things**
+
+[ITU-T Y.4114] addresses IoT challenges from the IoT data ecosystem aspect, including:
+
+- fulfilment of different service requirements;
+- being interoperable;
+- being scalable and flexible;
+- efficient usage of IoT data.
+
+Due to IoT infrastructure enhancement, some IoT network issues identified in [ITU-T Y.4114], e.g., meeting different transmission latency requirements, may be relieved. However, new issues may appear for big data processing in the IoT, including, but not limited to:
+
+- collection, pre-processing, storage, querying, analysis, transfer and visualization [ITU-T Y.4114] of data across IoT data sources, IoT platform(s) and application server(s) deployed in proximity to IoT data sources, as well as across IoT platform(s) and application server(s) deployed remotely from data sources;
+- splitting and assignment of relevant big data processing tasks to different IoT technical components in order to meet service requirements;
+- protection of data from unauthorized usage by newly introduced IoT platform(s) and application server(s) deployed in proximity to data sources.
+
+## **6.3 Addressing the Internet of things challenges**
+
+Clauses 6.3.1 and 6.3.2 describe how IoT-supporting EC may address the identified IoT challenges.
+
+### **6.3.1 Help reducing data overload**
+
+IoT-supporting EC may reduce data overload by buffering, storage and processing of data in IoT devices or gateways at the edge of the network. So, it can help to reduce data overload in data centres, mitigating big data challenges faced by data intensive IoT applications.
+
+### **6.3.2 Enabling more flexible service provisioning**
+
+IoT-supporting EC may provide more flexible services by analysing data in IoT devices or gateways at the edge of network. Distributing data analysis and service-provisioning capabilities to IoT devices or gateways may be based on service-provisioning rules customized by IoT users or applications.
+
+# **7 Service requirements from an edge-computing deployment perspective**
+
+This clause focuses on service requirements of the IoT [ITU-T Y.4000] to support EC. Service requirements are described from a deployment perspective [ITU-T Y.4401].
+
+Based on the service requirements identified in this clause, clause 8 describes functional requirements from the angle of which logical functionalities IoT technical components need in order to fulfil service requirements.
+
+Appendix I provides some detailed scenarios of EC in the IoT related to different application domains in support to the requirements identified in this clause and clause 8.
+
+## 7.1 Edge-computing deployment perspective
+
+From a deployment perspective, the IoT technical components [ITU-T Y.4113] – as shown in Figure 4 – may need to support requirements corresponding to EC enablement.
+
+
+
+Figure 4: Service requirements from an EC deployment perspective. The diagram illustrates the network architecture and associated service requirements for edge computing (EC) enablement. It shows three main network segments: IoT area network, Access network, and Core network. IoT devices connect to the IoT area network, which connects to a Gateway in the Access network. The Access network connects to the Core network, which contains the Edge platform, IoT application servers, and IoT platforms. Service requirements for EC are indicated by boxes with arrows pointing to specific components: 'Service requirements for IoT device for support of EC' points to IoT devices; 'Service requirements for IoT area network for support of EC' points to the IoT area network; 'Service requirements for gateway for support of EC' points to the Gateway; 'Service requirements for access network for support of EC' points to the Access network; 'Service requirements for edge platform for support of EC' points to the Edge platform. The diagram is labeled Y.4208(19)\_F04 in the bottom right corner.
+
+**Figure 4 – Service requirements from an EC deployment perspective**
+
+- (1) IoT device [ITU-T Y.4000]: In order to support EC enablement, IoT devices may need to enhance their capabilities related to computation, storage and connectivity, for example.
+- (2) IoT area network [ITU-T Y.4113]: The IoT area network may need to enhance its capabilities, e.g., in terms of reliability, bandwidth and latency, in order to fulfil EC-related service requirements. Vehicle-to-vehicle (V2V) scenarios described in Appendix I are examples of these IoT area network requirements.
+- (3) Gateway [ITU-T Y.4101]: In order to support EC, apart from common capabilities [ITU-T Y.4101], the gateway may need to enhance its capabilities, e.g., in terms of computation, storage and connectivity.
+- (4) Access network [ITU-T Q.1742.11]: In order to support EC, the access network may need to enhance its network capabilities.
+- (5) Edge platform: in order to support EC, some IoT capabilities move from IoT platform(s) and IoT application server(s) to a new IoT technical component, the edge platform. Cooperation between edge platforms, gateways, devices, IoT platforms or IoT application servers may be needed.
+
+NOTE – The edge platform is usually a kind of cloud platform.
+
+## 7.2 Service requirements for support of edge-computing capabilities in the Internet of things
+
+### 7.2.1 Service requirements for Internet of things devices
+
+- (1) The IoT device is recommended to have computing and storage capabilities to support the processing of collected data directly, with or without help from gateway(s) or edge platform(s). Vehicle-to-infrastructure (V2I) and vehicle-to-network (V2N) scenarios described in clause I.1 are examples of these IoT device requirements.
+
+### 7.2.2 Service requirements for the gateway
+
+- (1) The gateway is recommended to provide capabilities to support the performance balance among IoT devices, e.g., for computation, storage and network consumption. For example,
+
+if one or more IoT devices managed by the gateway are overloaded, the gateway can assign related tasks to other managed IoT devices for relief. Smart manufacturing scenarios described in clause I.2 are examples of these IoT gateway requirements.
+
+- (2) The gateway is recommended to support collaboration among IoT devices to support requirements corresponding to EC enablement.
+- (3) The gateway may support collaboration with other gateways to support requirements corresponding to EC enablement.
+- (4) If IoT device(s) connect(s) to the access network via the gateway, the gateway is recommended to support context awareness, e.g., context information at connectivity and application levels.
+
+### **7.2.3 Service requirements for the edge platform**
+
+- (1) Depending on service requirements, the edge platform may support time-sensitive applications.
+- (2) Depending on service requirements, the edge platform is recommended to support applications with different service requirements, e.g., bandwidth, storage or computation.
+- (3) Depending on service requirements, the edge platform is recommended to support multiple network interfaces and application interfaces in order to support connection between elements, e.g., an IoT device, gateway, edge platform, IoT platform and IoT application server.
+- (4) Depending on service requirements, the edge platform may provide IoT applications with the location of IoT devices. The V2N scenarios described in Appendix I are examples of this requirement.
+- (5) Depending on service requirements, the edge platform may support high integrity and availability applications. The V2I, V2V and V2N scenarios in Appendix I are examples of this requirement.
+
+### **7.2.4 Service requirements for the Internet of things area network**
+
+The IoT area network is recommended to be enhanced, including enabling transmission latency and connection fault probability reduction. The V2V, V2P and V2I scenarios described in Appendix I are examples of these IoT area network requirements.
+
+#### **7.2.5 Service requirements for the access network**
+
+The access network may support flexible network capabilities as necessary and appropriate in IoT for support of EC.
+
+The V2N scenario described in Appendix I is an example of access network capabilities.
+
+# **8 Functional requirements of the Internet of things to support edge computing**
+
+The categories of functional requirements of the IoT to support EC in clauses 8.1 to 8.4 are based on the categories of IoT common requirement specified in [ITU-T Y.4100].
+
+## **8.1 Data management requirements**
+
+As described in [ITU-T Y.4100], data management requirements refer to the functional requirements for storage, aggregation, transfer and processing of IoT data. The enhanced data management requirements of the IoT to support EC are as described in clauses 8.1.1 and 8.1.2.
+
+### **8.1.1 Data processing at the edge of the network**
+
+According to clauses 7.2.1 entry (1), 7.2.2 entry (1), 7.2.3 entry (1) and 7.2.3 entry (2), in order to support data processing in EC, capabilities to process data at the edge of the network are required.
+
+### **8.1.2 Data buffering and storage at the edge of the network**
+
+According to clauses 7.2.1 entry (1), 7.2.2 entry (1), 7.2.3 entry (1) and 7.2.3 entry (2), in order to support data buffering and storage in EC, the capabilities to buffer and store data at the edge of the network are required.
+
+## **8.2 Functional requirements to support service provisioning**
+
+Service provisioning refers to the supply of services from providers to users.
+
+### **8.2.1 Location awareness and location-based service provisioning**
+
+According to clause 7.2.3 entry (4), the capability to analyse location awareness data for IoT devices or gateways is recommended.
+
+According to clause 7.2.3 entry (4), IoT devices, gateways or edge platform(s) are recommended to support location-based service provisioning.
+
+### **8.2.2 Context awareness and context-based service provisioning**
+
+According to clause 7.2.3 entry (3), interface context awareness, e.g., network interface context and application interface context, is required.
+
+According to clause 7.2.2 entry (4), the capabilities to analyse context aware data and context-based service provisioning in IoT devices or gateways are recommended.
+
+## **8.3 Application support requirements**
+
+As described in [ITU-T Y.4100], application support requirements refer to the functional requirements for the development of IoT applications in different application domains. The enhanced application support requirements of the IoT to support EC are described in clauses 8.3.1 and 8.3.2.
+
+#### **8.3.1 Collaboration at the edge of the network**
+
+According to clauses 7.2.2 entry (2) and 7.2.2 entry (3), in order to support collaboration at the edge of the network, the capabilities to collaborate among IoT devices, gateways and the edge platform in respect of service provisioning are required.
+
+NOTE – "Collaboration is required among services or among devices accessing, with the same goal, IoT applications, so that the IoT can enable autonomous goal-driven collaboration among such services or devices." is specified in clause 8.3.4 of" [ITU-T Y.4100].
+
+#### **8.3.2 Network capability exposure**
+
+According to clause 7.2.4, the IoT area network is required to be able to expose appropriate network capabilities to IoT applications according to their requirements, e.g., in order to support time-sensitive services or high-bandwidth services.
+
+NOTE – According to clause 7.2.5, the IoT access network may expose appropriate network capabilities in IoT for support of EC.
+
+## **8.4 Management requirements**
+
+As described in [ITU-T Y.4100], the IoT non-functional requirements refer to the requirements related to the implementation and operation of the IoT. Management capabilities belong to the category of IoT non-functional requirements.
+
+### **8.4.1 Distributed service management**
+
+According to clauses 7.2.2 entry (2) and 7.2.2 entry (3), in order to support service management at the edge of the network, distributed service management is recommended.
+
+NOTE – The service management functions may be distributed to multiple edge platforms from the deployment perspective.
+
+#### **8.4.2 Distributed account management**
+
+According to clauses 7.2.2 entry (2) and 7.2.2 entry (3), in order to support account management at the edge of the network, distributed account management is recommended.
+
+NOTE – The account information and related operations need to be synchronized with the associated edge platform and IoT platform from the deployment perspective.
+
+# Appendix I
+
+## Detailed scenarios of edge computing in the Internet of things related to different application domains
+
+(This appendix does not form an integral part of this Recommendation.)
+
+### I.1 Edge-computing scenarios for vehicle-to-everything
+
+Vehicle-to-everything (V2X) [b-3GPP TS 22.185] [b-ETSI TR 102 638] is one important domain in which EC technology can be applied.
+
+V2X applications can be classified into the following four types [b-3GPP TS 22.185]:
+
+- vehicle-to-vehicle (V2V) applications;
+- vehicle-to-infrastructure (V2I) applications;
+- vehicle-to-network (V2N) applications;
+- vehicle-to-pedestrian (V2P) applications.
+
+Based on the capabilities provided by EC and their deployment, the four types of V2X applications can be enriched with more intelligent services for end-users.
+
+#### I.1.1 Vehicle-to-vehicle
+
+V2V involves vehicles in proximity to each other exchanging application information [b-3GPP TS 22.185]. In this case, EC capabilities may need to be deployed in the vehicles so that the vehicles can transmit data and handle V2V-related messages.
+
+In V2V scenarios, vehicles connect to each other as in an IoT area network. The IoT area network may need enhanced capabilities to support V2V.
+
+In V2V scenarios, data exchanged between vehicles should have high integrity and availability, e.g., speed and accelerated speed of the vehicles.
+
+Figure I.1 shows a V2V scenario example.
+
+
+
+The diagram illustrates a Vehicle-to-Vehicle (V2V) scenario. Two black cars are positioned on a grey road with white dashed lines. Each car has a yellow rectangular box on its side labeled 'EC capabilities'. A horizontal dashed double-headed arrow connects the two cars, indicating bidirectional communication. The road is shown with a dashed white line in the center and solid white lines at the edges. The background is a light grey gradient.
+
+Y.4208(20)\_FI.1
+
+Diagram of a V2V scenario example showing two vehicles on a road, each with a yellow box labeled 'EC capabilities'. A dashed double-headed arrow indicates communication between them.
+
+Figure I.1 – V2V scenario example
+
+#### I.1.2 Vehicle-to-infrastructure
+
+V2I involves a vehicle with applications support exchanging messages containing application information with a roadside unit (RSU) in proximity to the vehicle or locally relevant application server [b-3GPP TS 22.185]. In this case, the RSU and the vehicle may need to deploy EC capabilities to support applications involving both the vehicle and the RSU.
+
+In V2I scenarios, the data exchanged between the vehicle and RSU or local application server should have high integrity and availability, e.g., financial data for electronic toll collection (ETC) applications. Figure I.2 shows a V2I scenario example.
+
+
+
+Y.4208(20)\_F1.2
+
+Figure I.2 – V2I scenario example: A diagram showing a Road Side Unit (RSU) and a Vehicle on a road. Both the RSU and the Vehicle have a yellow box labeled 'EC capabilities'. A dashed blue arrow points from the RSU to the Vehicle, indicating communication between them.
+
+**Figure I.2 – V2I scenario example**
+
+#### I.1.3 Vehicle-to-network
+
+V2N involves a vehicle with applications supporting the transmission of messages containing application information to an edge platform to provide optimized network quality of service (QoS) and necessary computing and storage capabilities [b-3GPP TS 22.185], e.g., an emergency call as a V2N application needs edge platform support for car-locating capabilities. In this case, EC capabilities may need to be deployed in the vehicle and the edge application server.
+
+In V2N scenarios, the data exchanged between the vehicle and edge platform should have high integrity and availability, e.g., driver's information and car information for emergency calls. Figure I.3 shows a V2N scenario example.
+
+
+
+Y.4208(20)\_F1.3
+
+Figure I.3 – V2N scenario example: A diagram showing a Vehicle on a road with a yellow box labeled 'EC capabilities'. Below the road, there is a network architecture consisting of an Access network (represented by a radio tower), an Edge platform (represented by a server rack with a yellow box labeled 'EC capabilities'), and a Core network (represented by a server rack). A dashed arrow points from the Vehicle to the Edge platform.
+
+**Figure I.3 – V2N scenario example**
+
+#### I.1.4 Vehicle-to-pedestrian
+
+V2P involves vehicles and user equipment (UE) used by pedestrians that are in proximity to each other exchanging application information [b-3GPP TS 22.185]. The V2P applications exchange messages containing V2P information, and this exchange may be directly among vehicles and UE or may need to be supported by an RSU. In this case, EC capabilities may be deployed in the vehicle, UE and the RSU. Figure I.4 shows a V2P scenario example.
+
+
+
+Figure I.4 – V2P scenario example. This diagram illustrates a Vehicle-to-Pedestrian (V2P) scenario. At the top, a car labeled 'Vehicle' is shown on a road, with a yellow box labeled 'EC capabilities' on its side. Below the road, a pedestrian is walking, carrying a smartphone labeled 'UE' (User Equipment), which also has a yellow box labeled 'EC capabilities'. To the left, a Road Side Unit (RSU) is shown with a yellow box labeled 'EC capabilities'. Dashed arrows indicate communication links between the RSU and both the vehicle and the UE. The label 'Y.4208(20)\_FI.4' is in the bottom right corner.
+
+**Figure I.4 – V2P scenario example**
+
+### I.2 Edge-computing scenarios for smart manufacturing
+
+For some control applications in smart manufacturing, the network transmission latency may need to be lower than 10 ms. On the other hand, the effective latency, based on practical measurements, may be higher than 100 ms in scenarios where the data needs to be transferred via a fourth generation cellular network to the cloud-hosted data centre accessed via the core network.
+
+EC is a method of optimizing data transmission latency for central cloud-computing deployments by processing data at the edge of the network, in proximity to the data source. In smart manufacturing, EC may be used in the following two ways:
+
+- Deploying EC at the gateway: heterogeneous industrial protocols, e.g., [b-Modbus], [b-PROFIBUS], object linking and embedding for process control unified architecture [b-OPC UA], cannot connect to the Internet directly. The gateway may deploy EC capabilities to provide functions such as industrial protocol conversion, data fusion and data cache to industrial terminal devices, and to provide industrial applications that may be deployed in the local cloud, as shown in Figure I.5.
+- Deploying EC at the edge platform: the edge platform integrates local network, computing and storage capabilities inside the factory, and can provide industrial applications in proximity to the users, as shown in Figure I.5. Because the edge platform is deployed close to the factory, real-time connectivity and increased integrity for data processing are achieved.
+
+
+
+Figure I.5 – Edge computing scenarios for smart manufacturing. This diagram shows the architecture of edge computing in a smart manufacturing context. On the left, four icons representing different industrial applications (Control application, Predictive maintenance, Product defect detection, and another generic application) are shown. These applications connect to a 'Gateway' (represented by a blue box with an antenna). The Gateway connects to an 'eNB' (evolved node base, represented by a blue tower icon). The eNB connects to an 'Edge platform' (represented by a blue cloud icon). The Edge platform connects to an 'EPC' (evolved packet core, represented by a blue box with a server icon), which then connects to the 'Internet' (represented by a blue cloud icon). The label 'Y.4208(20)\_FI.5' is in the bottom right corner.
+
+eNB: evolved node base; EPC: evolved packet core
+
+**Figure I.5 – Edge computing scenarios for smart manufacturing**
+
+# Bibliography
+
+- [b-ITU-T Y.101] Recommendation ITU-T Y.101 (2000), *Global Information Infrastructure terminology: Terms and definitions*.
+- [b-ITU-T Y.3105] Recommendation ITU-T Y.3105 (2018), *Requirements of capability exposure in the IMT-2020 networks*.
+- [b-ITU-T Y.4455] Recommendation ITU-T Y.4455 (2017), *Reference architecture for Internet of things network capability exposure*.
+- [b-IEEE 1609.0] IEEE 1609.0-2019, *IEEE Guide for wireless access in vehicular environments (WAVE) architecture*.
+- [b-IEEE 802.11p] IEEE 802.11p-2010, *IEEE Standard for information technology – Local and metropolitan area networks – Specific requirements – Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications – Amendment 6: Wireless access in vehicular environments*.
+- [b-ETSI] ETSI (2019), Multi-access Edge Computing (MEC); *Framework and Reference Architecture*.
+- [b-3GPP TS 22.185] 3GPP TS 22.185 V15.0.0 (2018), *3rd Generation Partnership Project; Technical specification group services and system aspects; Service requirements for V2X services; Stage 1 (Release 15)*.
+- [b-ECC] Edge Computing Consortium (Internet). *Edge Computing Consortium homepage*. Beijing: Edge Computing Consortium. Available [viewed 2020-03-20] at:
+- [b-ECC-architecture] ECC (2017), *Edge computing reference architecture 2.0*. Beijing: Edge Computing Consortium (ECC) and Internet Industry Alliance (IIA).
+- [b-EdgeX] EdgeXFoundry (2017). *The World's first plug and play ecosystem-enabled open platform for the IoT edge*. San Francisco, CA: Linux Foundation. Available [viewed 2020-03-20] at:
+- [b-ETSI TR 102 638] ETSI TR 102 638 V1.1.1 (2009), *Intelligent transport systems (ITS); Vehicular communications; Basic set of applications; Definitions*.
+- [b-IIC] Industrial Internet Consortium (2020), *Industrial Internet Consortium and OpenFog FAQ*. Needham, MA: Object Management Group. Available [viewed 2020-03-20] at:
+- [b-MEC] European Telecommunications Standards Institute (2020). *Multi-access edge computing (MEC)*. Sophia Antipolis: ETSI. Available [viewed 2020-03-20] at:
+- [b-Modbus] Modbus (2005-2020). *Modbus homepage*. Hopkinton, MA: Modbus. Available [viewed 2020-03-20] at:
+- [b-OECI] Open Edge Computing Initiative (2020). *Open Edge Computing initiative*. Pittsburgh, PA: Open Edge Computing Initiative. Available [viewed 2020-03-20] at:
+- [b-OPC UA] OPC Foundation (Internet). *Object linking and embedding for process control unified architecture (OPC UA)*. Scottsdale, AZ: OPC Foundation. Available [viewed 2020-03-20] at:
+
+- [b-OpenFog] OpenFog Consortium Architecture Working Group (2017), *OpenFog reference architecture for fog computing*. Fremont, CA: OpenFog Consortium. 162 pp. Available [viewed 2020-03-20] at:
+[https://www.iiconsortium.org/pdf/OpenFog\\_Reference\\_Architecture\\_2\\_09\\_17.pdf](https://www.iiconsortium.org/pdf/OpenFog_Reference_Architecture_2_09_17.pdf)
+- [b-PROFIBUS] PROFIBUS & PROFINET International (2020). *PROFIBUS technology and application – System description*. Karlsruhe: PROFIBUS Nutzerorganisation. Available [viewed 2020-03-20] at:
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+## Y.4211
+
+(12/2020)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Internet of things and smart cities and communities –
+Requirements and use cases
+
+# --- **Accessibility requirements for smart public transport services**
+
+Recommendation ITU-T Y.4211
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Network control architectures and protocols | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+| | |
+|-----------------|---------------|
+| CLOUD COMPUTING | Y.3500–Y.3599 |
+|-----------------|---------------|
+
+### BIG DATA
+
+| | |
+|-----------------------------------|---------------|
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800–Y.3999 |
+|-----------------------------------|---------------|
+
+## INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|----------------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+For further details, please refer to the list of ITU-T Recommendations.
+
+# Recommendation ITU-T Y.4211
+
+# Accessibility requirements for smart public transport services
+
+## Summary
+
+Recommendation ITU-T Y.4211 specifies accessibility requirements for smart public transport services. The concept of accessibility in public transport services has been mainly concerned with eliminating physical barriers such as adopting accessible trains and buses that allow wheelchair accessibility by mechanical lowering-entrance floors. In smart public transport services, the use of Internet of things (IoT), when properly designed, may increase accessibility of public transport services by providing access of information and physical accessibility. The IoT can be used to create tools for persons with many types of disability and specific needs, including physical, visual, hearing and cognitive disabilities. In order for the smart transport services to appropriately provide accessible services, information about accessibility profiles must be agreed upon in advance. Such accessibility profiles should basically include information on accessibility needs while travelling on public transport services.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.4211 | 2020-12-14 | 20 | 11.1002/1000/14577 |
+
+## Keywords
+
+Accessibility, inclusive design, persons with disabilities, persons with specific needs, smart cities and communities, smart public transport services, universal design.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2021
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|---|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------|
+| 1 | Scope ..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 2 |
+| 6 | Accessible smart public transport services ..... | 3 |
+| 7 | Accessibility requirements for smart public transport services..... | 4 |
+| | 7.1 Overview of accessibility requirements for accessible smart public
transport services ..... | 4 |
+| | 7.2 Two-layer structure of accessibility requirements ..... | 5 |
+| | 7.3 Accessibility requirements for the information layer ..... | 9 |
+| | 7.4 Accessibility requirements for the interface layer..... | 11 |
+| 8 | Accessibility profile requirements for smart public transport services ..... | 12 |
+| | 8.1 Accessibility profile requirements for the information layer ..... | 13 |
+| | 8.2 Accessibility profile requirements for the interface layer ..... | 13 |
+| | Appendix I – Functional areas of accessible public transport services..... | 14 |
+| | Appendix II – Use cases indicating the need for accessible smart public transport services
that benefit persons with disabilities and those with specific needs..... | 17 |
+| | II.1 Use case 1. Person with low vision travel by metro..... | 17 |
+| | II.2 Use case 2. Person with a physical disability riding on a bus ..... | 17 |
+| | II.3 Use case 3. Finding a way to the metro platform ..... | 18 |
+| | II.4 Use case 4. Paratransit service..... | 18 |
+| | II.5 Use case 5. Temporal bus timetable changes ..... | 19 |
+| | Bibliography..... | 20 |
+
+# **Introduction**
+
+Many persons with disabilities (PWDs) have difficulty in using public transport. Transportation issues also apply to persons with age-related disabilities and those with specific needs, which include temporary disabilities as well as literacy difficulties. If the use of public transport is challenging, PWDs and those with specific needs would be socially disconnected and their quality of life would, as a result, be degraded. Thus, mobility rights are an important issue for PWDs. The use of the Internet of things (IoT), when properly designed, may increase accessibility to smart public transport services by providing appropriate information. This information can be used by persons with many types of disability and those with specific needs. In order for smart transport services to appropriately provide accessible services, information on the type of disability profiles must be agreed upon in advance. Such accessibility profiles basically include information about the accessibility needs of PWDs while travelling on public transport services.
+
+# Recommendation ITU-T Y.4211
+
+## Accessibility requirements for smart public transport services
+
+# 1 Scope
+
+This Recommendation specifies accessibility requirements for smart public transport services.
+
+This Recommendation includes:
+
+- accessibility requirements for smart public transport services for persons with disabilities (PWDs), persons with age-related disabilities and those with specific needs to utilize the benefits of Internet of things (IoT) applications and services;
+- accessibility profile requirements for accessible smart public transport services.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T Y.4204] Recommendation ITU-T Y.4204 (2019), *Accessibility requirements for Internet of things applications and services*.
+
+# 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 accessibility** [b-ITU-T F.791]: The degree to which a product, device, service or environment (virtual or real) is available to as many people as possible.
+
+**3.1.2 accessibility feature** [b-ITU-T F.791]: An additional content component that is intended to assist people hindered in their ability to perceive an aspect of the main content.
+
+**3.1.3 assistive technology** [b-ITU-T F.791]: Piece of equipment, product system, hardware, software or service that is used to enable, maintain or improve functional capabilities of individuals with disabilities.
+
+**3.1.4 Internet of things (IoT)** [b-ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.
+
+NOTE 1 – Through the exploitation of identification, data capture, processing and communication capabilities, the IoT makes full use of things to offer services to all kinds of applications, whilst ensuring that security and privacy requirements are fulfilled.
+
+NOTE 2 – From a broader perspective, the IoT can be perceived as a vision with technological and societal implications.
+
+**3.1.5 person with age-related disabilities** [b-ITU-T F.791]: A person with cognitive or physical disabilities caused by the aging process. Examples are impaired eyesight, deafness in varying degrees, reduced mobility or cognitive abilities.
+
+**3.1.6 person with specific needs** [b-ITU-T F.791]: Includes persons with disabilities (PWDs), persons who are not literate, those with learning disabilities, children, indigenous people, older persons with age-related disabilities, and anyone who has a temporary disability.
+
+**3.1.7 platform accessibility feature** [b-ITU-T F.791]: Accessibility functionality provided as standard on a particular hardware or software platform.
+
+**3.1.8 profile setting** [b-ITU-T F.791]: The ability for users to store and retrieve multiple profiles containing sets of user interface preference settings without having to reset them each time, including accessibility settings.
+
+**3.1.9 specific needs [b-ITU-T F.791]**: This replaces the use of the term 'special needs'. This term refers to a wide range of categories including women, children, youth, indigenous people, older persons with age-related disabilities, persons with illiteracy, as well as persons with disabilities (PWDs), see [b-ITU PP Res.175], [b-WTDC Res.58], and [b-WTDC AP] and clause 6.39 (of [b-ITU-T F.791]).
+
+### **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following term:
+
+**3.2.1 universal design**: The design of products, environments, programmes and services to be usable by all people, to the greatest extent possible, without the need for adaptation or specialized design. "Universal design" shall not exclude assistive devices for particular groups of persons with disabilities where this is needed.
+
+NOTE – Paraphrased from [b-UNCRPD].
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|------|------------------------------------------|
+| AAC | Alternative Augmentative Communication |
+| AT | Assistive Technology |
+| GPS | Global Positioning System |
+| ICT | Information and Communication Technology |
+| IoT | Internet of Things |
+| IPTV | Internet Protocol Television |
+| PWD | Person with Disabilities |
+| UI | User Interface |
+
+# **5 Conventions**
+
+In this Recommendation:
+
+The expression "**is required to**" indicates a requirement that must be strictly followed and from which no deviation is permitted if conformance to this Recommendation is to be claimed.
+
+The expression "**is recommended**" indicates a requirement that is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+
+The expression "**can optionally**" and "**may**" indicates an optional requirement that is permissible, without implying any sense of being recommended. This term is not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with this Recommendation.
+
+The expression "**user**" indicates any public transport service customer who is using the service. The user can be any person with or without disabilities.
+
+# **6 Accessible smart public transport services**
+
+In the UN Convention on the Rights of Persons with Disabilities (UNCRPD), Article 20 on personal mobility states
+
+"to ensure personal mobility ... by facilitating access ... to quality mobility aids, devices ... including ... making them available at affordable cost; ... encouraging entities that produce mobility aids, devices and other assistive technologies to take into account all aspects of mobility for persons with disabilities." (p. 12 of [b-UNCRPD])
+
+Also, in Article 26, it further mentions that:
+
+"States Parties shall promote the availability, knowledge and use of assistive devices and technologies, designed for persons with disabilities ..." (p. 17 of [b-UNCRPD])
+
+Therefore, public transport service providers have been working on rectifying lack of accessibility in transportation. The concept of accessibility in transportation has been mainly concerned with eliminating physical barriers such as the adoption of accessible trains and buses that allows wheelchair access by mechanical lowering-entrance floors. Smart services for public transport that make usage of the IoT, when properly designed, may increase accessibility. This can be done by providing information that can be used by persons with various types of disabilities including physical, visual, hearing and cognitive impairments. For example, persons with visual disabilities may purchase a bus ticket by using their smartphone with accessibility features already set up. Persons with physical disabilities may use their computer to search the route and any accessibility information about the train services prior to leaving home. Persons with hearing disabilities could receive an alert message through their smartphones activated by the message as it is broadcast on the speakers of a train station. Such features not only increase the accessibility for PWDs, but also expand usability for everyone, including persons with and without disabilities.
+
+Smart services embedded into the existing public transport system would improve service quality radically. Such smart public transport services will include various passenger services. However, the level of sophistication of different services may vary. The most elementary service may be a simple presentation of information, such as timetables, stop locations and terminal information, route and fare information, and any notice of exceptional conditions. More sophisticated services may include automatic ticket purchasing, finding the best route, arrival and departure information and information on how crowded a vehicle is. There will be many other creative services under development for future introduction.
+
+As anticipated, IoT can be utilized in smart public transport services. IoT is defined in clause 3.1.4. IoT may be used to recognize the information and communicate it to passengers and service providers. It can also assist in the integration of communication, control and information processing across various transport systems.
+
+Each state has its own public transport service systems. A centralized service system might provide different public transport services such as bus, train, metro and tram. Others might have independent providers for each service. Moreover, a provider of smart services may differ from a transport service provider. Thus, in order for smart transport services to appropriately provide accessibility, information on a set of accessibility profiles must be agreed upon in advance, which basically includes information on accessibility while travelling through a public transport system, e.g., wheelchair accessible departures and arrivals at train stations and timetables of low-floor buses on specific routes.
+
+Even though the public transport ecosystem may involve various players, passengers do not need to know whether systems are integrated. A smart public transport system seeks to create seamless services no matter how the underlying operational systems are organized. To achieve this goal, a vast
+
+amount of information must be exchanged among public transport service providers. From the accessibility standpoint, such information includes passenger accessibility needs and preferences, and the service provider's list of accessible services including detailed information. When enough information is obtained, smart public transport services can provide the most convenient means of travel while taking into account user needs and capabilities.
+
+There are significant barriers to the use of public transport by some PWDs. Some of the most salient problems of the public transport services for PWDs include safety, frequency and reliability of services, connectivity and transfer between the departure location and other bus stops and train stations in the absence of direct services.
+
+Information that needs to be provided prior to travel for PWDs mostly concerns access to specific services. This includes the provision and location of lifts at metro stations, the availability of clear signage for persons with vision impairment, the use of audible announcements for persons with hearing disabilities, the availability of amenities including accessible toilets and the capacity to access bus or train stations.
+
+An environment ensuring appropriate pedestrian access to public transport services is also important. Thus, it is essential that walkways offer a direct and safe route to public transport and are free of obstacles that hinder access for PWDs. [b-ITU-T F.921] addresses these aspects with applicable audiovisual guidelines for designing and operating such pathways for persons with impaired vision.
+
+Note that not all such barriers can be removed with the aid of IoT services. However, an IoT can provide efficient and economical means to remove at least some of the significant barriers.
+
+Appendix II presents use cases indicating the needs for smart public transportation systems that benefit PWDs. The use cases serve the role of identifying accessibility requirements for smart public transport services. Clause 7 identifies accessibility requirements for smart public transport services. Clause 8 presents the accessibility profile requirements for smart public transport services.
+
+# **7 Accessibility requirements for smart public transport services**
+
+This clause addresses accessibility requirements specific to smart public transport services. Accessibility requirements listed here are based on general IoT accessibility requirements as identified by [ITU-T Y.4204] and are categorized by functional areas of public transport services.
+
+## **7.1 Overview of accessibility requirements for accessible smart public transport services**
+
+Concerning smart public transport services, which may provide personalized services to address each user's needs, the information that can be beneficial to PWDs and those with specific needs also needs to consider the content of the information in addition to the accessible interface. In this regard, the general accessibility requirements for IoT identified in [ITU-T Y.4204] are the basis for the requirements identified in this Recommendation. In the context of smart public transport services, those requirements can be classified into two groups, which concern the content of information and how the information interfaces with users. Therefore, a two-layer structure of the requirements for accessible smart public transportation is suggested.
+
+[ITU-T Y.4204] provides general requirements for accessible IoT applications and services. Smart public transport services that incorporate IoT technology are bounded by the general accessibility requirements for IoT as stated in [ITU-T Y.4204]. Figure 1 summarizes [ITU-T Y.4204].
+
+
+
+| | | |
+|---------------------|--------------------------------------------------------------------------------------------------|------------------------------------------------------------------|
+| Category I | Ability to perceive all the information and capabilities of an IoT application or service | |
+| | Alternative representation of information | Accurate and timely delivery of accessibility features |
+| | Consistency between multiple user interfaces | |
+| Category II | Ability to understand the information presented by an IoT application or service | |
+| | Malfunction and recovery guidance | Temporary disabilities |
+| Category III | Ability to perform the required operations of an IoT application or service | |
+| | User accessibility profile and service status recovery | Installation and initialization of IoT service and/or IoT device |
+| Category IV | Ability to use suitable assistive technology with an IoT application or service | |
+| | Compatibility with existing assistive technology | |
+| Category V | Ability to satisfy user's specific needs | |
+| | Notification of malfunction and safety hazards | Disaster preparedness |
+| | Disaster relief | |
+
+Y.4211(20)\_F01
+
+**Figure 1 – Summary of IoT applications and services accessibility requirements
+(Source – [ITU-T Y.4204])**
+
+Categories I and IV of [ITU-T Y.4204] mainly focus on communicating information through a user interface (UI). Category I is about the ability to perceive information to communicate with IoT application. Ability to perceive information mainly focuses on operation and communication through UI. Therefore, Category I mainly focuses on requirements of accessible UI. Moreover, Category IV is about the compatibility with assistive technology (AT), which is also a type of UI dedicated to PWDs and those with specific needs.
+
+However, just communicating the information perceivable and understandable to PWDs is not enough. The content of the information should consider a user's capabilities. Categories II and V of [ITU-T Y.4204] concern how the information should be prepared so that users can clearly understand the information. Requirements from those categories mainly focus on accessible information that should be understandable regardless of disability.
+
+In addition, Category III of [ITU-T Y.4204] concerns both an accessible UI and accessible information. Use of a user profile and installation process for first time use of IoT devices must be accessible so that the UI is easily accessible, and, at the same time, information provided should be understandable.
+
+To make smart public transport services accessible in accordance with [ITU-T Y.4204], all information presented to a user should be accessible. Meaning that the information should be presented in an audio and visual format, supporting sign language, braille, text-to-speech, and so on. Moreover, the information should also be prepared considering the user's specific requirements. For example, a pathway for a user using a wheelchair to a platform in an metro station may not be the same as that for one who can walk.
+
+## **7.2 Two-layer structure of accessibility requirements**
+
+In this Recommendation, a two-layer structure is recommended for accessibility requirements that fulfil each user's specific demands for accessibility. Figure 2 illustrates the two-layer structure of accessibility requirements.
+
+
+
+**Various user needs**
+
+One arm Arm injured New parent Blind Deaf
+
+**Providing customized information according to accessibility requirements**
+
+**Interface layer**
+
+**Communicating information considering user's accessibility needs**
+
+- Considering user's physical, audio, visual capabilities
+- Compatible with user's assistive technology
+
+**Information layer**
+
+**Context of information should consider a user's capabilities**
+
+- Prepare information considering user's physical, audio, visual, linguistic and cognitive abilities
+
+Y.4211(20)\_F02
+
+Diagram illustrating the two-layer structure of accessibility requirements. At the top, 'Various user needs' are shown with icons for 'One arm', 'Arm injured', 'New parent', 'Blind', and 'Deaf'. A green arrow points down to a central box: 'Providing customized information according to accessibility requirements'. Below this are two layers: 'Interface layer' (communicating information considering user's accessibility needs) and 'Information layer' (context of information should consider a user's capabilities).
+
+**Figure 2 – The two-layer structure of accessibility requirements**
+
+To provide customized information using user accessibility requirements to fulfil various user needs, a two-layer approach is recommended. The first layer is the information layer, which prepares information concerning the user's physical, audio, visual, linguistic and cognitive abilities. Then the information prepared is manipulated in the interface layer, taking into account the user's physical, audio and visual capabilities, and considering compatibility with any AT used by the user. One benefit of using this two-layer approach is that, in many cases, information is prepared by the service provider or in a dedicated server and presented using a UI. One distinguishing characteristic of IoT is that various UIs can be used at the same time.
+
+Figure 3 summarizes the concept of information layer.
+
+
+
+The diagram illustrates the structure of the Information layer. At the top is a blue bar labeled "Information layer". Below it is a large white box with a blue border. Inside this box, on the left, is a blue box labeled "Customized information". To its right is a white box containing the text: "The context of the information should consider a user's abilities, capabilities and preferences." followed by a bullet point: "• Information with same purpose may have different content" and two examples: "E.g., Person who can walk: Shortest path to destination" and "Person who uses wheelchair: Wheelchair accessible pathway". Below this are three rounded rectangular boxes labeled "TYPE I: Common information", "TYPE II: Selective information", and "TYPE III: Targeted information". Each box contains specific details about that type of information.
+
+**Information layer**
+
+**Customized information**
+
+The context of the information should consider a user's abilities, capabilities and preferences.
+
+- Information with same purpose may have different content
+
+E.g., Person who can walk: Shortest path to destination
+Person who uses wheelchair: Wheelchair accessible pathway
+
+**TYPE I: Common information**
+
+**The same information is supplied to ALL users.**
+
+Content of information is the same. Only presentation may vary according to user's needs.
+
+Such presentation is decided according to interface layer.
+
+**TYPE II: Selective information**
+
+**Not all users require to know this information.**
+
+Some users may receive accessibility information considering user's abilities (i.e., physical, audio, visual, linguistic and cognitive abilities), capabilities and preferences.
+
+**TYPE III: Targeted information**
+
+**Information is for everyone, but different users receive different content.**
+
+A user's abilities (i.e., physical, audio, visual, linguistic and cognitive abilities) must be considered while preparing the information.
+
+Y.4211(20)\_F03
+
+Diagram of the Information layer structure showing customized information and three types of information: Common, Selective, and Targeted.
+
+**Figure 3 – Information layer**
+
+Accessible information required for PWDs can be categorized into three types, as follows.
+
+The first type is common information (type I). The same information is supplied to all users. For PWDs and those with specific needs, only the presentation of the information needs to be accessible, but the content itself is common to everyone. This common information includes fixed and floating information. The common information may be announced to the public ahead of time, and does not change over a certain period of time. Therefore, many routine users are well informed. Examples of this type of information are location of a bus stop, a timetable, and a regularly scheduled vehicle route. This type of information is announced or posted to all users. It does not require any customization of content. The information is prepared and supplied to users in advance possibly through a pre-recorded announcement, printed material or a signboard. Floating information can be a specific announcement for special or abnormal events, such as an emergency or an accident. Such information cannot be prepared ahead of time. Also, it is critical to deliver prompt information to affected users. However, this information is also announced to all users, and does not require any customization of its content. Note that this information only concerns alert messages to users, not specific information on a course of action following an alert. A specific course of action in response to certain events may vary according to a user's capabilities, and thus, such information can be classified as selective information, which is explained in next paragraph.
+
+Another type is selective information (type II). The accessibility information specific to PWDs and those with specific needs falls into this category. Not all users are required to know this information, and various users will receive different information according to their needs (including user-specific needs). For example, not everyone using public transport needs to know how to access assistance services for PWDs. However, those with disabilities who require such services for their journey need to know about service availability. Therefore, such information must be selectively supplied to users who need such information. A user's physical, audio, visual, linguistic and cognitive abilities must be considered when preparing the information.
+
+The final type is targeted information (type III). Examples of such information are a route to a station or a stop and a route to a destination from the user's current location. This type of targeted information is for everyone, but various users will receive different content as needed. For example, there could be more than one access path to a particular station. The information is prepared according to each
+
+user's requirements. A user's physical, audio, visual, linguistic and cognitive abilities must be considered when preparing the information.
+
+In this Recommendation, accessibility requirements for smart public transport services are identified according to their functional areas.
+
+NOTE – For details of the identified functional areas of public transport, see Appendix I.
+
+In Table 1, accessible information needed for PWDs and those with specific needs for each functional area are listed according to the type of information discussed in the preceding paragraphs.
+
+**Table 1 – Type of accessible information identified for each functional area**
+
+| Functional area | Accessible information needed for persons with disabilities | Type of information |
+|------------------------------------|--------------------------------------------------------------------|----------------------------|
+| Access to information and services | Access to customer services | I |
+| | Service change notice | I |
+| | Access to assistance services | II |
+| | Toilet information | I |
+| | Information to other service facilities | I |
+| Journey planning | Route to destination | III |
+| | Transit timetable | I |
+| | Transfer information | III |
+| | Station/stop location | I |
+| Travel to point of boarding | Footpath to station or stop | III |
+| | Wheelchair accessible path to station or stop | II |
+| Finding the correct service | Route within the station | III |
+| | Finding a platform or stop | III |
+| | Transfer information | III |
+| | Wheelchair accessibility | II |
+| | Lift availability | II |
+| Purchasing ticket(s) | Ticket purchasing and validating information | I |
+| | Ticket office location | I |
+| | Vending machine (kiosk) usage information | III |
+| | Mobile ticket usage information | I |
+| Boarding | Gap or step to vehicle | I |
+| | Getting assistance from the driver | II |
+| | Baggage checking | I |
+| | Crowdedness of vehicle | III |
+| In transit | Finding (assigned) seats | III |
+| | Finding priority seats | II |
+| | Access to audiovisual information (including signage) | II |
+| Alighting | Notifying driver of alighting (bell) | I |
+| | Upcoming stop information | I |
+| | Claim checked baggage | I |
+
+Regardless of the type of information identified in the information layer, the information prepared may be presented through various UIs of the user's choice and availability. When communicating the
+
+information with users, user preferences (i.e., whether the user prefers text, audio, sign language, braille, caption, etc.) should be considered. Then, the information is manipulated and presented through the UI according to user preferences or capabilities. The communication method should also be chosen by users. Figure 4 summarizes the interface layer.
+
+
+
+The diagram illustrates the 'Interface layer' process. It begins with 'Information prepared in information layer' (represented by an 'i' icon) entering a box labeled 'Considering user's needs'. Inside this box, four interlocking gears represent different user capabilities: 'Cognitive' (red gear with a brain icon), 'Vision' (green gear with an eye icon), 'Hearing' (blue gear with an ear icon), and 'Motor skills' (yellow gear with a hand icon). An arrow from the 'Cognitive' gear points to a grid of icons representing various communication methods: a hearing aid, a person with a white cane, a person in a wheelchair, a person using a sign language interpreter, a person using a computer, and a question mark. The grid is labeled 'Selecting means of communication according to user's needs'. Above the grid, a text box states: 'Means of communication can vary according to user's needs' with two bullet points: '• Information is exchanged between the service and users using various formats including use of text, audio, sign language, braille, caption, etc.' and '• Existing standards for accessible user interfaces should be considered (if any)'. A label 'Information exchange with users' is also present in the top left corner of the interface layer box.
+
+Diagram of the Interface layer showing the flow from information preparation to user selection of communication means.
+
+Y.4211(20)\_F04
+
+**Figure 4 – Interface layer**
+
+### 7.3 Accessibility requirements for the information layer
+
+In this clause, accessibility requirements for each type of information are presented.
+
+#### 7.3.1 Accessibility requirements applicable to all information types (I, II and III)
+
+All types of information need to satisfy following accessibility requirements:
+
+- 1) an expression that describes the same information is required to be consistent throughout the service;
+- 2) an expression that describes the same information is required to remain semantically the same when translated into another language (including sign language);
+- 3) provision of a means to control the level of exposure of the user's own sensitive information is required;
+- 4) the content of information is recommended not to depend on specific senses (e.g., colour, sound and flicker) – however, if the content cannot avoid relying on a specific sense (e.g., a red-light image), provision of alternatives (e.g., a word "stop" in text format) is required.
+
+#### 7.3.2 Accessibility requirements for common information (type I)
+
+Common information (type I) needs to satisfy following accessibility requirements:
+
+- 1) provision without the assumption that the user has any prior knowledge or memory that is needed to understand it;
+
+- 2) standard conventions, words and symbols used in any information are readily comprehensible;
+- 3) provision is recommended with minimized interference with the user's social, cultural and geographical background;
+- 4) provision is recommended using non-linguistic methods – where possible – to make it easier for users who do not understand language adequately.
+- 5) where appropriate, provision in multiple steps with details addressing all steps, along with any sequential repetition at all steps.
+
+#### **7.3.3 Accessibility requirements for selective information (type II)**
+
+Selective information (type II) needs to satisfy following accessibility requirements:
+
+- 1) identification of the user who is a recipient of selective information according to the user accessibility profile that is entered in advance;
+- 2) clear information to the user when selective information is not available to the user whose accessibility needs are indicated in the accessibility profile;
+- 3) on request of a user, provision is recommended of selective information on the following accessibility features:
+ - languages supported by the service (including sign language),
+ - wheelchair access support,
+ - support for accompanying service animals,
+ - availability of accessible facilities (e.g., toilets),
+ - availability and types of priority services for PWDs,
+ - availability of accessible vehicles (e.g., low floor or wheelchair lift-equipped bus),
+ - availability and location of priority seats on vehicles,
+ - fare reduction for PWDs,
+ - availability of parental or guardian notifications,
+ - availability of human assistance support (e.g., from bus driver or service personnel),
+ - novice user assistance.
+
+#### **7.3.4 Accessibility requirements for targeted information (type III)**
+
+Targeted information type (type III) needs to satisfy following accessibility requirements:
+
+- 1) on receipt, notification of the user that the information is provided according to the user's accessibility profile;
+- 2) for users who are unable to understand the information provided in the default format, optional provision of the information in alternative layouts, as appropriate;
+- 3) for location-based services, optional incorporation of the following information:
+ - braille blocks linked with the information,
+ - pedestrian risk factors, such as ramps, road width and obstacles, like stairs, walls and bollards,
+ - wheelchair accessibility,
+ - presence of any devices requiring operation on the move (e.g., door open push buttons);
+- 4) for users who require full learning experience prior to usage of a specific service (due to developmental or cognitive disabilities or other reasons), optional provision of the following information:
+
+- ability to store previous trip information (e.g., footpath, station or stop, route or transfer information),
+ - assignment of priority to known routes when planning a new trip,
+ - warning to user, parent or guardian when the user is off a known route;
+- 5) on user request, optional provision of the following medical-related information:
+- first aid kit availability,
+ - automated external defibrillator availability,
+ - location of medical office.
+
+## **7.4 Accessibility requirements for the interface layer**
+
+Smart public transport services need to satisfy the following interface accessibility requirements.
+
+- 1) Provision of appropriate presentation alternatives ensuring semantically equivalent visual or auditory information. In addition, two or more alternative means are recommended to provide for multiple disabilities.
+- 2) Ability to provide information that can be expressed via appropriate alternative means (e.g., speech to text or image to voice) according to the accessibility profile set by the user in advance.
+- 3) Provision of appropriate accessibility features for visual and auditory information according to the accessibility profile set by the user in advance.
+
+Examples of accessibility features that visual information may provide are:
+
+- appropriate brightness;
+- colour change function, such as inversion and highlight;
+- zoom function;
+- glare avoidance;
+- clear distinction between background and foreground;
+- support for simultaneous operation of text and voice.
+
+Examples of accessibility features that auditory information may provide are as follows:
+
+- adequate volume;
+ - appropriate quality audio;
+ - control of audio properties, such as pitch, balance, volume and tone.
+- 4) When the UI supports accessibility features (e.g., screen reading capabilities or screen-magnifying functionality), the service is required to be compatible with them.
+ - 5) According to the accessibility profile set by the user in advance, the following presentation features are recommended to be adjustable:
+ - font size;
+ - colour of icons, buttons, etc;
+ - magnifying features;
+ - size of actionable elements;
+ - location and layout of controls.
+ - 6) Depending on the user profile, one of the following methods of feedback to the user in response to input is recommended to be selected and provided:
+ - audio;
+ - visual;
+
+- tactile.
+- 7) Depending on the user's choice, utilization is recommended of a user input method without using one or more of the following functionalities:
+ - touch or very light touch;
+ - speech;
+ - simultaneous actions;
+ - pushing with high force or continuous high force;
+ - pinching;
+ - direct body contact;
+ - manipulation.
+- 8) When using biometric information for user identification, provision of appropriate alternative means is required according to the user profile.
+- 9) Compatibility of services with known assistive technologies is recommended.
+- 10) If online services are not available due to lack of service coverage, the following essential features are required to be available even in offline mode:
+ - latest timetable for the route the user is on;
+ - location of the stop for alighting;
+ - upcoming stop information;
+ - connection information.
+- 11) Depending on the user profile, the interface can optionally be configured with one of the following language support features:
+ - default language;
+ - one of the other supporting languages, including sign language (if any);
+ - interface using non-linguistic expression (if any).
+- 12) Depending on the user profile, only the previously learned or used transportation method can optionally be provided.
+
+# **8 Accessibility profile requirements for smart public transport services**
+
+In this clause, accessibility profiles for smart public transport services are addressed. As an example, in Internet protocol television (IPTV), the service supports the ability to save and retrieve multiple profiles that contain a set of UI preferences and language settings, as it provides users with the ability to easily switch to different personal preferences without having to reset each time. User profiles are used as a tool for personalization. In [b-ITU-T H.702], the profile includes accessibility features such as captions, sign language and audio description settings.
+
+Similarly, in a smart public transport service, an accessibility profile is a set of capabilities for accessibility to be implemented. This profile can be used in communications among different transport service providers within the same geographical locations, or between the information and communication technology (ICT) service providers and transport service providers. Figure 5 illustrates the use of an accessibility profile in smart public transport services.
+
+
+
+User interface could be a mobile device, personal computer, etc.
+
+Public transport could be a bus, train, underground, tram, etc.
+
+Y.4211(20)\_F05
+
+Diagram illustrating the use of an accessibility profile in smart public transport services. It shows a flow from User interfaces (containing Accessibility features) to Application service providers (containing Accessibility profiles), which then connect to various Public transport service providers (A, B, X, each containing an Accessibility service). Dashed arrows indicate the flow of information. Vertical ellipses indicate multiple instances of each component. A note at the bottom left states: 'User interface could be a mobile device, personal computer, etc.' and a note at the bottom right states: 'Public transport could be a bus, train, underground, tram, etc.' with the identifier 'Y.4211(20)\_F05'.
+
+**Figure 5 – The use of accessibility profile in smart public transport services**
+
+In order for smart transport to appropriately provide accessible services, user accessibility profiles must be known to service providers in advance. Such accessibility profiles basically include information on accessibility needs of PWDs while travelling on public transport services. Clauses 8.1 and 8.2 specify accessibility profile requirements for the information layer and the interface layer.
+
+## 8.1 Accessibility profile requirements for the information layer
+
+To support information requirements for smart public transport services, as identified in clause 7, the accessibility profile is required to identify the following user accessibility information:
+
+- preferred language;
+- use of walking aids (e.g., assistive canes, crutches, walkers);
+- use of wheelchair;
+- use of alternative augmentative communication (AAC);
+- physical abilities related to mobility;
+- communication abilities;
+- health information (e.g., allergy, chronic disease).
+
+## 8.2 Accessibility profile requirements for the interface layer
+
+To support interface requirements for smart public transport services, as identified in clause 7, the accessibility profile is required to identify the following user information:
+
+- ability to use camera on a personal communication device;
+- preferences to AAC;
+- degree of sensory utilization (e.g., sight, hearing, touch);
+- mental functions (e.g., attention function, thought function, calculation function):
+- communication ability (to understand, for example, sign language, verbal communication, how to send and receive text messages);
+- ability to utilize complex gestures to control touchscreen-based devices.
+
+# Appendix I
+
+## Functional areas of accessible public transport services
+
+(This appendix does not form an integral part of this Recommendation.)
+
+Several studies have identified accessibility barriers to public transportation for PWDs, including older persons with age-related disabilities and those with specific needs. An early study [b-Griffin] pointed out that entrances must be fully accessible and provide convenient access for passengers.
+
+PWDs, including older persons with age-related disabilities, find standing for any length of time uncomfortable or even impossible, so providing seating at appropriate points throughout the terminal is very important. [b-Sawyer] stressed that the provision of accessible toilet facilities in the building is important. In 2010, Malhotra (as cited in [b-Soltani]) conducted a study in accessible public transport, and suggested that highlighted priority seats for PWDs in the vehicle should be close to both the driver and to the entrance or exit of vehicles to ease communication with the driver and minimize the distance to be walked in the bus.
+
+[b-Soltani] identified several areas that are the most problematic travel components. This includes walking to and from the terminal, buying tickets, finding the correct service, and boarding and alighting the vehicle. The authors also reported that there is a lack of standardization of accessibility for the provision of public transport information, including signage and audible announcements both in the terminal and the vehicle.
+
+[b-Haning] also studied accessibility for PWDs in transportation through a survey. Many respondents provided suggestions to assist in increasing transport accessibility for PWDs. The most common responses were related to the pedestrian environment. With respect to public transport, the following common suggestions were identified:
+
+- more carriages on trains to prevent overcrowding and to ensure more seats designated and reserved for PWDs;
+- more frequent accessible buses;
+- improved alignment of the vehicle step height with the curb or platform.
+
+[b-Bezyak] also reported a number of public transport barriers. Further analysis uncovered significant differences in the experience of barriers in public transport according to the type of disability. The list of barriers reported includes drivers not calling out stops, no accessible route to a stop or station, driver's lack of knowledge, inability to navigate the public system, inaccessible stop or station, gap or step to vehicle and problems with lifts.
+
+[b-Mashiri] scans the existing practices in both developed and developing countries relating to the provision of public transport information to PWDs. The contribution also provides an overview of the range of issues including technology features and the general environment that need to be taken into account in designing inclusive, robust, easily accessible and practical public transport information packages to facilitate ever-increasing and stress-free travel not only for PWDs, but for all passengers.
+
+Pp. 151-154 of [b-NCD] also reported that policies should be implemented that support the availability of accessible transport modes, such as taxis, buses and trains.
+
+Figure I.1 shows the journey cycle for PWDs and those with specific needs. According to Lafratta (as cited in [b-Soltani]), it is important to consider the journey cycle for a better understanding of the experience of the whole journey for PWDs. It also helps to know the problems faced by a person with disabilities and those with specific needs.
+
+
+
+```
+
+graph TD
+ A[A. Journey planning] --> B[B. Travel to transport station/stop]
+ B --> C[C. Arriving at station/stop]
+ C --> D[D. Buying ticket(s)]
+ D --> E[E. Finding the correct service]
+ E --> F[F. Boarding the chosen mode of transport]
+ F --> G[G. Getting to desired destination]
+ G --> H[H. Alighting from transport mode]
+ H --> A
+
+```
+
+Y.4211(20)\_Fl.1
+
+A circular flow diagram showing the eight steps of a journey cycle: A. Journey planning, B. Travel to transport station/stop, C. Arriving at station/stop, D. Buying ticket(s), E. Finding the correct service, F. Boarding the chosen mode of transport, G. Getting to desired destination, and H. Alighting from transport mode. The steps are connected in a clockwise cycle with arrows.
+
+**Figure I.1 – The journey cycle (source – Lafratta (as cited in [b-Soltani]))**
+
+Based on the assessment of the existing studies cited previously, functional areas of public transport service and information that may be provided to enhance accessibility are identified and illustrated in Table I.1.
+
+**Table I.1 – Functional areas and accessible information needed for persons with disabilities for public transport services**
+
+| Functional area | Accessible information needed for persons with disabilities |
+|------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Access to information and services | Access to customer services
Service change notice (alert, detour, schedule change (delay), emergency, hazards, etc.)
Access to assistance services
Toilet information
Information to other service facilities |
+| Journey planning | Route to destination
Transit timetable
Transfer information
Station or stop location |
+| Travel to point of boarding | Footpath to station or stop
Wheelchair accessible path to station or stop |
+| Finding the correct service | Route within the station
Finding a platform/stop
Transfer information
Wheelchair accessibility
Lift availability |
+
+**Table I.1 – Functional areas and accessible information needed for persons with disabilities for public transport services**
+
+| Functional area | Accessible information needed for persons with disabilities |
+|------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Purchasing ticket(s) | Ticket purchasing and validating information
Ticket office location
Vending machine (kiosk) usage information
Mobile ticket usage information |
+| Boarding | Gap or step to vehicle
Getting assistance from the driver
Baggage checking
Crowdedness of vehicle |
+| In transit | Finding (assigned) seats
Finding priority seats
Access to audio/visual information (including signage) |
+| Alighting | Notifying driver of alighting (bell)
Upcoming stop information
Claim checked baggage |
+
+Smart public transport services may provide at least some of the information listed in Table I.1 to improve accessibility. Much of the information listed in Table I.1 is straightforward, but items are often not explicitly provided. However, many PWDs find it difficult to obtain such information. Lack of such information may be considered a barrier to the use of public transport services.
+
+NOTE – The accessible information items listed in Table I.1 cover only the principal elements. Many other services may be provided using IoT applications (i.e., more intelligent services using artificial intelligence technology, etc.).
+
+## Appendix II
+
+## **Use cases indicating the need for accessible smart public transport services that benefit persons with disabilities and those with specific needs**
+
+(This appendix does not form an integral part of this Recommendation.)
+
+In this appendix, some accessible smart public transport services use cases that benefit PWDs are presented as examples. Use cases are presented to explain the needs for accessibility when developing smart public transport services.
+
+### **II.1 Use case 1. Person with low vision travel by metro**
+
+Mr Kim, who has low-vision, and works for an information technology company, needs to move to a business meeting in a location he had never been before. He decides to use the metro as the destination is close to a station. Although he knows exactly where he can find the assistive personnel at the station from where he departs, he is not sure about their location in the destination station. He is even not sure if the assistive personnel are available there or how to access such services in detail.
+
+He uses a smartphone application that the metro service has provided. He has been using the application for a long time, and he has updated his accessibility needs to the application. He just enters his travel details including the destination station into the app.
+
+Immediately, the application answers with the information that the assistive personnel service is available. He is told that his request for assistance has been received. When the metro train approaches the destination station, the mobile phone transmits a global positioning system (GPS) signal to the service personnel information indicating the exact location of the metro train he is on. Although not all stations have assistive personnel, it is possible to successfully deliver services by moving assistants from one station to another.
+
+When he arrives at the station, a member of the assistive personnel is already there to assist him.
+
+### **II.2 Use case 2. Person with a physical disability riding on a bus**
+
+See Figure II.1.
+
+Mr A has a physical disability. Every morning, he rides on a bus to get to work. At home, he selects the departing and arrival bus stop, and the bus that he wants to ride. He uses his smartphone and makes a reservation. During the booking process, the smart public transport service acknowledges Mr A's specific requests and knows his needs using previously entered profile.
+
+When Mr A arrives at the bus stop, his smartphone and the wireless communication terminal installed at the bus stop communicate with each other to confirm his arrival. The smart public transport service informs Mr A about the anticipated arrival time of the bus he wants to board through his smartphone. At the same time, the driver on the bus that Mr A will be boarding is informed of Mr A's reservation and his specific needs, so that the driver, can give Mr A proper assistance to board the bus.
+
+When Mr A gets on the bus, the smart public transport service notifies the accessibility services of his boarding. When the bus is approaching Mr A's destination, the smart public transport service notifies Mr A with exit guidance information. At the same time, the bus driver is also informed that Mr A will get off the bus at a specific stop, so that Mr A can receive necessary assistance and the smart public transport service is also informed of the stop to greet Mr A.
+
+
+
+When a user arrives, reservation information is sent to the bus.
+
+Collect reservation information
+
+Bus stop equipped with smart service
+
+Cloud service platform
+
+Bus equipped with smart service
+
+Reservation device
+
+Sensor receiver
+
+External speaker
+
+User can make reservation, and receive notification
+
+A bus number XX is arriving in 3 minutes.
+
+User can make reservation through communicating with the sensor receiver and the smart phone.
+
+Wireless communication terminal
+
+Wireless communication terminal
+
+Alarm device
+
+A person with a wheelchair will embark at next station
+
+Information display
+
+External speaker
+
+Notify destination stop
+
+Confirm boarding request
+
+Y.4211(20)\_Fil.1
+
+Figure II.1: Service scenario of the bus trip assistance service for persons with disabilities. The diagram illustrates a system where a user's smartphone (Reservation device) communicates with a bus stop (Bus stop equipped with smart service) via a cloud service platform. The bus stop has a wireless communication terminal. The bus (Bus equipped with smart service) also has a wireless communication terminal. The user can make a reservation and receive a notification (e.g., 'A bus number XX is arriving in 3 minutes.') through the sensor receiver and external speaker of the reservation device. The bus stop can notify the destination stop and confirm the boarding request. The bus can also notify the destination stop and confirm the boarding request. The bus stop has an alarm device with an information display and an external speaker. The bus stop can notify the destination stop and confirm the boarding request. The bus can also notify the destination stop and confirm the boarding request.
+
+**Figure II.1 – Service scenario of the bus trip assistance service for persons with disabilities**
+
+### II.3 Use case 3. Finding a way to the metro platform
+
+Ms. Jay, a person who uses motorized wheelchairs, must use lifts instead of stairs or escalators to move within a metro station, and must also use a ticket barrier that is wheelchair accessible.
+
+The city where Ms. Jay lives provides a smart service including an interactive map of metro stations. The smart service has an application that guides the user through the most convenient route to the boarding platform from the user's current location. The users can use the service through a mobile application that is capable of tracking the user's location.
+
+Ms. Jay would like to avoid stairs and ticket barriers that are not wheelchair accessible on her way to the boarding platform. So, Ms. Jay sets her accessibility preferences in her smartphone application in advance. The application provides the most convenient routes accommodating her accessibility needs. This is done by downloading details of and analysing the station's available accessibility services to her smartphone.
+
+Note that to maintain the confidentiality of sensitive personal information, personal accessibility preferences must be stored and used in the user's personal UIs (in this case, a smartphone). Even in an environment where multiple UIs are available, transferring a user's accessibility preferences from one interface to another must be handled strictly at the user's discretion. Clear instructions and information about how the user's accessibility preferences are handled must be provided.
+
+### II.4 Use case 4. Paratransit service
+
+Many municipalities provide complementary paratransit service for PWDs. A paratransit service is provided as a supplement to fixed-route bus and rail systems. Those with disabilities who for diverse reasons cannot use public transport services may alternatively choose to use a paratransit service.
+
+However, even with a specifically designed service to satisfy PWDs, there are still some barriers such as difficulties in scheduling reservations, excessive waiting times for vehicles to arrive, late arrivals, no show and lengthy travel times. Individuals with disabilities who rely on paratransit services typically have to schedule and plan their activities well in advance to receive transport services.
+
+Not all barriers to (complementary) paratransit services can be resolved with the introduction of smart services geared to IoT technology. However, many issues can be resolved when utilizing location
+
+services (e.g., GPS tracking of the driver or customer) in real-time and interactive notification of information services, etc.
+
+### **II.5 Use case 5. Temporal bus timetable changes**
+
+Ms. Kay, who has visual impairment, routinely takes a bus to work at a bus stop in front of her home. The bus runs according to a predetermined schedule, and Ms. Kay leaves home every day according to the timetable.
+
+One day, road construction begins on one of Ms. Kay's bus routes, and the buses temporarily operate on a different route from usual. The bus company decides to change the bus timetable to reflect delays due to the detour. Notice of the schedule change is posted at the bus stop. Because of her visual impairment, Ms. Kay is unaware of the changed bus timetable as notification was provided in a printed paper format.
+
+Bus companies can increase reliability and predictability of their service by directly informing users of changes in public transport services using push notification services in a smartphone application. More sophisticatedly, the company may provide real-time tracking of the vehicle on the road and its expected time schedule using real-time information collection and traffic prediction technology.
+
+Smart services using a smartphone application and real-time vehicle tracking technology (e.g., GPS transmitter) can provide users with more accurate information in timely manner. Also, PWDs may benefit from services that provide accessibility functionalities, such as screen-reading tools, vibration notification and automatic captioning functionality. Without much effort, digitally formatted information can be transformed into different formats (e.g., text-to-audio and vice-versa) compared to its traditional counterparts (e.g., printed paper format and audio announcements).
+
+# Bibliography
+
+- [b-ITU-T F.790] Recommendation ITU-T F.790 (2007), *Telecommunications accessibility guidelines for older persons and persons with disabilities*.
+- [b-ITU-T F.791] Recommendation ITU-T F.791 (2018), *Accessibility terms and definitions*.
+- [b-ITU-T F.921] Recommendation ITU-T F.921 (2018), *Audio-based indoor and outdoor network navigation system for persons with vision impairment*.
+- [b-ITU-T H.702] Recommendation ITU-T H.702 (2020), *Accessibility profiles for IPTV systems*.
+- [b-ITU-T Y.4000] Recommendation ITU-T Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+- [b-ITU PP Res.175] ITU Plenipotentiary Conference Resolution 175 (Busan, 2014), *Telecommunication/information and communication technology accessibility for persons with disabilities and persons with specific needs*. Available [viewed 2021-02-11] at:
+- [b-ITU WTDC AP] ITU World Telecommunication Development Conference (2014), Action plan. In: *Final Report World Telecommunication Development Conference (WTDC-14)*, Dubai, United Arab Emirates, 2014-03-30/04-10, pp. 43-144. Available [viewed 2021-02-11] in:
+- [b-ITU WTDC Res.58] ITU World Telecommunication Development Conference Resolution 58 (Rev Dubai 2014), *Telecommunication/information and communication technology accessibility for persons with disabilities, including persons with age-related disabilities*. In: *Final Report World Telecommunication Development Conference (WTDC-14)*, Dubai, United Arab Emirates, 2014-03-30/04-10, pp. 396-410. Available [viewed 2021-02-11] in:
+- [b-ISO/IEC TR 29138-1] ISO/IEC TR 29138-1:2009, *Information technology – Accessibility considerations for people with disabilities – Part 1: User needs summary*.
+- [b-ISO/TR 22411] ISO/TR 22411:2021, *Ergonomics data for use in the application of ISO/IEC Guide 71:2014*.
+- [b-UNCRPD] United Nations (2006), *Convention on the rights of persons with disabilities*. New York, NY: United Nations. 37 pp. Available [viewed 2021-02-10] from: [https://treaties.un.org/doc/Publication/CTC/Ch\\_IV\\_15.pdf](https://treaties.un.org/doc/Publication/CTC/Ch_IV_15.pdf)
+- [b-W3C UAAG 2.0] W3C UAAG 2.0 (2015), *W3C User Agent Accessibility Guidelines (UAAG) 2.0*. Available [viewed 2021-03-24] at:
+- [b-W3C WCAG 2.0] W3C WCAG 2.0 (2008) | ISO/IEC 40500:2012, *Information technology – W3C Web Content Accessibility Guidelines (WCAG) 2.0*. Available [viewed 2021-03-24] at:
+- [b-Bezyak] Bezyak, J.L., Sabella, S.A., Gattis, R.H. (2017). Public transportation: An investigation of barriers for people with disabilities. *J. Disability Pol. Stud.* **28**(1), pp. 52–60.
+- [b-Griffin] Griffin, K.W. (2004). *Building type basics for transit facilities*. Hoboken, NJ: Wiley. 356 pp.
+
+- [b-Haning] Haning, A., Gazey, C., Woolmer, J. (2012). People with disability: The forgotten road user group. In: *Australasian Transport Research Forum 2012 Proceedings*, 2012-09-26/28, Perth, Australia.
+- [b-Mashiri] Mashiri, M., Maunder, D., Venter, C.J., Lakra, A., Bogopane-Zulu, H., Zukulu, R., Buiten, D., Boonzaier, D. (2005). Improving the provision of public transport information for persons with disabilities in the developing world. In: *Proceedings of 24th Annual Southern African Transport Conference*, Pretoria, South Africa, 2005-06-11/17., pp. 308–322. Available [viewed 2021-02-10] at: [https://repository.up.ac.za/bitstream/handle/2263/6413/Mashiri\\_Improving%282005%29.pdf?sequence=1&isAllowed=y](https://repository.up.ac.za/bitstream/handle/2263/6413/Mashiri_Improving%282005%29.pdf?sequence=1&isAllowed=y)
+- [b-NCD] National Council on Disability (2005). *The current state of transportation for people with disabilities in the United States..* Washington, DC: National Council on Disability. Available [viewed 2021-02-10] at:
+- [b-Sawyer] Sawyer A., Bright, K. (2014). *The access manual: Designing, auditing and managing inclusive built environments*, third edition. Oxford: Wiley Blackwell. 288 pp.
+- [b-Soltani] Soltani, S.H.K., Sham, M., Awang, M., Yaman, R. (2012). Accessibility for disabled in public transportation terminal. *Procedia – Soc. Behav. Sci.* **35**, pp. 89-96.
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation
+
+## **ITU-T Y.4229 (01/2025)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Internet of things and smart cities and communities –
+Requirements and use cases
+
+---
+
+## **Requirements and reference functional model for an Internet of things-based smart forest firefighting system**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+| | |
+|---------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | Y.100-Y.999 |
+| INTERNET PROTOCOL ASPECTS | Y.1000-Y.1999 |
+| NEXT GENERATION NETWORKS | Y.2000-Y.2999 |
+| FUTURE NETWORKS | Y.3000-Y.3499 |
+| CLOUD COMPUTING | Y.3500-Y.3599 |
+| BIG DATA | Y.3600-Y.3799 |
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800-Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | Y.4000-Y.4999 |
+| General | Y.4000-Y.4049 |
+| Definitions and terminologies | Y.4050-Y.4099 |
+| Requirements and use cases | Y.4100-Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250-Y.4399 |
+| Frameworks, architectures and protocols | Y.4400-Y.4549 |
+| Services, applications, computation and data processing | Y.4550-Y.4699 |
+| Management, control and performance | Y.4700-Y.4799 |
+| Identification and security | Y.4800-Y.4899 |
+| Evaluation and assessment | Y.4900-Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4229
+
+## Requirements and reference functional model for an Internet of things-based smart forest firefighting system
+
+## Summary
+
+Recommendation ITU-T Y.4229 introduces a smart forest firefighting system based on the Internet of things (IoT), for which it specifies a reference functional model and requirements. The IoT-based smart forest firefighting system uses IoT and other technologies to realize full time and full space forest environment data perception and provides users with forest firefighting intelligent services before, during and after forest fire occurrence. Recommendation ITU-T Y.4229 aims to guide the design, development and implementation of the IoT-based smart forest firefighting system.
+
+## History \*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T Y.4229 | 2025-01-15 | 20 | 11.1002/1000/16024 |
+
+## Keywords
+
+Internet of things, reference functional model, requirements, smart forest firefighting, use cases.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2025
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|-----------------------------------------------------------------------------------------------------------|-------------|
+| 1 Scope ..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 2 |
+| 3.1 Terms defined elsewhere..... | 2 |
+| 3.2 Terms defined in this Recommendation..... | 3 |
+| 4 Abbreviations and acronyms ..... | 3 |
+| 5 Conventions ..... | 3 |
+| 6 Overview of smart forest firefighting system..... | 3 |
+| 7 Requirements for smart forest firefighting system ..... | 6 |
+| 7.1 Functional requirements for smart forest firefighting system ..... | 6 |
+| 7.2 Adaptability, compatibility and performance requirements for smart
forest firefighting system..... | 12 |
+| 8 Reference functional model of smart forest firefighting system ..... | 12 |
+| 9 Security considerations..... | 14 |
+| Appendix I – Forest environmental data and typical sensing devices ..... | 15 |
+| Appendix II – Use cases of IoT-based smart forest firefighting system..... | 17 |
+| II.1 Forest emergency network set-up..... | 17 |
+| II.2 Intelligent forest mapping for firefighting..... | 18 |
+| Bibliography..... | 20 |
+
+
+
+# Recommendation ITU-T Y.4229
+
+## Requirements and reference functional model for an Internet of things-based smart forest firefighting system
+
+# 1 Scope
+
+This Recommendation specifies the requirements and a reference functional model for a smart forest-firefighting system based on the Internet of things (IoT).
+
+For the smart forest firefighting system, this Recommendation includes:
+
+- an overview;
+- a reference functional model;
+- requirements.
+
+Use cases of the IoT-based smart forest firefighting system are provided in Appendix II.
+
+NOTE 1 – The smart forest firefighting system can also be applied to other wildland-firefighting scenarios, such as scrublands, grasslands or rangelands.
+
+NOTE 2 – Unmanned aircraft system (UAS) flight and control requirements lie outside the scope of this Recommendation. Regulation and supervision lie outside the scope of this Recommendation. Any implementation based on this Recommendation should align with regional and national regulations.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- [[ITU-T F.743.22](#)] Recommendation ITU-T F.743.22 (2022), *Requirements and architecture of an algorithm-training system for intelligent video surveillance*.
+- [[ITU-T F.748.36](#)] Recommendation ITU-T F.748.36 (2024), *Requirements and framework of multi-algorithm scheduling systems*.
+- [[ITU-T G.711](#)] Recommendation ITU-T G.711 (1988), *Pulse code modulation (PCM) of voice frequencies*.
+- [[ITU-T H.264](#)] Recommendation ITU-T H.264 (V15) (2024), *Advanced video coding for generic audiovisual services*.
+- [[ITU-T H.265](#)] Recommendation ITU-T H.265 (V10) (2024), *High efficiency video coding*.
+- [[ITU-T T.81](#)] Recommendation ITU-T T.81 (1992), *Information technology – Digital compression and coding of continuous-tone still images – Requirements and guidelines*.
+- [[ITU-T Y.4000](#)] Recommendation ITU-T Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+- [[ITU-T Y.4100](#)] Recommendation ITU-T Y.4100/Y.2066 (2014), *Common requirements of the Internet of things*.
+
+- [[ITU-T Y.4101](#)] Recommendation ITU-T Y.4101/Y.2067 (2017), *Common requirements and capabilities of a gateway for Internet of things applications*.
+- [[ITU-T Y.4113](#)] Recommendation ITU-T Y.4113 (2016), *Requirements of the network for the Internet of things*.
+- [[ITU-T Y.4215](#)] Recommendation ITU-T Y.4215 (2022), *Use cases, requirements and capabilities of unmanned aircraft systems for the Internet of things*.
+- [ISO/IEC 15948] ISO/IEC 15948:2004, *Information technology – Computer graphics and image processing – Portable Network Graphics (PNG): Functional specification*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 device** [ITU-T Y.4000]: With regard to the Internet of things, this is a piece of equipment with the mandatory capabilities of communication and the optional capabilities of sensing, actuation, data capture, data storage and data processing.
+
+**3.1.2 geographical information systems (GIS)** [b-ISO 23611-6]: In the strictest sense, a computer system capable of assembling, storing, manipulating, and displaying geographically referenced information, i.e., data identified according to their locations.
+
+**3.1.3 Internet of things (IoT)** [ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.
+
+NOTE 1 – Through the exploitation of identification, data capture, processing and communication capabilities, the IoT makes full use of things to offer services to all kinds of applications, whilst ensuring that security and privacy requirements are fulfilled.
+
+NOTE 2 – From a broader perspective, the IoT can be perceived as a vision with technological and societal implications.
+
+**3.1.4 IoT area network** [ITU-T Y.4113]: A network of devices for the IoT and gateways interconnected through local connections.
+
+**3.1.5 satellite network** [b-ITU-R V.573-4]: A satellite system or a part of a satellite system, consisting of only one satellite and the cooperating earth stations.
+
+**3.1.6 thing** [ITU-T Y.4000]: With regard to the Internet of things, this is an object of the physical world (physical things) or the information world (virtual things), which is capable of being identified and integrated into communication networks.
+
+**3.1.7 unmanned aircraft system** [b-ISO/IEC 22460-2]: Aircraft and its associated elements which are operated with no pilot on board.
+
+**3.1.8 wide area network** [b-ITU-T Y.4409]: An IP based communication network that covers a wide geographical area including the Internet and accommodates devices and local area networks.
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following term:
+
+**3.2.1 smart forest firefighting system:** A system that uses Internet of things and other technologies to realize full time and full space forest environment data perception and provide users with forest-firefighting intelligent services before, during and after forest fire occurrence.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|------|------------------------------------|
+| 2D | two Dimensional |
+| 3D | three Dimensional |
+| AI | Artificial Intelligence |
+| CoAP | Constrained Application Protocol |
+| DTLS | Datagram Transport Layer Security |
+| EMC | Electromagnetic Compatibility |
+| GIS | Geographical Information System |
+| GNSS | Global Navigation Satellite System |
+| IAN | IoT Area Network |
+| IoT | Internet of Things |
+| IP | Internet Protocol |
+| JPEG | Joint Photographic Experts Group |
+| O&M | Operation and Maintenance |
+| PNG | Portable Network Graphics |
+| RTP | Real-Time Transport Protocol |
+| RTSP | Real-Time Streaming Protocol |
+| SDG | Sustainable Development Goal |
+| TS | Transport Stream |
+| UAS | Unmanned Aircraft System |
+| UDP | User Datagram Protocol |
+| WAN | Wide Area Network |
+
+# **5 Conventions**
+
+In this Recommendation:
+
+- The phrase "is required" indicates a requirement that must be strictly followed and from which no deviation is permitted if conformance to this Recommendation is to be claimed.
+- The phrase "is recommended" indicates a requirement that is recommended but which is not absolutely required. Thus, this requirement needs not be present to claim conformance.
+- The phrase "can optionally" indicates an optional requirement that is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor must include the option in their implementation, nor that the network operator or service provider must enable it if the feature is available. It rather means that the vendor may optionally provide the feature and still claim conformance with the specification.
+
+# **6 Overview of smart forest firefighting system**
+
+Forests occupy one-third of the Earth's land area and play an important role in mitigating climate change, reducing air and noise pollution, providing livelihoods, food and water, and protecting biodiversity. In recent years, the frequent occurrence of forest fires has become a global issue.
+
+According to statistics, there are 220 000 forest fires worldwide every year, and the affected area exceeds 90 000 000 ha, resulting in significant losses to the Earth and human beings. The *United Nations strategic plan for forests, 2017-2030* [b-UNSPF] calls on countries to actively seek to harness the power of science, innovation and technologies to advance solutions to the root causes of forest destruction. At the same time, the United Nations Sustainable Development Goals (SDGs), SDG 13 (Climate Action) and SDG 15 (Life on Land) underscore the importance of forest protection.
+
+NOTE 1 – [b-ISO 13065] defines "forest" as "land spanning more than 0.5 ha with trees higher than 5 m and a canopy cover of more than 10 percent or trees able to reach these thresholds *in situ*, not including land that is predominantly under agricultural or urban land use".
+
+Forest firefighting involves actions to prevent and extinguish forest fires.
+
+At present, prior the occurrence of forest fires, most fire monitoring is carried out by means of artificial lookouts. However, the use of artificial lookouts presents issues such as small monitoring scope, inability to monitor in real-time, and only detecting large fires. In addition, when forest fires occur, rescuers and vehicles may not reach the site in time to carry out firefighting and rescue operations due to the complex geographical environments. At the same time, forest network coverage is often poor and prone to failure, meaning data may not be transmitted normally. After forest fires occur, the capacity for manual troubleshooting of potential safety hazards is often insufficient, resulting in fire recurrence. Another consequence of the terrain is that forest fire loss often cannot be accurately assessed.
+
+As defined in clause 3.2.1, an IoT-based smart forest firefighting system uses Internet of things (IoT) and other technologies to realize full time and full space forest environment data perception, and provides users with forest firefighting intelligent services before, during and after forest fire occurrence.
+
+An IoT-based smart forest firefighting system can assist rescuers in conducting full-time and full-space forest safety monitoring during forest fires, and in extinguishing fires (spraying extinguishing agents, delivering firefighting materials, etc.). Such a system can also provide rescue assistance (auxiliary lighting, personnel positioning, etc.) when forest fires occur. This is especially the case in forest areas with complex geographical environments that are inaccessible to rescuers and vehicles and where the value of an IoT-based smart forest firefighting system could be particularly important. On the other hand, it is worthwhile to note that the smart forest firefighting system can also be applied to other wildland-firefighting scenarios, such as scrublands, grasslands or rangelands [b-ISO/TR 24188].
+
+NOTE 2 – Rescuers include forest firefighters and forest rangers.
+
+NOTE 3 – An extinguishing agent is a substance that can effectively destroy combustion conditions and stop combustion, including water, foam, powder and CO2.
+
+Figure 1 is an overview diagram of an IoT-based smart forest firefighting system. It consists of four parts, including forest environment, smart forest firefighting system (devices, network and platform), users and external systems for resource interaction.
+
+
+
+Figure 1: Overview diagram of IoT-based smart forest firefighting system. The diagram shows a central 'Smart forest firefighting system' box connected to 'Users' at the top, 'Forest environment' at the bottom, and four external monitoring systems on the sides. The central system is divided into three layers: 'Platform' (with icons for alert, brain, map, network, building, document, and heart), 'Network' (with icons for truck, drone, antenna, signal, and cable), and 'Devices' (with icons for drone, camera, sensor, clock, face, globe, location, battery, antenna, laptop, and light). The external systems are: 'Forest wildlife monitoring systems' (globe icon), 'Hydrology monitoring systems' (water drop icon), 'Ecological environment monitoring systems' (plant icon), and 'Smart city systems' (building icon).
+
+Y.4229(25)
+
+**Figure 1 – Overview diagram of IoT-based smart forest firefighting system**
+
+The forest environment is the target object of the smart forest firefighting system. The target object can be sensed by sensors and executed by actuators. The categories and parameters of forest environmental data and typical sensing devices for related data collection are listed and described in Appendix I.
+
+The smart forest firefighting system includes sensing devices, actuating devices, mobile devices and gateways. Sensing devices include those for multimedia data collection, sensor data collection, geographic and position information collection, which collect forest environmental data, such as fire, smoke, temperature, humidity, wind direction, wind speed, combustible gas concentration, light intensity, weather and position. Actuating devices include unmanned aircraft systems (UASs), which provide night lighting, fire extinguisher delivery and temporary emergency network set-up. Mobile devices provide notification and information exchange between rescuers and platforms. Gateways are devices that connect sensing and actuating devices with the platform, providing protocol conversion, data processing, device management and other functions. Gateways can operate as independent devices or be integrated with sensing and actuating devices.
+
+The network enables the exchange of information between the platform and the devices. The network is constituted by different networks, including fixed networks, mobile networks, satellite networks and other networks, in order to address the different forest scenarios. See Appendix II for detailed use cases.
+
+The platform manages and analyses collected data and provides users with applications and services such as disaster identification, early warning, fire position, spread analysis, situation plotting, path planning, fire prediction, command and dispatch, disaster damage assessment, and fire risk level classification.
+
+Users include forest regulatory authorities, managers, firefighters and rescuers.
+
+At the same time, the smart forest firefighting system can exchange information and data with external systems, such as those for forest wildlife monitoring, hydrological monitoring, ecological environment monitoring and smart cities. Interactive data usually includes forest basic information data, forest maps, forest weather information data and forest ecological environment distribution.
+
+# **7 Requirements for smart forest firefighting system**
+
+High-level requirements for IoT are identified in [ITU-T Y.4000]. Common requirements for IoT are identified in [ITU-T Y.4100]. Requirements for the network for the IoT are identified in [ITU-T Y.4113].
+
+In this Recommendation, requirements specific to the IoT-based smart forest firefighting system (hereafter "the system") are identified.
+
+## **7.1 Functional requirements for smart forest firefighting system**
+
+### **7.1.1 General requirements**
+
+- The system is required to support data and information sharing with external systems.
+- The system is required to support data collection from external systems, including but not limited to basic forest information data, forest map (two dimensional (2D), three dimensional (3D)), forest weather information data (real-time, future) and forest satellite remote sensing image data.
+
+### **7.1.2 Requirements of devices**
+
+Forest firefighting devices are found in the forest environment, including but not limited to multimedia data collection devices (e.g., visible light cameras and infrared thermal imaging cameras), sensor data collection devices (e.g., temperature sensors, humidity sensor, light sensors, wind sensors, weather sensors, and gas sensors), geographic and position information data collection devices (e.g., Lidar, radar, global navigation satellite system (GNSS) locator), UASs, mobile devices and gateways.
+
+#### **a) General requirements**
+
+- Devices are required to support the collection of data from a forest environment that is relevant to firefighting.
+NOTE 1 – Forest environmental data and typical sensing devices for data collection are provided in Appendix I.
+- Devices are required to support real-time collection and collection duration of forest environmental data.
+NOTE 2 – Collection duration represents the time period set for collection for the device.
+- Devices are required to support the uploading of device status, device position information and collected data to the platform.
+- Devices are required to support both fixed and mobile installation scenarios.
+NOTE 3 – The forest environment is complex, devices cannot have fixed installation in some positions.
+- Devices are recommended to support data processing capabilities, including but not limited to threshold evaluation, and algorithm inference.
+NOTE 4 – The algorithms used for firefighting-related data processing include, but are not limited to, fire identification algorithms, and smoke identification algorithms.
+- Devices are required to support unique identification.
+- Devices are recommended to support temporary data storage, when a network outage occurs, and support data retransmission after network recovery.
+
+#### **b) Multimedia data collection device**
+
+- A multimedia data collection device is required to support the collection of multimedia data in the forest environment, including video, audio and image.
+
+- The multimedia data collection device is required to support 720P, 1 080P, 2K, and 4K resolution data collection.
+- The multimedia data collection device is required to support joint photographic experts group (JPEG) [ITU-T T.81] and portable network graphics (PNG) [ISO/IEC 15948] image format data collection.
+- The multimedia data collection device is required to support H.264 [ITU-T H.264] and H.265 [ITU-T H.265] video coding format.
+- The multimedia data collection device is required to support G.711a [ITU-T G.711], G.711 $\mu$ [ITU-T G.711], and pulse code modulation [ITU-T G.711] audio coding format.
+- The multimedia data collection device is required to support the collection of images in the forest environment, as well as the artificial intelligence (AI) algorithm-based image identification of fire, flame and smoke parameters.
+- The multimedia data collection device is recommended to support video and image data collection to effectively filter interference information in the forest environment, including but not limited to fog, haze, clouds, strong light and shadows.
+- The multimedia data collection device is recommended to support algorithm self-training based on the data collected in the forest environment.
+- The multimedia data collection device is required to support infrared thermal imaging.
+- The multimedia data collection device is required to support temperature measurement and positioning of targets in forest.
+
+NOTE 5 – The temperature measurement and positioning can be supported by artificial intelligence (AI) algorithm analysis or other technologies.
+
+#### **c) Sensor data collection device**
+
+- The sensor data collection device is required to support the collection of combustibles, gases and meteorological data in the forest environment.
+- The sensor data collection device is recommended to support dynamic adjustment of sensing data upload frequency based on energy consumption and fire risk level.
+
+NOTE 6 – This is particularly applicable to passive sensors and low-power devices.
+
+#### **d) Geographic and position information data collection device**
+
+- The geographic and position information data collection device is required to support the collection of forest geographic information, fire areas and position information of key focus objects in the forest environment.
+
+NOTE 7 – The collection of forest geographic information can benefit from the presence of a forest geographic database. Forest geographic information can support the prediction of fire spread trends and decision-making for the rescue path. The key focus objects position information can support firefighting decision-making.
+
+#### **e) Unmanned aircraft system**
+
+- The UAS requirements are aligned with [ITU-T Y.4215].
+- The UAS is required to support emergency network set-up (see use case in clause II.1 for detail).
+
+#### **f) Mobile device**
+
+NOTE 8 – Mobile devices are hand-held communication devices carried by rescuers in the forest.
+
+- The mobile device is required to support receiving real-time video and image data, decision commands, rescue routes and geographical information system (GIS) forest maps.
+
+- The mobile device is required to support the reporting of real-time position information of rescuers.
+- The mobile device is required to support sending controlling information to other devices.
+- The mobile device can optionally support forest environmental data collection.
+
+#### **g) Gateway**
+
+- The gateway is required to support data storage, pre-processing and edge computing.
+- The gateway is required to support the aggregation of sensing data to the platform.
+- The gateway is required to support transferring platform commands to devices.
+- The gateway is required to support protocol conversion [ITU-T Y.4101] between IoT area network (IAN) and wide area network (WAN).
+- The gateway can optionally be a stand-alone device or integrated with sensing and actuating devices (e.g., a UAS can be considered as a sensing or actuating device or as a gateway).
+
+### **7.1.3 Requirements of network**
+
+- The network is required to support one or more communication technologies, including but not limited to WAN, local area network and low-power WAN.
+- It is recommended that the fixed network and mobile network are both supported in the forest area, in order to support fixed terminals, e.g., camera, wind sensor, temperature sensor, humidity sensor and mobile devices such as handheld terminals used by rescuers.
+- For a large area of forest, there may be multiple fixed or mobile IANs. The interconnection between these networks is required to be supported.
+- It is required to support audio, video and data communication functions and the positioning function.
+
+NOTE 1 – This requirement can provide support for handheld devices, e.g., forest rescuer mobile devices.
+
+- The network is required to have the ability to support emergency network set-up using communication satellites, emergency communication vehicles and UAS relays when the forest network infrastructure is damaged or when a forest area has no network infrastructure.
+- The network is required to support multiple network connections simultaneously, in order to enable automatic selection of the appropriate networks.
+
+NOTE 2 – As mentioned in clause 6, the communication infrastructure of the smart forest firefighting system is capable of supporting different networks at the same time. The system can automatically select the most suitable network based on current conditions such as signal strength, network congestion, data transmission needs and other factors. This can ensure continuous and reliable connectivity, which is crucial for real-time monitoring and swift communication during firefighting operations.
+
+- The network is required to support automatic local networking.
+
+NOTE 3 – The system is able to establish a local network automatically. In remote forest areas where network coverage might be weak or unavailable, the devices can form an *ad-hoc* local network among themselves without manual intervention. This allows devices to communicate directly with each other, sharing data and coordinating actions effectively, even in the absence of rich network connectivity. Automatic local networking ensures that the system remains functional and efficient in all circumstances, enhancing the reliability of fire detection, monitoring, and response efforts.
+
+- The transmission protocol for multimedia data (i.e., data from multimedia data collection devices) is required to support the separation of signalling channels and media channels.
+
+NOTE 4 – Session initialization protocol [b-IETF RFC 3261], hypertext transfer protocol [b-IETF RFC 9110] and real-time streaming protocol (RTSP) [b-IETF RFC 7826] are widely used for the signalling channels of multimedia data. Session initialization protocol secure [b-IETF RFC 3261], hypertext transfer protocol secure [b-IETF RFC 9110] and real-time streaming protocol secure [b-IETF RFC 7826] are widely used for encrypted transmission in the signalling channels of multimedia data.
+
+NOTE 5 – Real-time transport protocol (RTP) [b-IETF RFC 3550] over user datagram protocol (UDP) [b-IETF RFC 768], RTP [b-IETF RFC 3550] over RTSP [b-IETF RFC 7826] and transport stream (TS) [b-ISO/IEC 13818-1] over UDP are widely used for the media channels of multimedia data. Secure real-time transport protocol [b-IETF RFC 3711] and TS over datagram transport layer security (DTLS) [b-IETF RFC 9147] are widely used for encrypted transmission in the media channels of multimedia data.
+
+NOTE 6 – Message queuing telemetry transport [b-ISO/IEC 20922] and constrained application protocol (CoAP) [b-IETF RFC 7252] are widely used for transmission of IoT data (i.e., data from sensor data collection devices, geographic and position information collection devices or other devices). Message queuing telemetry transport secure [b-ISO/IEC 20922] and CoAP over DTLS are widely used for encrypted transmission of IoT data.
+
+### **7.1.4 Requirements of platform**
+
+#### **7.1.4.1 Basic requirements**
+
+- The platform is required to support device access, including a multimedia data collection device, sensor data collection device, geographic and position information data collection device, UAS, mobile device and gateway.
+- The platform is required to support data collection, storage, processing and analysis.
+- The platform is required to support retrieval and playback of video, image and audio data.
+- The platform is required to support the real-time video data display of monitored positions.
+- The platform is required to support periodic display of fire status, types, and trends in the form of videos and charts.
+- The platform is required to support sending data analysis results to users, transmitting decision commands to mobile devices and delivering control information to sensing and actuating devices.
+- The platform is required to support statistical analysis of all sensing data, alarm events, fire related data, number of rescuers, and number of online devices.
+- The platform is required to support GIS forest maps.
+- The platform is required to display the device position information data, satellite map, device collected data, device information on GIS forest maps.
+- The platform is required to support algorithm inference.
+- The platform is recommended to support algorithm management by algorithm warehouse, and support algorithm scheduling [ITU-T F.748.36] and deployment to devices on demand.
+
+NOTE 1 – The algorithm warehouse manages algorithms, including their storage, addition, deletion, modification, query, version management, type management and provider information management.
+
+NOTE 2 – The scheduling of algorithms is a process of algorithm dynamic allocation based on service and task requirements. The scheduling can take utilization of computing power resources into account.
+
+- The platform is recommended to support algorithm training [ITU-T F.743.22] for updating inference capabilities.
+
+NOTE 3 – The platform uses algorithm training technology based on forest actual scene data. Algorithm training can generate models used for inference in new scenarios or for upgrading existing models.
+
+#### 7.1.4.2 Application requirements
+
+##### a) Disaster identification and early warning
+
+- The platform is required to support automatic generation and transmission of alarm information to users when environmental parameters exceed a certain risk threshold value.
+- The platform is required to support automatic generation and transmission of alarm information to users and mobile devices when identifying fire, flame and smoke information in the forest environment.
+- The platform is required to support automatic recording of alarm information and alarm video and image.
+- The platform is required to support secondary confirmation and judgement of alarm information.
+
+NOTE 1 – The platform retrieves on-site video and images collected by other multimedia data collection devices for fire confirmation and judgement.
+
+###### b) Fire positioning
+
+NOTE 2 – Fire positioning is the marking of fire coordinates on the GIS forest map based on the information provided by UASs and satellite remote sensing system, etc. In order to assist users to quickly understand the situation around the fire, it analyses the nearest water source, rescue route and UAS firefighting flight route, etc.
+
+- The platform is required to support the positioning of fires and smoke identified in the forest environment.
+- The platform is required to support the calculation of the fire position based on the coordinates of devices (e.g., pan, tilt and zoom data), camera elevation angle, and digital elevation model data.
+- The platform is required to support the calculation of fire position based on satellite remote sensing images data.
+- The platform is required to support the calculation of fire position based on UAS flight attitude.
+
+NOTE 3 – The position of the fire can be calculated using UAS flight attitude data (e.g., yaw, pitch, and roll), GNSS information, and camera (or other on-board sensors) parameters through ray projection algorithms or trigonometric calculations. The UAS collects its position and flight attitude information and, combined with the camera's field of view, converts the fire's position in the image into a spatial direction vector relative to the UAS.
+
+- The platform is required to support manual reporting of fire position.
+- The platform is required to support sending the longitude and latitude coordinates of the fire position to users and mobile devices.
+- The platform is required to support GIS forest map to display the fire position.
+
+##### c) Spread analysis
+
+NOTE 4 – The development of forest fires is a dynamic process. According to the geographic and position information, combustibles index factors and meteorological factors of forest fire, a mathematical model of forest fire spread is developed to dynamically estimate the area, direction and speed of forest fires. By combining GIS forest map technology, the results are displayed as images, helping users in decision-making.
+
+- The platform is required to support dynamic simulation and prediction of the development and spread of forest fires, including direction, speed and area.
+- The platform is required to support the use of GIS forest map to display the fire spreading trend in real time.
+- The platform is recommended to support dynamic analysis of the fire scene.
+
+NOTE 5 – This analysis may be enabled by digital twin technologies.
+
+##### **d) Path planning**
+
+- The platform is required to support the planning of optimal rescue paths, firefighting paths and rescue vehicle paths for forest firefighting.
+- The platform is recommended to support rescue strategy generation.
+
+NOTE 6 – This may be enabled by digital twin technologies.
+
+- The platform is required to support the use of GIS forest map to display optimal and alternative rescue paths, firefighting paths and rescue vehicle paths.
+
+##### **e) Situation plotting**
+
+NOTE 7 – The situation plotting map is a graphical representation of the information reflecting the current situation and development situation of the forest fire. Map elements, such as labels, markers and colour, indicate information, such as fire boundary, fire centre, smoke centre, spreading direction, rescue path and danger area.
+
+- The platform is required to support plotting on GIS forest maps with text and colour annotations.
+
+NOTE 8 – The elements to be plotted can include current fire situation, fire trend and direction, locations and movement directions of firefighting teams, safe areas, other relevant areas, and firefighting resources such as water sources and rescue supplies.
+
+##### **f) Command and dispatch**
+
+NOTE 9 – Command and dispatch are based on a GIS forest map; users obtain information such as fire position, fire area, spread analysis and geographic information to formulate the best firefighting strategic plan.
+
+- The platform is required to support sending optimal and alternative rescue paths, firefighting paths and rescue vehicle paths to users and mobile devices.
+- The platform is required to support command and dispatch of UASs, rescuer and firefighting materials.
+
+##### **g) Disaster damage assessment**
+
+- The platform is required to support the measurement of forest fire-damaged areas.
+- The platform is recommended to support the survey and assessment of forest fauna and flora data.
+- The platform can optionally support resource loss and economic loss estimation.
+- The platform can optionally support carbon emission statistics and calculation.
+
+NOTE 10 – Disaster damage assessment consists of statistics and reporting of the area of forest destruction and economic losses caused by forest fires, providing data support for post-disaster reconstruction.
+
+##### **h) Fire risk classification**
+
+NOTE 11 – Fire risk level classification involves calculation of the current and future fire risk level based on real-time and future weather information, fire information and combustible data, etc.
+
+- The platform is required to support the calculation and classification of fire risk level.
+- The platform is required to support generating fire risk levels for different regions based on forest environmental information data.
+- The platform is required to support displaying fire risk warning levels through different colours on the GIS map.
+
+#### **7.1.4.3 Operation and maintenance requirements**
+
+- The platform is required to support operation and maintenance (O&M) capabilities, including user management, device management, log management, network management, and security management.
+- The platform is required to support audio and video data quality diagnosis of multimedia data collection devices.
+
+## **7.2 Adaptability, compatibility and performance requirements for smart forest firefighting system**
+
+### **a) Clock synchronization**
+
+- The system is required to support clock synchronization capability, and the clock synchronization accuracy is required to satisfy user requirements.
+
+### **b) Data collection accuracy and precision**
+
+- The system is required to support high data collection accuracy and precision to satisfy user requirements.
+
+NOTE 1 – The accuracy and precision will affect the reliability level of applications and services of systems. For different applications and services, data type accuracy and precision requirements vary.
+
+### **c) Device environmental adaptability**
+
+- The device is required to support high environmental adaptability, including but not limited to operating temperature, lightning protection, waterproof, dust-proof and corrosion resistance.
+
+### **d) Device electromagnetic compatibility (EMC)**
+
+- The device is required to satisfy the requirements for EMC.
+
+### **e) Power supply**
+
+- The system is required to support stable and reliable power supply.
+- The device is recommended to support battery power supply.
+- The system is recommended to support renewable power supply, e.g., solar power supply.
+
+### **f) Network performance and quality**
+
+- The network is required to provide appropriate network performance to satisfy data transmission requirements for different types of data.
+
+NOTE 2 – For different types of perception data, network performance requirements are different, especially for alarm events and related video clips when emergency situations happen such as forest fires, which require very high network performance.
+
+- The network is required to support reliable data transmission in weak network conditions, such as unstable or low signal strength conditions in disaster areas and densely forested regions.
+
+NOTE 3 – Mechanisms that can be used for reliable data transmission include resuming transmission upon network reconnection, real-time monitoring and adjustment of network quality, and utilizing multiple transmission paths.
+
+# **8 Reference functional model of smart forest firefighting system**
+
+Figure 2 shows the reference functional model of smart forest firefighting system.
+
+
+
+**Smart forest firefighting platform**
+
+| Application functions | | | | | | | | | | O&M functions | | |
+|-------------------------|-----------------------------|------------------------------|--------------------------|----------------------|----------------|--|--|--|--|-------------------|--------------------|--|
+| Disaster identification | Early warning | Fire positioning | Spread analysis | Path planning | | | | | | User management | | |
+| Situation plotting | Command and dispatch | Disaster damage assessment | Fire risk classification | ... | | | | | | Device management | | |
+| Basic functions | | | | | | | | | | Log management | | |
+| Device access | Data collection and storage | Data processing and analysis | Retrieval and playback | Statistical analysis | GIS forest map | | | | | | Network management | |
+| Data display | Commands distribution | Algorithm training | Algorithm scheduling | Algorithm inference | ... | | | | | | ... | |
+
+**WAN**
+
+**Gateway**
+
+**LAN**
+
+| Forest firefighting devices | | | | | | Forest firefighting devices | | | | | |
+|-----------------------------|-------------------|-------------------|----------|---------------|-----|-----------------------------|-------------------|-------------------|----------|---------------|-----|
+| Sensor device | Geographic device | Multimedia device | Actuator | Mobile device | UAS | Sensor device | Geographic device | Multimedia device | Actuator | Mobile device | UAS |
+
+**Forest environmental data**
+
+| | | | | | | | |
+|------|-------|-------------|-----|-------------|-----------|----------|-----|
+| Fire | Smoke | Combustible | Gas | Meteorology | Geography | Position | ... |
+|------|-------|-------------|-----|-------------|-----------|----------|-----|
+
+**Data from external systems**
+
+| |
+|---------------------------------------------|
+| Basic forest information data |
+| 2D/3D forest map |
+| Forest satellite remote sensing data |
+| Real-time/Future forest weather information |
+| ... |
+
+↔ Communication
+↔ Sensing and actuating
+
+Y.4229(25)
+
+Figure 2: Reference functional model of IoT-based smart forest firefighting system. The diagram shows a hierarchical architecture. At the top is the 'Smart forest firefighting platform' containing 'Application functions' (Disaster identification, Early warning, Fire positioning, Spread analysis, Path planning, Situation plotting, Command and dispatch, Disaster damage assessment, Fire risk classification, ...), 'Basic functions' (Device access, Data collection and storage, Data processing and analysis, Retrieval and playback, Statistical analysis, GIS forest map, Data display, Commands distribution, Algorithm training, Algorithm scheduling, Algorithm inference, ...), and 'O&M functions' (User management, Device management, Log management, Network management, ...). To the right is a 'Users' block (Forest regulatory authorities, Forest managers, Firefighters, Rescuers, ...). Below the platform is a 'WAN' block. A 'Gateway' connects the WAN to an 'LAN'. The LAN connects to two 'Forest firefighting devices' blocks, each containing Sensor device, Geographic device, Multimedia device, Actuator, Mobile device, and UAS. These devices connect to 'Forest environmental data' (Fire, Smoke, Combustible, Gas, Meteorology, Geography, Position, ...). To the right, 'Data from external systems' (Basic forest information data, 2D/3D forest map, Forest satellite remote sensing data, Real-time/Future forest weather information, ...) also connects to the WAN. Red double-headed arrows indicate communication, and green double-headed arrows indicate sensing and actuating.
+
+**Figure 2 – Reference functional model of IoT-based smart forest firefighting system**
+
+NOTE – In Figure 2, the frames with ellipses indicate that new functions might be included to address potential additional needs.
+
+The reference functional model of a smart forest firefighting systems consists of devices, IAN, WAN, smart forest firefighting platform, external systems, users and the forest environment.
+
+The devices include sensor devices, geographic devices, multimedia devices, actuator devices, mobile devices, UASs and gateways. The requirements for devices are specified in clause 7.1.2.
+
+The requirements for IAN and WAN are specified in clause 7.1.3.
+
+The smart forest firefighting platform includes basic functions, application functions, and O&M functions. The basic functions include device access, data storage, data processing and analysis, retrieval and playback, statistical analysis, user management, network management, a GIS forest map, algorithm training, algorithm scheduling and algorithm inference. The application functions include disaster identification, early warning, fire positioning, spread analysis, path planning, situation plotting, command and dispatch, disaster damage assessment and fire risk classification. The O&M functions include user management, device management, log management, network management and other functions. The requirements for smart forest firefighting platform are specified in clause 7.1.4.
+
+The external systems include basic forest information data interchange, 2D or 3D forest map interchange, forest satellite remote sensing data interchange and real-time or future weather
+
+information interchange. The requirements for data interchange with external systems are specified in clause 7.1.1.
+
+The users include forest regulatory authorities, forest managers, firefighters and rescuers.
+
+The forest environmental data can be found in Appendix I.
+
+Furthermore, the association between the reference functional model depicted in Figure 2 and the IoT reference model (and related layers) defined in [ITU-T Y.4000] can be categorized as follows.
+
+Devices, including gateways, can be mapped to the device layer; WAN and IAN can be mapped to the network layer; the basic functions of the smart forest firefighting platform can be mapped to the service support and application support layer; the application functions of the smart forest firefighting platform can be mapped to the application layer; the O&M platform can be mapped to the cross-layer management capabilities.
+
+# **9 Security considerations**
+
+For common security requirements related to IoT, see [b-ITU-T X.1352] and [b-ITU-T X.1369].
+
+In the IoT-based smart forest firefighting system, assets with security risks mainly include: sensing devices, actuating devices, mobile devices and gateways; wired networks, mobile communication networks, and satellite communication networks; databases, application systems, or other software and hardware.
+
+Security threats to the devices mainly include: attacker interception or destruction of data through impersonation of identity and tampering with forest environmental data; the theft of or tampering with device information, resulting in the inability of devices in the forest to function properly; the copy of data collected by sensing devices without authorization. The data security level can be improved through data backup, encrypted storage, access permission settings, identity authentication and other methods. Security of data collected by devices is crucial for the construction of forest firefighting databases.
+
+Security threats to the network mainly include: data interception, tampering, forgery and eavesdropping, resulting in transmission interruption, transmission delay, data theft and data loss. Additionally, risks involve secret key information leakage and potential damage to network transmission equipment. By preventing and resisting possible attacks on network resources, it can be ensured that network resources are not illegally used or accessed, as well as data transmission security. This may be achieved through the implementation of data encryption mechanisms, secret key management mechanisms and access control mechanisms to enhance the level of data security transmission. Specifically, for forest environmental data, including forest maps, encryption during transmission is essential to ensure confidentiality and privacy.
+
+Security threats to the platform mainly include: obtaining access permissions to the platform, resulting in the leakage and tampering of user information and related data. Implementing regular data backups helps mitigate data loss in emergencies, such as fire. Preventing security vulnerabilities is crucial to thwart illegal control of the platform and prevent platform performance degradation.
+
+# Appendix I
+
+## Forest environmental data and typical sensing devices
+
+(This appendix does not form an integral part of this Recommendation.)
+
+Table I.1 lists the categories and parameters of forest environmental data and provides typical sensing devices for related data collection.
+
+NOTE – Definitions of parameters related to fire, flame, smoke, combustible and gas can be found in [b-ISO 13943].
+
+**Table I.1 – Forest environmental data and typical sensing devices**
+
+| Categories | Parameters | Typical sensing devices |
+|------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|
+| Fire, flame and smoke | Fire classification
Shape of fire
Burned area
Damaged area
Flame colour
Flame height
Fire propagation speed
Fire propagation direction
Smoke colour
Smoke height | Camera
Smoke sensor |
+| | Fire point temperature
Smoke concentration | Temperature sensor
Infrared thermal imaging camera |
+| Combustible and gas | Types of combustibles
Concentration of combustibles
Flammability
CO 2 concentration
O 2 concentration
Toxic gas concentration | Gas sensor |
+| Meteorology | Air temperature [b-ISO 16165]
Air pressure [b-ISO 10782-1]
Humidity [b-ISO/TR 18931]
Wind direction [b-ISO 10596]
Wind speed [b-ISO 10596]
Light intensity [b-ISO 7686]
Radiation intensity [b-ISO 25457]
Precipitation intensity [b-IWA 33-1] | Air temperature sensor
Air pressure sensor
Air humidity sensor
Wind sensor
Light sensor
Water level sensor |
+| Geography and position | Forest geographic information
Terrain [b-ISO 10788]
Elevation [b-ISO 20524-1]
Slope [b-ISO 6707-1]
Longitude [b-ISO 22932-1]
Latitude [b-ISO 1998-6] | Lidar
Radar
GNSS locator
UAS
Camera |
+
+**Table I.1 – Forest environmental data and typical sensing devices**
+
+| Categories | Parameters | Typical sensing devices |
+|------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------|
+| | Geographic coordinates of fire area and key focus objects [b-ISO 7078]
Fire area coordinates
Rescuer coordinates
Rescue vehicle coordinates
Living body coordinates
Natural reserve coordinates
Residential area coordinates
Important facilities coordinates
Scenic spots coordinates
Historical sites coordinates
Mining area coordinates | |
+
+# Appendix II
+
+## Use cases of IoT-based smart forest firefighting system
+
+(This appendix does not form an integral part of this Recommendation.)
+
+## II.1 Forest emergency network set-up
+
+Figure II.1 shows the forest emergency network set-up of smart forest firefighting system.
+
+
+
+The diagram illustrates the forest emergency network set-up, showing the integration of UAS sub-systems, ground sub-systems, and a central platform connected to users and external systems.
+
+**UAS sub-systems:**
+
+- UAS mounted devices:** Visible light camera, Infrared thermal imaging camera, Gas sensor, Locator, Meteorology sensor, Laser radar, Lighting, and Extinguisher.
+- UAS:** The drone itself.
+- UAS gateway:** Connects the UAS to the ground sub-system.
+- UAS mobile controller:** Controls the UAS.
+
+**Ground sub-systems:**
+
+- Ground devices:** Visible light camera, Infrared thermal imaging camera, Meteorology sensor, Gas sensor, and a Gateway.
+- Rescuer devices:** Mobile device and Locator.
+
+**Network and Data Flow:**
+
+- Forest network A:** Represented by black arrows, connecting UAS and ground sub-systems.
+- Forest network B:** Represented by blue arrows, connecting the UAS gateway, ground gateway, and base station.
+- Forest network C:** Represented by red arrows, connecting the UAS, UAS gateway, communication satellite, emergency communication vehicle, and base station.
+- Communication satellite:** Provides long-range communication for the UAS and emergency vehicles.
+- Emergency communication vehicle:** A truck equipped with communication equipment.
+- Base station:** The central hub for ground network communication.
+- Cloud:** The central data storage and processing hub.
+
+**Platform and User Interaction:**
+
+- User:** Interacts with the system via **User devices** (computer and smartphone).
+- Platform:** The central processing unit, including:
+ - Disaster, identification, and early warning
+ - Fire position
+ - Path planning
+ - Spread analysis
+ - Command and dispatch
+ - Situation plotting
+ - Disaster damage assessment
+ - Fire risk classification
+- External systems:** Interact with the platform.
+
+**Legend:**
+
+- ↔ Forest network A (black arrow)
+- ↔ Forest network B (blue arrow)
+- ↔ Forest network C (red arrow)
+
+Y.4229(25)
+
+Figure II.1 – Forest emergency network set-up diagram
+
+**Figure II.1 – Forest emergency network set-up**
+
+The geographical environment of forests is complex, and a network set-up may not cover all forest areas. Also, when forest fires occur, ground network infrastructure is vulnerable to fire damage. To monitor fire-related information in the forest environment in real time, a smart forest firefighting system needs to establish a forest emergency network to ensure that data from the forest environment can be transmitted in real time.
+
+In Figure II.1, the sensing and actuating system deployed in the forest as part of the smart forest firefighting system consists of a series of UAS sub-systems and ground sub-systems (with the number and distribution density of each sub-system depending on the forest area and situation). The UAS sub-system performs monitoring and firefighting tasks through the sensing and actuating units mounted on the UASs and carries out flight and cruise tasks through the control of the UAS mobile controller. The ground sub-system includes sensing devices deployed on the ground and mobile devices carried by rescuer. At the same time, the ground sub-system can transmit data through UAS relaying (Forest network A).
+
+If the forest has full network coverage, the UAS and ground sub-systems can transmit data through the ground base station. When the devices are far away from the ground base station or located in special terrain areas, data can be transmitted through UAS relaying (forest network B).
+
+If the forest has partial network coverage of the forest or if ground network infrastructure is damaged, a satellite network can be established through emergency communication vehicles to transmit data. A mobile device carried by a rescuer can communicate directly with the communication satellite (forest network C).
+
+The forest emergency network, established through the smart forest firefighting system, can upload the data collected in the forest to the cloud platform in real time. This provides users with a series of intelligent applications and services, while also enabling information interaction with external systems.
+
+## II.2 Intelligent forest mapping for firefighting
+
+Figure II.2 shows an example of intelligent forest mapping for firefighting, which includes fire position, spread analysis, path planning, situation plotting, and command and dispatch.
+
+
+
+The figure is a topographic map of a forested area with various firefighting and rescue elements overlaid. A central fire area is depicted with a red flame icon and a red outline. A blue line, representing the UAS flight path, starts from a 'Water resource' (blue dot) in the upper right, moves left, then down and left, ending near the fire area. A blue line representing the 'Rescue path' starts from the bottom left and moves towards the fire area. A red dot at the top left marks the 'Residence community'. A red dot at the bottom right marks the 'Animal reserve'. A blue dot on the left marks the 'Rescuer position'. A yellow dot on the left marks the 'Vehicle position'. A black dot near the fire area marks the 'UAS position'. Two concentric red outlines around the fire area represent the 'One hour warning line' (inner) and 'Two hours warning line' (outer). The map also shows a road on the left and a river on the right.
+
+Figure II.2: Example of intelligent forest mapping for firefighting. The map shows a fire area (red) with a UAS flight path (blue) and a rescue path (blue). Key locations include a residence community, water resource, animal reserve, rescuer position, and vehicle position. The UAS position is also marked.
+
+Y.4229(25)
+
+**Figure II.2 – Example of intelligent forest mapping for firefighting**
+
+Based on various types of data collected in the forest environment (audio and video data, sensor data, geographic and position information data, etc.), the smart forest firefighting system can provide users with intelligent forest maps that assist in firefighting, and can display the fire area, fire position, spread trend, rescue routes, UAS flight routes, surrounding resource positions, key focus object positions, rescuer positions, vehicle positions, UAS positions, etc.
+
+As shown in Figure II.2, based on collected forest fire data, the smart forest firefighting system generates a map of the fire area and fire shape automatically, predicting the fire spread trend, and forming a 1 h warning line and a 2 h warning line. Based on the forest GIS data, the system automatically marks the resources, such as water, around the fire on an intelligent map and automatically marks the key focus objects around the fire, such as residence community or animal reserve areas. The system automatically plans rescue routes based on forest terrain information and displays them on the intelligent map, including rescuer and vehicle routes. The system automatically plans UAS flight routes and delivery points for firefighting materials and supplies based on the centre position of the fire. The real-time positions of rescuers, vehicles and UASs can be also displayed.
+
+## Bibliography
+
+- [b-ITU-T X.1352] Recommendation ITU-T X.1352 (2022), *Security requirements for Internet of things devices and gateway*.
+- [b-ITU-T X.1369] Recommendation ITU-T X.1369 (2022), *Security requirements for IoT service platform*.
+- [b-ITU-T Y.4409] Recommendation ITU-T Y.4409/Y.2070 (2015), *Requirements and architecture of the home energy management system and home network services*.
+- [b-ITU-R V.573-4] Recommendation ITU-R V.573-4 (2000), *Radiocommunication vocabulary*.
+- [b-IETF RFC 768] IETF RFC 768 (1980), *User datagram protocol*.
+- [b-IETF RFC 3261] IETF RFC 3261 (2002), *SIP: Session initiation protocol*.
+- [b-IETF RFC 3550] IETF RFC 3550 (2003), *RTP: A transport protocol for real-time applications*.
+- [b-IETF RFC 3711] IETF RFC 3711 (2004), *The secure real-time transport protocol (SRTP)*.
+- [b-IETF RFC 7252] IETF RFC 7252 (2014), *The constrained application protocol (CoAP)*.
+- [b-IETF RFC 7826] IETF RFC 7826 (2016), *Real-time streaming protocol version 2.0*.
+- [b-IETF RFC 9110] IETF RFC 9110 (2022), *HTTP semantics*.
+- [b-IETF RFC 9147] IETF RFC 9147 (2022), *The datagram transport layer security (DTLS) protocol version 1.3*.
+- [b-ISO 1998-6] International Standard ISO 1998-6:2000, *Petroleum industry – Terminology – Part 6: Measurement*.
+- [b-ISO 6707-1] International Standard ISO 6707-1:2020, *Buildings and civil engineering works – Vocabulary – Part 1: General terms*.
+- [b-ISO 7078] International Standard ISO 7078:2020, *Buildings and civil engineering works – Procedures for setting out, measurement and surveying – Vocabulary*.
+- [b-ISO 7686] International Standard ISO 7686:2005, *Plastics pipes and fittings – Determination of opacity*.
+- [b-ISO 10596] International Standard ISO 10596:2009, *Ships and marine technology – Marine wind vane and anemometers*.
+- [b-ISO 10782-1] International Standard ISO 10782-1:1998, *Definitions and attributes of data elements for control and monitoring of textile processes – Part 1: Spinning, spinning preparatory and related processes*.
+- [b-ISO 10788] International Standard ISO 10788:2014, *Space systems – Lunar simulants*.
+- [b-ISO 13065] International Standard ISO 13065:2015, *Sustainability criteria for bioenergy*.
+- [b-ISO 13943] International Standard ISO 13943:2023, *Fire safety – Vocabulary*.
+- [b-ISO 16165] International Standard ISO 16165:2020, *Ships and marine technology – Marine environment protection – Vocabulary relating to oil spill response*.
+
+- [b-ISO 20524-1] International Standard ISO 20524-1:2020, *Intelligent transport systems – Geographic data files (GDF) GDF5.1 – Part 1: Application independent map data shared between multiple sources.*
+- [b-ISO 22932-1] International Standard ISO 22932-1:2020, *Mining – Vocabulary – Part 1: Planning and surveying.*
+- [b-ISO 23611-6] International Standard ISO 23611-6:2012, *Soil quality – Sampling of soil invertebrates – Part 6: Guidance for the design of sampling programmes with soil invertebrates.*
+- [b-ISO 25457] International Standard ISO 25457:2023, *Oil and gas industries including lower carbon energy – Flare details for general refinery and petrochemical service.*
+- [b-ISO/IEC 13818-1] International Standard ISO/IEC 13818-1:2023, *Information technology – Generic coding of moving pictures and associated audio information – Part 1: Systems.*
+- [b-ISO/IEC 20922] International Standard ISO/IEC 20922:2016, *Information technology – Message queuing telemetry transport (MQTT) v3.1.1.*
+- [b-ISO/IEC 22460-2] International Standard ISO/IEC 22460-2:2024, *Cards and security devices for personal identification – ISO UAS license and drone/UAS security module – Part 2: Drone/UAS security module.*
+- [b-ISO/TR 18931] Technical Report ISO/TR 18931:2001, *Imaging materials – Recommendations for humidity measurement and control.*
+- [b-ISO/TR 24188] Technical Report ISO/TR 24188:2025, *Large outdoor fires and the built environment – Global overview of different approaches to standardization.*
+- [b-IWA 33-1] International Standard IWA 33-1:2019, *Technical guidelines for the development of small hydropower plants – Part 1: Vocabulary.*
+- [b-UNSPF] Department of Economic and Social Affairs – Forests (2017). *United Nations strategic plan for forests, 2017-2030.* New York, NY: United Nations. Available [2024-07-24] at: [https://www.un.org/esa/forests/wp-content/uploads/2016/12/UNSPF\\_AdvUnedited.pdf](https://www.un.org/esa/forests/wp-content/uploads/2016/12/UNSPF_AdvUnedited.pdf)
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation
+
+## **ITU-T Y.4233 (01/2025)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Internet of things and smart cities and communities –
+Requirements and use cases
+
+---
+
+**Information and communication technology
+implementation framework for smart public
+health emergency management in smart and
+sustainable cities**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## **Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities**
+
+| | |
+|---------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | Y.100-Y.999 |
+| INTERNET PROTOCOL ASPECTS | Y.1000-Y.1999 |
+| NEXT GENERATION NETWORKS | Y.2000-Y.2999 |
+| FUTURE NETWORKS | Y.3000-Y.3499 |
+| CLOUD COMPUTING | Y.3500-Y.3599 |
+| BIG DATA | Y.3600-Y.3799 |
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800-Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | Y.4000-Y.4999 |
+| General | Y.4000-Y.4049 |
+| Definitions and terminologies | Y.4050-Y.4099 |
+| Requirements and use cases | Y.4100-Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250-Y.4399 |
+| Frameworks, architectures and protocols | Y.4400-Y.4549 |
+| Services, applications, computation and data processing | Y.4550-Y.4699 |
+| Management, control and performance | Y.4700-Y.4799 |
+| Identification and security | Y.4800-Y.4899 |
+| Evaluation and assessment | Y.4900-Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4233
+
+# Information and communication technology implementation framework for smart public health emergency management in smart and sustainable cities
+
+## Summary
+
+Recommendation ITU-T Y.4233 specifies the information and communication technology (ICT) implementation framework of smart public health management in smart and sustainable cities (SSCs).
+
+SSCs are capable of fostering data-driven smart applications to manage limited resources and implement them to thwart the advent of future pandemics of a similar magnitude to the COVID-19 pandemic. Linking SSCs with public health frameworks to manage future pandemics and epidemics and to the attainment of the Sustainable Development Goals (SDGs) (SDG 3: Global health, SDG 1: Poverty eradication and SDG 11: Make cities inclusive, safe, resilient, and sustainable), and to the Sendai Framework for Disaster Risk Reduction is a challenge and serves a dual purpose. With the utilization of appropriate emergency communication and public health frameworks, it will become easier to develop models to predict the spread of diseases, ascertain the source of illnesses, coordinate lockdowns, detect and report symptoms, identify viral strains and provide remote assistance as required with limited human interaction, through an infrastructure based on the Internet of things.
+
+This Recommendation is based on the U4SSC report entitled "Smart public health emergency management and ICT implementations" (listed as U4SSC-2 in the bibliography) and its structure is as follows: it starts with an analysis of the public health context and of corresponding frameworks and returns a generic public health framework, which specifies a pandemic's lifecycle. This generic framework is then interconnected with the SSC and with city resilience. Further, it depicts with unified modelling language (UML) diagrams how this framework can be executed within the SSC environment and highlights the SSC components that play a role in this execution.
+
+## History\*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T Y.4233 | 2025-01-15 | 20 | 11.1002/1000/16028 |
+
+## Keywords
+
+Emergency management framework, ICT implementation framework, information communication technology, pandemics, smart public health, smart sustainable cities.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2025
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|-------------------------------------------------------------------------------------------------|------|
+| 1 Scope ..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere..... | 1 |
+| 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 2 |
+| 6 Introduction to smart public health emergency management in smart and sustainable cities..... | 3 |
+| 7 Smart public health emergency framework and the role of smart sustainable cities.... | 4 |
+| 8 Smart public health framework requirements for ICT implementation in the SSC ..... | 8 |
+| 8.1 General requirements..... | 8 |
+| 8.2 Requirements for data collection..... | 10 |
+| 8.3 Interoperability requirements ..... | 10 |
+| 8.4 Requirements for applications and services ..... | 10 |
+| 8.5 Requirements for communications and other functionalities ..... | 10 |
+| Appendix I – Review of existing public health frameworks ..... | 11 |
+| Bibliography..... | 13 |
+
+
+
+# Recommendation ITU-T Y.4233
+
+## Information and communication technology implementation framework for smart public health emergency management in smart and sustainable cities
+
+# 1 Scope
+
+This Recommendation introduces an ICT implementation framework for public health emergency management within the smart city ecosystem. It explores the context of public health and associates it with the city environment. The result is a generic public health framework, which can be supported in terms of information and communication technology (ICT) implementation by smart sustainable city (SSC) technologies (e.g., Internet of things (IoT), artificial intelligence (AI), data, apps and platforms), to deal with public health emergencies and to provide early responses to epidemics and pandemics. It then concludes with a smart public health framework, which is applied in the SSC, defining a pandemic's lifecycle and specifying when epidemic surveillance tools should be applied for dealing with the outbreaks.
+
+The scope of this Recommendation includes:
+
+- Introduction to public health and corresponding terminology;
+- An analysis of the public health background;
+- Association of public health with SSC and city resilience;
+- Smart public health emergency management framework in SSCs;
+- SSC components that are necessary for the smart public health framework.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T Y.4201] Recommendation ITU-T Y.4201 (2018), *High-level requirements and reference framework of smart city platforms*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 city** [b-ITU-T Y.4900]: An urban geographical area with one (or several) local government and planning authorities.
+
+**3.1.2 city platform** [ITU-T Y.4201]: A computer system or integration of computer systems that uses information and communication technologies (ICTs) to access data sources and process them to offer urban operation and services to the city.
+
+**3.1.3 Internet of things (IoT)** [b-ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.
+
+**3.1.4 smart city platform** [ITU-T Y.4201]: A city platform that offers direct integration of city platforms and systems, or through open interfaces between city platforms and third parties, in order to offer urban operation and services supporting the functioning of city services, as well as efficiency, performance, security and scalability.
+
+**3.1.5 smart sustainable city (SSC)** [b-ITU-T Y.4900]: A smart sustainable city is an innovative city that uses information and communication technologies (ICTs) and other means to improve quality of life, efficiency of urban operation and services and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social, environmental, as well as cultural aspects.
+
+## **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following terms:
+
+**3.2.1 epidemic surveillance:** Ongoing information and communication technology (ICT)-based systematic collection, analysis, interpretation and dissemination of health data, for the planning, implementation and evaluation of public health action against an epidemic.
+
+NOTE – Identification of individuals is out of scope of epidemic surveillance.
+
+**3.2.2 epidemic surveillance system:** An information and communication technology (ICT) system that detects public health outbreaks through the systematic collection of pre-defined big data specific to diseases.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-----|------------------------------------------|
+| AI | Artificial Intelligence |
+| GIS | Geographical Information System |
+| ICT | Information and Communication Technology |
+| IoT | Internet of Things |
+| KPI | Key Performance Indicator |
+| SDG | Sustainable Development Goal |
+| SSC | Smart Sustainable City |
+| UML | Unified Modelling Language |
+
+# **5 Conventions**
+
+In this Recommendation:
+
+The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+
+The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+
+# 6 Introduction to smart public health emergency management in smart and sustainable cities
+
+The COVID-19 pandemic has exposed the global risks and threats posed by unpreparedness, thus lending urgency to the need to build a robust system for early warning, risk reduction and health management. It is believed that the "worst" epidemics (single outbreaks) are most likely to occur in cities where individuals randomly mix (proportionate mixing) [b-Chowell].
+
+Pandemics impact countries and communities, may cause national laws to be rewritten, initiate a restructuring of public health infrastructure and encourage the application of modified methods of combating disease in the areas of epidemic surveillance and lockdowns.
+
+Despite improvements in urban conditions and the emergence of SSCs, the incidence of infectious diseases continues to be on the rise. Therefore, ICTs should play a greater role in predicting pandemics and identifying early warning signals.
+
+Epidemic surveillance has become ICT-based with the use of satellites, drones and of cutting-edge technologies such as cameras, sensors, actuators and the IoT combined with emerging applications (e.g., dashboards, analytics and AI-based estimations).
+
+This Recommendation suggests approaches to utilize the SSC infrastructure in dealing with future health related emergencies.
+
+SSCs are in the process of leveraging cutting-edge technologies to become greener and more autonomous and homogeneous. In this respect, cities form strategies and follow frameworks to adopt ICT innovation, especially in the field of data management, big data analytics and AI, to make cities autonomous or, in other words, enable them to make informed political and management decisions. Such AI-based services could detect emerging trends in the absence of any human intervention. However, whether AI's superiority in terms of speed, accuracy, reliability, latency, volume and convergence is still behind human decision-making capabilities, especially on contentious issues, is still under study [b-Zorins-1] [b-Zorins-2].
+
+During the COVID-19 pandemic, some ICT-based infrastructures in cities were utilized to deal with the emergency (e.g., AI-based estimations for hospital occupancy, mobile applications for crowd-based epidemic data collection and social distancing alerts and web dashboards to visualize the pandemic figures in terms of numbers of cases and deaths).
+
+The public health emergency management process that was followed during the COVID-19 pandemic was a generic three-step process, which, according to the literature cited in Appendix I, includes:
+
+- 1) **Preparatory step – before the crisis:** This step consists of actions that deal with the organization of a public health system that performs continuous threat analysis, accompanied by training activities and information collection, processing and release. It also involves the implementation of measures that secure the community against typical threat factors (data collection and process, risk analysis, etc.). This step can be upgraded with the contribution of ICTs, in terms of big data analytics, more accurate risk estimation, ICT-based training and training on ICT tools for emergency management (e.g., geographical information system (GIS) and fleet management).
+- 2) **Operational step – after registration of the event:** This step consists of initiatives that are launched after the appearance of a public health emergency. An epidemic surveillance system is applied to continually monitor the progress of the crisis, the application of an appropriate clinical response and measures to minimize and control the outbreak of the pandemic.
+- 3) **Concluding step – elimination of the consequences:** This step consists of initiatives that try to strengthen social coherence and economically support communities. ICTs can be utilized to enhance economic growth (e.g., as business platforms and for the data economy), monitor community recovery via data collection and key performance indicator (KPI) calculation and enhance evidence-based policy-making.
+
+This management process has similarities with a crisis management/emergency framework such as the one presented in Figure 1.
+
+![Figure 1 – Emergency management framework [b-U4SSC-2]. The diagram illustrates a cyclical emergency management process. It starts with 'Social systems' (Built environment, Natural systems) and 'Inherent vulnerability' (Inherent resilience). A 'Disaster' (Sources, Characteristics, Immediate effects) leads to 'Coping responses', which then leads to another 'Disaster'. This triggers a 'Capacity exceeded' state. If 'Yes', it leads to 'Adaptation' (Improvisation, Social learning), which then leads to 'Degree of recovery' (High/Low). If 'No', it leads to 'Mitigation'. The process is divided into 'Short Term' and 'Long Term' phases. 'Preparedness' is shown as a foundational element. A vertical arrow on the right indicates the 'Degree of recovery' from Low to High. The diagram is labeled Y.4233(25) in the bottom right corner.](f4fdd410cdb84df81274da55721e56fb_img.jpg)
+
+Figure 1 – Emergency management framework [b-U4SSC-2]. The diagram illustrates a cyclical emergency management process. It starts with 'Social systems' (Built environment, Natural systems) and 'Inherent vulnerability' (Inherent resilience). A 'Disaster' (Sources, Characteristics, Immediate effects) leads to 'Coping responses', which then leads to another 'Disaster'. This triggers a 'Capacity exceeded' state. If 'Yes', it leads to 'Adaptation' (Improvisation, Social learning), which then leads to 'Degree of recovery' (High/Low). If 'No', it leads to 'Mitigation'. The process is divided into 'Short Term' and 'Long Term' phases. 'Preparedness' is shown as a foundational element. A vertical arrow on the right indicates the 'Degree of recovery' from Low to High. The diagram is labeled Y.4233(25) in the bottom right corner.
+
+**Figure 1 – Emergency management framework [b-U4SSC-2]**
+
+Before the event, preparedness planning engages social, natural and physical systems and initiates response processes. In the case of an outbreak, there is a mitigation step to comprehend the impact and release short-term treatment and relief activities. The introduction of ICTs transforms this process to a smart public health emergency management process, which can be integrated with the SSCs as illustrated in clause 7.
+
+# 7 Smart public health emergency framework and the role of smart sustainable cities
+
+The implementation of a smart public health emergency framework involves the identification of the appropriate ICT components that can be used in public health emergency management and the determination of public health stakeholders. It must address three generic steps: the pre-crisis step, the emergency and the post-event phase. The pre-crisis step addresses the establishment of a network of people and professionals, the strengthening of social coherence and the development of government–community cooperation through the use of ICTs. During the emergency, ICT components can be utilized to control the response. Finally, during the post-event phase, continuous big data collection and ICT-based monitoring are combined with community protection.
+
+In terms of data generation and access, the smart public health emergency framework consists of the previously defined three steps requiring access to specific repositories:
+
+- 1) The *interventions repository* that stores the public health measures planned or undertaken for the community's safety.
+- 2) The *incidents repository*, where information that is being collected by research labs, hospitals and epidemic surveillance systems is stored.
+- 3) The *KPIs repository*, which collects processed data for the measurement of the crisis size and sprawl (e.g., the epidemic curve).
+- 4) The *civil protection repository*, which stores corresponding data (e.g., source allocation, activities and events).
+
+Some indicative information systems that should interoperate and collaborate are the following:
+
+- 1) The *national public health control centre dashboard* where all the collected and processed data will be depicted.
+- 2) The *national e-health system*.
+
+- 3) The *civil protection system*.
+- 4) The *external dashboards* that belong to international organizations (e.g., WHO COVID-19 dashboard [b-WHO]) or regional organizations (e.g., European Centre for Disease Prevention and Control [b-EU]).
+
+With respect to SSCs, both the framework and data flow requirements utilize smart infrastructure, smart services and crowdsourcing in cities. The SSC infrastructure can detect operational changes when an emergency occurs and interact with local safety systems, as in environmental disasters, in the following phases [b-Anthopoulos]:
+
+- 1) Phase 1 (IoT sensing): Uses city sensors to predict disasters, while monitoring community behaviour after an epidemic (e.g., personal protection and distancing).
+- 2) Phase 2 (Disaster safety monitoring): Analyses real-time collected data from various IoT devices (e.g., sewage analysis) to estimate epidemic size.
+- 3) Phase 3 (Disaster simulation): The disaster-affected population area is estimated by multidimensional data analysis to mitigate the damage from the epidemic.
+- 4) Phase 4 (Safety management): Determines the countermeasures (e.g., alerts and public announcements) when an epidemic has occurred to mitigate the damage suffered by the community.
+
+Similar synergies can be considered to exist between an SSC, its SSC platform and all the local operational subsystems that are based on utilities (e.g., water, energy and waste) or on typical services (e.g., health and training) that are affected during a crisis. Accordingly, Figure 2 depicts how an SSC architecture [b-U4SSC-2] serves these four phases during a disaster. The local physical environment and infrastructure are sensed by the SSC infrastructure which triggers the safety management phases (2, 3 and 4) with the support of the medical and safety teams (soft infrastructure), enabling information to flow across the entire SSC ecosystem.
+
+![Figure 2: IoT-based emergency management with the SSC architecture [b-U4SSC-2]. The diagram illustrates a multi-layered architecture for disaster safety monitoring, simulation, and management. It is organized into five main horizontal layers: 1. Natural environment (top, blue background) with icons for weather, mountains, trees, and a crane. 2. Hard infrastructure (Non ICT-based) (green background) with icons for a water tap, wind turbine, train, hospital, fire truck, hotel, trash bin, recycling bin, construction site, government building, and bank. 3. IoT sensing (Phase 1) (yellow background) with a large yellow arrow pointing down to the next layer. 4. Hard infrastructure (ICT-based) (dark blue background) with icons for server racks, wireless tower, router, satellite, laptop, desktop monitor, tablet, smartphone, and clock. 5. Smart services (orange background) with icons for smart water, smart energy, smart transportation, smart health care, smart safety/emergency, smart education, smart tourism, smart waste management, smart buildings, smart government, and smart economy. Below the smart services layer is the Soft infrastructure (purple background) with icons for various digital services and data flows. At the bottom, three phases are indicated: Disaster safety monitoring (Phase 2) in yellow, Disaster simulation (Phase 3) in green, and Safety management (Phase 4) in red, connected by red arrows indicating a sequential process.](d4af765160d04ecef538e5066006dc77_img.jpg)
+
+Figure 2: IoT-based emergency management with the SSC architecture [b-U4SSC-2]. The diagram illustrates a multi-layered architecture for disaster safety monitoring, simulation, and management. It is organized into five main horizontal layers: 1. Natural environment (top, blue background) with icons for weather, mountains, trees, and a crane. 2. Hard infrastructure (Non ICT-based) (green background) with icons for a water tap, wind turbine, train, hospital, fire truck, hotel, trash bin, recycling bin, construction site, government building, and bank. 3. IoT sensing (Phase 1) (yellow background) with a large yellow arrow pointing down to the next layer. 4. Hard infrastructure (ICT-based) (dark blue background) with icons for server racks, wireless tower, router, satellite, laptop, desktop monitor, tablet, smartphone, and clock. 5. Smart services (orange background) with icons for smart water, smart energy, smart transportation, smart health care, smart safety/emergency, smart education, smart tourism, smart waste management, smart buildings, smart government, and smart economy. Below the smart services layer is the Soft infrastructure (purple background) with icons for various digital services and data flows. At the bottom, three phases are indicated: Disaster safety monitoring (Phase 2) in yellow, Disaster simulation (Phase 3) in green, and Safety management (Phase 4) in red, connected by red arrows indicating a sequential process.
+
+Y.4233(25)
+
+**Figure 2 – IoT-based emergency management with the SSC architecture [b-U4SSC-2]**
+
+In this regard, the public health emergency management framework must include the SSC infrastructure as well as incorporating local stakeholders that played a crucial role during the pandemic, as can be depicted in a UML use-case diagram (Figure 3).
+
+The SSC infrastructure can be used to continuously collect data from the local environment (sensors and even text, voice and video from local media) and contribute to the national public health control centre, together with the data from the national research labs and hospitals (*process step 1.2.4 of Figure 3*). This SSC role can be included in national planning (*process step 1.1 of Figure 3*). The collected data can be processed and analysed and perform threat analysis at local levels (*process step 1.4.1 of Figure 3*).
+
+The SSC infrastructure can contribute with the release of a public website that will post corresponding information (*process step 2.2.1 of Figure 3*) as well as supporting the national epidemic surveillance system with activity-based data collection from sensors, cameras and even media (*process step 2.2.2 of Figure 3*). Activity monitoring, analytics and AI-based predictions at the local level (*process step 2.2.3 of Figure 3*), either with the use of local control centres or independently (sewage analysis), can also contribute.
+
+Additionally, the SSC infrastructure can be used by safety stakeholders (police, hospitals, etc.) to monitor activity (i.e., social distancing apps) (*process steps 2.2.3 and 2.2.4 of Figure 3*) as well as to submit location-based alerts (notifications on crowded areas and/or spaces to be avoided owing to incidents, busy bike lanes, etc.) (*process step 2.3.1 of Figure 3*). Local stakeholders can also start developing or sharing ICT tools and solutions at an early stage after the appearance of a crisis (*process*
+
+step 1.2.5 of Figure 3) and these tools can be used for crowdsensing (process steps 1.2.6 and 2.2.4 of Figure 3).
+
+Additionally, early notifications can be submitted and received via smart applications (e.g., Corona Map, Corona 100, Self-diagnosis and Mask Apps).
+
+The framework, depicted on the UML use-case diagram (Figure 3), shows when epidemic surveillance with the ICT is triggered (the framework's process step 2.2: *Secondary prevention of Figure 3*) and when it ends (at the end of the framework's process step 2.3: *Tertiary prevention of Figure 3*).
+
+
+
+The diagram is a UML use-case diagram for public health management in SSC. It features seven actors: Working group, Control centre, Smart city, Research labs, Hospitals, Local stakeholders, and WHO/Other national systems. The use cases are organized into three main phases:
+
+- Phase 1: Planning and Primary prevention**
+ - 1.1 Planning** (Working group): Resource allocation, Duty assignment, Network setup.
+ - 1.3 Primary prevention** (Working group): Public health training, Community training, Establish community coherence.
+ - 1.4 Threat analysis** (Control centre): Distinguish biological/chemical incidents.
+ - 1.5 Pre-emption of attack** (Control centre): Case recognition, Impact assessment, Preparing to respond, Preparing public information and communication packages.
+ - 1.2.4 Continuous sensing (IoT, media)** (Smart city).
+ - 1.2.1 Laboratory and epidemic data collection** (Research labs).
+ - 1.2.2 Clinical data collection** (Hospitals).
+ - 1.2.5 ICT tools development** (Local stakeholders).
+ - 1.2.6 Crowd sensing** (Local stakeholders).
+ - 1.2.3 Alerting public health systems** (WHO/Other national systems).
+- Phase 2: Response and Secondary prevention**
+ - 2.1 Response** (Working group): Public health interventions, High-risk population groups' identification, Risk factor determination.
+ - 2.2 Secondary prevention** (Working group): Establish surveillance and monitoring systems, Improve protective systems for citizens (e.g., lockdowns).
+ - 2.2.1 Activity monitoring** (Control centre): Data analysis and indicators' calculation, Interventions' effectiveness monitoring, Epidemic curve (with data gathered on cases over time).
+ - 2.2.2 Activity-based data collection (IoT, media, etc.)** (Smart city).
+ - 2.2.3 Activity monitoring at local level/AI analytics** (Smart city).
+ - 2.2.5 Early warnings and location-based notifications** (Smart city).
+ - 2.2.4 Crowd sensing** (Local stakeholders).
+ - 1.6 Data collection** (WHO/Other national systems): Processed data from the system.
+- Phase 3: Tertiary prevention**
+ - 2.3 Tertiary prevention** (Working group): Early detection of the sources, Prevent the extension of impairments, Rescue the survivors, Console the rest of the population.
+ - 2.3.1 Community notifications** (Local stakeholders).
+
+The diagram shows the flow of information and actions between these actors and use cases across different stages of epidemic management. The diagram is labeled Y.4233(25) in the bottom right corner.
+
+UML use-case diagram for public health management in SSC. The diagram shows actors: Working group, Control centre, Smart city, Research labs, Hospitals, Local stakeholders, and WHO/Other national systems. Use cases are organized into three main phases: 1. Planning and Primary prevention, 2. Response and Secondary prevention, and 3. Tertiary prevention. The diagram illustrates the flow of information and actions between these actors and use cases across different stages of epidemic management.
+
+**Figure 3 – A UML use-case framework for public health management in SSC [b-U4SSC-2]**
+
+Considering data flows, the corresponding UML diagram (Figure 4) shows the local entities (local stakeholders, SSC infrastructure and SSC dashboard for local monitoring) and the ICT solutions repository where the applications will be delivered and accessed by the community. Corresponding requests and flows are simple, since ICT solutions contribute to the repositories. However, they also collect data and notifications. The potential local SSC dashboard also interacts with the rest of the data sources and analyses and depicts information, and it performs threat analyses that can be submitted both to apps and to the national public health control centres.
+
+![UML data flow diagram of the framework in SSC [b-U4SSC-2]. The diagram shows a complex network of interactions between various entities. Key components include: 1.1 Plan drafting, 1.2 Data requests, 1.3 Primary prevention, 1.4 Threat analysis, 2. Response and prevention, Working group, Control centre dashboard, Civil protection system, Local stakeholders, ICT solutions repository, ICT solutions, SSC infrastructure, SSC dashboard, WHO/Others' dashboard, Hospitals' e-Health system, Research Labs' e-Health system, KPIs file, Incidents repository, and Civil protection repository. Arrows indicate data flow between these components, with some components having multiple incoming and outgoing flows. The diagram is color-coded with blue circles for main processes, blue rectangles for supporting systems, and red rectangles for external or specific data sources.](4801720824e4b5e2361a5564f91cfb70_img.jpg)
+
+UML data flow diagram of the framework in SSC [b-U4SSC-2]. The diagram shows a complex network of interactions between various entities. Key components include: 1.1 Plan drafting, 1.2 Data requests, 1.3 Primary prevention, 1.4 Threat analysis, 2. Response and prevention, Working group, Control centre dashboard, Civil protection system, Local stakeholders, ICT solutions repository, ICT solutions, SSC infrastructure, SSC dashboard, WHO/Others' dashboard, Hospitals' e-Health system, Research Labs' e-Health system, KPIs file, Incidents repository, and Civil protection repository. Arrows indicate data flow between these components, with some components having multiple incoming and outgoing flows. The diagram is color-coded with blue circles for main processes, blue rectangles for supporting systems, and red rectangles for external or specific data sources.
+
+Y.4233(25)
+
+**Figure 4 – A UML data flow diagram of the framework in SSC [b-U4SSC-2]**
+
+City policy-makers who follow this framework can support preventing communities from being under a continuous epidemic surveillance even after the end of a pandemic or other public health emergencies.
+
+# 8 Smart public health framework requirements for ICT implementation in the SSC
+
+## 8.1 General requirements
+
+The analysis in the previous clauses indicates that the ICT implementation of the smart public health emergency management framework is recommended to align with the reference framework of a smart city platform [ITU-T Y.4201].
+
+The SSC components depicted in Figure 5, where the reference framework of a smart city platform [ITU-T Y.4201] is shown with extensions represented by the components dashboard and website and city apps, are required for the implementation of the smart public health emergency management framework.
+
+NOTE – The proposed smart public health framework is applied in the health care smart service group of the reference framework and uses all the smart city platform components and expands them with the incorporation of the components dashboard and website for public information release to the community (*Steps 1.5 and 2.3.1 in the framework of Figure 3*), and the city apps that are developed by the community to support dealing with the emergency (*Steps 1.2.5, 1.2.6 and 2.3.1 in the framework of Figure 3*).
+
+
+
+The diagram illustrates the SSC components for the ICT implementation of the smart public health emergency management framework. It is structured as follows:
+
+- Smart services** (top green box): Includes e-Government, Health care (highlighted with a red border), Transportation, Tourism, Logistics, Environment, and others.
+- SSC PLATFORM** (central grey box):
+ - Security and management functions**: Security, Monitoring, Audit, Logging, OAM, Configuration.
+ - Services support functions**: e-Government support, ..., Transportation support.
+ - Interfacing functions**: APIs, Open data portal.
+ - Data/knowledge functions**: Data management, Data analysis, Real-time repository, Big data, GIS.
+ - Acquisition/interconnection functions**: Abstract, Tagging.
+- Data and computation providers** (right green box): Includes Database and computation systems.
+- City IoT** (bottom green box): Includes Sensing and data collection system (sensors, RFID, video) and City infrastructure (water, gas, electricity, traffic, buildings).
+- Interfaces**:
+ - Services interface**: Connects Smart services to the SSC PLATFORM.
+ - Interoperability interface**: Connects the SSC PLATFORM to Data and computation providers.
+ - Acquisition interface**: Connects the SSC PLATFORM to City IoT.
+- External Applications**:
+ - Dashboard and Website**: Connected to the SSC PLATFORM via a bidirectional arrow.
+ - City Apps**: Connected to the SSC PLATFORM via a bidirectional arrow.
+
+Figure 5: SSC components required for the ICT implementation of the smart public health emergency management framework. The diagram shows a central 'SSC PLATFORM' block with four main functional areas: Security and management functions, Services support functions, Interfacing functions, and Data/knowledge functions. It also includes an Acquisition/interconnection functions section. The platform is connected to 'Smart services' (e-Government, Health care, Transportation, Tourism, Logistics, Environment, etc.), 'Data and computation providers' (Database and computation systems), and 'City IoT' (Sensing and data collection system, City infrastructure). The platform also interacts with 'Dashboard and Website' and 'City Apps' via interfaces.
+
+Y.4233(25)
+
+NOTE – OAM: operation and maintenance.
+
+**Figure 5 – SSC components required for the ICT implementation of the smart public health emergency management framework**
+
+The "Dashboard and website" and "City Apps" applications are required to be integrated with the SSC platform via appropriate interfaces.
+
+NOTE – As shown in Figure 5, the dashboard and website application interacts unidirectionally with the smart city platform as it only receives information from it. On the other hand, the city apps interact bidirectionally with the smart city platform as they can both collect and transmit information to it.
+
+## 8.2 Requirements for data collection
+
+Information relative to the public health emergency is collected from the urban space (framework *process step 1.2.4* and *process step 2.2.2 of Figure 3*) and feeds into the public health threat analysis system (framework *process step 1.4 of Figure 3*) and the epidemic curves (framework *process step 2.2.1 of Figure 3*).
+
+Data is required to be collected by the SSC platform from the IoT devices installed in the city, labelled *city IoT infrastructure* [b-ITU-T Y.3605].
+
+NOTE 1 – Devices include cameras, environmental sensors, new types of sensors (e.g., for sewage analysis) and biosensors.
+
+Moreover, data is required to be collected by the SSC platform from the community via applications (web-based and mobile apps) labelled *city apps*.
+
+NOTE 2 – These applications collect data from the community in forms of crowdsourcing [b-ITU-T E.812] (outbreak tracing; public space use, etc.).
+
+Data is required to be fed by the SSC platform into the public health threat analysis system and the epidemic curves.
+
+Location-based notifications are recommended to be submitted by the SSC platform to the city apps (framework *process steps 1.2.5, 1.2.6 and 2.2.5 of Figure 3*).
+
+## 8.3 Interoperability requirements
+
+Interoperability (organizational, semantic and technological) among the SSC stakeholders via the SSC platform is required to support a city when it faces pandemics or other public health emergencies. To facilitate interoperability, standards are required to be used for communication and exchanging data; for example, gateways and application programming interfaces (APIs) might act as a glue between the components of the SSC platform [b-U4SSC-1].
+
+## 8.4 Requirements for applications and services
+
+ICT-based services are required to be offered to the community in order to ensure its public health conditions, which are labelled *smart services*.
+
+Smart services are required to support location information (framework *process steps 2.2.1 and 2.3.1 of Figure 3*).
+
+Smart services are required to generate alerts before and during the crisis (e.g., call social services or the security services in the city to respond to an incident).
+
+NOTE – These smart services may be custom-triggered, AI-based or other.
+
+## 8.5 Requirements for communications and other functionalities
+
+Information is required to be generated and offered to the community via *city dashboard*, *website* and *city apps*.
+
+NOTE – All of these can visualize outbreak data and other indices that measure the size of the outbreak (framework *process steps 2.2.1 and 2.2.3 of Figure 3*).
+
+# Appendix I
+
+## Review of existing public health frameworks
+
+(This appendix does not form an integral part of this Recommendation.)
+
+Table I.1 lists some existing public health frameworks.
+
+**Table I.1 – Existing public health frameworks**
+
+| Framework | Context |
+|---------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Sendai Framework (Sendai Framework for Disaster Risk Reduction 2015-2030) | Priority 1: Understanding disaster risk.
Priority 2: Strengthening disaster risk governance to manage disaster risk.
Priority 3: Investing in disaster risk reduction for resilience.
Priority 4: Enhancing disaster preparedness for effective response and to "build back better" in recovery, rehabilitation and reconstruction.
|
+| World Bank public health toolkit | - 1 Case recognition to trigger interventions.
- 2 Public health impact assessment.
- 3 Justification for public health interventions and corresponding planning.
- 4 Effectiveness of monitoring interventions.
- 5 Identification of high-risk population groups.
- 6 Risk factor determination.
|
+| Process for safety performance indicator (SPI) definition | - 1 SPI team.
- 2 Key issues of concern.
- 3 Outcome indicators.
- 4 Activity indicators.
- 5 Data collection/process.
- 6 Taking action.
- 7 SPI programme evaluation.
|
+| i-Prevention model for training, team building and surveillance | - 1 i-Prevention web application.
- 2 Community training (civil defence guard).
- 3 Neighbourhood watch surveillance process.
|
+| Intelligent tutoring systems (ITS) for community training and awareness | - 1 Preparedness programme design.
- 2 Teaching with ITS.
- 3 Community-based public health preparedness.
|
+| United States of America national framework for crisis standards of care | Framework in boxes for care preparation, substitution, adaptation, conservation, reuse and reallocation. |
+| United States Centres for Disease Control and Prevention (CDC) Global Infectious Disease Strategy | - 1 International outbreak assistance.
- 2 Global approach to disease surveillance.
- 3 Applied research on diseases of global importance.
- 4 Application of proven public health tools.
- 5 Global initiatives for disease control.
- 6 Public health training and capacity-building.
|
+
+**Table I.1 – Existing public health frameworks**
+
+| Framework | Context |
+|---------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Epidemic Outbreak System (EOS): model for microarray identification of organisms in an outbreak investigation | - 1 Biologic agent identification.
- 2 Diagnostic correlation with specific syndromic indicators.
- 3 Longitudinal tracking of affected population.
- 4 Relationship, association and predictive modelling.
- 5 Clinical accuracy.
- 6 Cross-platform comparison with chain reaction technologies.
- 7 Predictive modelling for epidemic surveillance.
|
+| Operational Risk Management (ORM) model | - 1 Identifying threats, targets or hazards.
- 2 Assess threats risk(s).
- 3 Make threat (risk) control decisions.
- 4 Implement threat (risk) controls.
- 5 Supervise or monitor the effect(s) of control implementation.
|
+| Mathematical epidemiology model for worst-case epidemic outbreaks | SIR (susceptible-infective-removed) compartmental epidemic model: the population under consideration is divided into classes or compartments defined by epidemiological status. |
+| Model for city resilience based on Arup/Rockefeller (2014) and Bujones/USAID (2013) frameworks | - 1 Definition of resilience dimensions.
- 2 Definition of resilience indicators.
- 3 Definition of resilience goals.
- 4 Justification of indicators and goals.
- 5 Measurement and monitoring of indicators.
- 6 Strategic alignment to goals.
|
+
+NOTE – References for these frameworks: [b-UNDRR], [b-Garcia-Abreu], [b-OECD], [b-Linkov], [b-Tseytlin], [b-Institute of Medicine], [b-Hick], [b-Chowell], [b-Furushima], [b-Rockefeller], [b-Bujones].
+
+# Bibliography
+
+- [b-ITU-T E.812] Recommendation ITU-T E.812 (2020), *Crowdsourcing approach for the assessment of end-to-end quality of service in fixed and mobile broadband networks*.
+- [b-ITU-T Y.3605] Recommendation ITU-T Y.3605 (2020), *Big data – Reference architecture*.
+- [b-ITU-T Y.4000] Recommendation ITU-T Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+- [b-ITU-T Y.4900] Recommendation ITU-T Y.4900/L.1600 (2016), *Overview of key performance indicators in smart sustainable cities*.
+- [b-Anthopoulos] Anthopoulos, L. (2017), *Understanding Smart Cities – A Tool for Smart Government or an Industrial Trick?* Cham, Springer.
+- [b-Chowell] Chowell, G. and Castillo-Chavez, C. (2003), *Worst-Case Scenarios and Epidemics*, In Banks, H. T. and Castillo-Chavez, G. (Eds), *Bioterrorism: Mathematical modelling applications in homeland security*, Philadelphia, Society for Industrial and Applied Mathematics.
+- [b-EU] European Centre for Disease Prevention and Control (2024), COVID-19.
+- [b-Furushima] Furushima, D., Kawano, S., Ohno, Y., and Kakehashi, M. (2017), *Estimation of the Basic Reproduction Number of Novel Influenza A (H1N1) pdm09 in Elementary Schools Using the SIR Model*, The Open Nursing Journal, Vol. 11, pp. 64-72.
+- [b-Hick] Hick, J. L., Barbera, J.A., and Kelen, G. D (2009), *Refining Surge Capacity: Conventional, Contingency, and Crisis Capacity*, Disaster Medicine and Public Health Preparedness, Vol. 3, Suppl. 2, S59–S67.
+- [b-Institute of Medicine] Institute of Medicine (2005), *Linking Hazards And Public Health: Communication And Environmental Health*, In Hook and Rogers (Eds), *Public Health Risks of Disasters: Communication, Infrastructure and Preparedness*, Washington, DC, National Academies Press.
+- [b-Bujones] Bujones, A., Jaskiewicz, K., Linakis, L., and McGirr, M. (2013), *A Framework for Analysing Resilience In Fragile and Conflict-Affected Situations*, New York, Columbia.
+- [b-Linkov] Linkov, F., Laporte, R., Sauer, F. and Shubnikov, E. (2007), *Public Health Preparedness: I-Prevention and Global Health Network Supercourse*, In Cummings, C.E. and Stikova, E. (Eds) *Strengthening National Public Health Preparedness and Response to Chemical, Biological and Radiological Agent Threats, Human and Societal Dynamics*, Vol. 20, Amsterdam, IOS Press.
+- [b-OECD] Organisation for Economic Co-operation and Development (2008), *Guidance on developing Safety Performance Indicators related to Chemical Accident Prevention, Preparedness and Response*, OECD Publishing, Paris.
+- [b-Rockefeller] Rockefeller Foundation (2014), *City Resilience Framework*.
+
+- [b-Tseytlin] Tseytlin, E. (2007), *Public Health Preparedness and Effective Access to Information: Getting the Most Out of Your PC*, In Cummings, C.E. and Stikova, E. (Eds) Strengthening National Public Health Preparedness and Response to Chemical, Biological and Radiological Agent Threats, Human and Societal Dynamics, Vol. 20, Amsterdam, IOS Press.
+- [b-U4SSC-1] United for Smart Sustainable Cities (U4SSC) (2022), *Setting the stage for Minimal Interoperability Mechanisms*.
+
+- [b-U4SSC-2] United for Smart Sustainable Cities (U4SSC) (2021), *Smart public health emergency management and ICT implementations*.
+
+- [b-UNDRR] United Nations Office for Disaster Risk Reduction (2015), *Sendai Framework for Disaster Risk Reduction 2015-2030*.
+- [b-WHO] World Health Organization (2024), *WHO COVID-19 Dashboard*.
+
+- [b-Garcia-Arbreu] Garcia-Abreu, A., Halperin, W., Danel, I. (2002), *Public Health Surveillance Toolkit: A Guide for Busy Task Managers*, Washington, DC, World Bank.
+- [b-Zorins-1] Zorins, A., and Grabusts, P. (2019), *Safety of Artificial Superintelligence*, Environment. Technology. Resources. Proceedings of the 12th International Scientific and Practical Conference, Vol. 2.
+- [b-Zorins-2] Zorins, A., and Grabusts, P. (2015), *Artificial Neural Networks and Human Brain: Survey of Improvement possibilities of learning*, Environment. Technology. Resources. Proceedings of the 10th International Scientific and Practical Conference, Vol. 3.
+
+
+
+# SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation
+
+## **ITU-T Y.4234/F.742.3 (01/2025)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Internet of things and smart cities and communities –
+Requirements and use cases
+
+SERIES F: Non-telephone telecommunication services
+Multimedia services
+
+---
+
+**Requirements, capabilities and deployment
+models for e-learning in remote classrooms**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+# Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+| | |
+|---------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | Y.100-Y.999 |
+| INTERNET PROTOCOL ASPECTS | Y.1000-Y.1999 |
+| NEXT GENERATION NETWORKS | Y.2000-Y.2999 |
+| FUTURE NETWORKS | Y.3000-Y.3499 |
+| CLOUD COMPUTING | Y.3500-Y.3599 |
+| BIG DATA | Y.3600-Y.3799 |
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800-Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | Y.4000-Y.4999 |
+| General | Y.4000-Y.4049 |
+| Definitions and terminologies | Y.4050-Y.4099 |
+| Requirements and use cases | Y.4100-Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250-Y.4399 |
+| Frameworks, architectures and protocols | Y.4400-Y.4549 |
+| Services, applications, computation and data processing | Y.4550-Y.4699 |
+| Management, control and performance | Y.4700-Y.4799 |
+| Identification and security | Y.4800-Y.4899 |
+| Evaluation and assessment | Y.4900-Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4234/F.742.3
+
+# Requirements, capabilities and deployment models for e-learning in remote classrooms
+
+## Summary
+
+Recommendation ITU-T Y.4234/F.742.3 includes a concept of e-learning in remote classrooms, i.e. places where information and communication technology (ICT) infrastructure and e-learning facilities, such as digital connectivity, computers, computer applications, virtual collaboration, online and digital educational catalogues, are made available for learners to educate themselves.
+
+There is a wide and rising disparity in access to quality education between remote and rural areas in most countries when compared to their urban counterparts. Various international organizations (e.g. the United Nations (UN) and the International Telecommunication Union (ITU)) and national bodies (such as ministries) worldwide have acknowledged the need for urgent and concerted efforts towards the fulfilment of the promise of universalization of education.
+
+It is also very clear that the future of education is digital and immersive, and that the delivery of future education will be heavily dependent on access to appropriate (ICT) infrastructure and connectivity.
+
+At the same time, there is a dire shortage of trained teaching staff, in both developed and developing countries, and the situation is much worse in the remote and underserved areas. In most of these places, there are very few teachers, only some of whom are capable of keeping pace with the demands of fast-evolving educational curriculums. In addition to education and learning, these remote areas are disadvantaged by a lack of access to other facilities, such as health and vocational capability development. New standards are required that bridge the digital divide and mitigate the growing disparity, by ensuring that more and more online services are delivered equitably to the remote and underserved areas.
+
+This Recommendation describes the challenges and considerations for providing digital education to remote schools, and develops requirements, capabilities and deployment models to impart high quality e-learning services in remote classrooms in rural and remote areas.
+
+## History \*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------------|------------|-------------|--------------------|
+| 1.0 | ITU-T Y.4234/F.742.3 | 2025-01-15 | 20 | 11.1002/1000/16029 |
+
+## Keywords
+
+Digital connectivity, digital divide, digital education tools, educational facilities, e-learning, hybrid classrooms, ICT infrastructure, remote classrooms, rural areas, underserved areas, virtual collaboration.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g. interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2025
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+# Table of Contents
+
+| | | Page |
+|----|----------------------------------------------------------------------------------------------|------|
+| 1 | Scope ..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 2 |
+| | 3.1 Terms defined elsewhere..... | 2 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 2 |
+| 6 | Overview of challenges and considerations for education in remote and underserved areas..... | 3 |
+| | 6.1 Challenges for education in remote and underserved areas ..... | 3 |
+| | 6.2 Considerations for deployment of e-learning in remote classrooms ..... | 3 |
+| 7 | Concept and Internet connectivity scenarios for e-learning in remote classrooms ..... | 4 |
+| | 7.1 Concept of e-learning ..... | 4 |
+| | 7.2 Internet connectivity scenarios for e-learning ..... | 5 |
+| 8 | Requirements for e-learning in remote classrooms ..... | 6 |
+| | 8.1 Internet connectivity, multimedia and ICT resources ..... | 6 |
+| | 8.2 Learning management and digital content management systems ..... | 7 |
+| | 8.3 Advanced learning resources..... | 7 |
+| 9 | Capabilities of remote classrooms to support e-learning..... | 8 |
+| | 9.1 Internet connectivity, multi-media and ICT resources ..... | 8 |
+| | 9.2 Learning management and digital content management systems ..... | 8 |
+| | 9.3 Advanced learning resources..... | 9 |
+| | 9.4 Complementary non-technical capabilities ..... | 9 |
+| 10 | Deployment models for remote classrooms to support e-learning ..... | 9 |
+| | 10.1 Deployment model for remote classrooms with Internet connectivity ..... | 9 |
+| | 10.2 Deployment model for remote classrooms with no Internet connectivity ..... | 10 |
+| | Appendix I – Use cases for e-learning in remote and rural areas ..... | 12 |
+| | Bibliography..... | 13 |
+
+
+
+# Recommendation ITU-T Y.4234/F.742.3
+
+# Requirements, capabilities and deployment models for e-learning in remote classrooms
+
+# 1 Scope
+
+There is a wide and rising inequality in access to quality education in remote and underserved areas around the world and the acknowledgement that immediate efforts are required for the fulfilment of the promise for the universalization of education. It is also very clear that the future of education is digital and immersive, and that delivery of that future education will be heavily dependent on access to appropriate information and communication technology (ICT) infrastructure and connectivity.
+
+To bridge the digital divide, and to ensure that the most vulnerable in society are not increasingly denied access to services, new standards are required to address the digital divide and the threat of the growing disparity as more and more services are delivered online.
+
+This Recommendation includes a concept of e-learning in remote classrooms, i.e. places where ICT infrastructure and e-learning facilities, such as digital connectivity, computers, computer applications, virtual collaboration, and online and digital content catalogues, are made available for willing learners to educate themselves by using said educational facilities.
+
+This Recommendation includes:
+
+- Challenges and considerations for education in remote and underserved areas;
+- Concept and Internet connectivity scenarios for e-learning in remote classrooms;
+- Requirements for e-learning in remote classrooms;
+- Capabilities of remote classrooms to support e-learning; and
+- Deployment models for remote classrooms to support e-learning.
+
+Relevant use cases are provided in Appendix I.
+
+NOTE 1 – Accessibility aspects related to persons with disabilities, persons with age-related disabilities and those with specific needs are out of the scope of this Recommendation.
+
+NOTE 2 – Security and privacy-related requirements are outside the scope of this Recommendation. However, it is expected that the hardware, software and applications that may be used in the e-learning classrooms will handle data security and privacy-related requirements, as per applicable standards.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- [ITU-T L.1700] Recommendation ITU-T L.1700 (2016), *Requirements and framework for low-cost sustainable telecommunications infrastructure for rural communications in developing countries*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+None.
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 e-learning:** Any form of learning that takes place through the use of information and communication technologies (ICTs) and tools that allow people to learn anytime and anywhere, including through hybrid classrooms, online classrooms, online courses, webinars, online educational games and online simulations.
+
+**3.2.2 hybrid classroom:** A classroom that has the Internet connectivity, information and communication technology (ICT) infrastructure and expert instructor(s) to simultaneously teach students physically present in the classroom, whilst also delivering e-learning to other classrooms virtually.
+
+**3.2.3 remote classroom:** A classroom where teaching assistants and appropriate information and communication technologies (ICTs) are used for the learners to participate in learning from an expert instructor who is physically present and teaching a classroom elsewhere.
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-----|------------------------------------------|
+| AR | Augmented Reality |
+| ICT | Information and Communication Technology |
+| LMS | Learning Management System |
+| PII | Personally Identifiable Information |
+| VR | Virtual Reality |
+| XR | Extended Reality |
+
+# 5 Conventions
+
+In this Recommendation, requirements are classified as follows:
+
+- The keywords "**is required to**" or "**are required to**" indicate a requirement/requirements, which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed;
+- The keywords "**is recommended**" indicate a requirement, which is recommended but which is not absolutely required. Thus, such requirements need not be present to claim conformance; and
+- The keywords "**can optionally**" or "**may**" indicate an optional requirement which is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor's implementation must provide the option; it means the vendor may optionally provide the feature and still claim conformance with the specification.
+
+# **6 Overview of challenges and considerations for education in remote and underserved areas**
+
+## **6.1 Challenges for education in remote and underserved areas**
+
+The world acknowledges that the growing digital divide will become larger if education cannot be reached in remote and underserved areas in an equitable manner.
+
+The key challenges faced in these areas for accessing quality education are listed below:
+
+- Lack of infrastructure: Remote areas often lack the necessary infrastructure, such as reliable electricity and Internet connectivity, required to support digital education;
+- Limited resources: Many schools in remote areas do not have the resources to purchase and maintain the necessary technologies, such as computers, phones and tablets;
+- Limited teacher training: Teachers in remote areas may not have the training or experience to effectively use digital education tools and resources;
+- Language barriers: Some students in remote areas may not be fluent in the language used in digital education materials, making it difficult for them to understand and engage with the digital content;
+- Limited access to digital materials: Students in remote areas may not have the access to digital materials and resources that those in more urban areas do;
+- Limited parental engagement: Some parents in remote areas may not be able to help their children with digital education due to limited access or skills; and
+- Limited awareness and adoption: People in remote areas may have a limited awareness of digital education and how it can benefit their children's education.
+
+The use cases of e-learning in underserved and remote areas are unique. Some relevant use cases are presented in Appendix I.
+
+## **6.2 Considerations for deployment of e-learning in remote classrooms**
+
+Schools and classrooms in remote and underserved areas often face unique challenges compared to those in more urban or affluent areas. These challenges can include limited access to resources such as technology, Internet connectivity, qualified teachers, and adequate infrastructure. Strategies and capabilities are required that can help ensure underserved learners have access to equitable education.
+
+- Internet connectivity solutions:
+In remote areas where Internet connectivity is scarce or unreliable, alternative solutions such as private networks, satellite Internet, mobile Internet hotspots, or community networks can be implemented. Additionally, offline digital resources like pre-loaded tablets or digital content stored on local servers can ensure continuous access to educational materials.
+- Teacher training and support:
+Providing ongoing professional development and support for teachers is crucial. Teachers in remote and underserved areas may face unique challenges, including limited access to training resources and isolation from professional networks. Providing training in innovative teaching methods, technology integration, and cultural sensitivity can enhance their effectiveness.
+- Adaptation of curriculums:
+Tailoring the curriculum to the local context and needs of the students can increase relevance and engagement. Incorporating local languages, cultures, and examples into the curriculum can make learning more meaningful for students in underserved areas.
+
+- **Access to technology:**
+While access to technology may be limited, providing essential technological tools such as computers, tablets, or smartphones can enhance learning opportunities. Additionally, leveraging low-cost or open-source technologies can make technology more accessible in resource-constrained environments.
+- **Community engagement and partnerships:**
+Engaging parents, community leaders, and local organizations in the educational process can foster a sense of ownership and support for education initiatives. Collaborating with non-governmental organizations, government agencies, and private sector partners can also provide additional resources and support.
+- **Flexible learning models:**
+Implementing flexible learning models, such as blended learning, distance learning, or alternative schooling options, can accommodate the diverse needs and circumstances of learners in underserved areas. This may involve a combination of in-person instruction, online learning, and peer-to-peer learning approaches.
+- **Monitoring and evaluation systems:**
+Establishing robust monitoring and evaluation systems can help identify gaps and measure progress towards educational equity goals. Regular assessments of student learning outcomes, teacher performance, and school infrastructure can inform decision-making and resource allocation.
+
+# **7 Concept and Internet connectivity scenarios for e-learning in remote classrooms**
+
+## **7.1 Concept of e-learning**
+
+The concept of e-learning in remote classrooms is the process of using ICTs, such as interactive panels, cameras, microphones, computers, tablets, smartphones, Internet, learning management platforms and digital content, to facilitate learning and teaching from an expert instructor who is physically present and teaching a classroom elsewhere.
+
+Remote classrooms are located in remote and underserved campuses, whilst hybrid classrooms exist in urban areas and have the required Internet connectivity, ICT infrastructure and expert instructors. For the purpose of this Recommendation, a campus with a remote classroom is described as a remote campus, and the one that hosts a hybrid classroom is referred to as a nodal campus. It is also expected that beyond the remote and nodal campuses, a central cloud may exist that will enable the storage of digital content, information and repositories related to e-learning and the profiles of the beneficiaries and stakeholders. The central cloud may host several applications that enable the sharing and synchronization of catalogues and digital content, and also provide the required video collaboration, augmented reality (AR)/virtual reality (VR) and other such features and facilities.
+
+In the context of remote classrooms, e-learning refers to the delivery of education through digital means, where teachers and students are, respectively, physically located in different places. With e-learning, teachers can create and deliver digital content such as videos, interactive quizzes, and other learning materials. Students can access these materials and complete assignments and assessments remotely from their own devices and at their own pace. E-learning in remote classrooms also allows for real-time communication between teachers and students through video conferencing tools, chat applications, and discussion forums.
+
+E-learning in remote classrooms can be a flexible and an effective way to deliver education, particularly in situations where physical classrooms are not feasible or accessible. It can also provide opportunities for personalized learning, as students can engage with digital content and receive feedback tailored to their individual needs and learning styles.
+
+Certain innovative teaching-learning approaches that shift direct instruction to the outside of the classroom are becoming popular. Flipped learning and blended learning are two such innovative approaches to education that have gained popularity in recent years, particularly in the context of primary and secondary school education.
+
+NOTE 1 – In a flipped classroom, students learn new concepts at home through pre-recorded lectures, readings, or other multimedia resources. Class time is then used for activities, discussions, and collaborative work that reinforce and apply the concepts learned at home. This model allows teachers to spend more time interacting with students, providing personalized support, and facilitating a deeper understanding of the material.
+
+NOTE 2 – Blended learning combines traditional face-to-face instruction with online learning components. It integrates technology into the learning process, offering a mix of in-person classroom instruction and digital resources. In a blended learning environment, students may engage in online discussions, complete interactive exercises, watch educational videos, or participate in virtual simulations as part of their coursework. The goal of blended learning is to personalize the learning experience, accommodate different learning styles, and provide flexibility in how and when students access educational digital content.
+
+NOTE 3 – Two types of e-learning classrooms are relevant to this Recommendation, namely, hybrid classrooms and remote classrooms. A remote classroom is situated in a remote and underserved remote school campus. A hybrid classroom is situated in a nodal school campus that is provided with the required ICT, multimedia facilities and an expert teacher. The teacher in an e-learning hybrid classroom can teach learners present locally in the hybrid classroom, and the learners in a remote classroom.
+
+The concept of deployment of e-learning in remote and hybrid classrooms is presented in Figure 1. It shows how learning can be facilitated in remote campuses, in online and offline nodes, depending on whether or not a remote campus has Internet connectivity.
+
+
+
+Y.4234/F.742.3(25)
+
+Figure 1: Concept of e-learning in remote and hybrid classrooms. The diagram illustrates three interconnected components: a Nodal campus, a Remote campus with Internet connectivity, and a Remote campus without Internet connectivity. The Nodal campus (left) contains 'ICT and multimedia equipment, applications and services', 'Digital content', and an 'Expert teacher and learners in hybrid classroom'. The Remote campus with Internet connectivity (top right) features 'Real-time lessons for learners in remote classroom', 'ICT and multimedia equipment, applications and services', and 'Digital content'. The Remote campus without Internet connectivity (bottom right) shows 'Teacher with offline content for learners in remote classroom', 'ICT and multimedia equipment, applications and services', and 'Digital content'. 'Online collaboration' is shown as a solid arrow from the Nodal campus to the Remote campus with Internet connectivity. 'Offline collaboration' is shown as a dashed arrow from the Nodal campus to the Remote campus without Internet connectivity.
+
+**Figure 1 – Concept of e-learning in remote and hybrid classrooms**
+
+## 7.2 Internet connectivity scenarios for e-learning
+
+For the purposes of this Recommendation, it is assumed that the hybrid classrooms have appropriate and reliable Internet connectivity and ICT infrastructure to support e-learning in remote classrooms. On the other hand, the following scenarios may be considered for the remote classrooms, based on whether or not there is the availability of appropriate ICT infrastructure and Internet connectivity.
+
+### **7.2.1 Reliable Internet connectivity exists**
+
+This is the first of the two scenarios, in which reliable Internet connectivity with appropriate bandwidth can be provisioned to support the teaching-learning activities in the remote classrooms.
+
+In this scenario, the ICT deployment ensures that real time e-learning activities can be performed between remote classrooms and the hybrid classroom, including the use of digital content and other resources available on the Internet.
+
+### **7.2.2 Reliable Internet connectivity does not exist**
+
+This is the second of the two scenarios, in which reliable Internet connectivity cannot be provisioned to support the teaching-learning activities in the remote classrooms.
+
+In this scenario, the ICT deployment must be such so as to ensure that e-learning activities are performed inside the remote classrooms, by the pre-provisioning and configuring of the digital content catalogues and learning management systems (LMS) before or at the time of the deployment of the ICT infrastructure in the e-learning remote classrooms. This scenario requires that periodic updates of the digital content catalogues and the exchange of performance data happen manually or by the use of unreliable or sporadic connectivity.
+
+#### **7.2.3 Options for last mile Internet connectivity for remote classrooms**
+
+There is a possibility that least developed and developing countries may not have the adequate telecommunication and ICT infrastructure in rural areas for providing high-speed Internet services.
+
+For providing smart services in rural and remote areas, it is required to build up a low-cost, sustainable and high-speed communication network with a transmission capacity of 1 Gbit/s in the backhaul for a population of around 1 000 persons [ITU-T L.1700].
+
+NOTE – Related ITU-T Supplements for developing low-cost sustainable telecommunication infrastructure for rural communications in developing countries, namely, [b-ITU-T L Suppl. 22] using optical fibre cable, [b-ITU-T L Suppl. 23] using radio links, [b-ITU-T L Suppl. 29] using cellular technologies, [b-ITU-T L Suppl. 30] using cellular networks with capacity transfer, and [b-ITU-T L Suppl. 31] using satellite systems, are useful complementary documents in terms of technical information.
+
+Low-cost and sustainable telecommunication infrastructure may be built up in rural areas using optical fibre communications, cellular networks, radio communications, and satellite services, depending upon the terrain. Wi-Fi hot spots, radio links or optical fibre communications may be used in the access networks.
+
+Smart devices (smartphones, laptops, tablets, etc.) may not be affordable to the lower income group population in the least developed as well as developing countries. The deployment of e-learning infrastructure in remote classrooms may be an efficient way to increase exposure to digital technologies and techniques to the underserved population [b-ITU-T Y.4218].
+
+# **8 Requirements for e-learning in remote classrooms**
+
+To support e-learning in remote classrooms, a number of important technical, pedagogical and operational requirements must be fulfilled. These requirements, under different categories, are listed below.
+
+## **8.1 Internet connectivity, multimedia and ICT resources**
+
+The e-learning classrooms have the following requirements related to Internet connectivity, multimedia and ICT resources:
+
+- 1) ICT infrastructure, including Internet connectivity, cloud computing, computing equipment, networking equipment, security devices and racks for mounting and connecting e-learning equipment, is required.
+
+- 2) Where Internet connectivity is scarce or unreliable, alternative means for continuous Internet access are required to be provided, which may include private networks, satellite Internet, mobile Internet hotspots, or community networks.
+- 3) Where Internet connectivity cannot be provided, tablets and servers with pre-loaded digital content catalogues may optionally be deployed.
+- 4) Air-conditioning equipment, generators, uninterruptible power supply and solar power equipment are recommended, to ensure uninterrupted teaching-learning activities.
+
+## **8.2 Learning management and digital content management systems**
+
+E-learning classrooms have the following requirements related to learning management and digital content management systems:
+
+- 1) Learning management systems to register and onboard the teachers, students, parents and staff having access control and personally identifiable information (PII) protection mechanisms are required;
+- 2) Applications for course management, lesson management and digital content delivery are required;
+- 3) Applications for learner assessment by the use of quizzes, exams and assignments are required;
+- 4) Applications for performance and progress tracking are required;
+- 5) Language translation facilities so that learners proficient in one language can understand digital content catalogues created in other languages are required;
+- 6) Applications for teacher training and onboarding for teachers to gain expertise in the use of e-learning equipment are required;
+- 7) Digital content catalogue management systems with access control mechanisms can be optionally provided;
+- 8) AR/VR/(XR) extended reality digital content facilities for teaching complex concepts can be optionally provided;
+- 9) Applications to enable flipped learning, homework assignments, offline student engagement and group work can be optionally provided;
+- 10) Applications for offline and online query response mechanisms can be optionally provided; and
+- 11) Artificial intelligence and machine learning-enabled assessment systems that assess the individual learner's profile and pace the curriculum according to the specific capabilities and interests of that individual can be optionally provided.
+
+## **8.3 Advanced learning resources**
+
+E-learning classrooms have the following requirements related to advanced learning resources:
+
+- 1) Multimedia equipment to enable collaboration and communication between remote and hybrid e-learning classrooms is required;
+NOTE – E-learning multimedia equipment includes, but is not limited to, web cameras, document cameras, e-kiosks, interactive panels, speakers and microphones.
+- 2) Where Internet access is provided, video conferencing and live virtual sessions of expert teachers can be optionally provided;
+- 3) Access to virtual e-learning labs can be optionally provided.
+
+# **9 Capabilities of remote classrooms to support e-learning**
+
+Based on the scenarios, challenges and considerations related to e-learning described in clause 7 and the requirements described in clause 8, the capabilities required to support e-learning in remote classrooms are stated below.
+
+## **9.1 Internet connectivity, multi-media and ICT resources**
+
+- 1) Remote e-learning classrooms are provided with reliable high-speed Internet connection. The Internet bandwidth is sufficient to accommodate the relay of multimedia digital content and video conferencing and to handle multiple simultaneous connections. A redundant Internet connection and a remote and nodal campus networking facility are provided to ensure continuous teaching-learning activities;
+- 2) Where Internet connectivity cannot be provided in a remote classroom, alternate manual processes are provided for the management of digital content catalogues, and reporting of performance and operating data from the remote class;
+- 3) Firewall and network security measures are provided to protect against unauthorized access and misuse of the network;
+- 4) Computers or laptops with audio and video capabilities for teachers, and optionally for students, are provided;
+- 5) Cameras for video conferencing and virtual classroom participation are provided;
+- 6) Headsets or speakers with microphones for audio communications are provided;
+- 7) Cameras and recording systems for creating and capturing e-learning classes, displays for sharing digital content during online classes, and document cameras for displaying physical documents or objects are provided; and
+- 8) A ticketing system for addressing technical issues and supporting queries is provided.
+
+## **9.2 Learning management and digital content management systems**
+
+- 1) An LMS is provided for learner, teacher and course registration and management, digital content delivery, and learner performance tracking with mechanisms for access control and PII protection;
+- 2) Video collaboration facilities and online access to hybrid classrooms are provided;
+- 3) Facilities for document sharing and storage, ensuring easy access to learning materials, are provided;
+- 4) Offline and online facilities for frequently asked questions and doubts clarification are provided;
+- 5) Offline assessment tools to evaluate learner progress in remote areas with no Internet connectivity, and online assessment tools with quizzes, exams, and assignments for Internet-connected classes, are provided;
+- 6) Content management system for organizing and distributing digital content catalogues and resources are provided;
+- 7) Digital content catalogues, curated and structured into lesson plans aligned with the curriculum, are provided;
+- 8) Language translation tools are provided;
+- 9) Collaboration tools, real-time chat and messaging systems for student engagement and group work are optionally provided;
+- 10) User-friendly applications for teachers to create, upload and distribute digital content are optionally provided;
+
+- 11) Content curation facilities to adapt the digital content for different learning abilities are optionally provided; and
+- 12) Regular updates and maintenance of digital content are optionally provided.
+
+## **9.3 Advanced learning resources**
+
+- 1) Multimedia resources, including videos, interactive activities and simulations, are provided for hands-on learning and experimentation;
+- 2) Computers, laptops, phones, tablets and AR/VR headsets are optionally provided for learners to use AR/VR digital content and experiments.
+
+## **9.4 Complementary non-technical capabilities**
+
+The technical capabilities are complemented by the following non-technical capabilities:
+
+Teaching assistants: The remote e-learning classrooms are provided with:
+
+- Adequate number of teaching assistants or moderators to support remote classrooms; and
+- Training and resources for teaching assistants to help with technical troubleshooting and student support.
+
+Teacher training: The remote e-learning classrooms are provided with:
+
+- Comprehensive training programmes for teachers to effectively use e-learning tools and platforms;
+- Pedagogical training to ensure teachers can adapt their teaching methods for remote learning; and
+- Ongoing professional development for teachers to stay updated with the latest technology and best practices.
+
+Classroom equipment: The remote e-learning classrooms are provided with:
+
+- Ergonomic furniture and comfortable seating arrangements for students;
+- Proper lighting and acoustics to create an optimal learning environment.
+
+# **10 Deployment models for remote classrooms to support e-learning**
+
+The deployment models describe the setup of e-learning classrooms, considering the Internet connectivity scenarios and the capabilities described in clause 9.
+
+Clause 10.1 presents the deployment model for e-learning in remote and hybrid classrooms in the scenario where Internet connectivity is available. Clause 10.2 presents the deployment model for e-learning in remote and hybrid classrooms in the scenario where Internet connectivity is not available.
+
+## **10.1 Deployment model for remote classrooms with Internet connectivity**
+
+When both the hybrid and remote classrooms have Internet access, learners in the remote classrooms can join the learners in the hybrid classroom to be taught by the expert teacher in the hybrid classroom in real time. The remote learners can interact with the expert teacher and also their counterparts in the hybrid classroom, using audio and video-enabled communication.
+
+In this scenario, the remote learners are also able to access the educational digital content catalogues online and updates to the educational digital content are available to them in near real time.
+
+Data related to the attendance and performance of the learners in the remote classroom may be exchanged in real time too.
+
+Figure 2 shows the components that are to be deployed in the e-learning hybrid and remote classrooms to fulfil the requirements and capabilities specified in clauses 8 and 9. It shows the interaction between a hybrid e-learning classroom in a nodal campus with remote e-learning classrooms situated in two remote campuses marked as remote campus A and remote campus B.
+
+NOTE – The full specification and feature description of each component is outside the scope of this Recommendation.
+
+
+
+Y.4234/F.742.3(25)
+
+Figure 2: E-learning deployment model for remote classrooms connected to the Internet. The diagram illustrates the architecture of a hybrid e-learning classroom in a nodal campus and its connection to two remote campuses, A and B. The nodal campus includes a hybrid classroom with an expert teacher and learners, and a digital content/performance data database. Remote campus A contains remote classroom 1 with a teaching assistant and learners, and a digital content/performance data database. Remote campus B contains remote classroom 2 with a teaching assistant and learners, and a digital content/performance data database. Solid arrows indicate real-time teaching-learning enabled by internet connectivity and online video collaboration. Dashed arrows indicate the online exchange of content and performance data between the nodal campus and the remote campuses. Each remote classroom also has its own power management infrastructure, internet connectivity, learning management systems, and advanced learning resources.
+
+**Figure 2 – E-learning deployment model for remote classrooms connected to the Internet**
+
+## 10.2 Deployment model for remote classrooms with no Internet connectivity
+
+In the scenario where the remote classrooms do not have Internet access, learners in the remote classrooms learn from the digital content catalogues created in hybrid classrooms and transferred offline to the remote classrooms. The teaching assistant replays the digital content using the multimedia equipment provided in the remote classroom. The remote learners in the hybrid classroom learn from the expert teacher in the hybrid classroom in an offline mode.
+
+In this scenario, updates to the educational digital content are made available to the remote learner by an offline mechanism. Data related to the attendance and performance of the learners in the remote classroom is exchanged offline too.
+
+Figure 3 shows the components that are to be deployed for the support of e-learning in remote classrooms, to fulfil the requirements and capabilities specified in clauses 8 and 9.
+
+
+
+The diagram illustrates an e-learning deployment model for remote classrooms without Internet connectivity. It is divided into three main sections: a Nodal campus and two Remote campuses (A and B).
+
+- Nodal campus:** Contains a box with 'Power management infrastructure', 'Internet connectivity, multimedia and ICT resources', 'Learning management and digital content management systems', and 'Advanced learning resources'. It also includes a 'Hybrid classroom' with an 'Expert teacher and learners in hybrid classroom' and a cylinder for 'Digital content, performance data'.
+- Remote campus A:** Contains a box with 'Power management infrastructure', 'Multimedia and ICT resources', 'Learning management and digital content management systems', and 'Advanced learning resources'. It includes 'Remote classroom 1' with a 'Teaching assistant' and 'Learners in remote classroom', and a cylinder for 'Digital content, performance data'.
+- Remote campus B:** Contains a box with 'Power management infrastructure', 'Multimedia and ICT resources', 'Learning management and digital content management systems', and 'Advanced learning resources'. It includes 'Remote classroom 2' with a 'Teaching assistant' and 'Learners in remote classroom', and a cylinder for 'Digital content, performance data'.
+
+Connections and Data Flow:
+
+- Dashed lines connect the 'Digital content, performance data' cylinders of the Nodal campus, Remote campus A, and Remote campus B to a central circle labeled 'Offline exchange of content updates and performance data'.
+- A dashed line connects the 'Hybrid classroom' to a central 'X' symbol, which is connected to another circle labeled 'No online teaching-learning collaboration'.
+
+Y.4234/F.742.3(25)
+
+Figure 3: E-learning deployment model for remote classrooms with no Internet connectivity. The diagram shows a Nodal campus connected to two Remote campuses (A and B) via offline data exchange. The Nodal campus includes infrastructure, connectivity, LMS, and resources, and a hybrid classroom. Remote campuses have their own infrastructure, resources, LMS, and advanced learning resources, with remote classrooms featuring teaching assistants and learners. A central 'X' indicates no online collaboration.
+
+**Figure 3 – E-learning deployment model for remote classrooms with no Internet connectivity**
+
+NOTE 1 – The full specification and feature description of each component is outside the scope of this Recommendation.
+
+NOTE 2 – The details of the services required for the periodic sharing of performance data and reports, and the periodic provisioning of the updated digital content for the remote classrooms are implementation specific and outside the scope of this Recommendation.
+
+# Appendix I
+
+## Use cases for e-learning in remote and rural areas
+
+(This appendix does not form an integral part of this Recommendation.)
+
+Relevant use cases of e-learning in remote and rural areas include the following:
+
+- 1) Use of low-latency communications and edge computing for real-time language translation in the context of a remote classroom: whilst distance learning presents an opportunity for remote learners to benefit from high-quality teachers in distant educational institutions, the language barrier remains a spoiler. There is a need to research and develop a solution that uses quality of experience (QoE)-enabled, low-latency communications, to undertake a real time language translation, such that a speaker speaking in English can teach learners who understand a local dialect without a perceptible delay.
+- 2) VR/AR applications in education: a mix of communication and edge computing technologies that can enable high-bandwidth, low-latency connectivity, which is required for VR and AR applications. There is a need to research and develop technologies that can be used to create immersive learning experiences and enhance the classroom experience.
+- 3) Online and distance learning: communication technologies that can enable high-quality video conferencing and streaming, which can be used to facilitate online and distance learning. There is a need to create a solution to enhance the quality of online learning and to make it more accessible to learners around the world.
+- 4) Collaborative learning: technology to enable real-time collaboration and communication between students, teachers, and other educational stakeholders. There is a need to integrate communication, collaboration and learning management technologies to facilitate collaborative learning and enhance the effectiveness of group work.
+- 5) Personalized and adaptive learning: technologies that can enable personalized and adaptive learning by allowing for the collection and analysis of large amounts of data on student learning and performance. There is a need to research and explore the use of these technologies to create a product that can assess individual aptitudes and tailor learning experiences to the needs and preferences of individual students.
+- 6) Gamification and game-based learning: technologies that can enable the creation of immersive and interactive game-based learning experiences.
+
+## Bibliography
+
+- [b-ITU-T F.742] Recommendation ITU-T F.742 (2023), *Service description and requirements for distance learning services.*
+- [b-ITU-T F.742.1] Recommendation ITU-T F.742.1 (2022), *Requirements for smart class systems based on artificial intelligence.*
+- [b-ITU-T F.742.2] Recommendation ITU-T F.742.2 (2024), *Functional architecture for distance learning services.*
+- [b-ITU-T L Suppl. 22] ITU-T L-series Recommendations – Supplement 22 (2016), *ITU-T L.1700 – Low-cost sustainable telecommunication for rural communications in developing countries using fibre optic cable.*
+- [b-ITU-T L Suppl. 23] ITU-T L-series Recommendations – Supplement 23 (2016), *ITU-T L.1700 – Low-cost sustainable telecommunications for rural communications in developing countries using microwave and millimetre radio links.*
+- [b-ITU-T L Suppl. 29] ITU-T L-series Recommendations – Supplement 29 (2016), *ITU-T L.1700 – Low-cost sustainable telecommunication for rural communications in developing countries using cellular radio technologies.*
+- [b-ITU-T L Suppl. 30] ITU-T L-series Recommendations – Supplement 30 (2016), *ITU-T L.1700 – Setting up a low-cost sustainable telecommunication network for rural communications in developing countries using cellular network with capacity transfer.*
+- [b-ITU-T L Suppl. 31] ITU-T L-series Recommendations – Supplement 31 (2016), *ITU-T L.1700 – Setting up a low-cost sustainable telecommunication network for rural communications in developing countries using satellite systems.*
+- [b-ITU-T Y.4218] Recommendation ITU-T Y.4218 (2023), *Internet of things and information and communication technology requirements for deployment of smart services in rural communities.*
+
+
+
+## ITU-T F-SERIES RECOMMENDATIONS **Non-telephone telecommunication services**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | F.1-F.109 |
+| Operating methods for the international public telegram service | F.1-F.19 |
+| The gentex network | F.20-F.29 |
+| Message switching | F.30-F.39 |
+| The international telemesssage service | F.40-F.58 |
+| The international telex service | F.59-F.89 |
+| Statistics and publications on international telegraph services | F.90-F.99 |
+| Scheduled and leased communication services | F.100-F.104 |
+| Phototelegraph service | F.105-F.109 |
+| MOBILE SERVICE | F.110-F.159 |
+| Mobile services and multideestination satellite services | F.110-F.159 |
+| TELEMATIC SERVICES | F.160-F.399 |
+| Public facsimile service | F.160-F.199 |
+| Teletex service | F.200-F.299 |
+| Videotex service | F.300-F.349 |
+| General provisions for telematic services | F.350-F.399 |
+| MESSAGE HANDLING SERVICES | F.400-F.499 |
+| DIRECTORY SERVICES | F.500-F.549 |
+| DOCUMENT COMMUNICATION | F.550-F.599 |
+| Document communication | F.550-F.579 |
+| Programming communication interfaces | F.580-F.599 |
+| DATA TRANSMISSION SERVICES | F.600-F.699 |
+| MULTIMEDIA SERVICES | F.700-F.799 |
+| ISDN SERVICES | F.800-F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850-F.899 |
+| ACCESSIBILITY AND HUMAN FACTORS | F.900-F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation
+
+## **ITU-T Y.4235 (09/2025)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Internet of things and smart cities and communities –
+Requirements and use cases
+
+## --- **Requirements of the Internet of things (IoT)- based power grid communication network**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+| | |
+|---------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | Y.100-Y.999 |
+| INTERNET PROTOCOL ASPECTS | Y.1000-Y.1999 |
+| NEXT GENERATION NETWORKS | Y.2000-Y.2999 |
+| FUTURE NETWORKS | Y.3000-Y.3499 |
+| CLOUD COMPUTING | Y.3500-Y.3599 |
+| BIG DATA | Y.3600-Y.3799 |
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800-Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | Y.4000-Y.4999 |
+| General | Y.4000-Y.4049 |
+| Definitions and terminologies | Y.4050-Y.4099 |
+| Requirements and use cases | Y.4100-Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250-Y.4399 |
+| Frameworks, architectures and protocols | Y.4400-Y.4549 |
+| Services, applications, computation and data processing | Y.4550-Y.4699 |
+| Management, control and performance | Y.4700-Y.4799 |
+| Identification and security | Y.4800-Y.4899 |
+| Evaluation and assessment | Y.4900-Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4235
+
+## Requirements of the Internet of things (IoT)-based power grid communication network
+
+## Summary
+
+Recommendation ITU-T Y.4235 specifies the requirements of the Internet of things (IoT)-based power grid communication network. The IoT-based power grid communication network provides bidirectional data interaction in all phases of power grid operations, including electric power generation, transmission, distribution and consumption. It is an effective means to achieve comprehensive awareness of power grid status and to enable human-computer interaction and ubiquitous access to the IoT devices of the power grid.
+
+## History\*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T Y.4235 | 2025-09-23 | 20 | 11.1002/1000/16202 |
+
+## Keywords
+
+Communication network, Internet of things, IoT, IoT-based power grid communication network, power grid.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2025
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|---|---------------------------------------------------------------------------------------------------------|------|
+| 1 | Scope..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere ..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 3 |
+| 6 | Overview of IoT-based power grid communication network..... | 3 |
+| | 6.1 Necessity of IoT-based power grid communication network..... | 3 |
+| | 6.2 Reference model of IoT-based power grid communication network..... | 3 |
+| 7 | Requirements of IoT-based power grid communication network ..... | 5 |
+| | 7.1 Data communication dedicated network requirements ..... | 6 |
+| | 7.2 Dispatching data dedicated network requirements..... | 7 |
+| | 7.3 Electric power dedicated line requirements ..... | 7 |
+| | 7.4 Electric power bearer network requirements..... | 7 |
+| | 7.5 Electric power access dedicated network requirements ..... | 8 |
+| | 7.6 Gateway interface requirements ..... | 9 |
+| | 7.7 Local communication network requirements ..... | 10 |
+| | 7.8 Communication network security requirements..... | 11 |
+| | Appendix I – Deployment and application examples of IoT-based power grid
communication network ..... | 13 |
+| | I.1 IoT-based power grid communication network for substation system ..... | 13 |
+| | I.2 Application of IoT-based power grid communication network in the
microgrid ..... | 15 |
+| | Bibliography..... | 18 |
+
+
+
+# Recommendation ITU-T Y.4235
+
+## Requirements of the Internet of things (IoT)-based power grid communication network
+
+# 1 Scope
+
+This Recommendation addresses the requirements of communication network for the IoT-based power grid. In particular, it provides the following:
+
+- Overview of the IoT-based power grid communication network;
+- Requirements of the IoT-based power grid communication network.
+
+Appendix I provides some relevant deployment and application examples of IoT-based power grid communication network.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[[ITU-T Y.4101](#)] Recommendation ITU-T Y.4101/Y.2067 (2017), *Common requirements and capabilities of a gateway for Internet of things applications*.
+
+[[ITU-T Y.4112](#)] Recommendation ITU-T Y.4112/Y.2077 (2016), *Requirements of the plug and play capability of the Internet of things*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 device** [b-ITU-T Y.4000]: With regard to the Internet of things, this is a piece of equipment with the mandatory capabilities of communication and the optional capabilities of sensing, actuation, data capture, data storage and data processing.
+
+**3.1.2 Internet of things** [b-ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.
+
+NOTE 1 – Through the exploitation of identification, data capture, processing and communication capabilities, the IoT makes full use of things to offer services to all kinds of applications, whilst ensuring that security and privacy requirements are fulfilled.
+
+NOTE 2 – From a broader perspective, the IoT can be perceived as a vision with technological and societal implications.
+
+**3.1.3 substation** [b-IEC 60050-605]: The part of a power system, concentrated in a given place, including mainly the terminations of transmission or distribution lines switchgear and housing and which may also include transformers. It generally includes facilities necessary for system security and control (e.g., the protective devices).
+
+## 3.2 Terms defined in this Recommendation
+
+None.
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|--------|--------------------------------------------|
+| ACL | Access Control List |
+| AP | Access Point |
+| ARP | Address Resolution Protocol |
+| DNP3 | Distributed Network Protocol 3 |
+| DoS | Denial of Service |
+| HD | High Definition |
+| IMT | International Mobile Telecommunications |
+| IoT | Internet of Things |
+| IoV | Internet of Vehicles |
+| IP | Internet Protocol |
+| IPv4 | Internet Protocol version 4 |
+| IPv6 | Internet Protocol version 6 |
+| ISIS | Intermediate System-to-Intermediate System |
+| LPWAN | Low-Power Wide-Area Network |
+| MAC | Media Access Control |
+| MACSec | Media Access Control Security |
+| MPLS | Multi-Protocol Label Switching |
+| MQTT | Message Queuing Telemetry Transport |
+| O&M | Operation and Maintenance |
+| OAM | Operations, Administration and Maintenance |
+| OSPF | Open Shortest Path First |
+| OTN | Optical Transport Network |
+| PLMN | Public Land Mobile Network |
+| PoE | Power over Ethernet |
+| PSTN | Public Switched Telephone Network |
+| QoS | Quality of Service |
+| SDH | Synchronous Digital Hierarchy |
+| SLA | Service Level Agreement |
+| SPN | Slicing Packet Network |
+| SRv6 | Segment Routing IPv6 |
+| TCP | Transmission Control Protocol |
+| VLAN | Virtual Local Area Network |
+
+| | |
+|------|---------------------------------|
+| VPN | Virtual Private Network |
+| WAC | Wireless Access Controller |
+| WPAN | Wireless Personal Area Networks |
+
+# **5 Conventions**
+
+In this Recommendation:
+
+The expression "is required" indicates a requirement which must be strictly followed and from which no deviation is permitted if conformance to this Recommendation is to be claimed.
+
+The expression "is recommended" indicates a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance with this Recommendation.
+
+# **6 Overview of IoT-based power grid communication network**
+
+## **6.1 Necessity of IoT-based power grid communication network**
+
+Power grid is the whole consisting of substations of various voltages and transmission and distribution lines in the power system [b-ITU-T F.751.5].
+
+The power grid communication network supports and ensures the production and operation of the power grid. It is composed of communication network devices in the production and operation sites of the power grid. It provides transmission channels for different service information of the power grid. The continuous information exchange of electric power Internet of things (IoT) devices and their associated application processing systems through the communication network ensures the safe and stable operation of the power grid.
+
+NOTE – Electric power IoT devices are for controlling electric power infrastructures and collecting information about the power grid (such as relay protection devices and fire protection devices).
+
+Under the background of global warming and limited fossil energy resources, the trend of energy decentralization has become increasingly apparent, which poses new challenges and requirements for traditional power grid communication networks.
+
+The wide access to clean energy, such as solar energy and wind energy, increases the fluctuation of the power grid, which poses strict requirements on communication reliability, access flexibility and other network transmission specifications. Dynamic collection and online monitoring of power grid status leads to large-scale access to electric power IoT devices and exponential growth of data volume.
+
+An IoT-based power grid communication network provides high-bandwidth and high-reliability communication services. Combined with advanced data analysis and processing technologies, the IoT-based power grid communication network supports the real-time control and management of the power grid.
+
+## **6.2 Reference model of IoT-based power grid communication network**
+
+A reference model of an IoT-based power grid communication network is shown in Figure 1.
+
+
+
+The diagram illustrates the reference model of the IoT-based power grid communication network, organized into four main layers:
+
+- Application layer:** Contains five service types: Production and control type services, Operation monitoring type services, Remote inspection type services, Operation and maintenance (O&M) and management type services, and Commanding and liaison type services.
+- Service support and application support layer:** Contains Generic support capabilities and Specific support capabilities.
+- Network layer:**
+ - IoT-based power grid core network:** Includes Electric power dedicated line (Primary path, Redundant path), Dispatching data dedicated network (Primary path, Redundant path), Data communication dedicated network (Primary path, Redundant path), and Electric power bearer network.
+ - IoT-based power grid access network:** Includes Electric power wired dedicated network and Electric power wireless dedicated network.
+- Device layer:** Includes a Gateway, Local communication network, IoT devices, and six types of power infrastructure: Power supply infrastructure, Power transmission infrastructure, Power conversion infrastructure, Power distribution infrastructure, Power consumption infrastructure, and Power storage infrastructure.
+
+Arrows indicate bidirectional communication between layers and components within layers.
+
+Y.4235(25)
+
+Figure 1 – Reference model of the IoT-based power grid communication network. The diagram shows a four-layer architecture: Application layer, Service support and application support layer, Network layer, and Device layer. The Application layer includes Production and control type services, Operation monitoring type services, Remote inspection type services, Operation and maintenance (O&M) and management type services, and Commanding and liaison type services. The Service support and application support layer includes Generic support capabilities and Specific support capabilities. The Network layer is divided into the IoT-based power grid core network (Electric power dedicated line, Dispatching data dedicated network, Data communication dedicated network, Electric power bearer network) and the IoT-based power grid access network (Electric power wired dedicated network, Electric power wireless dedicated network). The Device layer includes a Gateway, Local communication network, IoT devices, and six types of power infrastructure: Power supply, Power transmission, Power conversion, Power distribution, Power consumption, and Power storage.
+
+**Figure 1 – Reference model of the IoT-based power grid communication network**
+
+The reference model includes the application layer, service support and application support layer, network layer and device layer.
+
+The application layer provides IoT applications for the power grid.
+
+NOTE 1 – The application layer can be deployed in a cloud-based platform.
+
+NOTE 2 – IoT-based power grid has five types of services, production and control type services, operation monitoring type services, remote inspection type services, operation and maintenance (O&M) and management type services, and commanding and liaison type services.
+
+The service support and application support layer provide generic and specific support capabilities to the IoT applications for the power grid.
+
+The network layer supports capabilities for dispatching data dedicated network, data communication dedicated network, electric power dedicated line, electric power bearer network and capabilities for the power grid access dedicated network, as follows:
+
+- a) The dispatching data dedicated network mainly carries production and control type services. It realizes the data transmission and exchange between electric power sub-dispatching systems and between dispatching systems, power plants and substations.
+- b) The data communication dedicated network is used to carry operation monitoring type services, remote inspection type services, O&M and management type services, and commanding and liaison type services.
+- c) The electric power dedicated line is used to carry production and control type services that are point-to-point and delay-sensitive (such as relay protection).
+- d) The electric power bearer network is the underlay network for the power grid communication network. It provides basic transmission services for the dispatching data network, data communication network and electric power dedicated line.
+- e) The power grid access dedicated network provides connections for widely distributed transformer substations [b-IEC 60050-605] and electric power IoT devices. Specifically, the access dedicated network can be divided into the wired dedicated access network and the wireless dedicated access network.
+
+NOTE 3 – The construction and O&M of public access networks (such as the International Mobile Telecommunications (IMT) Advanced and IMT-2020 networks) are controlled by telecom operators. In addition to electric power data, public user data is also carried in the public access network. Therefore, in order to protect electric power services and enhance the security of the services from the influence of other services that are carried on the access network, some electric power companies build their own dedicated access network to connect electric power IoT devices.
+
+NOTE 4 – The coordination between primary path and redundant path in Figure 1 provides redundancy assurance for services.
+
+The device layer supports gateway capabilities, local communication network capabilities and device capabilities:
+
+- a) The gateway supports the access of various electric power IoT devices. It provides management capabilities for electric power IoT devices and interworking capabilities between different protocols.
+- b) The local communication network is responsible for the interaction among electric power IoT devices within the substation, as well as the interaction between electric power IoT devices and gateways.
+
+The electric power IoT devices provide sensing and control capabilities for the IoT-based power grid. They are connected to the power grid access-dedicated network directly or through the local communication network and gateways. They collect data on the environment and operating status of the power grid. They also control the electric power infrastructure based on management and control instructions from IoT applications.
+
+The electric power infrastructure includes power supply, transmission, transformation, distribution, consumption and storage devices. The electric power infrastructure is monitored and managed by electric power IoT devices.
+
+# **7 Requirements of IoT-based power grid communication network**
+
+The IoT-based power grid communication network has specific requirements that are essential for its successful implementation. These requirements span various components of the network, ensuring efficient power grid management and secure data transmission.
+
+NOTE – With respect to the below identified requirements of the IoT-based power grid communication network, Appendix I.1 illustrates a deployment example that highlights technologies that may be used in support of these requirements. Appendix I.2 illustrates an applicability example for services and corresponding requirements in the microgrid [b-IEEE 2030.7].
+
+## **7.1 Data communication dedicated network requirements**
+
+- 1) The data communication dedicated network is required to support the Internet protocol (IP) address management capability to allocate unique IP addresses for electric power IoT devices.
+- 2) The data communication dedicated network is required to support layer 3 routing capability (e.g., intermediate system-to-intermediate system (ISIS) [b-ISO/IEC 10589] and open shortest path first (OSPF) [b-IETF RFC 2328] [b-IETF RFC 5340]).
+- 3) The data communication dedicated network is required to support virtual private network (VPN) capability, preferably based on a secure element of the dynamic identity management capability to meet the logic isolation requirements of different services.
+- 4) The data communication dedicated network is required to provide network quality assurance in terms of network latency and packet loss rate.
+
+NOTE 1 – The network assurance can rely on technologies such as differentiated services (e.g., DiffServ [b-IETF RFC 2475], quality of service (QoS)), service path planning and network resource reservation. Low latency facilitates real-time decision-making, fault detection and response, enabling efficient power grid management and reducing downtime. QoS mechanisms allow for the differentiation of data types, assigning higher priority to essential data such as real-time monitoring and control signals, in order to ensure that critical power grid data is not compromised or delayed by non-essential data traffic.
+
+- 5) The data communication dedicated network is required to support bandwidth scale-out.
+
+NOTE 2 – As IoT devices proliferate within the power grid ecosystem, the volume of data generated increases exponentially. To accommodate this massive influx of data, the network must support the capability of dynamic scaling of the available bandwidth between the different services. This ensures that critical real-time data, such as that on power consumption, fault detection and grid performance, can be transmitted without delay or congestion.
+
+- 6) The data communication dedicated network is required to support massive IoT device access.
+
+NOTE 3 – The network must support the connection and communication of a vast number of IoT devices distributed across the power grid.
+
+- 7) The data communication dedicated network is required to support cloud-network synergy.
+
+NOTE 4 – The seamless integration of network and cloud capabilities enables efficient data storage, processing and analytics. By leveraging cloud computing resources, the power grid can benefit from advanced data analytics, predictive maintenance and machine learning algorithms, facilitating more informed decision-making and proactive grid management.
+
+- 8) The data communication dedicated network is required to support network traffic monitoring and management.
+
+- 9) The data communication dedicated network is required to support intelligent network O&M and service quality visibility.
+
+NOTE 5 – Service quality visibility means service level agreement (SLA) visualization and monitoring of key performance indicators (including delay, jitter and packet loss rate) at the service flow level.
+
+NOTE 6 – In the event of a service defect, the data communication dedicated network can locate the defect and analyse the cause of the defect in time.
+
+- 10) The data communication dedicated network is required to support reliability assurance.
+NOTE 7 – The network should be designed with redundancy measures such as redundant links, failover mechanisms, and backup infrastructure. These redundancies enhance the network's reliability and resilience against network failures, natural disasters or cyberattacks, and minimizing the risk of power grid disruptions.
+- 11) The data communication dedicated network is required to support robust security measures to protect sensitive power grid data from unauthorized access, tampering or cyber threats.
+NOTE 8 – Security of the data communication dedicated network can be ensured by implementing strong encryption algorithms, authentication mechanisms, intrusion detection systems, and access control monitoring. Compliance with industry standards and best practices ensures the integrity, confidentiality and availability of power grid data.
+
+## **7.2 Dispatching data dedicated network requirements**
+
+Dispatching data dedicated network and data communication dedicated network are divided physically or logically according to the type of services carried on. Most of the dispatching data dedicated network requirements are consistent with the electric power data communication dedicated network. However, since the dispatching data dedicated network carries production and control type services, it has some additional specific requirements:
+
+- 1) Dispatching data dedicated network is required to support redundancy assurance, including device-level redundancy assurance and network-layer redundancy assurance.
+- 2) Dispatching data dedicated network is required to support high QoS in terms of network latency, packet loss rate, availability, security, etc.
+
+## **7.3 Electric power dedicated line requirements**
+
+- 1) The electric power dedicated line is required to provide low latency, so that data on production and control type services (such as relay protection services) can be transported in time.
+- 2) The electric power dedicated line is required to support hard isolation [b-GSTR-TN5G]. In order to ensure that the services carried by the electric power dedicated line operate stably and properly without being interfered with by other services, it is required they are hard isolated from other services.
+
+NOTE – As a network, the protection switching time should not exceed 50 ms.
+
+## **7.4 Electric power bearer network requirements**
+
+- 1) The electric power bearer network is required to provide both hard isolation and soft isolation [b-GSTR-TN5G] capabilities for supporting various SLAs of different types of services.
+- 2) The electrical power bearer network is required to support fine grain hard isolation channel capability with 10 Mbit/s level granularity.
+
+NOTE 1 – The current production and control type services currently use an E1 interface whose rate is 2.048 Mbit/s and are expected to evolve to use an Ethernet interface whose rate is 10 Mbit/s or 100 Mbit/s. The 10 Mbit/s level hard isolation channel granularity supports the bandwidth requirement of both current production and control type services and future services evolution.
+
+- 3) The electrical power bearer network is required to have time synchronization capability for power grid real-time dispatching, fault analysis and fault determination.
+- 4) The electrical power bearer network is required to support deterministic latency capability for production and control type services.
+
+NOTE 2 – As an example, the relay protection service requires a peer-to-peer data communication service with a jitter of less than 50% cycle time [b-3GPP TR 22.804].
+
+- 5) The electrical power bearer network is required to support large bandwidth and flexible bandwidth deployment.
+NOTE 3 – The electrical power bearer network is required to support a large bandwidth in order to support video transmission. For example, based on deployment experience, each city has hundreds of substations. The bandwidth requirements for concurrent video transmission in a single substation is 100 Mbit/s to 250 Mbit/s.
+- 6) The electrical power bearer network is required to support automatic O&M capability for enhanced network O&M efficiency.
+- 7) The electrical power bearer network is required to support real-time service quality monitoring capability.
+- 8) The electrical power bearer network is required to support service flow detection capability.
+
+## 7.5 Electric power access dedicated network requirements
+
+The electric power access dedicated network is composed of a wireless access dedicated network and a wired access dedicated network.
+
+- 1) Generic requirements of the access dedicated network:
+ - a) The electric power access dedicated network is required to support the access of diverse electric power IoT devices with multiple access modes and protocols (wireless personal area networks (WPAN) [b-IEEE 802.15.1], low-power wide-area network (LPWAN) [b-ITU-T Y.4218], and industrial Ethernet [b-IEC 61784-2-19]). So that it can flexibly adapt to multiple scenarios (such as control signal transmission, data communication and video transmission).
+ - b) The electric power access dedicated network is required to support the access of massive electric power IoT devices. The electric power access dedicated network is also required to support Internet protocol version 6/Internet protocol version 4 (IPv6/IPv4) dual stack capability to meet the address and resource allocation requirements of massive electric power IoT devices.
+ - c) The electric power access dedicated network is required to support high capacity and scalability.
+NOTE 1 – The dedicated network infrastructure needs to have the capacity to handle the increasing volume of data traffic generated by electric power IoT devices. Scalability ensures that the network can support large-scale deployments and expanding power grid infrastructures without compromising performance or efficiency.
+ - d) The electric power access dedicated network is required to support the intelligent analysis and management of massive electric power IoT devices (such as device registration, device upgrade, device control and device monitoring).
+NOTE 2 – By means of advanced analysis technologies based on big data and artificial intelligence algorithms, network failures can be detected in time.
+ - e) Electric power access dedicated network is required to support seamless integration and interoperability.
+NOTE 3 – This requires adherence to industry standards and protocols, enabling IoT devices to communicate and exchange data efficiently. Interoperability ensures that devices from different manufacturers or with different communication technologies can work together seamlessly within the power grid ecosystem.
+- 2) Wireless access dedicated network requirements:
+ - a) The wireless access dedicated network is required to have wide coverage so as to meet the access requirements of widely distributed IoT devices (such as electric vehicle charging stations [b-IEC 61851-1] and energy meters [b-IEC TR 62051]).
+
+- b) The wireless access dedicated network backhaul is required to support the capability of end-to-end dual redundancy in order to protect services in time when an error occurs.
+
+NOTE 4 – As a network, the protection switching time should not exceed 50 ms.
+
+- c) The wireless access dedicated network is required to support the capability of roaming, so as to provide lossless roaming and data transmission for mobile IoT devices.
+- d) The wireless access dedicated network is required to support the capability of interference avoidance and wireless optimization, so as to avoid co-channel interference between multiple access points (APs) with the same coverage area.
+
+NOTE 5 – Wireless optimization means the channel and power of APs can be adjusted dynamically. The channel and power of APs managed by the same wireless access controller (WAC) are balanced, ensuring that APs work in the optimal state.
+
+- e) The wireless access dedicated network is required to provide robust wireless secure connectivity including authorization and authentication.
+
+NOTE 6 – This includes support for wireless protocols such as Bluetooth [b-Bluetooth v5.3] and Zigbee [b-Zigbee R23]. Robust wireless connectivity enhances communication reliability, facilitates real-time data transmission and enables efficient monitoring and control of power grid assets.
+
+### 3) **Wired access dedicated network requirements:**
+
+- a) The wired access dedicated network is required to support high-bandwidth transmission, so as to meet the video transmission requirements for remote inspection services.
+
+NOTE 7 – For example, the access bandwidth for a video camera in a substation is 4-6 Mbit/s.
+
+- b) The wired access dedicated network is required to be reliable. In particular, it is required to support inter-device backup to improve device-level reliability and inter-device link aggregation to improve link-level reliability.
+- c) The wired access dedicated network is required to support secure connectivity and device authentication (media access control (MAC) address authentication, 802.1X [b-IEEE 802.1X] authentication).
+- d) The wired access dedicated network is required to support the dynamic delivery of IoT device network policies (including virtual local area network (VLAN), QoS and access control list (ACL)), so as to prevent the access of unauthorized devices and restrict network permissions for devices.
+
+- e) The wired access dedicated network is required to be deployed and maintained easily. It is also required to support zero-touch deployment and automated upgrades.
+
+NOTE 8 – Zero-touch deployment is an automatic deployment process without user involvement [b-ITU-T X.1353].
+
+NOTE 9 – Automated upgrade means the network devices can automatically obtain the latest-version system software and download it for upgrades. The upgrade process is automated.
+
+## **7.6 Gateway interface requirements**
+
+- 1) The gateway is required to support edge computing [b-ITU-T Y.3073], so as to process and analyse data collected by IoT devices.
+- 2) The gateway is required to provide plug-and-play capability [ITU-T Y.4112] for various devices to realize the on-demand deployment of IoT devices and applications.
+
+- 3) The gateway is required to support communication interface management.
+
+NOTE 1 – This includes adaptation to different data rates, bandwidths, transmission modes and other interface-specific characteristics.
+
+- 4) The gateway is required to support protocol translation and data transformation capabilities [ITU-T Y.4101].
+
+NOTE 2 – This enables seamless communication between devices that may use different communication protocols. Gateways translate the protocols used by IoT devices into protocols compatible with the communication networks they connect to.
+
+The communication protocols may include but are not limited to: transmission control protocol and Internet protocol (TCP/IP) [b-IETF RFC 793] [b-IETF RFC 791], message queuing telemetry transport (MQTT) [b-OASIS MQTT] and distributed network protocol 3 (DNP3) [b-IEEE 1815].
+
+NOTE 3 – By supporting a variety of communication protocols and technologies, the gateway interfaces ensure compatibility and interoperability across different IoT devices and networks within the power grid ecosystem. Interoperability ensures smooth and efficient data exchange between devices, control centres and other network components, enabling effective grid management and real-time monitoring.
+
+- 5) The gateway is required to support encryption algorithms, authentication mechanisms and secure communication protocols.
+
+NOTE 4 – These capabilities can authenticate devices connecting to the network and enforce secure communication channels to prevent unauthorized access and data breaches.
+
+- 6) The gateway is required to support a high number of connections and be capable of adapting to evolving communication standards and technologies.
+
+NOTE 5 – Scalability ensures that the gateway can handle the expanding power grid ecosystem and the increasing volume of data traffic generated by electric power IoT devices.
+
+- 7) Devices and gateways to be connected directly to the dedicated access network or public network (e.g., public switched telephone network (PSTN) and public land mobile network (PLMN)) are required to support IPv6 or IPv4/IPv6 dual stack.
+
+NOTE 6 – In view of the Internet Architecture Board's statement on IPv6 [b-IETF IAB IPv6], IPv4 compatibility may not be available in future developments, i.e., in new or extended protocols. Therefore, transition to IPv6 only in PSTN/PLMN networks will be required in the future. Gateways and devices to be connected directly to these networks will also be required to switch over to IPv6-only capability.
+
+## 7.7 Local communication network requirements
+
+The local communication network is composed of a wired local communication network and a wireless local communication network.
+
+- 1) Wireless local communication network requirements:
+
+- a) The wireless local communication network is required to support the capability of roaming and high reliability, so as to provide lossless roaming and reliable data transmission for mobile devices.
+
+- b) The wireless local communication network is required to support the capability of interference avoidance and wireless optimization.
+
+NOTE 1 – The capability of interference avoidance prevents co-channel interference between multiple wireless APs with the same coverage area.
+
+- c) Wireless local communication network devices are required to support wireless networking capability.
+
+NOTE 2 – The environment inside the substation is complex. There are areas where wired cables cannot be laid. Therefore, wireless local communication devices are required to support wireless networking capability, so as to establish wireless links with nearby network devices.
+
+- d) The wireless local communication network is required to provide robust wireless connectivity. Robust wireless connectivity enhances communication reliability, facilitates real-time data transmission and enables efficient monitoring and control of power grid assets.
+
+- e) The wireless local communication network is required to support access control and secure access capabilities.
+
+NOTE 3 – This requirement includes support of bidirectional identity authentication among electric power IoT devices, APs and networks. For example, by means of AP wired authentication and automatic configuration delivery, unauthorized APs cannot access the network.
+
+### 2) Wired local communication network requirements:
+
+- a) Wired local communication network devices are required to support the capability of access at different rates, so as to meet the access requirements of IoT devices with different communication rates.
+
+- b) The wired local communication network is required to support multicast capability, so as to meet the access requirements of high definition (HD) video surveillance and videoconference applications.
+
+NOTE 4 – Multicast is one transmission mode which allows packets sent by a source to be forwarded to a specific group of receivers. There is at most one copy of the same multicast data flow on each link. Compared with traditional unicast and broadcast, multicast effectively conserves network bandwidth and reduces network load.
+
+- c) Wired local communication network devices are required to support power over Ethernet (PoE)++ [b-IEEE 802.3bt] interfaces, fast PoE function and fast power supply for IoT devices after startup.
+
+NOTE 5 – Many electric power IoT devices in substations obtain power from network devices (such as cameras).
+
+- d) The wired local communication network is required to support Ethernet operations, administration and maintenance (OAM) capability [b-IEEE 802.3ah] to detect link faults promptly.
+
+- e) The wired local communication network is required to support the switch stacking function.
+
+NOTE 6 – By this function, multiple switches can be logically virtualized into one switch, which can simplify the management of network devices and improve network reliability.
+
+Switch stacking is a method of binding multiple switches so that they can act as a single switch.
+
+- f) The wired local communication network is required to support strict address resolution protocol (ARP) learning, so as to avoid illegal devices and user network failure caused by ARP spoofing attacks.
+
+NOTE 7 – Strict ARP learning means the device does not learn the ARP entry of the source IP address when it receives an ARP request packet. The ARP entry will be learned only when the device receives an ARP reply packet and the destination IP address of the packet is the local IP address.
+
+## 7.8 Communication network security requirements
+
+- 1) The power grid communication network devices are required to support access security and threat detection capabilities. This includes, but is not limited to, support of device authentication and access control capabilities.
+- 2) The power grid communication network is required to support secure transmission protocols (e.g., media access control security (MACSec) [b-IEEE 802.1AE]) to achieve end-to-end data protection.
+- 3) The power grid communication network is required to support data transfer analysis and prevention of unauthorized data transfer for sensitive data, in order to ensure that data resources are manageable and controllable.
+
+NOTE 1 – Sensitive data in the power grid includes but is not limited to user data and production and control type service data.
+
+- 4) Network segmentation is recommended to be employed to isolate critical systems and sensitive data from other parts of the network. This minimizes the impact of a potential security breach and helps to contain threats within a limited scope.
+- 5) The power grid communication network is required to undergo regular security audits to identify and address vulnerabilities.
+
+NOTE 2 – These audits are to assess compliance with established security policies, standards, and regulatory requirements [b-ISO/IEC 27002].
+
+- 6) The power grid communication network is required to perform periodic penetration testing to evaluate its security posture and ensure the protection of critical infrastructure.
+
+NOTE 3 – Penetration tests simulate cyberattacks to identify and exploit vulnerabilities in a controlled environment, providing insights into potential security weaknesses and enabling the implementation of corrective measures [b-ISO/IEC 27001].
+
+- 7) Endpoint IoT devices are required to be secured based on security standards.
+
+NOTE 4 – The vulnerabilities in these devices may significantly impact the trust of devices, device software assets and communication networks in various ways, such as the spread of malware and ransomware, denial of service (DoS), data interception and eavesdropping. It may result in a network outage impacting the network operations.
+
+- 8) The power grid communication network is required to support the network fault management capability, including fault detection, fault isolation and fault correction. This capability can reduce the impact of network faults on electric power services.
+
+# **Appendix I**
+
+## **Deployment and application examples of IoT-based power grid communication network**
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix provides two examples for the deployment and application of the IoT-based power grid communication network.
+
+The deployment example given in clause I.1 provides a description of the deployment practice of the IoT-based communication network in a substation. It introduces technologies that could be used to support the requirements described in clause 7. This example will be of great value to guide the construction of an IoT-based power grid communication network.
+
+The application example given in clause I.2 provides a description of the services carried by different components of the IoT-based power grid communication network reference model in the microgrid [b-IEEE 2030.7]. It also introduces the related requirements of these services in the microgrid, which are a subset of the requirements described in clause 7. This example will be helpful for the understanding of the power grid communication network's requirements.
+
+### **I.1 IoT-based power grid communication network for substation system**
+
+As one of the important energy transmission nodes of the power grid, a substation provides the functions of power grid production, operation and control.
+
+The basic components of an IoT-based power grid communication network for a substation system are shown in Figure I.1.
+
+
+
+Figure I.1 – IoT-based power grid communication network for a substation system. The diagram is organized into three main layers: Application layer and SSAS layer, Network layer, and Device layer. In the Application layer, there are 'Dispatching and control system' and 'Equipment monitoring system' connected to the Network layer. In the Network layer, the 'Electric power bearer network' (cloud) connects to 'Provincial area (OTN)', 'Metro area (SPN/SDH)', and 'Metro area (SPN/SDH)'. It also connects to 'Dispatching data dedicated network' (with routers) and 'Data communication dedicated network' (with IPv4/IPv6 routers). The 'Dispatching data dedicated network' connects to 'Power grid access dedicated network' (with Industrial LAN switches). The 'Data communication dedicated network' connects to 'Industrial LAN switch' and 'Wireless network'. In the Device layer, there are 'Electric power IoT devices for production and control type services', 'Electric power IoT devices operation monitoring type services', 'Electric power IoT devices remote inspection type services', 'Electric power IoT devices O&M and management type services', and 'Electric power IoT devices commanding and liaison type services'. These devices connect to the Industrial LAN switches and the Wireless network. A 'Common middleware' connects the Application layer to the Network layer. A 'Centralized remote intelligent inspection monitor system' and a 'Management information type service system' are also connected to the Network layer.
+
+**Figure I.1 – IoT-based power grid communication network for a substation system**
+
+The IoT application layer for a substation includes two systems based on the service type, one system for production and control type services and the other system for information management services.
+
+To support the communication from IoT devices to the IoT applications, the basic components of an IoT-based power grid communication network can be divided into five parts: electric power bearer network, data communication dedicated network, dispatching data dedicated network, power grid access dedicated network and IoT devices.
+
+#### I.1.1 Electric power bearer network
+
+The electric power bearer network is divided into the provincial fibre bearer network and metro fibre bearer network. The electric power bearer network is used to support the data transmission from the substations of each voltage level to the IoT application system. The slicing packet network (SPN) [b-CCSA YD/T 3826] and synchronous digital hierarchy (SDH) [b-ITU-T G.703] technologies are deployed in the metro bearer network. The optical transport network (OTN) [b-ITU-T G.709] technology is deployed in the provincial bearer network.
+
+#### **I.1.2 Data communication dedicated network**
+
+The data communication dedicated network is divided into two levels: data communication backbone network and data communication metro network. The segment routing IPv6 (SRv6) [b-IETF RFC 8986], network slicing [b-ITU-T Y.3112] and in-situ flow information telemetry [b-IETF RFC 9341] technologies are deployed in the data communication dedicated network.
+
+#### **I.1.3 Dispatching data dedicated network**
+
+The dispatching data dedicated network provides two VPNs for dispatching services: real-time VPN to carry production and control type services and non-real-time VPNs to carry production control services and operation monitoring services, both with high requirements on latency, security and QoS. The multi-protocol label switching (MPLS) VPN [b-IETF RFC 4364] technology is deployed in the dispatching data dedicated network.
+
+#### **I.1.4 Power grid access dedicated network**
+
+The power grid access dedicated network includes the communication network deployed in substations and the wireless dedicated network. It supports data aggregation and transmission of electric power IoT devices in substations. The industrial Ethernet technologies (such as those based on the real-time Ethernet communication profiles described in [b-IEC 61784-2-19]) are deployed in the power grid access dedicated network.
+
+#### **I.1.5 IoT device layer of substation**
+
+The IoT device layer of the substation mainly refers to the electric power IoT devices that need to be accessed by wired or wireless means, including production and control, operation monitoring, remote inspection, operation and maintenance management and command and liaison services.
+
+### **I.2 Application of IoT-based power grid communication network in the microgrid**
+
+The microgrid is an important supplement to the large power grid and an important part of the power grid. It is a small power system consisting of a distributed power generation, loads, energy storage, power transformation, power distribution and control systems. It is an autonomous power system capable of self-control, protection and management, with complete power generation, distribution and consumption functions, and can achieve energy optimization within the network.
+
+Figure I.2 shows the basic components of an IoT-based power grid communication network in the microgrid.
+
+
+
+The diagram illustrates the components of an IoT-based power grid communication network in the microgrid, organized into three main layers:
+
+- Application layer and SSAS layer:** Contains six services/platforms: Energy storage control service, Automated distribution service, Load control service, Distributed power supply control service, Power consumption information collection, and Internet of vehicles platform.
+- Network layer:** Contains several network components:
+ - Electric power dedicated line (with Primary path and Redundant path)
+ - Dispatching data dedicated network (with Primary path and Redundant path)
+ - Data communication dedicated network (with Primary path and Redundant path)
+ - Microgrid bearer network
+ - Microgrid core network
+ - Microgrid access dedicated network
+- Device layer:** Contains:
+ - Microgrid local communication network
+ - Microgrid IoT devices: Energy storage devices, Distribution automation devices, Load control devices, Distributed power supply devices, Smart meter, Electric vehicle charging pile, and Transformers.
+
+Arrows indicate bidirectional communication between the layers and within the Network layer components.
+
+Figure I.2 – Components of an IoT-based power grid communication network in the microgrid. The diagram shows a three-layer architecture: Application layer and SSAS layer, Network layer, and Device layer. The Application layer includes Energy storage control service, Automated distribution service, Load control service, Distributed power supply control service, Power consumption information collection, and Internet of vehicles platform. The Network layer includes Electric power dedicated line (Primary path, Redundant path), Dispatching data dedicated network (Primary path, Redundant path), Data communication dedicated network (Primary path, Redundant path), Microgrid bearer network, Microgrid core network, and Microgrid access dedicated network. The Device layer includes Microgrid local communication network and Microgrid IoT devices (Energy storage devices, Distribution automation devices, Load control devices, Distributed power supply devices, Smart meter, Electric vehicle charging pile, Transformers).
+
+Y.4235(25)
+
+**Figure I.2 – Components of an IoT-based power grid communication network in the microgrid**
+
+The microgrid IoT application layer includes the energy storage control service, automated power distribution service, load control service, distributed power control service, power consumption information collection, and Internet of vehicles (IoV) platform.
+
+To support the communication between IoT devices and IoT applications, the microgrid power communication network can be divided into seven parts: electric power dedicated line, dispatching data dedicated network, data communication dedicated network, microgrid bearer network, microgrid access dedicated network, microgrid local communication network and microgrid IoT devices.
+
+#### **I.2.1 Electric power dedicated line**
+
+The electric power dedicated line in the microgrid supports the transmission of precise load control services and power distribution line protection services for important users and stations. High security and service quality and low latency are essential for this network.
+
+#### **I.2.2 Dispatching data dedicated network**
+
+The dispatching data dedicated network in the microgrid is used to support the transmission of the dispatching and control services of the microgrid. It provides transmission and exchange of real-time and near-real-time production data services between the microgrid and the dispatching station. Low latency and redundancy assurance are essential for this network.
+
+#### **I.2.3 Data communication dedicated network**
+
+The data communication network in the microgrid is used to support the transmission of microgrid management information and provide the transmission of various microgrid services such as data, video and voice. High bandwidth and network quality assurance are essential for this network.
+
+#### **I.2.4 Microgrid bearer network**
+
+The microgrid bearer network is used to support the aggregation and transmission of various power grid services in the microgrid. High bandwidth and different-level isolation are essential for this network.
+
+#### **I.2.5 Microgrid access dedicated network**
+
+The access dedicated network in the microgrid includes wired and wireless dedicated networks. It supports access, data aggregation and transmission for IoT devices in the microgrid. There are many types of microgrid IoT devices, which are widely distributed. Therefore, wide coverage and access for massive IoT devices are essential for these services.
+
+#### **I.2.6 Microgrid local communication network**
+
+The microgrid local communication network is used to support the access of various IoT devices in the microgrid, including wired and wireless access. Robust and secure access and a flexible access mode based on the type of devices and on-site environment are essential for this network.
+
+#### **I.2.7 Microgrid IoT devices**
+
+Microgrid IoT devices include but are not limited to energy storage devices and distribution automation devices, load control devices, distributed power supply devices, smart meters, electric vehicle charging piles and transformers. Multiple communication modes, plug-and-play capability, and adapting to complex environments are essential for the local communication network and gateway.
+
+## Bibliography
+
+- [[b-ITU-T F.751.5](#)] Recommendation ITU-T F.751.5 (2022), *Requirements for distributed ledger technology-based power grid data management*.
+- [[b-ITU-T G.703](#)] Recommendation ITU-T G.703 (2016), *Physical/electrical characteristics of hierarchical digital interfaces*.
+- [[b-ITU-T G.709](#)] Recommendation ITU-T G.709/Y.1331 (2020), *Interfaces for the optical transport network*.
+- [[b-ITU-T X.1353](#)] Recommendation ITU-T X.1353 (2024), *Blockchain-based security methodology for zero-touch deployment of massive Internet of things*.
+- [[b-ITU-T Y.3073](#)] Recommendation ITU-T Y.3073 (2024), *Framework for service function chaining in information-centric networking*.
+- [[b-ITU-T Y.3112](#)] Recommendation ITU-T Y.3112 (2018), *Framework for the support of network slicing in the IMT-2020 network*.
+- [[b-ITU-T Y.4000](#)] Recommendation ITU-T Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+- [[b-ITU-T Y.4218](#)] Recommendation ITU-T Y.4218 (2023), *Internet of things and information and communication technology requirements for deployment of smart services in rural communities*.
+- [b-GSTR-TN5G] Technical Report ITU-T GSTR-TN5G (2018), *Transport network support of IMT-2020/5G*.
+<[https://www.itu.int/dms\\_pub/itu-t/opb/tut/T-TUT-HOME-2018-PDF-E.pdf](https://www.itu.int/dms_pub/itu-t/opb/tut/T-TUT-HOME-2018-PDF-E.pdf)>
+- [b-IEC 60050-605] IEC 60050-605:1983, *International Electrotechnical Vocabulary (IEV) – Part 605: Generation, transmission and distribution of electricity – Substations*.
+<>
+- [b-IEC 61784-2-19] IEC 61784-2-19:2023, *Industrial networks – Profiles – Part 2-19: Additional real-time fieldbus profiles based on ISO/IEC/IEEE 8802-3 – CPF 19*.
+<>
+- [b-IEC 61851-1] IEC 61851-1:2017, *Electric vehicle conductive charging system – Part 1: General requirements*. <>
+- [b-IEC TR 62051] IEC TR 62051:1999, *Electricity metering – Glossary of terms*.
+<>
+- [b-IEEE 802.15.1] IEEE 802.15.1-2005, *IEEE Standard for Information technology – Local and metropolitan area networks – Specific requirements – Part 15.1a: Wireless Medium Access Control (MAC) and Physical Layer (PHY) specifications for Wireless Personal Area Networks (WPAN)*.
+<>
+- [b-IEEE 802.1AE] IEEE 802.1AE-2018, *IEEE Standard for Local and metropolitan area networks – Media Access Control (MAC) Security*.
+<>
+- [b-IEEE 802.1X] IEEE 802.1X-2020, *IEEE Standard for Local and Metropolitan Area Networks – Port-Based Network Access Control*.
+<>
+
+- [b-IEEE 802.3ah] IEEE 802.3ah-2004, *IEEE Standard for Information technology – Local and metropolitan area networks – Part 3: CSMA/CD Access Method and Physical Layer Specifications Amendment: Media Access Control Parameters, Physical Layers, and Management Parameters for Subscriber Access Networks*.
+<>
+- [b-IEEE 802.3bt] IEEE 802.3bt-2018, *IEEE Standard for Ethernet Amendment 2: Physical Layer and Management Parameters for Power over Ethernet over 4 pairs*.
+<>
+- [b-IEEE 1815] IEEE 1815-2012, *IEEE Standard for Electric Power Systems Communications-Distributed Network Protocol (DNP3)*.
+<>
+- [b-IEEE 2030.7] IEEE 2030.7-2017:2018, *IEEE Standard for the Specification of Microgrid Controllers*.
+<>>
+- [b-IETF IAB IPv6] IETF IAB IPv6 (2016), *IAB Statement on IPv6*.
+<>
+- [b-IETF RFC 791] IETF RFC 791 (1981), *Internet Protocol*.
+<>
+- [b-IETF RFC 793] IETF RFC 793 (1981), *Transmission Control Protocol*.
+<>
+- [b-IETF RFC 2328] IETF RFC 2328 (1998), *OSPF Version 2*.
+<>
+- [b-IETF RFC 2475] IETF RFC 2475 (1998), *An Architecture for Differentiated Services*.
+<>
+- [b-IETF RFC 4364] IETF RFC4364 (2006), *BGP/MPLS IP Virtual Private Networks (VPNs)*.
+<>
+- [b-IETF RFC 5340] IETF RFC 5340 (2008), *OSPF for IPv6*.
+<>
+- [b-IETF RFC 8986] IETF RFC 8986 (2021), *Segment Routing over IPv6 (SRv6) Network Programming*.
+<>
+- [b-IETF RFC 9341] IETF RFC 9341 (2022), *Alternate-Marking Method*.
+<>
+- [b-ISO/IEC 10589] ISO/IEC 10589:2002, *Information technology – Telecommunications and information exchange between systems – Intermediate System to Intermediate System intra-domain routing information exchange protocol for use in conjunction with the protocol for providing the connectionless-mode network service (ISO 8473)*.
+<>
+- [b-ISO/IEC 27001] ISO/IEC 27001:2022, *Information security, cybersecurity and privacy protection – Information security management systems – Requirements*.
+<>
+- [b-ISO/IEC 27002] ISO/IEC 27002:2022, *Information security, cybersecurity and privacy protection – Information security controls*.
+<>
+
+- [b-3GPP TR 22.804] 3GPP TR 22.804 (2017), *Study on Communication for Automation in Vertical domains (CAV)*.
+<>
+- [b-Bluetooth v5.3] Bluetooth SIG Bluetooth Specification (2021), *Bluetooth Core Specification v5.3*.
+<[https://www.bluetooth.org/DocMan/handlers/DownloadDoc.ashx?doc\\_id=521059](https://www.bluetooth.org/DocMan/handlers/DownloadDoc.ashx?doc_id=521059)>
+- [b-CCSA YD/T 3826] CCSA YD/T 3826-2021 (2021), *General technical requirements for Sliced Packet Network (SPN)*.
+<[https://transcustoms.cn/GB\\_standards/GB\\_standards\\_cn.asp?code=YD/T%203826-2021](https://transcustoms.cn/GB_standards/GB_standards_cn.asp?code=YD/T%203826-2021)>
+- [b-OASIS MQTT] OASIS (2014), *MQTT standard Version 3.1.1*.
+<>
+- [b-Zigbee R23] Zigbee Alliance Document 05-3474-23:2023, *Zigbee Specification Revision 23*.
+<>
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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new file mode 100644
index 0000000000000000000000000000000000000000..db6ea7855788c07cb13d65e23b8b58e395cd6792
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@@ -0,0 +1,565 @@
+
+
+I n t e r n a t i o n a l T e l e c o m m u n i c a t i o n U n i o n
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+# Y.4419
+
+(07/2021)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Internet of things and smart cities and communities –
+Frameworks, architectures and protocols
+
+# --- **Requirements and capability framework of smart utility metering (SUM)**
+
+Recommendation ITU-T Y.4419
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Computing power networks | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+Y.3000–Y.3499
+
+### CLOUD COMPUTING
+
+Y.3500–Y.3599
+
+### BIG DATA
+
+Y.3600–Y.3799
+
+### QUANTUM KEY DISTRIBUTION NETWORKS
+
+Y.3800–Y.3999
+
+### INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|----------------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+## Recommendation ITU-T Y.4419
+
+# Requirements and capability framework of smart utility metering (SUM)
+
+## Summary
+
+Recommendation ITU-T Y.4419 specifies requirements and capabilities for support for smart utility metering (SUM).
+
+Smart utility metering (SUM) can provide remote data collection for utility metering and device maintenance in real time and can support a variety of applications. Compared with other types of utility metering, SUM intends to improve utility management and meet the emerging requirements from advanced applications, such as intelligent utility scheduling.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.4419 | 2021-07-14 | 20 | 11.1002/1000/14736 |
+
+## Keywords
+
+Capabilities, IoT, requirements, smart utility metering.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2021
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|-------------------------------------------------------|-------------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere..... | 1 |
+| 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 2 |
+| 6 Introduction to smart utility metering..... | 2 |
+| 7 Requirements of SUM ..... | 3 |
+| 7.1 SUM platform requirements..... | 3 |
+| 7.2 SUM device requirements ..... | 4 |
+| 8 Capability framework of SUM ..... | 5 |
+| 8.1 Smart utility metering platform capabilities..... | 5 |
+| 8.2 Smart utility metering device capabilities ..... | 7 |
+| Appendix I – Use cases of smart utility metering..... | 9 |
+| I.1 Remote data collection ..... | 9 |
+| I.2 Device maintenance..... | 9 |
+| I.3 Data analysis and presentation ..... | 10 |
+| Bibliography..... | 11 |
+
+
+
+## Recommendation ITU-T Y.4419
+
+## Requirements and capability framework of smart utility metering (SUM)
+
+## 1 Scope
+
+This Recommendation specifies the requirements and capability framework of smart utility metering (SUM).
+
+As a smart application of the internet of things (IoT) in the field of utility metering, SUM is an important means to improve utility metering management.
+
+The scope of this Recommendation includes:
+
+- Introduction of SUM;
+- Requirements of SUM;
+- Capability framework of SUM.
+
+Use cases of SUM are provided in Appendix I.
+
+NOTE 1 – Though different utilities, such as electricity, water and gas, are considered in this context, the scope of this Recommendation focuses on the common requirements and capability framework for SUM. The specific requirements and capability framework for each utility, including utility management and utility delivery, lie outside the scope of this Recommendation.
+
+NOTE 2 – Metering related security aspects are specified in [b-ITU-T X.1332] and are not addressed in this Recommendation.
+
+NOTE 3 – Policy and regulation matters lie outside the scope of this Recommendation.
+
+## 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- | | |
+|----------------|---------------------------------------------------------------------------------------------------|
+| [ITU-T Y.4000] | Recommendation ITU-T Y.4000/Y.2060 (2012), Overview of the Internet of things . |
+| [ITU-T Y.4100] | Recommendation ITU-T Y.4100/Y.2066 (2014), Common requirements of the Internet of things . |
+
+## 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 device** [ITU-T Y.4000]: With regard to the Internet of things, this is a piece of equipment with the mandatory capabilities of communication and the optional capabilities of sensing, actuation, data capture, data storage and data processing.
+
+**3.1.2 Internet of things (IoT)** [ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.
+
+NOTE 1 – Through the exploitation of identification, data capture, processing and communication capabilities, the IoT makes full use of things to offer services to all kinds of applications, whilst ensuring that security and privacy requirements are fulfilled.
+
+NOTE 2 – From a broader perspective, the IoT can be perceived as a vision with technological and societal implications.
+
+**3.1.3 meter** [b-ITU-T Y.4109]: A device that measures and optionally records the quantity, degree or rate of something, especially the amount of electricity, gas or water used.
+
+NOTE – A meter is responsible for measuring the total amount of something consumed in a period.
+
+**3.1.4 usage metering** [b-ITU-T X.742]: The abstraction of activities that monitor the utilization of resources, for the purpose of accounting and controlling the recording of usage data.
+
+### **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following term:
+
+**3.2.1 utility:** A service that is used by the public, such as an electricity, water or gas supply.
+
+## **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+API Application Programming Interface
+
+GNSS Global Navigation Satellite System
+
+IoT Internet of Things
+
+SUM Smart Utility Metering
+
+Wi-Fi Wireless Fidelity
+
+## **5 Conventions**
+
+In this Recommendation:
+
+The phrase "is required to" indicates a requirement that must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+
+The phrase "is recommended" indicates a requirement that is recommended but which is not absolutely required. Thus, this requirement needs not be present to claim conformance.
+
+The phrase "can optionally" and "may" indicate an optional requirement that is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator or service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with the specification.
+
+## **6 Introduction to smart utility metering**
+
+Utility metering is widely used in private homes and commercial areas, providing measurements of utility services including electricity, gas and water. Utility metering applications include data management and device maintenance.
+
+SUM provides self-monitoring utility metering that supports data management with remote data collection and efficient device maintenance, and can also support other applications. Remote data
+
+collection saves human resources and improves data management efficiency. Efficient device maintenance leads to reduced system downtime and operation interruptions. Advanced applications, such as utility quality monitoring, can improve the user experience.
+
+This Recommendation describes requirements and a capability framework for SUM.
+
+Figure 1 is an overall conceptual diagram of SUM.
+
+
+
+Figure 1 – Overall conceptual diagram for SUM. The diagram shows a central 'SUM platform' box containing server icons. To the left, 'SUM devices' (represented by a city and industrial icons) connect to the platform via a dashed line labeled 'IoT network'. Above the platform are three boxes: 'Smart water platform', 'Smart building platform', and 'Smart gas platform', each connected to the central platform by a double-headed arrow. Below the platform are two boxes: 'Smart city platform' and 'Other platforms', also connected by double-headed arrows. To the right, 'Other SUM users' (represented by a laptop and a smartphone) are connected to the platform by a double-headed arrow. A legend at the bottom indicates that dashed lines represent 'Communication' and double-headed arrows represent 'Interface'. The identifier 'Y.4419(21)' is located in the bottom right corner.
+
+**Figure 1 – Overall conceptual diagram for SUM**
+
+SUM devices measure utility information, which includes but is not limited to utility consumption. SUM devices consist of meters connected to an IoT network. The IoT network enables the interaction between SUM devices and the SUM platform. The SUM platform is responsible for collecting and managing metering data. It provides the resulting metering information to SUM users, including utility consumers and providers, third party applications and other platforms.
+
+NOTE – The SUM platform may interact with other platforms for mutual exchange of beneficial information as shown in Figure 1. In some scenarios, the SUM platform may even be integrated within a larger scope system such as a smart city system.
+
+## 7 Requirements of SUM
+
+SUM devices are resource-constrained and time delay insensitive, and have low power consumption. Based on these characteristics, SUM has some specific requirements.
+
+In addition to the common requirements specified in [ITU-T Y.4100], specific requirements for SUM are listed in clauses 7.1 and 7.2.
+
+### 7.1 SUM platform requirements
+
+The SUM platform is required:
+
+- To collect measurement information;
+
+NOTE 1 – Measurement information includes utility consumption, other data from other sensors (e.g., water pressure), and device information (e.g., working status, working battery capacity).
+
+- To check and analyse the integrity and correctness of the collected data;
+
+NOTE 2 – When received, the SUM platform discards incomplete or erroneous data. Re-transmission of such data is not required, in order to save power consumption.
+
+- To process and analyse collected data, in order to implement applications such as metering data analysis and faulty SUM device detection;
+
+- To provide capabilities of data presentation to SUM users;
+
+NOTE 3 – Examples of data presentation modalities include web portal and mobile applications.
+
+- To manage the location information of SUM devices as appropriate;
+
+- To provide detection of faulty SUM devices;
+
+- To report faulty SUM devices and present fault information;
+
+- To support remote SUM device configuration;
+
+NOTE 4 – For example, the platform can set the uploading time of metering information for SUM devices.
+
+- To support data recovery after platform failures.
+
+The SUM platform can optionally:
+
+- Expose open application programming interfaces (APIs) to third party applications for SUM service purposes;
+
+- Provide interfaces to other platforms to exchange information as appropriate;
+
+- Manage SUM device maintenance records and send reminders to relevant personnel when any scheduled maintenance procedure is needed.
+
+NOTE 5 – For example, the platform can manage replacement and calibration records.
+
+### **7.2 SUM device requirements**
+
+SUM devices are required:
+
+- To collect measurement information;
+
+- To transfer collected measurements in an appropriate format;
+
+NOTE 1 – The reporting interval is normally set to 1 day or 1 week. It can be modified by SUM device configuration.
+
+NOTE 2 – To avoid too many wake-ups and interactions, the reported data is suggested to be aggregated in one message, so the SUM device can transfer only once to complete the reporting.
+
+- To store and execute configuration settings received from the SUM platform;
+
+- To report fault information to the SUM platform where possible.
+
+SUM devices are recommended:
+
+- To be time synchronized with the SUM platform.
+
+NOTE 3 – Time synchronization does not imply a frequent and/or constant exchange with the platform (in line with the SUM devices' limited resources).
+
+SUM devices can optionally:
+
+- Report their location information to the SUM platform where possible.
+
+NOTE 4 – SUM devices may not have location capabilities such as global navigation satellite system (GNSS) and wireless fidelity (Wi-Fi) [b-IEEE-802.11] positioning.
+
+## 8 Capability framework of SUM
+
+Based on the IoT reference model specified in [ITU-T Y.4000], Figure 2 illustrates the SUM capability framework, which consists of four layers and two cross-layer capability groups.
+
+In addition to the capabilities specified in [ITU T Y.4000], specific capabilities are required for the SUM platform and SUM devices. These specific capabilities are shown via the yellow highlighted boxes and their explanatory panels in Figure 2.
+
+
+
+Y.4419(21)
+
+Figure 2: Capability framework for SUM. The diagram shows a four-layer architecture: Application layer, Service support and application support layer, Network layer, and Device layer. The Application layer contains 'SUM platform capability' (yellow). The Service support and application support layer contains 'Data processing capability' and 'Data storage capability'. The Network layer contains 'Network capability' and 'Transport capability'. The Device layer contains 'SUM device capability' (yellow) and 'Gateway capability'. Two vertical bars on the sides represent 'Generic management capabilities' and 'Generic security capabilities'. Below the layers, two detailed boxes explain the yellow-highlighted capabilities. The left box details 'SUM platform capability' with sub-capabilities: Connecting capability, Data processing capability, Configuration setting storage and execution capability, Maintenance capability, and Data measurement capability. The right box details 'SUM device capability' with sub-capabilities: Data presentation capability, Configuration setting management capability, Maintenance capability, Statistical and analysis capability, Data transfer capability, and Interface capability to third party applications or other platforms. Dashed lines connect the yellow boxes in the layers to their respective detailed boxes.
+
+**Figure 2 – Capability framework for SUM**
+
+### 8.1 Smart utility metering platform capabilities
+
+According to the SUM requirements specified in clauses 7.1 and 7.2, the SUM platform capabilities include those for data transfer, configuration setting management, maintenance, statistics and analysis, data presentation and interface to other platforms. The details of these capabilities are described in clauses 8.1.1 to 8.1.6.
+
+NOTE – Additional SUM platform capabilities related to object modelling techniques, for example [b-IEC TS 62056-6-9], are not addressed in this Recommendation.
+
+#### 8.1.1 Data transfer capability
+
+The data transfer capability transfers data between different capabilities of the SUM platform. It includes but is not limited to:
+
+- Sending the measurement, identity and type of SUM devices to maintenance management capability, and statistics and analysis capability;
+- Sending configuration settings from the configuration setting management capability to SUM devices;
+
+- Checking and analysing the integrity and correctness of the collected SUM data, discarding it when it is erroneous or incomplete.
+
+#### **8.1.2 Configuration setting management capability**
+
+The configuration setting management capability manages the creation, modification and deletion of configuration settings. It includes but is not limited to:
+
+- Creating configuration settings, such as the measurement frequency and time interval of report;
+- Modifying and deleting configuration settings;
+- Sending configuration settings to the data transfer capability;
+- Caching commands when SUM devices are offline, and sending commands when SUM devices are online.
+
+#### **8.1.3 Maintenance capability**
+
+The maintenance capability maintains SUM devices. It includes but is not limited to:
+
+- Storing, updating and deleting SUM device information, such as identity, type and location information;
+- Addressing queries about device information and operating status to SUM devices;
+- Recognizing and detecting the identity, type and operating status of SUM devices from the data transfer capability;
+- Informing maintenance personnel when a fault is detected;
+- Automatically generating fault reports from the operating status;
+- Optionally managing the SUM device maintenance records and sending reminders to relevant personnel when any scheduled maintenance procedure is needed;
+- Providing data recovery after platform failures.
+
+#### **8.1.4 Statistics and analysis capability**
+
+The statistics and analysis capability analyses measurement data, and generates analysis reports and warning events. It includes but is not limited to:
+
+- Processing measurement data based within one area or one time period, such as water consumption in a certain area or electricity consumption within a certain time interval;
+- Detecting abnormal measurement data, and generating warning events.
+
+#### **8.1.5 Data presentation capability**
+
+The data presentation capability presents measurement information. It includes, but is not limited to, interface provision:
+
+- To authorized SUM users to present raw measurement data and analysis reports;
+- To authorized SUM users to present the physical distribution of all SUM devices, and the maintenance status of each SUM device;
+- To authorized SUM users to present the physical distribution of faulty SUM devices with their fault information;
+- To authorized SUM users to present abnormal data and warnings about particular SUM devices.
+
+#### **8.1.6 Interface capability to third party applications or other platforms**
+
+The interface capability to third party applications or other platforms provides interfaces between the SUM platform and third party applications or other platforms. It includes but is not limited to:
+
+- The optional exposure of open APIs to third party applications for SUM service purposes;
+- The optional provision of interfaces to other platforms to exchange information as appropriate.
+
+### **8.2 Smart utility metering device capabilities**
+
+According to the SUM requirements specified in clause 7.2, the SUM device capabilities include those for data measurement, data processing, connecting, configuration setting storage and execution, and maintenance.
+
+#### **8.2.1 Data measurement capability**
+
+The data measurement capability measures SUM data. It includes but is not limited to:
+
+- Measuring SUM information related to utility consumption, such as electricity consumption;
+- Measuring SUM information related to utility quality and status, such as water pressure and remaining battery power.
+
+#### **8.2.2 Data processing capability**
+
+The data processing capability processes data. It includes but is not limited to:
+
+- Formatting data as appropriate for communication purposes.
+
+#### **8.2.3 Connecting capability**
+
+The data connecting capability enables SUM devices to communicate with the SUM platform. It includes but is not limited to:
+
+- Setting up communication between SUM devices and the SUM platform;
+- Receiving configuration settings from the SUM platform;
+- Sending configuration settings to configuration setting storage and execution capability;
+- Periodically reporting working status from maintenance capability to the SUM platform;
+- Reporting fault information from maintenance capability to the SUM platform;
+- Regularly reporting measurement data from the data measurement capability to the SUM platform.
+
+#### **8.2.4 Configuration setting storage and execution capability**
+
+The configuration setting storage and execution capability manages configuration settings. It includes but is not limited to:
+
+- Receiving and storing configuration settings from the connecting capability;
+- Automatically executing the configuration settings when new configuration settings are received.
+
+#### **8.2.5 Maintenance capability**
+
+The maintenance capability maintains SUM devices. It includes but is not limited to:
+
+- Monitoring the working status of SUM devices;
+- Detecting abnormal measurements and reporting the fault information automatically to the connecting capability.
+
+## Appendix I
+
+### Use cases of smart utility metering
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix provides some use cases of SUM.
+
+Figure I.1 shows smart water metering as a typical application of SUM. Through the IoT network and SUM platform, smart water metering can provide remote data collection, efficient device maintenance, and flexible data analysis and presentation.
+
+
+
+The diagram illustrates the architecture of smart water metering. On the left, two sources of water consumption are shown: 'Private home's water consumption' (represented by a house icon) and 'Commercial area's water consumption' (represented by a city skyline icon). Both sources feed into a 'Smart water meter' (represented by a circular icon with a star and 'm³'). The smart water meter is connected to an 'IoT network' (represented by a radio tower icon). The IoT network connects to a 'Smart water meter platform' (represented by server racks and a database icon). The platform performs several functions: 'Configuration setting management' and 'Remote device control' (indicated by a dashed line from the platform to the meter), 'Data collection' and 'Operation status report' (indicated by a dashed line from the meter to the platform), and 'Data analysis and presentation' and 'Device maintenance' (indicated by a dashed line from the platform to a database icon). The reference 'Y.4419(21)' is located at the bottom right of the diagram.
+
+Diagram of smart water metering system architecture showing data flow from private and commercial water consumption to a smart water meter, then via an IoT network to a smart water meter platform for configuration management, data collection, and analysis.
+
+**Figure I.1 – Smart water metering**
+
+### I.1 Remote data collection
+
+A smart water meter sends water consumption data to the SUM platform periodically through the IoT network. This time period can be modified in the configuration setting.
+
+The SUM platform can also collect other data from the smart water meter through sensors such as water pressure sensors. Water pressure is used to analyse the status of the water pipes and water storage.
+
+### I.2 Device maintenance
+
+The SUM platform can manage various aspects of smart water meters, such as device information management, device operation status analysis, configuration setting and remote device control.
+
+#### I.2.1 Device information management
+
+When a smart water meter is installed and powered up, it is registered on the SUM platform with its device information, such as its identity and device type. Maintenance personnel can also add the device location to the device information. Device information can be modified, queried and deleted on the SUM platform.
+
+#### I.2.2 Device operation status analysis
+
+The smart water meter reports its operation status periodically to the SUM platform. The SUM platform analyses whether the smart water meter is working well. When a faulty device is detected, the SUM platform informs the maintenance personnel promptly.
+
+#### **I.2.3 Configuration setting**
+
+The SUM platform can remotely update the smart water meter configuration to set device working parameters for a single device or a group of devices on demand.
+
+#### **I.2.4 Remote device control**
+
+Maintenance personnel can turn off a specific smart water meter to cut off the water supply if its user is in arrears. Maintenance personnel can also turn off a group of devices when a water pipe is broken. In addition, the SUM platform can query smart water meters so that they can react back immediately with water consumption data, and accurate consumption invoices can then be issued.
+
+### **I.3 Data analysis and presentation**
+
+The SUM platform can analyse water consumption in a certain area or within a certain time interval.
+
+The SUM platform can present raw measurement data, analysis reports, physical distribution and maintenance status of a single smart water meter. The platform can also present faulty device information and abnormal data to the user.
+
+## Bibliography
+
+- [b-ITU-T X.742] Recommendation ITU-T X.742 (1995), *Information technology – Open Systems Interconnection – Systems management: Usage metering function for accounting purposes*.
+- [b-ITU-T X.1332] Recommendation ITU-T X.1332 (2020), *Security Guidelines for Smart Metering Services in Smart Grids*.
+- [b-ITU-T Y.4109] Recommendation ITU-T Y.4109/Y.2061 (2012), *Requirements for the Support of Machine-oriented Communication Applications in the Next Generation Network Environment*.
+- [b-IEC TS 62056-6-9] IEC TS 62056-6-9:2016, *Electricity Metering Data exchange – The DLMS/COSEM Suite – Part 6-9: Mapping between the Common Information Model Message Profiles (IEC 61968-9) and DLMS/COSEM (IEC 62056) Data models and Protocols*.
+- [b-IEEE 802.11] IEEE Standard 802.11 (2020), *IEEE Standard for Information Technology – Telecommunications and Information Exchange between Systems – Local and Metropolitan Area Networks – Specific Requirements – Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications*.
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+## Y.4456
+
+(03/2018)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Internet of things and smart cities and communities –
+Frameworks, architectures and protocols
+
+# --- **Requirements and functional architecture for smart parking lots in smart cities**
+
+Recommendation ITU-T Y.4456
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Network control architectures and protocols | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+| | |
+|--|---------------|
+| | Y.3000–Y.3499 |
+| | Y.3500–Y.3999 |
+
+## CLOUD COMPUTING
+
+## INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|----------------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+## Recommendation ITU-T Y.4456
+
+# Requirements and functional architecture for smart parking lots in smart cities
+
+## Summary
+
+Smart parking lots can provide various parking services for different parking lot scenarios, including parking guidance, parking space reservation, vehicle reverse search, vehicle automatic access control and self-service payment.
+
+Recommendation ITU-T Y.4456 specifies the requirements and functional architecture for smart parking lots.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.4456 | 2018-03-01 | 20 | 11.1002/1000/13498 |
+
+## Keywords
+
+Architecture, requirement, smart parking lot, use case.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2018
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|---|-------------------------------------------------------|------|
+| 1 | Scope..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 2 |
+| 6 | Introduction to SPL..... | 2 |
+| 7 | Requirements for SPLs ..... | 3 |
+| | 7.1 Parking guidance ..... | 3 |
+| | 7.2 Parking space reservation ..... | 3 |
+| | 7.3 Vehicle automatic access control ..... | 4 |
+| | 7.4 Self-service payment ..... | 4 |
+| | 7.5 Vehicle reverse search..... | 4 |
+| | 7.6 Information management..... | 4 |
+| 8 | Functional architecture of SPLs..... | 4 |
+| | 8.1 Functional architecture overview ..... | 4 |
+| | 8.2 Off-street and on-street parking lots (OOPL)..... | 5 |
+| | 8.3 Smart parking networking platform (SPNP)..... | 5 |
+| | Appendix I – Use cases of SPL..... | 7 |
+| | I.1 Parking guidance ..... | 7 |
+| | I.2 Parking space reservation ..... | 7 |
+| | I.3 Vehicle automatic access control ..... | 8 |
+| | I.4 Self-service payment ..... | 8 |
+| | I.5 Vehicle reverse search..... | 8 |
+
+
+
+## Recommendation ITU-T Y4456
+
+# Requirements and functional architecture for smart parking lots in smart cities
+
+## 1 Scope
+
+Smart parking lots (SPLs) integrate parking information to enable the coordination of parking facilities within smart cities. SPLs work with other systems to provide various parking services. This Recommendation specifies the requirements and functional architecture for SPLs.
+
+The scope of this Recommendation includes:
+
+- introduction of SPLs
+- requirements for SPL
+- Functional architecture of SPL
+
+NOTE – For use cases of SPL see Appendix I.
+
+## 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- [ITU-T Y.101] Recommendation ITU-T Y.101 (2000), *Global Information Infrastructure terminology: Terms and definitions*.
+- [ITU-T Y.2012] ITU-T Recommendation Y.2012 (2010), *Functional requirements and architecture of next generation networks*.
+- [ITU-T Y.2261] ITU-T Recommendation Y.2261 (2006), *PSTN/ISDN evolution to NGN*.
+- [ITU-T Y.4000] ITU-T Recommendation Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+
+## 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 application** [ITU-T Y.2261]: A structured set of capabilities, which provide value-added functionality supported by one or more services, which may be supported by an API interface.
+
+**3.1.2 functional entity** [ITU-T Y.2012]: An entity that comprises an indivisible set of specific functions. Functional entities are logical concepts, while groupings of functional entities are used to describe practical, physical implementations.
+
+**3.1.3 service** [ITU-T Y.101]: A structure set of capabilities intended to support applications.
+
+### 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following term:
+
+**3.2.1 smart parking lot:** An application that integrates citywide parking information and provides various parking services to produce an enhanced parking experience.
+
+## 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|--------|-----------------------------------------------------|
+| APP | Application |
+| AAFE | Access and Authentication Functional Entity |
+| DAFE | Data Analytics Functional Entity |
+| FE | Functional Entity |
+| OOPL | Off-street and On-street Parking Lots |
+| PGFE | Parking Guidance Functional Entity |
+| POMFE | Platform Operation and Management Functional Entity |
+| SCMFE | SPL Ctrl. and Mgmt. Functional Entity |
+| SPL | Smart Parking Lot |
+| SPNP | Smart Parking Networking Platform |
+| VAACFE | Vehicle Automatic Access Control Functional Entity |
+| WEB | World Wide Web |
+
+## 5 Conventions
+
+In this Recommendation:
+
+The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+
+The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required. Thus this requirement need not be present to claim conformance.
+
+The keywords "can optionally" and "may" indicate an optional requirement which is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with this Recommendation.
+
+## 6 Introduction to SPL
+
+The number of vehicles in cities has increased sharply and finding parking spaces has become increasingly difficult. Furthermore, the lack of parking guidance and parking space booking services makes it difficult for drivers to find parking spaces.
+
+A smart parking lot (SPL) brings the efficient integration of parking resources and coordinated parking facilities together with other systems (e.g., external payment systems, WEB/APP-parking systems, urban parking guidance systems, traffic systems, etc.).
+
+SPLs can provide various parking services to meet the particular requirements of different scenarios. Typical services may include parking guidance, parking space reservation, vehicle reverse search, vehicle automatic access control and self-service payment.
+
+- Parking guidance: An SPL publishes information about unoccupied parking spaces with parking guidance information.
+- Parking space reservation: An SPL can help search for available parking spaces and reserve parking spaces in advance.
+- Vehicle automatic access control: An SPL may support vehicle parking without the need for stopping at entries and exits.
+- Self-service payment: An SPL supports payment through self-service terminals, hand-held devices, WEB/APP-based parking systems or fully-automatic charging, etc.
+- Vehicle reverse search: An SPL could help vehicle users to identify where their vehicles are parked, should they forget where they have left them.
+
+The overview of the SPL environment is depicted in Figure 1.
+
+- Off-street parking lots may have controlled entries and exits and on-street parking lots usually do not have controlled entries and exits. Both off-street and on-street parking lots (OOPL) may use sensors and actuators to monitor and control the use of parking spaces.
+- Communication networks provide communication capabilities between off-street and on-street parking lots, smart parking network platforms (SPNPs) and external systems.
+- An SPL platform provides capabilities (operation and management, access and authentication, data analytics, etc.) for the integration of parking information via interfaces.
+- External systems are relatively independent of the SPL. They include WEB/APP-based parking systems, urban parking guidance systems, external payment systems and traffic systems. The SPL supports external interfaces for external systems to provide various parking services.
+
+
+
+```
+
+graph LR
+ SPNP[Smart parking network platform] --- CN[Communication network]
+ CN --- ES[External systems]
+ ES --- OOPL[Off-street parking lots]
+ ES --- OOPL
+ OOPL --- OOPL
+ OOPL --- OOPL
+
+```
+
+The diagram illustrates the SPL environment architecture. It consists of three main components: the Smart parking network platform, the Communication network, and the External systems. The Smart parking network platform is connected to the Communication network. The Communication network is connected to the External systems, which include WEB/APP-based parking, Urban parking guidance, External payment, and Traffic system. The Communication network is also connected to the Off-street parking lots and On-street parking lots.
+
+Figure 1: Overview of the SPL environment. The diagram shows a Smart parking network platform connected to a Communication network. The Communication network is connected to a stack of External systems (WEB/APP-based parking, Urban parking guidance, External payment, Traffic system) and to a box containing Off-street parking lots and On-street parking lots.
+
+Y.4456(18)\_F01
+
+**Figure 1 – Overview of the SPL environment**
+
+## **7 Requirements for SPLs**
+
+### **7.1 Parking guidance**
+
+OOPL are required to collect parking space information and report it to the SPNP.
+
+The SPNP is required to provide interfaces to external systems to support parking guidance.
+
+OOPL are recommended to use parking space lights, electronic guide screens to indicate parking space information to drivers.
+
+### **7.2 Parking space reservation**
+
+The SPNP is recommended to receive requests for parking space reservations from external systems.
+
+OOPL may reserve parking spaces according to requests from the SPNP.
+
+The SPNP is recommended to provide interfaces to external systems to support parking space reservations.
+
+### **7.3 Vehicle automatic access control**
+
+OOPL may control vehicle automatic access.
+
+The SPNP is recommended to update vehicle information from OOPL.
+
+### **7.4 Self-service payment**
+
+OOPL are required to support a method of self-service payment.
+
+NOTE – Self-service payment can be supported through self-service terminals, hand-held terminals, WEB/APP-based parking systems and fully-automatic collection.
+
+OOPL are required to collect payment information and may report the information to the SPNP.
+
+The SPNP may support interfaces to external systems for self-service payment.
+
+NOTE – Payment information is required to enable self-service payment. The payment information may include vehicle identification (licence plate number, e-tag, RFID, etc.), payment amount, payment time and payment status (paid, unpaid) and rate.
+
+### **7.5 Vehicle reverse search**
+
+An SPNP may check vehicle identification and request the parking space location of the vehicle with the corresponding parking lot.
+
+OOPL may provide a response of the parking space location to the SPNP.
+
+The SPNP may provide the interface to external systems for vehicle reverse search.
+
+### **7.6 Information management**
+
+OOPL are recommended to provide parking lot information and parking space information, and they may provide vehicle information.
+
+An SPNP is required to manage parking lot information and parking space information, and may manage vehicle information.
+
+OOPL and SNNPs are recommended to exchange parking lot information and parking space information, and they may exchange vehicle information.
+
+NOTE 1 – Parking lot information: parking lot ID, parking lot type and parking lot location.
+
+NOTE 2 – Parking space information: parking space ID, parking space status (occupied, vacant, temporarily reserved, long-time reserved).
+
+NOTE 3 – Vehicle information: vehicle identification (licence plate number, e-tag, RFID, etc.), vehicle status (long-term, temporary, etc.), vehicle arrival time, vehicle departure time, vehicle arrival and departure and parking images.
+
+# **8 Functional architecture of SPLs**
+
+### **8.1 Functional architecture overview**
+
+The SPL environment, as shown in Figure 1, consists of four components. From the requirements in clause 7, this Recommendation mainly focuses on OOPL and SNNPs. Communication networks and external systems are out of the scope of this Recommendation in terms of functional architecture.
+
+
+
+The diagram illustrates the functional architecture of a Smart Parking Lot (SPL). It is organized into four main layers:
+
+- Smart parking networking platform (SPNP):** Located at the top left, it contains three functional entities (FEs): Platform operation and management FE, Access and authentication FE, and Data analytics FE.
+- External systems:** Located at the top right, it includes four components: WEB/App-based parking services, Third-party payment and bank system, Urban parking guidance system, and Traffic system.
+- Communication network:** A central layer connecting the SPNP and the parking lots.
+- Off-street and on-street parking lots:** Located at the bottom, it contains three functional entities: SPL Ctrl. and Mgmt. FE, Vehicle automatic access control FE, and Parking guidance FE.
+
+Y.4456(18)\_F02
+
+Functional architecture of an SPL diagram showing the Smart parking networking platform, external systems, communication network, and off-street and on-street parking lots.
+
+**Figure 2 – Functional architecture of an SPL**
+
+### 8.2 Off-street and on-street parking lots (OOPL)
+
+OOPL includes the vehicle automatic access control functional entity (VAACFE), parking guidance functional entity (PGFE) and SPL Ctrl. and Mgmt. functional entity (SCMFE). The main functions of these functional entities are described below:
+
+Vehicle automatic access control functional entity (VAACFE):
+
+- identifies vehicles;
+- sends arrival and departure information to the SCMFE;
+- controls vehicle access automatically, according to responses received from the SCMFE.
+
+NOTE – This last function is applicable only for off-street parking lots.
+
+Parking guidance functional entity (PGFE):
+
+- detects parking spaces inside parking lots;
+- sends parking space information to the SCMFE;
+- updates parking space lights and electronic guide screens to indicate parking space information to drivers.
+
+SPL Ctrl. and Mgmt. functional entity (SCMFE):
+
+- collects payment information and reports payment information to the SPNP;
+- manages parking lot information including parking lot configuration, parking space information and vehicle information;
+- sends alarm messages (vehicle block alarm, equipment abnormal alarm and vehicle arrearage alarm, etc.) to parking lot staff;
+- communicates with the platform operation and management functional entity (POMFE) of the SPNP to report information and receive messages.
+
+### 8.3 Smart parking networking platform (SPNP)
+
+The smart parking networking platform (SPNP) includes the access and authentication functional entity (AAFE), platform operation and management functional entity (POMFE) and data analytics functional entity (DAFE). The main functions of these functional entities are described below:
+
+Access and authentication functional entity (AAFE):
+
+- authenticates parking lot information stored in the POMFE;
+
+- provides interfaces for authenticated users from external systems to access information to which they have rights.
+
+Platform operation and management functional entity (POMFE):
+
+- manages and stores information including parking lot configuration, parking space information, vehicle information and payment information;
+- provides service execution for smart parking operation with relevant capabilities;
+- communicates with OOPL to get the information and sends the messages to support various parking lot services.
+
+Data analytics functional entity (DAFE):
+
+- supports data analytics and reporting for getting statistical information from the SPNP and OOPL;
+- supports data mining to optimize the operation of the SPL.
+
+## Appendix I
+
+### Use cases of SPL
+
+(This appendix does not form an integral part of this Recommendation.)
+
+### I.1 Parking guidance
+
+Without guidance drivers may cause congestion while looking for parking spaces. The location of parking lots and real-time information of parking spaces is provided to drivers to allow them to park conveniently.
+
+
+
+The figure illustrates parking guidance through three visual elements:
+
+- Smartphone App:** A smartphone screen displays a map of a city area. A callout box for 'ABC Parking Lot' shows 'Vacant space number: 82', 'Rate: \$5/h', and a 'Navigate' button. Other landmarks like '南京图书馆' (Nanjing Library) and '万达广场' (Wanda Plaza) are visible on the map.
+- Physical Road Sign:** A blue overhead road sign provides real-time parking availability. It shows 'P' for parking, '空位' (Vacant spaces), and counts for various locations: '中兴大厦' (57), '新世界' (25), '万达广场' (8), '伊势丹百货' (150), '远大医院' (106), '欧亚联盟' (10), and '商贸饭店' (14). Arrows indicate directions to these locations.
+- Schematic Diagrams:** Two line drawings show parking facility layouts. The left diagram shows a multi-level parking structure with a sign indicating '空车位 Available' and a count of '48'. The right diagram shows a single-level parking lot with several cars parked and a sign indicating '空车位 Available' and a count of '32'.
+
+Figure I.1 – Parking guidance. The figure illustrates parking guidance through three visual elements: a smartphone app, a physical road sign, and two schematic diagrams of parking facilities.
+
+Figure I.1 – Parking guidance
+
+### I.2 Parking space reservation
+
+SPLs can help drivers search for information on available parking spaces and to reserve parking spaces in advance. Drivers check electronic road maps with general information about the parking lots around a particular area and they can select the parking lot where they would like to make a parking space reservation, via a WEB/APP-based parking system.
+
+
+
+Figure I.2 – Parking space reservation. Two smartphone screens are shown. The left screen displays a map of a city with several red location pins numbered 1 through 7. A callout box for 'ABC Parking Lot' shows 'Vacant space number: 82', 'Rate: \$5/hr', and a 'Navigate >' button. The right screen shows the 'Reservation details' for 'ABC Parking Lot \$5/hr'. It includes a 'Duration' section with radio buttons for '1hr', '2hr', and '3hr'. At the bottom is a large circular 'Reserve' button.
+
+**Figure I.2 – Parking space reservation**
+
+### **I.3 Vehicle automatic access control**
+
+An SPL supports vehicle access to parking lots without the need to stop at entries and exits.
+
+When a vehicle enters or leaves a parking lot an SPL automatically senses and identifies the vehicle; it then makes subsequent operations according to defined policies, such as:
+
+- for long-term vehicles the SPL will directly release them;
+- for overdue vehicles the SPL will stop them or provide an alarm;
+- for paid vehicles the SPL will release them;
+- for unpaid vehicles the SPL will release the vehicle following payment or a record of payment.
+
+### **I.4 Self-service payment**
+
+Drivers can check information about parking fees and pay the fees through the WEB/APP-based parking system, handheld terminals, self-service terminals or automatic collection.
+
+
+
+Figure I.3 – Self-service payment. A smartphone screen displays a payment interface. At the top is 'Car XYZ'. Below that is 'Parking fee: \$20.00' and 'Parking time: 8h 09:00-17:00 Mar.15'. The 'Payment method:' section has three radio buttons: 'Bank card', 'Alipay' (which is selected), and 'Wechat'. At the bottom is a large circular 'Pay' button.
+
+**Figure I.3 – Self-service payment**
+
+### **I.5 Vehicle reverse search**
+
+It is easy to forget the parking space location when there are many parking spaces and several floors inside parking lots. SPLs could help drivers to identify where their vehicles are parked, should they
+
+forget where they have left them. The drivers can input the licence plate numbers on the interface of the WEB/APP-based parking system and get the detailed location of where their vehicles are parked.
+
+
+
+A line drawing of a smartphone. The screen displays a parking application interface. At the top of the screen is a 3D illustration of two cars parked in a lot. Below the illustration, the text reads: "ABC parking lot", "Car XYZ:", and "1st Floor A123". The phone has a home button at the bottom.
+
+A line drawing of a smartphone displaying a parking app interface. The screen shows a 3D illustration of two cars parked in a lot. Below the illustration, the text reads: 'ABC parking lot', 'Car XYZ:', and '1st Floor A123'.
+
+**Figure I.4 – Vehicle reverse search**
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation
+
+## **ITU-T Y.4463 (08/2024)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Internet of things and smart cities and communities –
+Frameworks, architectures and protocols
+
+---
+
+## **Framework of delegation service for Internet of things devices**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+| | |
+|---------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | Y.100-Y.999 |
+| INTERNET PROTOCOL ASPECTS | Y.1000-Y.1999 |
+| NEXT GENERATION NETWORKS | Y.2000-Y.2999 |
+| FUTURE NETWORKS | Y.3000-Y.3499 |
+| CLOUD COMPUTING | Y.3500-Y.3599 |
+| BIG DATA | Y.3600-Y.3799 |
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800-Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | Y.4000-Y.4999 |
+| General | Y.4000-Y.4049 |
+| Definitions and terminologies | Y.4050-Y.4099 |
+| Requirements and use cases | Y.4100-Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250-Y.4399 |
+| Frameworks, architectures and protocols | Y.4400-Y.4549 |
+| Services, applications, computation and data processing | Y.4550-Y.4699 |
+| Management, control and performance | Y.4700-Y.4799 |
+| Identification and security | Y.4800-Y.4899 |
+| Evaluation and assessment | Y.4900-Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4463
+
+# Framework of delegation service for Internet of things devices
+
+## Summary
+
+Recommendation ITU-T Y.4463 describes the framework of the delegation service for transferring ownership (i.e., access rights to the Internet of things (IoT) devices) among authorized IoT devices. This Recommendation gives an overview and types of delegation service in an IoT environment. It also describes the requirements and architectural models of the delegation service.
+
+## History\*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T Y.4463 | 2020-01-13 | 20 | 11.1002/1000/14166 |
+| 2.0 | ITU-T Y.4463 | 2024-08-29 | 20 | 11.1002/1000/16065 |
+
+## Keywords
+
+Delegation service, IoT, ownership.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2024
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|------------------------------------------------------------------------------------|------|
+| 1 Scope ..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere..... | 1 |
+| 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 Abbreviations and acronyms ..... | 3 |
+| 5 Conventions ..... | 3 |
+| 6 Overview of delegation service ..... | 4 |
+| 6.1 Delegation service ..... | 4 |
+| 6.2 Key components of delegation service..... | 5 |
+| 7 Types of delegation service ..... | 6 |
+| 7.1 Single delegation service..... | 6 |
+| 7.2 Pre-defined relational delegation service ..... | 7 |
+| 7.3 Group delegation service..... | 8 |
+| 8 Requirements of the delegation service..... | 9 |
+| 8.1 Physical/Virtual object requirements ..... | 9 |
+| 8.2 Services requirements..... | 10 |
+| 9 Architectural model of the delegation service ..... | 11 |
+| Appendix I – Types of delegation device ..... | 15 |
+| I.1 Security phases for IoT devices..... | 15 |
+| I.2 Delegation service among IoT devices..... | 15 |
+| Appendix II – Procedures of delegation service ..... | 20 |
+| II.1 Single delegation service..... | 20 |
+| II.2 Pre-defined relational delegation service ..... | 20 |
+| II.3 Group delegation service..... | 21 |
+| Appendix III – Data model of delegation service ..... | 23 |
+| III.1 Physical objects for delegation service..... | 23 |
+| III.2 Data models for delegation service ..... | 25 |
+| Appendix IV – Example scenario of independently deployable event data ..... | 28 |
+| IV.1 Infrastructure safety service ..... | 28 |
+| IV.2 Distributed database for validating independently deployable event data ..... | 29 |
+| Bibliography..... | 30 |
+
+
+
+# Recommendation ITU-T Y.4463
+
+## Framework of delegation service for Internet of things devices
+
+# 1 Scope
+
+This Recommendation describes the framework of the delegation service for transferring ownership (i.e., access rights to Internet of things (IoT) devices) among authorized IoT devices.
+
+In particular, the scope of this Recommendation includes:
+
+- Overview of the delegation service in an IoT environment;
+- Types of delegation service among authorized IoT devices;
+- Requirements of the delegation service;
+- Architectural model of the delegation service.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T Y.4000] Recommendation ITU-T Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+
+[ITU-T Y.4400] Recommendation ITU-T Y.4400/Y.2063 (2012), *Framework of the web of things*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 device** [ITU-T Y.4000]: With regard to the Internet of things, this is a piece of equipment with the mandatory capabilities of communication and the optional capabilities of sensing, actuation, data capture, data storage and data processing.
+
+**3.1.2 identifier** [b-ITU-T Y.2091]: An identifier is a series of digits, characters and symbols or any other form of data used to identify subscriber(s), user(s), network element(s), function(s), network entity(ies) providing services/applications, or other entities (e.g., physical or logical objects). Identifiers can be used for registration or authorization. They can be either public to all networks, shared between a limited number of networks or private to a specific network (private IDs are normally not disclosed to third parties).
+
+**3.1.3 identity** [b-ITU-T Y.2720]: Information about an entity that is sufficient to identify that entity in a particular context.
+
+**3.1.4 Internet of things (IoT)** [ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on, existing and evolving, interoperable information and communication technologies.
+
+NOTE 1 – Through the exploitation of identification, data capture, processing and communication capabilities, the IoT makes full use of things to offer services to all kinds of applications, whilst ensuring that security and privacy requirements are fulfilled.
+
+NOTE 2 – From a broader perspective, the IoT can be perceived as a vision with technological and societal implications.
+
+**3.1.5 object** [b-ITU-T Y.2002]: An intrinsic representation of an entity that is described at an appropriate level of abstraction in terms of its attributes and functions.
+
+NOTE 1 – An object is characterized by its behaviour. An object is distinct from any other object. An object interacts with its environment including other objects at its interaction points. An object is informally said to perform functions and offer services (an object which makes a function available is said to offer a service). For modelling purposes, these functions and services are specified in terms of the behaviour of the object and of its interfaces. An object can perform more than one function. A function can be performed by the cooperation of several objects.
+
+NOTE 2 – Objects include terminal devices (e.g., used by a person to access the network such as mobile phones, Personal computers, etc.), remote monitoring devices (e.g., cameras, sensors, etc.), information devices (e.g., content delivery server), products, contents, and resources.
+
+**3.1.6 resource owner** [b-ITU-T Y.2724]: An entity capable of granting access to a protected resource. When the resource owner is a person, they are referred to as an end-user.
+
+**3.1.7 event** [b-ITU-T H.761]: Occurrence in time that may be instantaneous or have measurable duration.
+
+**3.1.8 record** [b-ITU-T Q.9]: A set of related data or words treated as a unit.
+
+## **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following terms:
+
+**3.2.1 data model**: A concrete and detailed representation as an abstraction of Internet of things (IoT) devices in the information world.
+
+NOTE 1 – The term "information world" is based on the illustration in Figure 2 of [ITU-T Y.4000].
+
+NOTE 2 – [b-IETF RFC 3444] defines a data model from the viewpoint of a network operator and a developer.
+
+**3.2.2 delegation**: Conveyance of privilege from one entity that holds such privilege, to another entity. It is also an action that assigns authority, responsibility, or a function to another entity.
+
+NOTE – Definition adapted from [b-ITU-T X.509] and [b-ITU-T X.1252].
+
+**3.2.3 resource**: An object of the information world, which inherits the same characteristics as a physical entity (e.g., IoT device) of the physical world and whose capability is bound to the capability of a physical entity.
+
+NOTE 1 – The terms "information world" and "physical world" are based on the illustration in Figure 2 of [ITU-T Y.4000].
+
+NOTE 2 – A resource in the information world is called a virtual object.
+
+NOTE 3 – A set of resources is called "resource group" in the information world. The resource group is also called "virtual object". This is the abstracted, analysed or manipulated resources, which may have different characteristics from resources and whose capability may not be bound to the capability of the resources. The "different characteristics" means simplification or extension of the resource characteristics. "Different characteristics" allows the resource group to expose access or control methods from the original physical resource.
+
+**3.2.4 resource ownership**: Capability of a resource owner to grant access to the resource.
+
+NOTE – The ownership of resources can be transferred to other owner(s). Some resources can be possessed by many resource owners at the same time.
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-----------------|-----------------------------------------------------|
+| ABAC | Attribute-Based Access Control |
+| DLT | Distributed Ledger Technology |
+| GDS | Group Delegation Service |
+| I DR | Interface between IoT Device(s) and Resources |
+| I DS | Interface between IoT Device(s) and Services |
+| I DU | Interface between IoT Device(s) and Users |
+| I RR | Interface between Roles and Resources |
+| I RS | Interface between Roles and Sessions |
+| I UR | Interface between Users and Roles |
+| I US | Interface between Users and Sessions |
+| IoT | Internet of Things |
+| Pa-PDS | Partial Pre-defined relational Delegation Service |
+| Pa-SDS | Partial Single Delegation Service |
+| Pe-PDS | Permanent Pre-defined relational Delegation Service |
+| Pe-SDS | Permanent Single Delegation Service |
+| PDS | Pre-defined relational Delegation Service |
+| RBAC | Role based Access Control |
+| REST | Representational State Transfer |
+| SDS | Single Delegation Service |
+| Te-PDS | Temporary Pre-defined relational Delegation Service |
+| Te-SDS | Temporary Single Delegation Service |
+| URI | Uniform Resource Locator |
+| Wh-PDS | Whole Pre-defined relational Delegation Service |
+| Wh-SDS | Whole Single Delegation Service |
+| WoT | Web of Things |
+
+# 5 Conventions
+
+In this Recommendation:
+
+The keywords **"is required to"** indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this Recommendation is to be claimed.
+
+The keywords **"is recommended"** indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+
+The keywords **"can optionally"** and **"may"** indicate an optional requirement which is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with the specification.
+
+# 6 Overview of delegation service
+
+## 6.1 Delegation service
+
+With the popularity of the Internet of things (IoT), various physical IoT devices are required to connect to the information world in order to process data speedily and efficiently in support of the cloud environment. This means that various physical devices can be easily converted to virtual devices by using web technologies [ITU-T Y.4000]. In this regard, web technologies, and especially web of things (WoT) [ITU-T Y.4400], use a uniform resource identifier (URI) to identify and access things based on the representational state transfer (REST) architecture style.
+
+Figure 1 gives an overview of a number of IoT devices, gateways and servers that are in the physical world. Some IoT devices are passive (e.g., sensors) that extract data from the physical environment (e.g., water, air and others), while others are active (e.g., actuators). IoT gateways have the same functions as IoT devices, and additionally comprise networking features for connecting to the Internet. Users can also manage these IoT devices and gateways to communicate with IoT servers. There are four types of entities in the physical world: IoT devices, gateways, servers and users. In this Recommendation these four types of entities are referred to as physical objects. As such, these physical objects are represented as virtual objects in the information world. Virtual objects are expressed as the components of cloud service providers and third parties, and become the owners of physical objects in order to easily control the ownership of the objects (e.g., the access rights to the IoT devices and gateways).
+
+This ownership could be transferred to other authorized virtual objects such as security services for IoT devices, which are described in clause I.1. This Recommendation considers the "ownership transfer service for physical objects" as the "delegation service". A physical object has many properties and functions. Ownership of the property and function can be transferred to others. There are two methods to support the delegation service: direct and indirect.
+
+- A direct delegation service occurs between physical objects (e.g., IoT device and gateway). A physical object can transfer ownership to another physical object.
+- An indirect delegation service is enabled between physical objects through virtual objects. For an indirect delegation service, the relationship between physical and virtual objects should be established in advance. After conforming the relationship between physical and virtual objects, physical objects can deliver their ownership indirectly through their own virtual objects. In other words, virtual objects can perform the delegation service on behalf of physical objects.
+
+
+
+— Information/operation flow □ Physical object - - - Indirect delegation service flow
+ - - - Direct delegation service flow □ Physical object group - - - Virtual object group
+
+Y.4463(20)\_F01
+
+Figure 1: Examples of delegation service. The diagram illustrates the flow of information and delegation between the Information world and the Physical world. In the Information world, there are Cloud service providers and Third parties. In the Physical world, there are IoT servers, IoT gateways, IoT devices, and a User (e.g., human). The Internet connects these entities. Solid blue arrows represent information/operation flows, while dashed blue arrows represent direct delegation service flows. Red dashed arrows represent indirect delegation service flows. Red dashed boxes represent virtual object groups, and solid blue boxes represent physical objects. The diagram shows how delegation can be direct (e.g., from an IoT gateway to an IoT device) or indirect (e.g., from a Cloud service provider to a User via the Internet).
+
+**Figure 1 – Examples of delegation service**
+
+## 6.2 Key components of delegation service
+
+Two types of object, i.e., physical and virtual objects, shown in Figure 2 are defined to support the delegation service.
+
+The first is physical objects such as IoT servers and devices, authorities and human beings. These objects have properties and functions representing physical entities such as sensors and actuators. Through interface $I_{DU}$ , physical objects can be created as virtual objects in the information world.
+
+The second is virtual objects such as resources, resource groups and services. A resource represents the same functionality in the information world as physical object has in the physical world. In other words, a resource has the same capability as a physical object. A one-to-one mapping between a physical object and a resource occurs through interface $I_{DU}$ . Resource groups are abstracted and manipulated from resources and the information of delegation and policy authorities through interface $I_{DR}$ . A resource service is a series of resources and resource groups with delegation operation (e.g., actuating of physical object). This resource service can be represented as a delegation service when it performs a function to manipulate the physical objects. These resource services should also perform some operations through interface $I_{DS}$ .
+
+In this Recommendation, resource(s), resource group(s) and resource service(s) have to use a globally unique identifier such as a uniform resource identifier and object identifier [b-ITU-T Y.4500.1].
+
+
+
+Y.4463(20)\_F02
+
+Figure 2: Key components for delegation service. The diagram illustrates the interaction between the Information world and the Physical world. In the Information world, a 'Virtual object group' (dashed red box) contains 'Resource(s)', 'Resource group(s)', and 'Resource service(s)'. In the Physical world, the 'Physical object group' (solid blue box) contains an 'IoT service group' (IoT device, IoT server), an 'Authority group' (Delegation authority with Access rights, Policy authority with Credentials), an 'Owner group' (Human), and another 'IoT service group' (IoT device, IoT server). Information flows (solid blue arrows) include Sensing (Physical to Info), Manipulation (Info to Physical), Controlling (Info to Physical), Delegation request (Physical to Info), and Actuating (Physical to Info). Control flows (dashed blue arrows) include I\_DU, I\_DR, and I\_DS. Interfacing among resources is shown with double-headed blue arrows. A legend defines symbols for information/control flow, physical/virtual objects and groups, and resource interfacing.
+
+**Figure 2 – Key components for delegation service**
+
+# 7 Types of delegation service
+
+Delegation services apply to physical and virtual objects and are classified into three delegation service types: single, pre-defined relational and group delegation.
+
+## 7.1 Single delegation service
+
+A single delegation service (SDS) is initiated from a physical object to create a virtual object. There is a one-to-one mapping between a physical and a virtual object. The virtual object can then transfer ownership to another virtual object. After transferring the ownership, this information should not be allowed to others. More information on single delegation service is provided in clause I.2.1.
+
+In the scenario for camera devices shown in Figure 3, the IoT device has a camera entity with image generation capabilities. The images are stored in a secure way as resources in the information world. When partial-single delegation service (Pa-SDS) is applied to resources (virtual object A), the ownership of data in resources (virtual object A) is divided into resource groups (virtual object C and virtual object D). For a resource (virtual object B) with the whole-single delegation service (Wh-SDS), the resource group (virtual object D) can get the whole access rights of data from the resource (virtual object B). Subsequently, a user can access the resource group (virtual object C) to view the images of the IoT device (physical object A). However, the user cannot show the full images without the help of others because the resource group (virtual object C) has a Pa-SDS about the resources (virtual object A). Meanwhile, a user can access the resource group (virtual object D) to show the whole image of the IoT device (physical object B).
+
+
+
+Figure 3: Single delegation service in camera devices. The diagram illustrates the flow of data from the Physical world to the Information world. In the Physical world, two IoT devices (Physical object A and B) are shown. IoT device A contains resources R1, R2, R3, and R4. IoT device B contains resources R5, R6, R7, and R8. In the Information world, these are mapped to Virtual object A (resources R1, R2, R3, R4) and Virtual object B (resources R5, R6, R7, R8). Virtual object A is linked to Virtual object C (Resource group) via Partial-SDS, which contains resources R1 and R4. Virtual object B is linked to Virtual object D (Resource group) via Whole-SDS, which contains resources R2, R3, R5, R6, R7, and R8. A legend at the bottom defines the symbols: Data (R1, R2, ...), Information flow (blue arrow), Virtual object group (dashed red box), and Virtual object (solid red box). The reference Y.4463(20)\_F03 is also present.
+
+**Figure 3 – Single delegation service in camera devices**
+
+## 7.2 Pre-defined relational delegation service
+
+A pre-defined relational delegation service (PDS) is similar to a single delegation service. However, PDS has a different transfer rule of delegated information. The PDS must allow the transfer of delegated information to others in accordance with policy rules. More information on PDS is given in clause I.2.2.
+
+Figure 4 shows a scenario for an online map application. According to the data collection policy of the online map application, a pre-defined relationship will be established before the data collection. Policy information should be obtained from delegation and policy authorities. Data from IoT devices is then collected in the online map application (resource group (virtual object E)). According to the collection policy of the resource (virtual object A), some of the collected data must be transferred from the resource (virtual object A) into the resource group (virtual object E). This is an instance of partial-pre-defined relational delegation service (Pa-PDS). At the same time, the whole of the data of the IoT device (physical object B) are collected in the resource group (virtual object E) through the resource (virtual object B). This is an instance of the whole pre-defined relational delegation service (Wh-PDS). In other words, full ownership of collected data must be transferred to the resource group (virtual object E). Finally, the resource group (virtual object E) actuates the IoT device (physical object C) with collected data from the IoT devices (physical object A and physical object B).
+
+
+
+IoT device (Physical object (C))
+
+Display device
+
+Geographic Info.
+
+IoT device (Physical object (A))
+
+IoT device (Physical object (B))
+
+Resource (Virtual object (C))
+
+Resource (Virtual object (A))
+
+Resource (Virtual object (B))
+
+Resource group (Virtual object (E))
+
+Pa-HDS
+
+Wh-HDS
+
+Y.4463(20)\_F04
+
+R1 R2 ... Collection data
+
+Information flow
+
+Control flow
+
+Virtual object
+
+Pre-defined relationship
+
+Figure 4: A pre-defined relational delegation service in an online map application. The diagram illustrates the flow of information and control between physical and virtual worlds. In the Physical world, IoT devices (A, B, C) and a Display device interact. IoT device (A) provides Geographic Info. to the Display device. IoT device (B) provides Collection data (R1, R2, ...) to the Display device. IoT device (C) provides Collection data (R1, R2, ...) to the Display device. In the Information world, Resources (Virtual objects A, B, C) are represented. Resource (A) is linked to IoT device (A) via Pa-HDS. Resource (B) is linked to IoT device (B) via Wh-HDS. Resource (C) is linked to IoT device (C) via a pre-defined relationship. A Resource group (Virtual object E) is linked to Resource (A) via Pa-HDS and to Resource (B) via Wh-HDS. The Resource group (E) is displayed on the Display device. A legend at the bottom defines the symbols: R1, R2, ... for Collection data; a blue arrow for Information flow; a red dashed arrow for Control flow; a dashed box for Virtual object; and a blue arrow with a box for Pre-defined relationship.
+
+**Figure 4 – A pre-defined relational delegation service in an online map application**
+
+## 7.3 Group delegation service
+
+A group delegation service (GDS) is applied to a virtual object group, unlike the previous two services that are applied to a virtual object. This group can be comprised of resources and resource groups. More information of the group delegation service is provided in clause I.2.3.
+
+Visitors without any access rights want to enter a smart home, as shown in Figure 5. The visitors request appropriate access rights from the owner of the smart home. The owner then transfers or copies the access rights for the physical objects (such as lights, doors, appliances, etc.) to the visitors in the physical world. According to the properties of the visitor, the owner must decide between SDS and PDS. If the visitor is a guest of a hotel, he will get the Wh-SDS and the temporary-single delegation service (Te-SDS) for the group of physical objects. In contrast, if a visitor buys a house, it is appropriate to choose Wh-SDS and a permanent-single delegation service (Pe-SDS) for full access rights of the whole of IoT devices in the smart home. More details of the Te-SDS and Pe-SDS are described in clause I.2.1.
+
+
+
+Smart home application (Virtual object group (A))
+
+Information world
+
+Physical world
+
+IoT devices (Physical object group (B))
+
+Owner (Physical object (A))
+
+Delegator/visitor (Physical object (C))
+
+Delegation service
+
+Internet
+
+3G/LTE
+
+3G/LTE
+
+Smart devices
+
+1 - 2 m
+
+10 m
+
+20 - 30 m
+
+20 - 30 m
+
+Resource Group A1
+
+Resource Group A2
+
+Resource Group A3
+
+...
+
+Y.4463(20)\_F05
+
+— Information flow - - - Control flow [ ] Virtual object [ ] Virtual object group
+
+Figure 5: Group delegation scenario in a smart home. The diagram illustrates the interaction between the Information world and the Physical world. In the Information world, a 'Smart home application (Virtual object group (A))' is shown, containing 'Resource Group A1', 'Resource Group A2', 'Resource Group A3', and others. In the Physical world, 'IoT devices (Physical object group (B))' are connected to 'Smart devices' (1-2 m, 10 m, 20-30 m) and a 'Router' (20-30 m). The 'Owner (Physical object (A))' is connected to the 'Internet' via '3G/LTE'. A 'Delegation service' is shown as a 'Delegator/visitor (Physical object (C))' interacting with the 'Internet' via '3G/LTE'. Information flow is indicated by blue arrows, and control flow by red dashed arrows. A legend at the bottom defines the symbols: blue arrow for Information flow, red dashed arrow for Control flow, solid red dashed box for Virtual object, and dashed red box for Virtual object group.
+
+**Figure 5 – Group delegation scenario in a smart home**
+
+# 8 Requirements of the delegation service
+
+According to the physical and virtual objects in Figure 2, the following requirements are described.
+
+## 8.1 Physical/Virtual object requirements
+
+### 8.1.1 Requirements for physical objects
+
+- Physical objects (e.g., human, IoT devices, gateways and servers and authorities) are required to manage their access rights;
+- Physical objects are required to be sensed and actuated according to ownership of physical objects (i.e., access rights);
+- Physical objects are required to have policies of transferring ownership;
+- Physical objects are required to search, store data via direct access to distributed databases;
+- Physical objects are recommended to get information from policy and delegation authorities;
+- Ownership of a physical object is recommended to be divided into resource groups.
+
+### 8.1.2 Requirements for virtual objects
+
+- Virtual objects (e.g., cloud service provider and third parties) are required to manage their access rights;
+- Virtual objects are recommended to manage the revocation information;
+- Virtual objects are required to manage their ownership in attributes of resources and resource groups;
+
+- Virtual objects are recommended to maintain the history of their ownerships to mitigate the threat caused by abnormal operations;
+- Virtual objects are recommended to use attributes in separate resources to manage information from policy and delegation authorities;
+- Resources are required to manage the history of the delegation service about the one-to-one mapped physical objects;
+- Resources are required to prevent the conflict of policy rules;
+- Resources are required to support the pre-defined relational delegation service;
+- Resource groups are required to manage the access rights of physical objects;
+- Resource groups are required to prevent the conflict of policy rules;
+- Resource groups are required to support the pre-defined relational delegation service.
+
+### **8.1.3 Requirements for interactions between physical and virtual objects**
+
+- Physical objects in the physical world are required to have mapping with resources in the information world;
+- Physical objects are recommended to have one-to-one mapping with resources;
+- Physical objects are recommended to have a mapping with resource groups;
+- Physical objects are recommended to have means that transfer the access rights between physical and virtual objects;
+- Physical objects are required to represent their ownership (i.e., access rights) as attributes in resources;
+- Physical objects are recommended to represent their ownership as attributes in resource groups;
+- Delegation authorities are recommended to support the creation and deletion of resource groups;
+- Policy authorities are recommended to manage the policy rules for resources and resource groups.
+
+## **8.2 Services requirements**
+
+### **8.2.1 Requirements for the single delegation service**
+
+- SDSs are recommended to apply the same resources and resource groups;
+- SDSs are required to validate resources and resource groups.
+
+### **8.2.2 Requirements for the pre-defined relational delegation service**
+
+- PDSs are required to have trust relationships among physical objects before the execution of the delegation service;
+- PDSs are recommended to support the pre-defined relation features;
+- PDSs are required to support the continuous the delegation service among resources and resource groups;
+- PDSs are required to prevent the conflict of policy rules to support the pre-defined relational features.
+
+### **8.2.3 Requirements for the group delegation service**
+
+- A group in GDS is recommended to be established according to physical and virtual object types;
+- All physical and virtual objects in a group are required to have the same ownership policy;
+
+- GDSs are required to have selection rules for a group manager;
+- Group manager (e.g., user and IoT device) is recommended to select the members for the group;
+- GDSs are required to manage the transfer of ownership between resources and resource groups through the group manager.
+
+# 9 Architectural model of the delegation service
+
+The architectural model of the delegation service is shown in Figure 6. The model extends the concept of physical and information world depicted in [ITU-T Y.4000]. The role-based access control (RBAC) and the attribute-based access control (ABAC) reference models [b-INCITS 359] and [b-NIST.SP.800-162] are used to describe the details of physical and virtual objects.
+
+
+
+Figure 6: Architectural model of delegation service. The diagram illustrates the mapping between the Information world and the Physical world. The Information world contains a Virtual object group with four roles: USER/THING resource, SESSION resource group, POLICY/ROLE resource group, and SERVICE resource group. The Physical world contains a Physical object group with five objects: Human, IoT device (sensing) and IoT server, Delegation authority and Access rights, Policy authority and Credentials, and IoT device (Actuating). Information flows (solid blue arrows) connect these objects: I\_DS from Human to USER/THING resource, I\_DU from IoT device (sensing) to USER/THING resource, I\_DR from Delegation authority to SESSION resource group, I\_DR from Policy authority to POLICY/ROLE resource group, and I\_DS from IoT device (Actuating) to SERVICE resource group. Control flows (dashed blue arrows) connect the roles to their corresponding physical objects. Information flow to the distributed databases (double blue arrows) connects the Virtual object group to the Distributed data repository and DLT, and the Physical object group to the Distributed databases. A legend at the bottom defines the symbols: solid blue arrow for Information flow, dashed blue arrow for Control flow, double blue arrow for Information flow to the distributed databases, rounded rectangle for Physical object, rectangle for Physical object group, dashed rounded rectangle for Virtual object, dashed rectangle for Virtual object group, and oval for Functionality. The reference Y.4463(20)\_F06 is noted at the bottom right.
+
+**Figure 6 – Architectural model of delegation service**
+
+Figure 6 shows the RBAC model that includes eleven objects and three mapping relationships between the information world and the physical world. Six virtual objects are mapped into either resource or resource group roles based on the RBAC model. Five physical objects for sensing and data processing are located in the physical world to control resource ownership (i.e., access rights) based on the RBAC and ABAC models. These physical objects are mapped into the following six resource/resource group roles of information world:
+
+- **THING resource:** An IoT server and an IoT device will be used to collect and store data from the physical environment. They will be mapped into THING resources through interface $I_{DU}$ ;
+- **USER resource:** Humans will be asked to create a USER resource through interface $I_{DS}$ . This resource will be used to identify a human-being;
+- **SESSION resource group:** Delegation authority manages the access rights of resources. These access rights are mapped into SESSION resource group through interface $I_{DR}$ . The SESSION resources are changed with time-dependency according to delegation service;
+- **POLICY resource group:** Policy authority manages the credentials of USER and THING resources. Policy authority with these credentials has human-oriented policies and is mapped into POLICY resource group through interface $I_{DR}$ . According to POLICY resources, the relation between USER/THING and SESSION resources will be decided. That is, POLICY resources are used when human-oriented conditions are met in order to support delegation service;
+
+- **ROLE resource group:** Policy authority manages the credentials of USER and THING resources. These credentials are machine-oriented policies and are mapped into ROLE resource group through interface *IDR*. According to ROLE resources, the relation between USER/THING and SESSION resources will be decided. That is, ROLE resources are used as the machine-oriented conditions in order to manipulate IoT devices for delegation service;
+- **SERVICE resource group:** An IoT device is mapped into a SERVICE resource group through interface *IDS*, according to the request of the delegation service from a human or an IoT server.
+
+The virtual objects for storing information of the delegation service are located in the information world. Event data is measurable data generated in sequence from IoT devices, which may be independently deployable in different places. Distributed databases comprising a distributed data repository and distributed ledger technology (DLT) are employed to manage the independently deployable event data securely in delegation service.
+
+IoT sensor devices create independently deployable event data and store them directly in the distributed databases according to the delegation service model. The independently deployable event data is also represented as a virtual object. Therefore, the distributed databases have interactions with virtual object group and physical object group. Data attributes are the collection of information required to manage the independently deployable event data. The virtual object in the information world manages attribute information such as identity of the data-generating device, data ownership, generation sequence, etc. The distributed databases enable the attribute information to be verifiable and linkable regardless of data distribution route.
+
+Record is information about an object stored in and provided by the distributed databases. There are two types of record: event record for representing independently deployable event data and device record for identifying IoT devices. Every event record consists of a body and a header.
+
+In preparation for creating independently deployable event data, an IoT sensor device in the physical world creates a device record using cryptographically identifiable information of the device and then registers the record in DLT, i.e., blockchain. From then on, an event record is created to represent the independently deployable event data generated from the sensor device. Specifically, the sensor device structures independently deployable event data in the form of event record comprising a body and a header. The sensor device creates a header of the event record, in which two hash values that link to the record body and the device record are placed. For a new event record to be distributed, the sensor device registers the header of the event record in DLT and stores the body of the event record in the distributed data repository. The hash value in the event header acts as a pointer to the body of the corresponding event record. The separated event record structure allows data consumers to verify the body of the event record by acquiring the header of the event record stored in DLT. The data consumers are applications or systems that utilize data collected by other systems or stored in a data repository. Example scenarios and more detail descriptions are given in clause IV.
+
+Figure 7, which is an extension of Figure 6, shows the relations of resources and resource groups in the information world. Here, five mapping relationships via interfaces between resources and resource groups are shown in the information world:
+
+- **IUT interface:** A USER resource has one-to-one mapping with a physical object (e.g., Human). A THING resource also has one-to-one mapping with a physical object (e.g., IoT device, gateway and server). Therefore, the USER resource has the ownership of physical objects from the THING resource through the interface *IUT*;
+- **IUS interface:** A USER resource will manage a SESSION resource group to show the current ownership information through the interface *IUS*. The SESSION resource group is time-dependent;
+- **IRS interface:** A relationship between a USER resource and a SESSION resource group will be decided according to policy information from POLICY and ROLE resource groups. These resource groups will communicate with SESSION resource through interface *IRS*;
+
+- $I_{RR}$ interface: USER and THING resources request to make the SERVICE resource group with SESSION and ROLE resources. In other words, the SERVICE resource group will be established according to the composition of the SESSION, POLICY and ROLE resource groups through interface $I_{RR}$ . The SERVICE resource group will then be able to manage the functions of an IoT device;
+- $I_{UR}$ interface: USER and THING resources manage POLICY and ROLE resource groups through interface $I_{UR}$ .
+
+
+
+Information world
+
+Physical world
+
+Virtual object group
+
+USER(s) resource
+
+SESSION(s) resource group
+
+THING(s) resource
+
+POLICY(ies), ROLE(s) resource group
+
+SERVICE(s) resource group
+
+$I_{US}$
+
+$I_{UT}$
+
+$I_{UR}$
+
+$I_{RS}$
+
+$I_{RR}$
+
+$I_{DU}$
+
+Sensing
+
+$I_{DR}$
+
+Controlling
+
+$I_{DS}$
+
+Actuating
+
+Human IoT server
+
+IoT device
+
+Delegation authority
+
+Access rights
+
+Policy authority
+
+Credentials
+
+Physical object group
+
+Information flow
+
+Control flow
+
+Interfacing among resources
+
+Physical object
+
+Physical object group
+
+Virtual object
+
+Virtual object group
+
+Y.4463(20)\_F07
+
+Figure 7: Mapping relation between virtual objects. The diagram illustrates the interaction between the Information world and the Physical world. The Information world contains a Virtual object group with four resources: USER(s) resource, SESSION(s) resource group, THING(s) resource, and POLICY(ies), ROLE(s) resource group. These resources are interconnected by information flows (I\_US, I\_UT, I\_UR, I\_RS, I\_RR) and control flows (dashed arrows). The Physical world contains a Physical object group with four objects: Human IoT server, IoT device, Delegation authority (with Access rights), and Policy authority (with Credentials). The mapping is shown through three interfaces: Sensing (I\_DU), Controlling (I\_DR), and Actuating (I\_DS). A legend at the bottom defines the symbols for information flow, control flow, interfacing among resources, physical objects, physical object groups, virtual objects, and virtual object groups.
+
+**Figure 7 – Mapping relation between virtual objects**
+
+Figure 8 shows in detail the mapping relation of SESSION, POLICY and ROLE resource groups for policy management. More detailed descriptions are given in Figure III.5 of clause III.2.
+
+- SESSION resource group: The SESSION resource group has the inner resource – EVENT, which invokes and triggers some virtual objects;
+- ROLE resource group: The ROLE resource group is mapped into USER and THING resources with information of the delegation service from a policy authority. The ROLE resource group also has inner resources – CONDITION and ACTION. The CONDITION resource could be used to trigger the ACTION resources. The types of ACTION resources may be CRUDN (Create, retrieve, update, delete and notification).
+- POLICY resource group: The POLICY resource group will be transferred from a policy authority in the physical world. The POLICY resource group has the inner resource – COMMAND. The COMMAND resource can be used to manage the delegation request from the physical world.
+
+
+
+Figure 8: Mapping relation for policy management. The diagram shows a 'Virtual object group' containing three 'resource groups': 'SESSION resource group', 'POLICY resource group', and 'ROLE resource group'. Inside 'SESSION' are 'EVENT resource' and 'COMMAND resource'. Inside 'POLICY' are 'COMMAND resource' and 'ACTION resource'. Inside 'ROLE' are 'CONDITION resource' and 'ACTION resource'. Blue double-headed arrows indicate interfacings: between 'EVENT' and 'COMMAND', 'COMMAND' and 'ACTION', and between 'SESSION' and 'ROLE' groups. A legend at the bottom shows a dashed box for 'Virtual object' and a dashed box with a double-headed arrow for 'Interfacing among resources'. The label 'Virtual object group' is also shown. Reference: Y.4463(20)\_F08.
+
+**Figure 8 – Mapping relation for policy management**
+
+Figure 9 shows the SERVICE resource group in detail. The SERVICE resource group has three inner resources: SERVICE, OPERATION and CONTROL. There are three inner mapping relationships between three resources in the SERVICE resource group. More detailed descriptions are presented in Figure III.6 of clause III.2.
+
+- SERVICE resource: The SERVICE resource is mapped into many resource groups such as SESSION, POLICY and ROLE as shown in Figure 8;
+- CONTROL resource: The CONTROL resource has a mapping relation with an IoT device with actuating capability;
+- OPERATION resource: The OPERATION resource has the execution information (e.g., smart contracts). That is, the OPERATION resource has execution codes and the triggering conditions from SERVICE resources.
+
+
+
+Figure 9: Mapping relation in the SERVICE resource group. The diagram shows a 'Service resource group' containing three resources: 'SERVICE resource', 'OPERATION resource', and 'CONTROL resource'. Blue double-headed arrows indicate interfacings between 'SERVICE' and 'OPERATION', 'OPERATION' and 'CONTROL', and 'SERVICE' and 'CONTROL'. To the right, a 'Virtual object group' contains multiple 'SERVICE resource group' boxes, with an ellipsis indicating more groups. A legend at the bottom shows a dashed box for 'Virtual object' and a dashed box with a double-headed arrow for 'Interfacing among resources'. Reference: Y.4463(20)\_F09.
+
+**Figure 9 – Mapping relation in the SERVICE resource group**
+
+# Appendix I
+
+## Types of delegation device
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix presents security phases for IoT devices cited from security services of [b-oneM2M] and defines delegation service.
+
+### I.1 Security phases for IoT devices
+
+Security services for IoT devices are generally composed of four phases as shown in Figure I.1 [b-oneM2M]. The first phase is network connectivity establishment to register network service. This phase is independent of the other phases. The second phase is security provisioning. During this phase, security credentials and identifiers are exchanged between the IoT device and the IoT server through an established network connection in order to provide security keys and related algorithms for each other, referred to as the "enrolment phase." The third phase is security association establishment. In this phase, access rights of resource(s) for IoT devices are negotiated and determined. The last phase is access control. This phase is the execution step in accordance with the results of negotiations in previous steps.
+
+
+
+The diagram illustrates the four security phases of IoT devices involving four main entities: IoT device, IoT server, Third-party, and Network. Each entity has a box representing its internal components: IoT device (Resources, Access rights for resources, Credentials and identifiers), IoT server (Resources, Access rights for resources, Credentials and identifiers), Third-party (Credentials and identifiers), and Network (empty box). The phases are represented by numbered arrows: ① Network connectivity establishment (IoT device ↔ Network, IoT server ↔ Network), ② Security provisioning (IoT device ↔ Third-party, IoT server ↔ Third-party), ③ Security association establishment and delegation services (IoT device ↔ IoT server), and ④ Access control (IoT device ↔ IoT server). The third phase is highlighted in orange.
+
+Y.4463(20)\_F1.1
+
+Figure I.1: Four security phases of IoT devices. The diagram shows the interaction between an IoT device, an IoT server, a third-party, and a network across four phases: 1. Network connectivity establishment, 2. Security provisioning, 3. Security association establishment and delegation services, and 4. Access control.
+
+Figure I.1 – Four security phases of IoT devices
+
+Delegation service refers to the third phase in Figure I.1. During this phase, ownership of the IoT device will be negotiated and transferred to an IoT server. These ownerships are access rights of IoT devices. For example, access right means the functional operation of IoT devices such as create, read, update, delete and notify (CRUDN).
+
+### I.2 Delegation service among IoT devices
+
+#### I.2.1 Single delegation service
+
+The single delegation service (SDS) is classified from two viewpoints: whole or partial ownership transfer and time dependency. According to the whole or partial ownership transfer viewpoint, there exists the whole and partial SDS (Wh-SDS and Pa-SDS). The time dependency viewpoint, encompasses permanent and temporary SDS (Pe-SDS and Te-SDS).
+
+A Wh-SDS transfers whole ownership to peer IoT device(s). That is, after whole ownership transfer, IoT devices may share whole ownership with peer IoT devices according to the policies. On the other hand, a Pa-SDS transfers ownership of an IoT device to a peer partially.
+
+Figure I.2 shows whole and partial-based single delegation services. At first, IoT device (A) has connectivity to physical entities such as sensors. This means that IoT device (A) has full access rights for its physical entities. IoT device (A) may be assumed to have six data. IoT device (A) then transfers the whole access rights into resource (B). That is, resource (B) will have full ownership for IoT device (A) after a Wh-SDS service. On the other hand, resource (B) transfers a part of the access rights into IoT device (C). That is, IoT device (C) has only partial ownership for resource (B). Therefore, if IoT device (C) uses full functions of IoT device (A), IoT device (C) will have to obtain ownership of the remaining resources from IoT device (A) or resource (B) temporarily.
+
+
+
+The diagram illustrates the flow of ownership and data between IoT devices and resources across two worlds: Information world and Physical world.
+
+**Information world:**
+
+- Resource (Virtual object(B)):** Contains "The ownership of resources". It is represented by a red dashed box.
+- IoT device (Physical object A):** Contains "The ownership of IoT device". It is represented by a blue solid box.
+- IoT device (Physical object C):** Contains "The ownership of IoT device". It is represented by a blue solid box.
+
+**Physical world:**
+
+- Data:** Represented by blue boxes containing resource IDs (R1, R2, ..., R12).
+- Information flow:** Indicated by blue arrows.
+- Physical object:** Represented by blue solid boxes.
+- Virtual object:** Represented by red dashed boxes.
+
+**Delegation Services:**
+
+- Whole-single delegation service (Wh-SDS):** Transfers all ownership from IoT device (A) to Resource (B).
+- Partial-single delegation service (Pa-SDS):** Transfers partial ownership from Resource (B) to IoT device (C).
+
+**Resource Ownership Data:**
+
+| Resource (Virtual object(B)) | | | | | |
+|------------------------------|----|----|----|-----|--|
+| R1 | R3 | R5 | R7 | R9 | |
+| R2 | R4 | R6 | R8 | R10 | |
+
+**IoT Device Ownership Data:**
+
+| IoT device (Physical object A) | | | IoT device (Physical object C) | | |
+|--------------------------------|----|----|--------------------------------|-----|-----|
+| R1 | R3 | R5 | R7 | R9 | R11 |
+| R2 | R4 | R6 | R8 | R10 | R12 |
+
+**Legend:**
+
+- Data:** R1 R2 ...
+- Information flow:** Blue arrow
+- Physical object:** Blue solid box
+- Virtual object:** Red dashed box
+
+Y.4463(20)\_F1.2
+
+Diagram illustrating whole and partial-based single delegation services (Wh-SDS and Pa-SDS) between IoT devices and resources.
+
+**Figure I.2 – Whole and partial-based single delegation services**
+
+Figure I.3 shows time-based delegation services such as Pe-SDS and Te-SDS. A Pe-SDS transfers ownership of resources permanently while a Te-SDS transfers ownership temporarily. The Pe-SDS is not able to withdraw transferred ownership. On the other hand, Te-SDS will be able to withdraw ownership in future. That is, the delegated information of Te-SDS will be cancelled automatically after a defined time period.
+
+Resource (virtual object B) transfers partial ownership temporarily to the IoT device (physical object A). That is, the IoT device (physical object A) has only partial ownership for the resource (virtual object B) like Pa-SDS. After the elapse of a given time period, ownership of the IoT device (physical object A) about resource (virtual object B) will be withdrawn. In the case of Pe-SDS, ownership of the IoT device (physical object C) should not be withdrawn.
+
+
+
+Diagram illustrating Time-based single delegation services. It shows the flow of information and control between the Information world and the Physical world. In the Information world, a Resource (Virtual object B) is shown with its ownership of resources (R1-R10). In the Physical world, two IoT devices (Physical objects A and C) are shown. IoT device A has its own ownership of IoT device (R1-R6). IoT device C has its own ownership of IoT device (R7-R10). A Temporary-single delegation service (Te-SDS) is shown as a blue arrow from the Resource to IoT device A, and a red dashed arrow from IoT device A back to the Resource, labeled 'Withdrawn of access rights after time-passing'. A Permanent-single delegation service (Pe-SDS) is shown as a blue arrow from the Resource to IoT device C, and a red dashed arrow from IoT device C back to the Resource, which is crossed out with a red 'X'. A legend at the bottom indicates that blue arrows represent Information flow, red dashed arrows represent Control flow, solid blue boxes represent Physical objects, and dashed red boxes represent Virtual objects. The diagram is labeled Y.4463(20)\_Fl.3.
+
+**Figure I.3 – Time-based single delegation services**
+
+#### I.2.2 Pre-defined relational delegation service
+
+A pre-defined relational delegation service is classified into two categories: whole or partial ownership transfer and time-based types. In the whole or partial ownership transfer, there is both whole pre-defined relational delegation service (Wh-PDS) and partial pre-defined relational delegation service (Pa-PDS). Wh-PDS transfers full ownership information from the parent IoT device into the child IoT devices and then the reverse process can also be possible. These operations take place through the resource in the information world or directly, otherwise, the Pa-PDS transfers the ownership information partially. In the time-based type, there are both permanent PDS (Pe-PDS) and temporary PDS (Te-PDS). In case of Pe-PDS, the first-level child an IoT device can transfer ownerships to second-level IoT devices.
+
+The PDS is different from the SDS from the viewpoint of prerequisite requirements. A group delegation, as described in clause I.2.3, is a super set of PDS because PDS should agree with the policy rule among IoT devices in advance. PDS should have relations of ownership policies between parent and child IoT devices in advance. In Figure I.4, IoT device (A) manages resource (D) for the PDS. That is, IoT device (A) already obtained ownership of IoT device (B)'s data from IoT device (C). In this case, the parent device, IoT device (A) has the role of the manager for the PDS. IoT devices (B) and (C) also have the policy rule of resource ownership in advance. Thus, PDS may only occur automatically according to the policy rule. That is, delegated ownership information may or may not be transferred to third parties.
+
+
+
+The diagram illustrates the flow of ownership information from IoT devices in the Physical world to a Resource in the Information world. It is divided into two horizontal layers: the Information world (top) and the Physical world (bottom).
+
+**Information world:**
+
+- Resource (Virtual object D) (Parent):** Contains "The ownership of resources". It is represented by a dashed red box.
+- Delegation Services:**
+ - Whole-pre-defined delegation service (Wh-PDS):** A blue box that receives information from IoT device A and IoT device B.
+ - Partial-pre-defined delegation service (Pa-PDS):** A blue box that receives information from IoT device B and IoT device C.
+- Resource Data Grid:** A 2x5 grid of resource identifiers:
+
+
+| | | | | | |
+|----|----|----|----|-----|---|
+| R1 | R3 | R5 | R7 | R9 | X |
+| R2 | R4 | R6 | R8 | R10 | X |
+
+**Physical world:**
+
+- IoT device (Physical object A) (Parent):** Contains "The ownership of IoT device". It is represented by a solid blue box. Its data grid is:
+
+
+| | |
+|----|----|
+| R1 | R3 |
+| R2 | R4 |
+- IoT device (Physical object B) (First-level child):** Contains "The ownership of IoT device". It is represented by a solid blue box. Its data grid is:
+
+
+| | |
+|----|----|
+| R5 | R7 |
+| R6 | R8 |
+- IoT device (Physical object C) (Second-level child):** Contains "The ownership of IoT device". It is represented by a solid blue box. Its data grid is:
+
+
+| | |
+|-----|-----|
+| R9 | R11 |
+| R10 | R12 |
+
+**Legend:**
+
+- Data:** Represented by a grid of resource identifiers (R1, R2, ..., R12).
+- Information flow:** Indicated by a blue arrow.
+- Physical object:** Represented by a solid blue box.
+- Virtual object:** Represented by a dashed red box.
+- Pre-defined relationship for the delegation service:** Indicated by a blue arrow pointing from a device to a service.
+
+Y.4463(20)\_FI.4
+
+Figure I.4: Pre-defined relational delegation services. The diagram illustrates the flow of ownership information from IoT devices in the Physical world to a Resource in the Information world. It shows three IoT devices (A, B, C) with their respective ownership data, and two delegation services (Wh-PDS, Pa-PDS) that aggregate this data into a central Resource (D).
+
+**Figure I.4 – Pre-defined relational delegation services**
+
+#### I.2.3 Group delegation service
+
+The group delegation service will be transferred and copied among sets of IoT devices. A resource should be selected for a group. When transferring its ownership information about a resource to group, each IoT device should do so either permanently or temporally. The manager of a group should also be selected among IoT devices in order to manage the resource. Subsequently, the ownership of a group will be transferred to the other IoT devices by the manager of the group. The change of ownership should also be disseminated to all IoT devices in the group by the manager.
+
+Figure I.5 demonstrates that the data of all IoT devices will be transferred to resource (D). The manager for resource (D) should be selected among IoT devices and the selected manager maintains the collected resources. The selection methods of the group manager are outside the scope of this Recommendation.
+
+
+
+The diagram illustrates a group delegation service across two worlds: the Information world and the Physical world.
+
+**Information world:** Contains a **Resource (Virtual object D)** represented by a dashed red box. Inside this box is a sub-section labeled **The ownership of resources**. To the right of this box is a 2x3 grid of resource identifiers: R1, R2, R3 in the top row and R4, R5, R6 in the bottom row.
+
+**Physical world:** Contains three IoT devices, each represented by a solid blue box:
+
+- IoT device (Physical object A) (Manager):** Contains a sub-section **The ownership of IoT device** and is associated with resource identifiers R1 and R2.
+- IoT device (Physical object B):** Contains a sub-section **The ownership of IoT device** and is associated with resource identifiers R3 and R4.
+- IoT device (Physical object C):** Contains a sub-section **The ownership of IoT device** and is associated with resource identifiers R5 and R6.
+
+**Information flow:** Three blue arrows point from the IoT devices in the Physical world up to the Resource in the Information world, indicating the delegation of ownership information.
+
+**Legend:**
+
+- Data:** Represented by a box containing R1, R2, and an ellipsis (...).
+- Information flow:** Represented by a blue arrow.
+- Physical object:** Represented by a solid blue rounded rectangle.
+- Virtual object:** Represented by a dashed red rounded rectangle.
+
+Y.4463(20)\_FI.5
+
+Diagram of Group delegation service showing information flow from physical IoT devices to a virtual resource.
+
+**Figure I.5 – Group delegation service**
+
+## Appendix II
+
+## Procedures of delegation service
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix provides the procedures of delegation service to illustrate delegation scenarios.
+
+### II.1 Single delegation service
+
+As shown in Figure 3, IoT devices (physical object A and physical object B) are the camera entities. They have the function of image generation. These generated images will be then stored in a secured method as resources (virtual object A and virtual object B) for each physical object. The IoT device (physical object A) generates images (R1 to R4) and registers them as image data into a resource (virtual object A). The IoT device (physical object B) also registers images (R5 to R8) into a resource (virtual object B). The control and policy information for a single delegation service should then be obtained with the help of delegation and policy authorities. Thereafter, resource groups (virtual object C and virtual object D) will be composed as a result of a single delegation service.
+
+
+
+The diagram illustrates the detailed procedures of a single delegation scenario. It features seven vertical lifelines: IoT device (Physical object A), IoT device (Physical object B), Resource (Virtual object A), Resource (Virtual object B), Resource group (Virtual object C), Resource group (Virtual object D), and Delegation and policy authority (Physical object E).
+
+The sequence of steps is as follows:
+
+- 1. Generate the image A:** IoT device (Physical object A) sends a message to Resource (Virtual object A). A box labeled "Image A {R1, R2, R3, R4}" is shown on the Resource (Virtual object A) lifeline.
+- 2. Request the control and policy information:** Resource (Virtual object A) sends a message to Delegation and policy authority (Physical object E). A return message is sent back to Resource (Virtual object A).
+- 3. Generate the image data B:** IoT device (Physical object B) sends a message to Resource (Virtual object B). A box labeled "Image data B {R5, R6, R7, R8}" is shown on the Resource (Virtual object B) lifeline.
+- 4. Request the control and policy information:** Resource (Virtual object B) sends a message to Delegation and policy authority (Physical object E). A return message is sent back to Resource (Virtual object B).
+- 5. Partial-SDS:** Resource (Virtual object A) sends a message to Resource group (Virtual object C). A box labeled "Image A' {R1, R4}" is shown on the Resource group (Virtual object C) lifeline.
+- 6. Partial-SDS:** Resource (Virtual object B) sends a message to Resource group (Virtual object D). A box labeled "Image A'' {R2, R3}" is shown on the Resource group (Virtual object D) lifeline.
+- 7. Whole-SDS:** Resource (Virtual object B) sends a message to Resource group (Virtual object D). A box labeled "Image B' {R5, R6, R7, R8}" is shown on the Resource group (Virtual object D) lifeline.
+
+Y.4463(20)\_F11.1
+
+Sequence diagram illustrating the detailed procedures of a single delegation scenario. The diagram shows interactions between IoT devices, resources, resource groups, and a delegation/policy authority.
+
+Figure II.1 – Detailed procedures of single delegation scenario
+
+### II.2 Pre-defined relational delegation service
+
+According to a PDS policy, a pre-defined relation for an online map application will be established for collecting data in the virtual objects A, B and C before the data collection service. In Figure 4, the IoT devices (physical object A, physical object B and physical object C) should have the pre-defined relation for the delegation service. IoT device (physical object C) then generates resource group (virtual object E) through the resource (virtual object C) for the online map service. Thereafter, IoT
+
+device (physical object A) generates geographic information and registers the information into resource (virtual object A) and afterwards resource (virtual object A) transfers part of its data into resource group (virtual object E).
+
+The remaining data in resource (virtual object A) will be maintained in its own storage, and this is a partial-PDS. At the same time, IoT device (physical object B) gets traffic and weather information. It then registers this information into resource group (virtual object E) through resource (virtual object B), and this is a whole-PDS. Finally, combined data will be transferred to IoT device (physical object C) such as a display device.
+
+
+
+```
+
+sequenceDiagram
+ participant A as IoT device (Physical object A)
+ participant B as IoT device (Physical object B)
+ participant C as IoT device (Physical object C)
+ participant RA as Resource (Virtual object A)
+ participant RB as Resource (Virtual object B)
+ participant RC as Resource (Virtual object C)
+ participant RE as Resource group (Virtual object E)
+ participant F as Delegation and policy authority (Physical object F)
+
+ Note over A,F: 1. Set the control and policy information
+ F->>A:
+ F->>B:
+ F->>C:
+ F->>RA:
+ F->>RB:
+ F->>RC:
+ F->>RE:
+
+ Note over A,F: 2. Generate the hierarchy for delegation service
+ A->>B:
+ A->>C:
+ A->>RA:
+ A->>RB:
+ A->>RC:
+ A->>RE:
+ A->>F:
+
+ C->>F: 3. Generate the map resource through the resource (C)
+ Note right of RE: Map data
+
+ A->>RA: 4-1. Generate the geographic data
+ Note over RA: Geographic data {R1, R2, R3, R4}
+ RA->>RE: 4-2. Perform the Pa-PDS
+ Note over RE: Geographic data {R1, R4}
+
+ B->>RB: 5-1. Generate the traffic and weather data
+ Note over RB: Traffic and weather data
+ RB->>RE: 5-2. Perform the Wh-PDS
+ Note over RE: Traffic and weather data
+
+ RE->>C: 6. Actuate the resource (C)
+ Note over C: Map data
+
+```
+
+Y.4463(20)\_FII.2
+
+Sequence diagram showing the detailed procedures of a pre-defined relational delegation scenario. The diagram involves eight participants: IoT device (Physical object A), IoT device (Physical object B), IoT device (Physical object C), Resource (Virtual object A), Resource (Virtual object B), Resource (Virtual object C), Resource group (Virtual object E), and Delegation and policy authority (Physical object F).
+
+**Figure II.2 – Detailed procedures of pre-defined relational delegation scenario**
+
+### II.3 Group delegation service
+
+Figure II.3 shows detail procedures to instantiate a smart home service to illustrate the concept of the group delegation service illustrated in Figure 5. At first, the owner of the smart home should make resource groups for IoT devices in order to make group delegation easy. Thereafter, the owner will transfer ownership of the group to a visitor.
+
+
+
+```
+
+sequenceDiagram
+ participant A as Physical object (A)
+ participant B as Physical object group (B)
+ participant C as Physical object (C)
+ participant VG as Virtual object group (A)
+ participant E as Delegation authority (E)
+ participant F as Policy authority (F)
+
+ B->>A: 1. Generate the groups for delegation service
+ B->>E: 2. Request the control information
+ E->>F: 3. Request the policies
+ C->>VG: 4. Request the access rights
+ VG->>A: 5. Request the access rights
+ A->>VG: 6. Reply the access rights
+ VG->>C: 7. Reply the access rights
+
+ Note over VG: Resource group {A1, A2, A3, ...}
+ Note over VG: Resource group for visitor
+
+```
+
+Y.4463(20)\_FII.3
+
+Sequence diagram showing the detailed procedures of group delegation scenario in smart homes. The diagram involves six participants: Physical object (A), Physical object group (B), Physical object (C), Virtual object group (A), Delegation authority (E), and Policy authority (F). The steps are: 1. Generate the groups for delegation service (B to A), 2. Request the control information (B to E), 3. Request the policies (E to F), 4. Request the access rights (C to Virtual object group (A)), 5. Request the access rights (Virtual object group (A) to A), 6. Reply the access rights (A to Virtual object group (A)), and 7. Reply the access rights (Virtual object group (A) to C). Two resource groups are shown: 'Resource group {A1, A2, A3, ...}' and 'Resource group for visitor'.
+
+**Figure II.3 – Detailed procedures of group delegation scenario in smart homes**
+
+## Appendix III
+
+## Data model of delegation service
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix provides the data model of delegation service in an IoT environment.
+
+### III.1 Physical objects for delegation service
+
+Figure III.1 shows the core function in the IoT gateway and the IoT device as the physical objects for the delegation service. First of all, the IoT device has four modules: session, thing, user and service modules. The IoT gateway may also have physical things at the same place. The IoT gateway has three more additional modules compared to the IoT device. In particular, a distributed ledger technology (DLT) module has the key function for security services such as integrity, access control and others.
+
+
+
+The diagram illustrates the core functions in IoT gateways and devices, organized into three main layers:
+
+- IoT gateway layer:** Contains the **Edge function** module, which includes the **DLT module**, **Learning module**, and **Storage module**.
+- IoT device layer:** Contains the **Device function** module, which includes the **SESSION module**, **THING module**, **USER module**, and **SERVICE module**.
+- Physical layer:** Contains **Users** and **Physical resources**.
+
+Interactions and connections:
+
+- IoT gateways or devices** (external) connect to the **SESSION module** in the IoT device layer.
+- SESSION module** connects to **THING module**, **USER module**, and **SERVICE module**.
+- THING module** connects to **DLT module**, **Learning module**, and **Storage module** in the IoT gateway layer.
+- USER module** connects to **Users** in the Physical layer.
+- SERVICE module** connects to **Physical resources** in the Physical layer.
+
+Vertical arrows on the right indicate the flow of data and control between the IoT gateway, IoT device, and Physical layers.
+
+Y.4463(20)\_FIII.1
+
+Figure III.1: Core functions in IoT gateways and devices. The diagram illustrates the architecture of IoT gateways and devices, showing the flow of data and control between various modules.
+
+**Figure III.1 – Core functions in IoT gateways and devices**
+
+Figure III.2 and Figure III.3 describe various interfaces in the IoT gateway and the IoT device. Figure III.2 shows the twelve interfaces in the IoT gateway and the IoT device. Figure III.3 also describes four types of messages (Command, Event, Control and Context) for IoT services, which are used through the twelve interfaces.
+
+
+
+Figure III.2 – Interfaces of IoT gateways and devices. This diagram illustrates the functional layers and interfaces of IoT gateways and devices. It is divided into three main horizontal sections: Edge function, Device function, and a bottom layer for Users and Physical resources. The Edge function layer contains DLT module, Learning module, and Storage module. The Device function layer contains SESSION module, THING module, USER module, and SERVICE module. The bottom layer contains Users and Physical resources. Numbered interfaces (1-12) connect these components. On the left, 'IoT gateways or devices' are shown with interfaces #3 and #4 to the SESSION module. On the right, 'IoT gateway' and 'IoT device' are indicated with vertical arrows. The bottom layer shows Users connected to the SESSION module via #10, and Physical resources connected to the THING module via #11 and #12. The diagram is labeled Y.4463(20)\_FIII.2 at the bottom right.
+
+**Figure III.2 – Interfaces of IoT gateways and devices**
+
+
+
+Figure III.3 – Four types of messages for delegation service. This diagram shows the flow of four types of messages: RESTful, Event, Command, and Control/Context. At the top, Cloud services and a Third party are connected to IoT servers and a User via RESTful messages. The Internet connects the IoT servers and the User. The User sends Command messages to IoT devices. IoT devices send Event (Type #2) messages to IoT gateways. IoT gateways send Event (Type #1) and Event (Type #3) messages to each other. IoT gateways send Control/Context messages to IoT devices. IoT devices send Physical data to IoT gateways. The diagram is labeled Y.4463(20)\_FIII.3 at the bottom right.
+
+**Figure III.3 – Four types of messages for delegation service**
+
+Figure III.4 shows Event messages. There are three different types of Event messages according to the subject of communication such as the IoT gateways and the devices.
+
+
+
+Y.4463(20)\_FIII.4
+
+Figure III.4: Different types of Event messages for delegation service. The diagram shows four components: two IoT gateways and two IoT devices. Each IoT gateway contains a DLT module and a SESSION module. Each IoT device contains a SESSION module. Three event messages are shown: Event #1 is a bidirectional arrow between the SESSION modules of the two IoT gateways. Event #2 is a bidirectional arrow between the SESSION modules of the two IoT devices. Event #3 is a bidirectional arrow between the SESSION modules of the two IoT gateways, passing through the IoT devices.
+
+**Figure III.4 – Different types of Event messages for delegation service**
+
+### III.2 Data models for delegation service
+
+Figure III.5 shows the data model for a SESSION resource to support the session module of Figure III.1. The ROLE resource has a "condition" field. The "condition" field is composed of context name, event name and token. Here, "token" has timing information to support various types of delegation services. The "action" field is composed of two components: action type and action name. There are six types of actions: create, retrieve, update, delete, notification and no-operation. There are also four names for actions: event, control, context and command.
+
+
+
+Y.4463(20)\_FIII.5
+
+Figure III.5: Data model for a SESSION resource. The diagram shows a hierarchical structure of data models. At the top is the SESSION model with fields Name, Event, and Policy. The Event field points to the EVENT model, and the Policy field points to the POLICY model. The EVENT model has fields Name and Data TLV. The POLICY model has fields Name, Role identifier, Role set, and Command set. The Role identifier field points to the ID model, the Role set field points to the ROLESSET model, and the Command set field points to the COMMANDSET model. The ID model has fields Name, Group ID, Device ID, and User ID. The ROLESSET model has fields Name and Role. The COMMANDSET model has fields Name and Command. The Role field in the ROLESSET model points to the ROLE model, and the Command field in the COMMANDSET model points to the COMMAND model. The ROLE model has fields Name, Condition, and Action. The COMMAND model has fields Name, Data TLV, and Control.
+
+**Figure III.5 – Data model for a SESSION resource**
+
+Figure III.6 shows the data model for a SERVICE resource to support the service module of Figure III.1. SERVICE resources are used to manage the physical objects through interface #11 in Figure III.2
+
+
+
+Y.4463(20)\_FIII.6
+
+Figure III.6: Data model for a SERVICE resource. The diagram shows a hierarchical structure with four levels: SERVICE, CONTROL, OPERATION, and a third level. SERVICE contains Name and Control. CONTROL contains Name, Data TLV, and Operation. OPERATION contains Name, Type, and Data TLV. Arrows indicate relationships: from SERVICE Control to CONTROL Name, from CONTROL Operation to OPERATION Name, and from OPERATION Data TLV to a third level.
+
+**Figure III.6 – Data model for a SERVICE resource**
+
+Figure III.7 shows the data model for a USER resource to support the user module of Figure III.1. Here, this data model defines the USER resource and these resources are managed by a human through interface #10 of Figure III.2.
+
+
+
+Y.4463(20)\_FIII.7
+
+Figure III.7: Data model for a USER resource. The diagram shows a hierarchical structure with four levels: USER, COMMAND, CONTROL, and OPERATION. USER contains Name and Command. COMMAND contains Name, Data TLV, and Control. CONTROL contains Name, Data TLV, and Operation. OPERATION contains Name, Type, and Data TLV. Arrows indicate relationships: from USER Command to COMMAND Name, from COMMAND Control to CONTROL Name, from CONTROL Operation to OPERATION Name, and from OPERATION Data TLV to a third level.
+
+**Figure III.7 – Data model for a USER resource**
+
+Figure III.8 shows the data model for a THING resource to support the thing module of Figure III.1. The thing module based on this data model gathers some raw data through interface #12 in Figure III.2. The THING resource will then be made from the raw data with their syntax.
+
+
+
+Y.4463(20)\_FIII.8
+
+Figure III.8: Data model for THING resource. The diagram shows a 'THING' resource group containing 'Name' and 'Context' (a stack of boxes). An arrow points from 'Context' to a 'CONTEXT' resource group containing 'Name' and 'Data TLV'. The label 'Y.4463(20)\_FIII.8' is at the bottom right.
+
+**Figure III.8 – Data model for THING resource**
+
+Figure III.9 shows the data model for the distributed database of Figure 6. This data model defines new DLT resource groups and supports the session module of Figure III.1. The DLT resource is transferred for discovery and security matters. This DLT resource is outside the scope of this Recommendation.
+
+
+
+Y.4463(20)\_FIII.9
+
+Figure III.9: Data model for a distributed database. The diagram shows a 'DLT' resource group containing 'Name', 'Event' (a stack of boxes), and 'Policy' (a stack of boxes). An arrow points from 'Event' to an 'Event model' resource group containing 'Name' and 'Data TLV' (a stack of boxes). Another arrow points from 'Policy' to a 'Policy model' resource group containing 'Name', 'Role identifier', 'Role set', and 'Command set'. The label 'Y.4463(20)\_FIII.9' is at the bottom right.
+
+**Figure III.9 – Data model for a distributed database**
+
+## Appendix IV
+
+## Example scenario of independently deployable event data
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix provides an example of a delegation service scenario for independently deployable event data.
+
+### IV.1 Infrastructure safety service
+
+Figure IV.1 shows an example of an infrastructure safety service to illustrate the delegation service for independently deployable event data. Various IoT sensor devices are placed around the roads to monitor the state of bridges, tunnels, slopes, road surfaces, etc. These sensor devices, along with communications under the IoT delegation service framework, enable service authorities to collect and analyse data to improve road safety management.
+
+
+
+The diagram illustrates the infrastructure safety service scenario, showing the flow of data from the physical world to the information world.
+
+**Physical world:** Includes an IoT base station, a Road surface state sensor, a Slope monitoring sensor, a Tunnel monitoring sensor, a Bridge monitoring sensor, and a Data repository. A car is also shown on the road.
+
+**Information world:** Shows a graph of Sensor data over time. The data is divided into two sections: "Data stream in old ownership" and "Data stream in current ownership", separated by an "Ownership change" point. The x-axis represents "Generation time".
+
+**Legend:**
+
+- R**: Resource (Virtual object)
+- Virtual object group**: Represented by a dashed red box containing R5, R6, R7, R8, and a vertical ellipsis.
+- Sensor data flow**: Represented by a blue arrow.
+- Sensor (Physical object)**: Represented by a wireless signal icon.
+- Distributed database**: Represented by a cylinder icon.
+
+Y.4463(24)
+
+Figure IV.1: Example of infrastructure safety service. The diagram illustrates the flow of sensor data from the physical world to the information world. In the physical world, an IoT base station and various sensors (Road surface state sensor, Slope monitoring sensor, Tunnel monitoring sensor, Bridge monitoring sensor) are deployed along a road with a bridge and a tunnel. A car is shown on the road. Data from these sensors is sent to a Data repository. The information world shows a graph of Sensor data over time, divided into 'Data stream in old ownership' and 'Data stream in current ownership' by an 'Ownership change' point. A legend identifies symbols for Resource (Virtual object), Virtual object group, Sensor data flow, Sensor (Physical object), and Distributed database. The reference Y.4463(24) is noted at the bottom right.
+
+**Figure IV.1 – Example of infrastructure safety service**
+
+The data from the sensor devices are represented as virtual objects and are accessible according to the ownership management. A combination of a virtual object and necessary access rights allows access to live data or historical data recorded in the past. The virtual object also manages data attributes and verifies data integrity. The trustworthiness of data collected determines the reliability of data analytics, which ultimately impacts the infrastructure safety service. In some cases, ownership of a sensor device may change. An ownership transfer in a delegation service applies to the event data recorded in the past. From the data perspective, the delegation service model eliminates a
+
+discontinuity in data acquisition caused by ownership changes. Consequently, a continuous data stream from the same source device expands data coverage in time and enhances the performance of infrastructure safety analysis.
+
+### IV.2 Distributed database for validating independently deployable event data
+
+The distributed databases allows the infrastructure safety service to acquire a series of event data distributed in the past. The IoT device in Figure IV.2 is one of the monitoring sensor devices around the road. This sensor device has the capability of monitoring changes around the road and generating data. This type of device not only pushes event data to the cloud but also disseminates the data through a distributed data repository. According to the delegation service model, the sensor device registers its independently deployable event data into a resource (virtual object R8). When new event data (A1) is ready to be distributed, the device hashes the record body of event data and pushes the digest into the record header. The sensor device then registers the record header in the DLT and stores the record body in the distributed data repository. The control and policy information for a single delegation service should be obtained with the help of delegation and policy authorities. Once a user gains access rights through a virtual object to the independently deployable event data, the user retrieves the event data from the distributed data repository. The accumulated data in the distributed data repository can be validated by data consumers, if necessary, with reference to the record header in the DLT. The scope of validation includes attribute information such as the data-generating device, ownership, generation sequence, etc.
+
+
+
+```
+
+sequenceDiagram
+ participant IoT as IoT device (Sensor)
+ participant Resource as Resource (Virtual object)
+ participant DLT as DLT (Distributed ledger technology)
+ participant Repository as Distributed data repository
+ participant Consumer as Data consumer
+ participant Authority as Delegation and policy authority
+
+ IoT->>Resource: 1. Create a metadata for distributable data
+ Resource->>DLT: 2. Register a cryptographical digest for sensor data A1
+ IoT->>Repository: 3. Store the sensor data A1
+ DLT->>Repository: Cryptographic digest for sensor data # {A1}
+ IoT->>Authority: 4. Request the control and policy information
+ Authority->>Repository: 5. Perform Pa-SDS on the sensor data A1
+ Repository->>Consumer: 6. Retrieve the sensor data A1
+ Consumer->>DLT: 7. Verify the integrity of the sensor data A1
+ DLT->>Consumer: Sensor data {A1}, digest # {A1}
+
+```
+
+The diagram illustrates the procedures for independently deployable event data across six entities: IoT device (Sensor), Resource (Virtual object), DLT (Distributed ledger technology), Distributed data repository, Data consumer, and Delegation and policy authority. The process follows these steps:
+
+- IoT device (Sensor)** creates metadata for distributable data and sends it to the **Resource (Virtual object)**.
+- Resource (Virtual object)** registers a cryptographical digest for sensor data A1 in the **DLT (Distributed ledger technology)**.
+- IoT device (Sensor)** stores the sensor data A1 in the **Distributed data repository**.
+- The **DLT (Distributed ledger technology)** provides the cryptographic digest for sensor data # {A1} to the **Distributed data repository**.
+- IoT device (Sensor)** requests control and policy information from the **Delegation and policy authority**.
+- The **Delegation and policy authority** performs Pa-SDS on the sensor data A1 and sends the result to the **Distributed data repository**.
+- The **Distributed data repository** retrieves the sensor data A1 and sends it to the **Data consumer**.
+- The **Data consumer** verifies the integrity of the sensor data A1 with the **DLT (Distributed ledger technology)**.
+- The **DLT (Distributed ledger technology)** provides the sensor data {A1} and digest # {A1} to the **Data consumer**.
+
+Sequence diagram showing the procedures for independently deployable event data across IoT device, Resource, DLT, Distributed data repository, Data consumer, and Delegation and policy authority.
+
+Figure IV.2 – Detailed procedures of independently deployable event data
+
+# Bibliography
+
+- [b-ITU-T H.761] Recommendation ITU-T H.761 (2014), *Nested context language (NCL) and Giga-NCL*.
+- [b-ITU-T Q.9] Recommendation ITU-T Q.9 (1988), *Vocabulary of switching and signalling terms*.
+- [b-ITU-T X.509] Recommendation ITU-T X.509 (2019), *Information technology – Open Systems Interconnection – The Directory: Public-key and attribute certificate frameworks*.
+- [b-ITU-T X.1252] Recommendation ITU-T X.1252 (2010), *Baseline identity management terms and definitions*.
+- [b-ITU-T Y.2002] Recommendation ITU-T Y.2002 (2009), *Overview of ubiquitous networking and of its support in NGN*.
+- [b-ITU-T Y.2091] Recommendation ITU-T Y.2091 (2011), *Terms and definitions for next generation networks*.
+- [b-ITU-T Y.2720] Recommendation ITU-T Y.2720 (2009), *NGN identity management framework*.
+- [b-ITU-T Y.2724] Recommendation ITU-T Y.2724 (2013), *Framework for supporting OAuth and OpenID in next generation networks*.
+- [b-ITU-T Y.4500.1] Recommendation ITU-T Y.4500.1 (2017), *oneM2M-Functional Architecture*.
+- [b-IETF RFC 3444] IETF RFC 3444 (2003), *On the Difference between Information Models and Data Models*.
+- [b-INCITS 359] ANSI INCITS 359-2012, *Information technology – Role Based Access Control*.
+- [b-NIST.SP.800-162] NIST Special Publication 800-162 (2019), *Guide to Attribute Based Access Control (ABAC) Definition and Considerations*.
+- [b-oneM2M] oneM2M-TS-0003-Security\_Solutions-V-2014-8, *oneM2M Security Solutions*.
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+## Y.4468
+
+(01/2020)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Internet of things and smart cities and communities –
+Frameworks, architectures and protocols
+
+# --- **Minimum set of data transfer protocol for automotive emergency response system**
+
+Recommendation ITU-T Y.4468
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Network control architectures and protocols | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+| | |
+|-----------------|---------------|
+| CLOUD COMPUTING | Y.3000–Y.3499 |
+| Y.3500–Y.3999 | |
+
+## INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|----------------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+## Recommendation ITU-T Y.4468
+
+# Minimum set of data transfer protocol for automotive emergency response system
+
+## Summary
+
+An automotive emergency response system (AERS) for aftermarket devices defined in Recommendation ITU-T Y.4119 is designed to bring rapid assistance to driver and passengers involved in accidents.
+
+For a normal operation purpose of the AERS, an accident related data (so-called minimum set of data, MSD) needs to be sent from an automotive emergency detection device (AEDD) to an automotive emergency response centre (AERC).
+
+Recommendation ITU-T Y.4468 specifies an MSD transfer protocol to provide the rules of MSD transfer operations between an AEDD and an AERC in an AERS.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.4468 | 2020-01-13 | 20 | 11.1002/1000/14171 |
+
+## Keywords
+
+AERS, MSD, protocol.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2020
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+# Table of Contents
+
+| | | Page |
+|---|------------------------------------------------------------|------|
+| 1 | Scope..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 2 |
+| 6 | Overview of MSD transfer protocol ..... | 2 |
+| | 6.1 Overview of automotive emergency response system ..... | 2 |
+| | 6.2 Overview of message structure ..... | 3 |
+| 7 | MSD transfer message types ..... | 3 |
+| | 7.1 Request messages ..... | 3 |
+| | 7.2 Response messages..... | 5 |
+| 8 | MSD transfer protocol operation ..... | 7 |
+| | 8.1 Request-response operation..... | 7 |
+| | 8.2 Retransmission ..... | 9 |
+| 9 | Security considerations..... | 9 |
+| | Annex A – AEDD operation procedure..... | 10 |
+| | A.1 AEDD operation procedure..... | 10 |
+| | A.2 Automatic cancellation determination procedure..... | 10 |
+| | Annex B – Accident detection procedures..... | 12 |
+| | B.1 Collision detection..... | 12 |
+| | B.2 Spin off detection ..... | 12 |
+| | B.3 Rollover or capsizing detection ..... | 13 |
+| | B.4 Abnormal wheel speed detection..... | 14 |
+
+
+
+# Recommendation ITU-T Y.4468
+
+# Minimum set of data transfer protocol for automotive emergency response system
+
+# 1 Scope
+
+This Recommendation specifies a minimum set of data (MSD) transfer protocol for automotive emergency response system (AERS).
+
+In particular, the scope of this Recommendation includes:
+
+- MSD transfer protocol parameters
+- Message types of MSD transfer protocol
+- Sequence of MSD transfer protocol operation
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T Y.4119] Recommendation ITU-T Y.4119 (2018), *Requirements and capability framework for IoT-based automotive emergency response system*.
+
+[ITU-T Y.4467] Recommendation ITU-T Y.4467 (2020), *Minimum set of data structure for automotive emergency response system*.
+
+[IETF RFC 7252] IETF RFC 7252 (2014), *The Constrained Application Protocol (CoAP)*.
+
+# 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 automotive emergency detection device (AEDD)** [ITU-T Y.4119]: A unit (or a set of units) expected to perform at least the following functions:
+
+- receiving sensing data, from internal sensors and/or vehicle sensors, for determining whether or not the accident occurred needs emergency recovery or receiving manual triggering signals,
+- determining whether or not the accident occurred needs emergency recovery,
+- receiving information about, or determining, the vehicle location,
+- sending minimum set of data (MSD) which is related to the accident, and
+- providing bidirectional voice communication.
+
+**3.1.2 automotive emergency response centre (AERC)** [ITU-T Y.4119]: A centre managed by a public authority or a private organization, responsible for:
+
+- answering each automotive emergency response request,
+- confirming whether or not the accident occurred, and
+
+- notifying the emergency authority (EA) if EA dispatch is necessary.
+
+NOTE – Considering the features of aftermarket devices, AERC is equipped with false alarms filtering functions.
+
+**3.1.3 minimum set of data (MSD)** [ITU-T Y.4119]: Data related to the accident sent from an automotive emergency detection device (AEDD) to an automotive emergency response centre (AERC).
+
+### **3.2 Terms defined in this Recommendation**
+
+None.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|------|---------------------------------------|
+| ACK | Acknowledgement |
+| AEDD | Automotive Emergency Detection Device |
+| AERC | Automotive Emergency Response Centre |
+| AERS | Automotive Emergency Response System |
+| CoAP | Constrained Application Protocol |
+| CON | Confirmable |
+| EA | Emergency Authority |
+| GNSS | Global Navigation Satellite System |
+| MSD | Minimum Set of Data |
+
+# **5 Conventions**
+
+None
+
+# **6 Overview of MSD transfer protocol**
+
+## **6.1 Overview of automotive emergency response system**
+
+An automotive emergency response system (AERS) reports automobile accidents to an automotive emergency response centre (AERC) by an automotive emergency detection device (AEDD) using vehicle sensors of the automobile and/or internal sensors installed on aftermarket devices such as the navigation system, dash cam, smartphone, etc. In the event of a serious road accident, the AEDD in the vehicle automatically connects to the AERC and transmits a minimum set of data (MSD), which is a set of information relating to the accident, to the emergency authority (EA) [ITU-T Y.4119].
+
+MSD transfer protocol defines the operations for sending an MSD from an AEDD to an AERC in order to request or cancel EA dispatch. Figure 1 shows the scope of MSD transfer protocol.
+
+
+
+Figure 1 – Scope of MSD transfer protocol. This diagram illustrates the system architecture for MSD transfer. A vehicle is shown with 'Vehicle sensors' and 'Internal sensors' connected to an 'AEDD' (Automobile Event Detection and Diagnosis) unit. A 'GNSS' (Global Navigation Satellite System) satellite is connected to the AEDD. The AEDD is connected to an 'AERC' (Automobile Event Reporting Center) via the 'MSD transfer protocol' (indicated by a red box and dashed line). The AERC is also connected to a 'Legacy system' and an 'EA' (Event Analysis) unit. A legend at the bottom indicates that dashed lines represent 'Voice (out of scope)' and solid lines represent 'Data'. The reference 'Y.4468(20)\_F01' is located at the bottom right.
+
+**Figure 1 – Scope of MSD transfer protocol**
+
+## 6.2 Overview of message structure
+
+MSD transfer operates over the constrained application layer protocol (CoAP) [IETF RFC 7252]. CoAP provides a request-response interaction between an AEDD and an AERC in order to report or cancel automobile accidents. Since CoAP is designed to support constrained devices with relatively small amounts of header size and low power consumption, it is suitable for AEDD operations such as the navigation system, dash cam, etc.
+
+Figure 2 represents a message structure for an MSD in CoAP message.
+
+
+
+Figure 2 – MSD over CoAP message structure. This diagram shows the hierarchical structure of an MSD over CoAP message. At the top, a 'CoAP message' is shown as a sequence of fields: Ver, Type, Token length, Code, Message ID, Token, and Payload marker. Below this, the 'CoAP message' is expanded into a 'Header' and a 'Payload'. The 'Header' is further expanded into an 'MSD' (Message Structure Definition) which consists of the following fields: MSD OID, MSD Ver, Message ID, Time stamp, ..., Cancel request, ..., VIN, Vehicle location, and ... The reference 'Y.4468(20)\_F02' is located at the bottom right.
+
+**Figure 2 – MSD over CoAP message structure**
+
+# 7 MSD transfer message types
+
+### 7.1 Request messages
+
+### 7.1.1 MSD notification message
+
+Figure 3 shows the *MSD notification message*. The message starts with a fixed-size 9-byte CoAP header including a 2-bit confirmable (CON) message type for transmission reliability, a 1-byte POST code, a 2-byte message ID for detecting message duplication, and an arbitrary 4-byte token used to match with response messages returned by AERC. The header is followed by an MSD as a message payload.
+
+
+
+| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
+|-------|----------------|---|------|---|--------------|---|---|---|
+| Byte | Ver | | Type | | Token length | | | |
+| 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |
+| | Code | | | | | | | |
+| 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
+| | Message ID | | | | | | | |
+| 3, 4 | (2 bytes) | | | | | | | |
+| | Token | | | | | | | |
+| 5 ~ 8 | (4 bytes) | | | | | | | |
+| | Payload marker | | | | | | | |
+| 9 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
+| 10 | MSD | | | | | | | |
+| : | | | | | | | | |
+
+**CoAP header**
+ Type = CON (0)
+ Code = POST (0.02)
+
+} Payload
+
+Y.4468(20)\_F03
+
+**Figure 3 – MSD notification message**
+
+#### 7.1.2 MSD cancellation message
+
+Figure 4 shows the *MSD cancellation message*. The message starts with a fixed-size 9-byte CoAP header including a 2-bit CON message type for transmission reliability, a 1-byte POST code, a 2-byte message ID for detecting message duplication, and an arbitrary 4-byte token used to match with response messages returned by AERC. The header is followed by an MSD with *Cancel Request* [ITU-T Y.4467] changed to *True* as a message payload.
+
+
+
+| Byte | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
+|-------|--------------------------------|---|------|---|--------------|---|---|---|
+| | Ver | | Type | | Token length | | | |
+| 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |
+| | Code | | | | | | | |
+| 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
+| | Message ID | | | | | | | |
+| 3, 4 | (2 bytes) | | | | | | | |
+| | Token | | | | | | | |
+| 5 ~ 8 | (4 bytes) | | | | | | | |
+| | Payload marker | | | | | | | |
+| 9 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
+| 10 | MSD
(Cancel request = True) | | | | | | | |
+| : | | | | | | | | |
+
+**CoAP header**
+ Type = CON (0)
+ Code = POST (0.02)
+
+Payload
+
+Y.4468(20)\_F04
+
+**Figure 4 – MSD cancellation message**
+
+### 7.2 Response messages
+
+### 7.2.1 Acknowledgement (ACK) response message
+
+Figure 5 shows the *ACK response message*. The message has a fixed-size 8-byte CoAP header including a 2-bit ACK type for notifying the successful reception of the message, a 1-byte response code for indicating success or failure of MSD processing result, and a 4-byte token used to match with request messages from AEDD.
+
+
+
+| Byte | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
+|-------|-----------------|---|------|---|------------------|---|---|---|
+| | Ver | | Type | | Token length | | | |
+| 1 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 |
+| | Code | | | | | | | |
+| 2 | Class (3 - bit) | | | | Detail (5 - bit) | | | |
+| | Message ID | | | | | | | |
+| 3, 4 | (2 bytes) | | | | | | | |
+| | Token | | | | | | | |
+| 5 ~ 8 | (4 bytes) | | | | | | | |
+
+**CoAP header**
+ Type = ACK (2)
+ Code = Success (2.01),
+ client error (4.00 or 4.04),
+ server error (5.00)
+
+Y.4468(20)\_F05
+
+**Figure 5 – ACK response message**
+
+### 7.2.2 Empty ACK message
+
+Figure 6 shows the *Empty ACK message*. The message has a fixed-size 4-byte CoAP header including a 2-bit ACK type for notifying the successful reception of the message, and an empty message code without any token.
+
+
+
+| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
+|------|------------|---|------|---|--------------|---|---|---|
+| Byte | Ver | | Type | | Token length | | | |
+| 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
+| | Code | | | | | | | |
+| 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
+| | Message ID | | | | | | | |
+| 3, 4 | (2 bytes) | | | | | | | |
+
+Y.4468(20)\_F06
+
+**CoAP header**
+Type = ACK (2)
+Code = Empty message (0.00)
+
+Figure 6 – Empty ACK message
+
+### 7.2.3 Confirmable response message
+
+Figure 7 shows the *Confirmable response message*. The message has a fixed-size 8-byte CoAP header including a 2-bit confirmable message type for transmission reliability, a 1-byte response code for indicating success or failure of MSD processing result, and a 4-byte token used to match with request messages from AEDD.
+
+
+
+| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
+|-------|-----------------|---|------|------------------|--------------|---|---|---|
+| Byte | Ver | | Type | | Token length | | | |
+| 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |
+| | Code | | | | | | | |
+| 2 | Class (3 - bit) | | | Detail (5 - bit) | | | | |
+| | Message ID | | | | | | | |
+| 3, 4 | (2 bytes) | | | | | | | |
+| | Token | | | | | | | |
+| 5 ~ 8 | (4 bytes) | | | | | | | |
+
+Y.4468(20)\_F07
+
+**CoAP header**
+Type = CON (0)
+Code = Success (2.01),
+client error (4.00 or 4.04),
+server error (5.00)
+
+Figure 7 – Confirmable response message
+
+#### 7.2.4 AERC response code
+
+Table 1 describes the AERC response codes used when a message is received.
+
+**Table 1 – AERC response code in CoAP**
+
+| Code | | Description |
+|-------|--------|----------------------------------------------------------------------------------------------------------------------------------------------|
+| Class | Detail | |
+| 2 | 01 | Created
Successfully received MSD send message or cancellation request message |
+| 4 | 00 | Bad request
An unrecognized message type, an error in the message structure or exceeding the maximum message length of receiving messages |
+| | 04 | Not found
Non-existence of MSD send message corresponding to receiving cancellation request message |
+| 5 | 00 | Internal server error
Unable to process receiving message due to unexpected AERC internal problems |
+
+# **8 MSD transfer protocol operation**
+
+## **8.1 Request-response operation**
+
+Figure 8 describes the sequence of *MSD notification message* and *MSD cancellation message* transfer.
+
+
+
+```
+
+sequenceDiagram
+ participant AEDD
+ participant AERC
+
+ Note over AEDD: 1. Accident detection ?
+(See Annex A and B)
+ AEDD-->>AEDD: No
+ AEDD-->>AEDD: Yes
+ Note over AEDD: 2. Generate MSD
+ AEDD->>AERC: 3. MSD notification message (See Figure 3)
+[Header | Payload]
+ Note over AERC: 4. [MSD processing delay
+≥ ACK_TIMEOUT] ?
+ AERC-->>AERC: Yes
+ AERC-->>AEDD: 5. ACK response message (See Figure 5)
+[Header]
+ Note over AERC: Piggybacked response
+ AERC-->>AERC: No
+ AERC-->>AEDD: 6. Empty ACK message (See Figure 6)
+[Header]
+ Note over AERC: Separate response
+ AEDD-->>AEDD: ~
+ AEDD-->>AERC: 7. Confirmable response message (See Figure 7)
+[Header]
+ AEDD-->>AEDD: ~
+ AEDD-->>AERC: 8. Empty ACK message (See Figure 6)
+[Header]
+ AEDD-->>AEDD: ~
+ AEDD-->>AEDD: 9. Receive ACK
+ Note over AEDD: 10. Cancellation request?
+(See Annex A)
+ AEDD-->>AEDD: No
+ AEDD-->>AEDD: End
+ AEDD-->>AEDD: Yes
+ AEDD->>AERC: 11. MSD cancellation message (See Figure 4)
+[Header | Payload]
+ AERC-->>AEDD: [Header]
+
+```
+
+Sequence diagram showing the request-response operation between AEDD and AERC. The process starts with AEDD checking for accident detection. If yes, it generates an MSD and sends it to AERC. AERC then checks if the MSD processing delay is greater than or equal to ACK\_TIMEOUT. If yes, it sends a piggybacked response (ACK response message). If no, it sends a separate response (Empty ACK message). AEDD receives the ACK and checks for a cancellation request. If yes, it sends an MSD cancellation message to AERC, which then sends back an ACK response message. If no, the process ends.
+
+Y.4468(20)\_F08
+
+**Figure 8 – Sequence of request-response operation between AEDD and AERC**
+
+(Steps 1 – 3) In case of accident detection, an AEDD generates an MSD and repeatedly transmits an *MSD notification message* including an arbitrary token to an AERC until an *ACK response message* or an *Empty ACK message* is received.
+
+(Step 4) The AERC decides the piggybacked response when it does not need longer time to obtain the response code of the AEDD request than *ACK\_TIMEOUT* predefined by the AERC (Step 5). Otherwise, the AERC chooses the separate response (Step 6 – 8).
+
+(Steps 5 – 9) The AERC sends back an *ACK response message* with both the response code issued by the AERC and the received token to the AEDD.
+
+(Steps 6 – 9) Once the AERC immediately sends back an *Empty ACK message*. When the AERC finally has issued the response code, it transmits a *Confirmable response message* with received token to the AEDD. And then, the AEDD sends back an *Empty ACK message* to the AERC.
+
+(Steps 10 – 11) In case of cancellation request is triggered, the AEDD transmits an *MSD cancellation message* to the AERC repeatedly until an *ACK response message* or an *Empty ACK message* is received (Go to Step 4). Otherwise, the AEDD terminates this operation.
+
+NOTE – The AEDD could consider that transmits the MSD to another AERC if there is no response from the AERC.
+
+## 8.2 Retransmission
+
+Every ACK\_TIMEOUT [IETF RFC 7252] seconds, the AEDD is required to repeatedly retransmit the *MSD notification message* or the *MSD cancellation message* to the AERC until the *ACK response message* or the *Empty ACK message* is received.
+
+Table 2 shows the parameters for retransmitting messages.
+
+**Table 2 – Retransmission parameters in CoAP**
+
+| Name | Value | Description |
+|-------------------|----------|----------------------------------------------------|
+| ACK_TIMEOUT | 1 | MSD retransmission time interval |
+| ACK_RANDOM_FACTOR | 1.0 | MSD retransmission random counter increment factor |
+| MAX_RETRANSMIT | Infinity | Maximum number of retransmitted MSDs |
+
+# 9 Security considerations
+
+As the MSD transfer protocol realizes a subset of the features in CoAP [IETF RFC 7252], the security mechanism should support the security considerations in clause 11 of [IETF RFC 7252].
+
+## Annex A
+
+### AEDD operation procedure
+
+(This annex forms an integral part of this Recommendation.)
+
+### A.1 AEDD operation procedure
+
+Figure A.1 shows the flow of the AEDD operation procedure. In case of accident detection, an AEDD sends an *MSD notification message* to an AERC. If the accident detection event frequency, which means the number of accident detection events during $T$ (s), is equal to or smaller than $F$ (Hz), then the AEDD goes to the automatic cancellation determination procedure described in Figure A.2.
+
+
+
+```
+graph TD
+ Start([Start AEDD]) --> Receive[/Receive sensor data/]
+ Receive --> Vehicle{Vehicle sensor data?}
+ Vehicle -- Yes --> UseVehicle[Use vehicle sensor]
+ Vehicle -- No --> UseInternal[Use internal sensor]
+ UseVehicle --> NoteB[NOTE - See Annex B]
+ UseInternal --> NoteB
+ NoteB --> Accident{Accident detection?}
+ Accident -- No --> Receive
+ Accident -- Yes --> Frequency{ *Event frequency ≤ F }
+ Frequency -- No --> SendMSD[Send MSD notification message]
+ SendMSD --> Manual{Manual cancellation}
+ Manual -- No --> SendMSD
+ Manual -- Yes --> SendCancellation[Send MSD cancellation message]
+ Frequency -- Yes --> AutoCancel[Automatic cancellation determination]
+ AutoCancel --> AutoCancelCheck{Automatic cancellation?}
+ AutoCancelCheck -- No --> Receive
+ AutoCancelCheck -- Yes --> SendCancellation
+ SendCancellation --> Frequency
+```
+
+\* Event frequency = The number of accident detections during $T$ (sec)
+
+Y.4468(20)\_FA.1
+
+Flowchart of the AEDD operation procedure.
+
+Figure A.1 – Flow of AEDD operation procedure
+
+### A.2 Automatic cancellation determination procedure
+
+Figure A.2 shows the flow of an automatic cancellation determination procedure. In the process, an AEDD measures automotive velocity during $T$ (sec) based on the global navigation satellite system (GNSS) or vehicle sensors in an automobile. If the minimum velocity during $T$ (s) is larger than the predetermined $V$ (km/h), the AEDD automatically transmits an *MSD cancellation message* to the AERC.
+
+
+
+```
+
+graph TD
+ Start([Start automatic
+cancellation determination]) --> D1{Measure velocity
+based on GNSS receiver?}
+ D1 -- Yes --> U1[Use
+GNSS receiver]
+ D1 -- No --> D2{Measure velocity
+based on vehicle sensor?}
+ D2 -- Yes --> U2[Use
+vehicle sensor]
+ D2 -- No --> End([End automatic
+cancellation determination])
+ U1 --> D3{Minimum velocity during
+T (sec) > V (km/h)}
+ U2 --> D3
+ D3 -- No --> C1[Cancel request =
+False]
+ D3 -- Yes --> C2[Cancel request =
+True]
+ C1 --> End
+ C2 --> End
+
+```
+
+The flowchart illustrates the procedure for automatic cancellation determination. It begins with a start node, leading to a decision diamond: "Measure velocity based on GNSS receiver?". If the answer is "Yes", the process moves to a rectangular box "Use GNSS receiver". If "No", it moves to another decision diamond: "Measure velocity based on vehicle sensor?". If this second decision is "Yes", it moves to a rectangular box "Use vehicle sensor". If "No", it bypasses the sensor use and proceeds directly to the final "End automatic cancellation determination" node. Both "Use GNSS receiver" and "Use vehicle sensor" boxes lead to a third decision diamond: "Minimum velocity during T (sec) > V (km/h)". If the answer to this diamond is "No", the process moves to a rectangular box "Cancel request = False". If the answer is "Yes", it moves to a rectangular box "Cancel request = True". Both of these boxes lead to the final "End automatic cancellation determination" node.
+
+Flowchart of automatic cancellation determination procedure
+
+Y.4468(20)\_FA.2
+
+**Figure A.2 – Flow of automatic cancellation determination procedure**
+
+## Annex B
+
+### Accident detection procedures
+
+(This annex forms an integral part of this Recommendation.)
+
+### B.1 Collision detection
+
+Figure B.1 shows the flow of a collision detection procedure. An AEDD determines collision detection according to the received acceleration data as well as a collision detection threshold predefined by itself. If a cancellation request is triggered on condition of collision detection, then the AEDD sets the threshold as the detected acceleration data.
+
+
+
+```
+graph TD; Start([Start collision detection procedure]) --> Receive[/Receive acceleration data/]; Receive --> Detect{Collision detection?}; Detect -- No --> Receive; Detect -- Yes --> Cancel{Cancellation request?}; Cancel -- No --> Detect; Cancel -- Yes --> Set[Set threshold, as detected acceleration data]; Set --> Receive;
+```
+
+The flowchart illustrates the collision detection procedure. It begins with an oval 'Start collision detection procedure' leading to a parallelogram 'Receive acceleration data'. This leads to a diamond decision 'Collision detection?'. If 'No', the flow loops back to 'Receive acceleration data'. If 'Yes', it proceeds to another diamond decision 'Cancellation request?'. If 'No', it loops back to 'Collision detection?'. If 'Yes', it leads to a rectangle 'Set threshold, as detected acceleration data', which then loops back to 'Receive acceleration data'.
+
+Flowchart of the collision detection procedure.
+
+Y.4468(20)\_FB.1
+
+**Figure B.1 – Flow of collision detection procedure**
+
+### B.2 Spin off detection
+
+Figure B.2 shows the flow of a spin off detection procedure. An AEDD determines spin off detection according to the received Yaw rate as well as a spin off detection threshold predefined by itself. If a cancellation request is triggered on condition of spin off detection, then the AEDD set the threshold as the detected Yaw rate.
+
+
+
+```
+
+graph TD
+ Start([Start spin off
+detection procedure]) --> Receive[/Receive
+Yaw rate data/]
+ Receive --> Detect{Spin off
+detection?}
+ Detect -- No --> Receive
+ Detect -- Yes --> Cancel{Cancellation
+request?}
+ Cancel -- No --> Detect
+ Cancel -- Yes --> SetThreshold[Set threshold, as
+detected Yaw rate]
+ SetThreshold --> Detect
+
+```
+
+Y.4468(20)\_FB.2
+
+Flowchart of spin off detection procedure
+
+**Figure B.2 – Flow of spin off detection procedure**
+
+### B.3 Rollover or capsizing detection
+
+Figure B.3 shows the flow of a rollover or capsizing detection procedure. An AEDD determines rollover or capsizing detection according to the received roll and pitch angles as well as a rollover or capsizing detection threshold predefined by itself. If a cancellation request is triggered on condition of rollover or capsizing detection, then the AEDD sets the threshold as the detected roll and pitch angles.
+
+
+
+```
+
+graph TD
+ Start([Start rollover and
+capsizing detection
+procedure]) --> Calibrate[Calibrate Pitch
+and Roll axes]
+ Calibrate --> Receive[/Receive Roll and
+Pitch angle data/]
+ Receive --> Detect{Rollover and
+capsizing detection?}
+ Detect -- No --> Receive
+ Detect -- Yes --> Cancel{Cancellation
+request?}
+ Cancel -- No --> Detect
+ Cancel -- Yes --> SetThreshold[Set threshold, as
+detected Pitch and
+Roll angle]
+ SetThreshold --> Detect
+
+```
+
+Y.4468(20)\_FB.3
+
+Flowchart of rollover or capsizing detection procedure
+
+**Figure B.3 – Flow of rollover or capsizing detection procedure**
+
+### B.4 Abnormal wheel speed detection
+
+Figure B.4 shows the flow of an abnormal wheel speed detection procedure. An abnormal wheel speed is found by comparing a target wheel's speed with an average wheel speed of other wheels. An AEDD determines abnormal wheel speed detection according to the received abnormal rate of wheel speed as well as an abnormal wheel speed detection threshold predefined by itself. If a cancellation request is triggered on condition of abnormal wheel speed detection, then the AEDD set the threshold as the detected abnormal rate of wheel speed.
+
+
+
+```
+
+graph TD
+ Start([Start abnormal wheel speed detection procedure]) --> Receive[/Receive wheel speed data/]
+ Receive --> Measure[Measure abnormal rate of wheel speed]
+ Measure --> Detect{Abnormal wheel speed detection?}
+ Detect -- No --> Receive
+ Detect -- Yes --> Cancellation{Cancellation request?}
+ Cancellation -- No --> Detect
+ Cancellation -- Yes --> SetThreshold[Set threshold, as measured abnormal rate of wheel speed]
+ SetThreshold --> Detect
+
+```
+
+The flowchart illustrates the process of detecting abnormal wheel speed. It begins with a start terminal 'Start abnormal wheel speed detection procedure'. This leads to an input block 'Receive wheel speed data', followed by a process block 'Measure abnormal rate of wheel speed'. A decision diamond 'Abnormal wheel speed detection?' follows; if 'No', the flow returns to 'Receive wheel speed data'. If 'Yes', it proceeds to another decision diamond 'Cancellation request?'. If 'No' to the cancellation request, the flow returns to the 'Abnormal wheel speed detection?' decision. If 'Yes', it proceeds to a process block 'Set threshold, as measured abnormal rate of wheel speed', which then also loops back to the 'Abnormal wheel speed detection?' decision.
+
+Flowchart of the abnormal wheel speed detection procedure.
+
+Y.4468(20)\_FB.4
+
+**Figure B.4 – Flow of abnormal wheel speed detection procedure**
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation**ITU-T Y.4486 (03/2023)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Internet of things and smart cities and communities –
+Frameworks, architectures and protocols
+
+---
+
+**Framework of cross edge decentralized service
+by using digital ledger technology and edge
+computing technologies for Internet of things
+devices**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Computing power networks | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+Y.3000–Y.3499
+
+### CLOUD COMPUTING
+
+Y.3500–Y.3599
+
+### BIG DATA
+
+Y.3600–Y.3799
+
+### QUANTUM KEY DISTRIBUTION NETWORKS
+
+Y.3800–Y.3999
+
+### INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|----------------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4486
+
+# Framework of cross edge decentralized service by using digital ledger technology and edge computing technologies for Internet of things devices
+
+## Summary
+
+Decentralized services such as distributed ledger technology (DLT) service for Internet of things (IoT) devices are usually deployed in local area networks (LANs) or in core clouds. When only deployed in LANs, the decentralized services may be affected by the limited capabilities of storage, computation and communication of IoT devices. When only deployed in core clouds, the decentralized services may be affected by the communication capabilities between the IoT devices in LANs and the peers in core clouds. With the popularization of the use of edge computing, parts or all of functionalities of the decentralized services can be deployed in edge clouds.
+
+Recommendation ITU-T Y.4486 introduces a cross edge decentralized service (CEDS) by using DLT and edge computing technologies, which supports seamless cross edge DLT services for IoT devices (fixed and mobile) by using DLT and edge computing technologies. The CEDS can take the advantages of edge computing to speed up the service efficiency of DLT services for IoT devices. In addition, the CEDS provides adaptive service management to match the dynamic changes of IoT devices.
+
+This Recommendation provides relevant general characteristics and requirements of the decentralized service by using DLT and edge computing technologies, and also provides its functional framework, common capabilities and general procedures.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.4486 | 2023-03-28 | 20 | 11.1002/1000/15485 |
+
+## Keywords
+
+Decentralized service, distributed ledger technology (DLT), edge computing, framework, Internet of things (IoT).
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2023
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|----|-------------------------------------------------------------------------------------------------------------------------------------|------|
+| 1 | Scope ..... | 1 |
+| 2 | References ..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere ..... | 1 |
+| | 3.2 Terms defined in this Recommendation ..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 3 |
+| 5 | Conventions ..... | 4 |
+| 6 | Introduction of the cross edge decentralized service by using DLT and edge computing technologies ..... | 4 |
+| 7 | General characteristics and requirements of the cross edge decentralized service by using DLT and edge computing technologies ..... | 5 |
+| | 7.1 General characteristics ..... | 5 |
+| | 7.2 General requirements ..... | 6 |
+| 8 | Functional framework of the cross edge decentralized service by using DLT and edge computing technologies ..... | 7 |
+| | 8.1 Functional components of core CEDS ..... | 9 |
+| | 8.2 Functional components of edge CEDS ..... | 11 |
+| | 8.3 External entities ..... | 14 |
+| | 8.4 Reference points ..... | 14 |
+| 9 | General procedures of the cross edge decentralized service by using DLT and edge computing technologies ..... | 15 |
+| | 9.1 Synchronization of data and service of DLT services between core cloud and edge cloud ..... | 15 |
+| | 9.2 Migration of data and service of DLT services between edge clouds ..... | 16 |
+| 10 | Security considerations ..... | 18 |
+| | Appendix I – Use case of the cross edge decentralized service for IoT devices by using DLT and edge computing technologies ..... | 19 |
+| | I.1 Cross edge traffic information sharing of Internet of vehicles enhanced by CEDS ..... | 19 |
+| | Bibliography ..... | 21 |
+
+
+
+# Recommendation ITU-T Y.4486
+
+# Framework of cross edge decentralized service by using digital ledger technology and edge computing technologies for Internet of things devices
+
+# 1 Scope
+
+This Recommendation introduces a cross edge decentralized service (CEDS) by using decentralized ledger technology (DLT) and edge computing technologies for IoT devices, and provides relevant general characteristics and requirements, a functional framework, common functionalities and general procedures.
+
+The scope of this Recommendation includes:
+
+- Introduction of the cross edge decentralized service by using DLT and edge computing technologies;
+- General characteristics and requirements of the cross edge decentralized service by using DLT and edge computing technologies;
+- Functional framework, common functionalities and general procedures of the cross edge decentralized service by using DLT and edge computing technologies.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T Y.4000] Recommendation ITU-T Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+
+# 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 application** [b-ITU-T Y.2091]: A structured set of capabilities, which provide value-added functionality supported by one or more services, which may be supported by an API interface.
+
+**3.1.2 core cloud** [b-ITU-T Y.3508]: A cloud computing, which manages resource pools including resources in the edge of the network and enables cloud service.
+
+NOTE – Enabled cloud service on the core cloud is provided by a cloud service provider (CSP).
+
+**3.1.3 decentralized system** [b-ITU-T X.1400]: Distributed system wherein control is distributed among the persons or organizations participating in the operation of system.
+
+**3.1.4 device** [ITU-T Y.4000]: With regard to the Internet of things, this is a piece of equipment with the mandatory capabilities of communication and the optional capabilities of sensing, actuation, data capture, data storage and data processing.
+
+**3.1.5 distributed ledger** [b-ITU-T X.1400]: A type of ledger that is shared, replicated, and synchronized in a distributed and decentralized manner.
+
+**3.1.6 distributed ledger technology (DLT)** [b-ITU-T X.1400]: Technology that enables the operation and use of distributed ledgers.
+
+**3.1.7 distributed ledger technology client (DLT client)** [b-ITU-T X.1409]: A client to access the distributed ledger technology system.
+
+**3.1.8 distributed ledger technology system (DLT system)** [b-ITU-T X.1400]: A system that implements a distributed ledger.
+
+**3.1.9 edge cloud** [b-ITU-T Y.3508]: A cloud computing deployed to the edge of the network accessed by cloud service customers (CSCs) with small capacity resources enabling cloud service.
+
+NOTE 1 – Enabled cloud service on the edge cloud is lightweight cloud service provided by a cloud service provider (CSP) depending on cloud service category.
+
+NOTE 2 – Lightweight cloud service refers to a portion of cloud service to reconfigure the functionality of cloud service to fit on edge cloud such as base station and gateway with small capacity resource.
+
+**3.1.10 edge computing** [b-ITU-T Y.3073]: This refers to a strategy to deploy processing capability at network edge where end terminals are connected, and to perform the processing of data which is derived from and fed to the end terminals.
+
+**3.1.11 Internet of things (IoT)** [ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on, existing and evolving, interoperable information and communication technologies.
+
+NOTE 1 – Through the exploitation of identification, data capture, processing and communication capabilities, the IoT makes full use of things to offer services to all kinds of applications, whilst ensuring that security and privacy requirements are fulfilled.
+
+NOTE 2 – In a broad perspective, the IoT can be perceived as a vision with technological and societal implications.
+
+**3.1.12 ledger** [b-ITU-T X.1400]: Information store that keeps final and definitive (immutable) records of transactions.
+
+**3.1.13 multi-access edge computing (MEC)** [b-ITU-T J.1303]: System which provides an IT service environment and cloud-computing capabilities at the edge of an access network that contains one or more types of access technology, and in close proximity to its users.
+
+**3.1.14 mobility** [b-ITU-T Q.1743]: The ability for the user to communicate whilst moving independent of location.
+
+**3.1.15 node** [b-ITU-T X.1400]: Device or process that participates in a distributed ledger network.
+
+NOTE – A node can store a complete or partial replica of the distributed ledger.
+
+**3.1.16 peer** [b-ITU-T X.1161]: Communication node on peer-to-peer (P2P) network that functions simultaneously as both "client" and "server" to the other nodes on the network.
+
+**3.1.17 service** [b-ITU-T Y.2091]: A set of functions and facilities offered to a user by a provider.
+
+**3.1.18 thing** [ITU-T Y.4000]: With regard to the Internet of things, this is an object of the physical world (physical things) or of the information world (virtual things), which is capable of being identified and integrated into the communication networks.
+
+### **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following terms:
+
+**3.2.1 distributed ledger technology service (DLT service)**: A decentralized service provided by a distributed ledger technology (DLT) system.
+
+NOTE – DLT system can be deployed in core clouds and/or edge clouds.
+
+**3.2.2 cross edge distributed ledger technology service** (cross edge DLT service): A distributed ledger technology (DLT) service for Internet of things (IoT) devices enabled by edge computing technologies, in which the IoT devices can get seamless service wherever they are roaming in different edge clouds.
+
+NOTE 1 – A cross edge DLT service is performed by multiple DLT systems as deployed in related edge clouds and core clouds, and those DLT systems collaborate to provide the service for IoT devices.
+
+NOTE 2 – A cross edge DLT service needs to interact with entities in edge clouds to follow mobility information (such as location) of the connected IoT devices in order to provide seamless service when the IoT devices are roaming in different edge clouds.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|--------|---------------------------------------------------|
+| CCA-FC | Core-Core Agent Functional Component |
+| CDA-FC | Core-DLT Agent Functional Component |
+| CDM-FC | Core Data Migration Functional Component |
+| CDS-FC | Core Data Synchronization Functional Component |
+| CEA-FC | Core-Edge Agent Functional Component |
+| CEDS | Cross Edge Decentralized Service |
+| CSC | Cloud Service Customer |
+| CSM-FC | Core Service Management Functional Component |
+| CSP | Cloud Service Provider |
+| CSS-FC | Core Service Synchronization Functional Component |
+| CVM-FC | Core service Migration Functional Component |
+| DLT | Distributed Ledger Technology |
+| ECA-FC | Edge-Core Agent Functional Component |
+| EDA-FC | Edge-DLT Agent Functional Component |
+| EDM-FC | Edge Data Migration Functional Component |
+| EDS-FC | Edge Data Synchronization Functional Component |
+| EEA-FC | Edge-Edge Agent Functional Component |
+| EMA-FC | Edge-MEC Agent Functional Component |
+| ESM-FC | Edge Service Management Functional Component |
+| ESS-FC | Edge Service Synchronization Functional Component |
+| EVM-FC | Edge service Migration Functional Component |
+| FC | Functional Component |
+| IoT | Internet of Things |
+| IoV | Internet of Vehicles |
+| MEC | Multi-access Edge Computing |
+| P2P | Peer-to-Peer |
+| PII | Personally Identifiable Information |
+
+# 5 Conventions
+
+The following conventions are used in this Recommendation:
+
+- The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted, if conformance to this Recommendation is to be claimed.
+- The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+
+# 6 Introduction of the cross edge decentralized service by using DLT and edge computing technologies
+
+Decentralized services such as distributed ledger technology (DLT) services for Internet of things (IoT) devices are usually deployed in local area networks (LANs) or in core clouds. When only deployed in LANs, the decentralized services may be affected by the limited capabilities of storage, computation and communication of IoT devices. When only deployed in core clouds, the decentralized services may be affected by the communication capabilities between the IoT devices in LANs and the peers in core clouds.
+
+Typically, edge clouds are deployed in the edge of communication networks, which provide services only for IoT devices in specific areas. Decentralized services can be deployed in edge clouds. In general, storage volume and computation capabilities of an edge cloud are limited. Therefore, generally, a decentralized service deployed in edge cloud can only provide part of functionalities, and can only serve part of IoT devices in specific areas.
+
+The cross edge decentralized service (CEDS) is one type of decentralized service, which provides seamless cross edge DLT services for IoT devices (fixed and mobile) by using DLT and edge computing technologies. A CEDS consists of one part in a core cloud (core CEDS) and multiple corresponding parts in edge clouds (edge CEDSs) (see Figure 6-1). Each part of a CEDS supports all or parts of functionalities of DLT services and collaborates with other parts to perform seamless cross edge DLT services for IoT devices.
+
+In a CEDS, the core CEDS and multiple corresponding edge CEDSs include DLT systems (core DLT systems and corresponding edge DLT systems) respectively. The DLT systems of an edge CEDS, collaborating with the core CEDS and relevant core DLT systems, provide DLT services to IoT devices as connected to the edge cloud. Due to limited capabilities of storage and computation of edge clouds, full data of DLT services for IoT devices usually are stored in core CEDS and relevant core DLT systems, and the corresponding edge CEDSs and relevant edge DLT systems only store necessary and new data of DLT services of the connected IoT devices.
+
+With the supports of CEDS, when an IoT device is roaming from one edge cloud to another edge cloud, related DLT services can be migrated to the target edge cloud simultaneously and seamlessly.
+
+The CEDS can take the advantages of edge computing to speed up the service efficiency of DLT services for IoT devices. In addition, the CEDS provides adaptive service management to match the dynamic changes of IoT devices. When an IoT device accesses to a DLT service, the CEDS performs synchronization of data and services of the DLT service from corresponding core clouds, and provides the DLT service to IoT devices in edge clouds. In addition, when an IoT device moves from a LAN to another one which is served by different edge clouds, the CEDS can retrieve necessary information (such as mobility information) from the edge clouds and offer migration management of data and services in order to promote the DLT services for the IoT device.
+
+Therefore, the CEDS can provide capabilities, collaborating with DLT services in core clouds and those in edge clouds, to perform all the functionalities and to serve all of the IoT devices.
+
+
+
+Figure 6-1 – Overview of CEDS. The diagram illustrates a three-tier architecture. The top tier, 'Core clouds', contains 'Core CEDS (In core clouds)' represented by server icons. The middle tier, 'Edge clouds', contains 'Edge CEDSs (In edge clouds)' also represented by server icons. The bottom tier, 'Local area networks', contains 'Local DLT client (In IoT devices, IoT gateways, etc.)' represented by various IoT device icons. Dashed lines show connections between Core CEDS and Edge CEDSs, and between Edge CEDSs and Local DLT clients. A vertical blue double-headed arrow on the right indicates 'Synchronization of data and services between edge and core clouds'. A horizontal red double-headed arrow at the bottom indicates 'Migration of data and services between different edge clouds'. The reference 'Y.4486(23)' is located at the bottom right of the diagram area.
+
+**Figure 6-1 – Overview of CEDS**
+
+NOTE – CEDS can be deployed in multi-access edge computing (MEC) nodes in edge clouds, and can integrate functionalities exposed by MEC nodes, such as getting mobility information (e.g., location) of IoT devices from mobility services of MEC (see clause 8.3.1). [b-ITU-T Y.3073] and [b-ITU-T J.1303] provide more information about MEC and MEC nodes.
+
+# **7 General characteristics and requirements of the cross edge decentralized service by using DLT and edge computing technologies**
+
+### **7.1 General characteristics**
+
+This clause describes the general characteristics of CEDS.
+
+#### **7.1.1 Supporting seamless cross edge DLT services**
+
+The CEDS provides seamless cross edge DLT services. The CEDS can take the advantages of edge computing to speed up service efficiency of DLT services for IoT devices, and can overcome the challenges of capabilities limitation of storage and computation of edge clouds.
+
+In order to overcome the limited storage and computation capabilities, each of the edge CEDSs of a CEDS only serves nearby IoT devices as connected to the relevant edge cloud, and it can synchronize the data and service of DLT services for IoT devices with its corresponding core CEDS of the CEDS, if needed.
+
+The edge CEDS of a CEDS can follow the location of connected IoT devices. When an IoT device is roaming in a new edge cloud, the original edge CEDS can collaborate with the corresponding core CEDS and target edge CEDS of the CEDS to migrate the data and service of the DLT services to the target CEDS, in order to provide dynamic seamless services.
+
+#### **7.1.2 Supporting service management for IoT devices**
+
+The CEDS interacts with functional entities in edge clouds to track status (e.g., available capacity resources) of the edge clouds in order to make full use of the capabilities of edge clouds, such as dynamically managing resource consumptions of DLT services in edge clouds.
+
+The CEDS interacts with functional entities (e.g., mobility services) in edge clouds to track status information (e.g., connection status, mobility information) of connected IoT devices, in order to select an appropriate edge CEDS to provide DLT services for IoT devices.
+
+#### **7.1.3 Supporting synchronization of data and services from core clouds**
+
+Parts or all of functionalities of DLT services as usually deployed in core clouds can be deployed in edge clouds. In this case, the CEDS provides a mechanism to synchronize data and service of DLT services between its core CEDS and corresponding edge clouds, in order to keep the consistency of data and service of DLT services for IoT devices.
+
+#### **7.1.4 Providing migration management of data and services among edge clouds**
+
+The CEDS can follow mobility information (such as location) of mobile IoT devices and provide migration mechanisms to keep the consistency of data and service of DLT services for IoT devices among different edge clouds.
+
+#### **7.1.5 Data security protection and PII privacy preservation**
+
+The CEDS provides multi-level data security protection and personally identifiable information (PII) privacy preservation support to the data and service of DLT services for IoT devices. In addition, the CEDS can comply with national and regional data regulations related to the DLT services.
+
+### **7.2 General requirements**
+
+This clause provides general requirements of CEDS.
+
+#### **7.2.1 Cross edge service provision**
+
+The cross edge service provision related requirements of CEDS are as follows:
+
+- It is required to provide dynamic seamless cross edge service of DLT services for IoT devices (fixed and mobile).
+- It is recommended to provide adaptive resource mechanisms to allow DLT services to manage resource consumptions in edge clouds and in core clouds, such as resources for storage, computation and communication, etc.
+- It is recommended to allow DLT services to interact with functional entities (e.g., mobility services of communication networks) in edge clouds to track status information of IoT devices (such as, connection status, mobility information, etc.).
+- It is recommended to be compatible with different types of DLT services.
+
+#### **7.2.2 Synchronization management of data and services between edge and core clouds**
+
+The synchronization management related requirements of CEDS are as follows:
+
+- It is required to support data and service synchronization of DLT services for IoT devices between the different parts of the DLT services in core clouds and in edge clouds, if requested, according to the policy of the CEDS.
+- It is required to provide mechanisms to keep data consistent when synchronizing data and service for DLT services in core and edge clouds.
+
+#### **7.2.3 Migration management of data and services between different edge clouds**
+
+The migration management related requirements of CEDS are as follows:
+
+- It is required to support seamless service and data migration of DLT services for IoT devices, when the IoT devices are roaming in different edge clouds, if requested, according to the location of the IoT devices and policy of the CEDS.
+- It is required to provide mechanisms to keep data consistent when migrating data for DLT services in different edge clouds.
+
+#### **7.2.4 Data security protection and PII privacy preservation**
+
+The data security protection and PII privacy preservation related requirements of CEDS are as follows:
+
+- It is recommended to provide mechanisms on data security protection and PII privacy preservation when interacting with functional entities (such as mobility systems) in edge clouds.
+- It is required to provide mechanisms on data security protection and PII privacy preservation when synchronizing data and service of DLT services between core clouds and edge clouds.
+- It is required to provide mechanisms on data security protection and PII privacy preservation when migrating data and services of DLT services between edge clouds.
+- It is required to be able to comply with national and regional data regulations involved when synchronizing and migrating data and services of DLT services.
+
+## **8 Functional framework of the cross edge decentralized service by using DLT and edge computing technologies**
+
+This clause provides a functional framework and common functionalities of CEDS according to the requirements listed in clause 7.
+
+The CEDS works on the service support and application support layer of the IoT reference model specified in [ITU-T Y.4000]. Figure 8-1 is a schematic diagram of the functional framework of CEDS.
+
+
+
+The diagram illustrates the functional framework of CEDS across three layers: Core clouds, Edge clouds, and Local area networks.
+
+- Core clouds:** Contains the **Core CEDS (In core clouds)**. It includes components for Core service management, Core data synchronization, Core data migration, Core-MLT agents, Core service synchronization, Core service migration, Core-MLT systems, Core-edge agents, and Core-core agents. It also connects to **Other core CEDSs (In same or different core clouds)** via interface R5.
+- Edge clouds:** Contains **Edge CEDSs (In edge clouds)**. It includes components for Edge-MEC agents, Edge-MLT agents, Edge-MLT systems, Edge service management, Edge-core agents, Edge-edge agents, Edge data synchronization, Edge data migration, Edge service synchronization, and Edge service migration. It also connects to **Other edge CEDSs (In same or different edge clouds)** via interface R2. MEC mobility services are connected via interface R4.
+- Local area networks:** Contains **Local DLT clients (In local area networks)**. It includes components for Client location management, Client configure, and Local applications. It connects to the Edge clouds via interface R3.
+
+Interfaces R1, R2, R3, R4, and R5 represent the connections between the different layers and components. A blue arrow indicates **Synchronization of data and services between core and edge clouds**, and a red arrow indicates **Migration of data and services between different edge clouds**.
+
+Figure 8-1 – Functional framework of CEDS. The diagram illustrates the functional framework of CEDS across three layers: Core clouds, Edge clouds, and Local area networks. Core clouds contain Core CEDS (In core clouds) with components like Core service management, Core data synchronization, Core data migration, Core-MLT agents, Core service synchronization, Core service migration, Core-MLT systems, Core-edge agents, and Core-core agents. Edge clouds contain Edge CEDSs (In edge clouds) with components like Edge-MEC agents, Edge-MLT agents, Edge-MLT systems, Edge service management, Edge-core agents, Edge-edge agents, Edge data synchronization, Edge data migration, Edge service synchronization, and Edge service migration. Local area networks contain Local DLT clients (In local area networks) with components like Client location management, Client configure, and Local applications. MEC mobility services are also shown. Interactions are labeled R1, R2, R3, R4, and R5. A blue arrow indicates 'Synchronization of data and services between core and edge clouds', and a red arrow indicates 'Migration of data and services between different edge clouds'.
+
+**Figure 8-1 – Functional framework of CEDS**
+
+CEDS mainly consists of two parts, one core CEDS and multiple corresponding edge CEDSs. Each of them includes groups of logical functional components (FCs):
+
+- edge CEDS: The FCs of each edge CEDS include edge service management, edge data synchronization, edge service synchronization, edge data migration, edge service migration, groups of agents (edge-MEC agents, edge-edge agents, edge-core agents and edge-MLT agents), and edge DLT systems.
+- core CEDS: The FCs of core CEDS include core service management, core data synchronization, core service synchronization, core service migration, core data migration, and groups of agents (core-edge agents, core-core agents and core-MLT agents), and core DLT systems.
+
+Edge CEDS, in collaboration with corresponding core CEDS, provides cross edge DLT services to IoT devices. Edge CEDS interacts with local DLT clients in IoT devices. Local DLT clients in IoT devices can notify edge CEDS of location information of their host IoT devices. Additionally, edge CEDS can interact with MEC mobility services (see clause 8.3.1) to follow location-related information of connected IoT devices.
+
+Edge CEDSs and corresponding core CEDS keep synchronization of data and services when it provides cross edge DLT services to IoT devices. Additionally, edge CEDSs in the same or different edge clouds can collaborate to provide dynamic seamless cross edge DLT services to mobile IoT devices.
+
+CEDS exposes a group of reference points R1 to R5 (see clause 8.4) to facilitate internal interactions of the CEDS, and external interactions between the CEDS and other entities, such as MEC mobility services in edge clouds, and local DLT clients in LANs, etc.
+
+### **8.1 Functional components of core CEDS**
+
+#### **8.1.1 Core service management functional component (CSM-FC)**
+
+The CSM-FC of core CEDS collaborates with corresponding edge CEDSs to manage cross edge DLT services, including data, services and resources in core clouds and information of IoT devices, etc.
+
+The CSM-FC of core CEDS provides functionalities as below:
+
+- Collaborating with corresponding edge CEDSs to manage cross edge DLT services;
+- Managing the profiles and policy of synchronization and migration of cross edge DLT services;
+- Supporting data and service synchronization of cross edge DLT services with corresponding edge CEDSs;
+- Supporting data and service migration of cross edge DLT services among corresponding edge CEDSs in the same or different edge clouds;
+- Collaborating with core DLT systems to provide core part of functionalities of cross edge DLT services in core clouds;
+- Providing and managing resources (such as storage, computation, communication, etc.) for cross edge DLT services in core clouds;
+- Supporting interaction with other CEDS in the same or different core clouds.
+
+#### **8.1.2 Core data synchronization functional component (CDS-FC)**
+
+The CDS-FC of core CEDS supports data synchronization between core CEDS and corresponding edge CEDSs, according to the profiles and policy of CEDSs and relevant national and regional data regulations.
+
+The CDS-FC of core CEDS provides functionalities as below:
+
+- Collaborating with corresponding edge CEDSs (EDS-FCs, see clause 8.2.2) to synchronize data of cross edge DLT services, including:
+ - Receiving data from corresponding edge CEDSs on demand;
+ - Dispatching data to corresponding edge CEDSs on demand;
+- Collaborating with CSM-FC and core DLT systems to manage the data for synchronization of cross edge DLT services, including:
+ - Storing relevant data into core DLT systems;
+ - Retrieving relevant data from core DLT systems;
+ - Keeping relevant data consistent between core CEDS and the core DLT systems.
+
+#### **8.1.3 Core service synchronization functional component (CSS-FC)**
+
+The CSS-FC of core CEDS supports dynamic seamless service synchronization between core CEDS and corresponding edge CEDSs, according to the profiles and policy of CEDSs and relevant national and regional data regulations.
+
+The CSS-FC of core CEDS provides functionalities as below:
+
+- Collaborating with corresponding edge CEDSs (ESS-FCs, see clause 8.2.3) to synchronize dynamic and real-time service information of cross edge DLT services, including:
+ - Receiving relevant information from corresponding edge CEDSs on demand;
+ - Dispatching relevant service information to corresponding edge CEDSs on demand;
+- Collaborating with CSM-FC and core DLT systems to manage dynamic and real-time service information for synchronization of cross edge DLT services, including:
+ - Storing relevant information into core DLT systems;
+ - Retrieving relevant information from core DLT systems;
+ - Keeping relevant information consistent between core CEDS and the core DLT systems.
+
+#### **8.1.4 Core data migration functional component (CDM-FC)**
+
+The CDM-FC of core CEDS supports data migration between corresponding edge CEDSs on demand, according to the profiles and policy of CEDSs and relevant national and regional data regulations.
+
+The CDM-FC of core CEDS provides functionalities as below:
+
+- Collaborating with corresponding edge CEDSs (EDM-FCs, see clause 8.2.4) to migrate data of cross edge DLT services, including:
+ - Validating the data migration requests;
+ - Supporting the transferring of data from one corresponding edge CEDS to other corresponding edge CEDS(s) on demand;
+- Collaborating with CSM-FC and core DLT systems to manage the data for migration of cross edge DLT services, including:
+ - Storing relevant data into core DLT systems;
+ - Retrieving relevant data from core DLT systems;
+ - Keeping relevant data consistent between core CEDS and the core DLT systems.
+
+#### **8.1.5 Core service migration functional component (CVM-FC)**
+
+The CVM-FC of core CEDS supports dynamic seamless service migration between corresponding edge CEDSs on demand, according to the profiles and policy of CEDSs and relevant national and regional data regulations.
+
+The CVM-FC of core CEDS provides functionalities as below:
+
+- Collaborating with corresponding edge CEDSs (EVM-FCs, see clause 8.2.5) to migrate service of cross edge DLT services, including:
+ - Validating relevant service migration requests;
+ - Supporting the transferring of relevant information from one corresponding edge CEDS to other corresponding edge CEDSs on demand;
+- Collaborating with CVM-FC and core DLT systems to manage the dynamic service information for migration of cross edge DLT services, including:
+ - Storing relevant information into core DLT systems;
+
+- Retrieving relevant information from core DLT systems;
+- Keeping relevant information consistent between core CEDS and the core DLT systems.
+
+#### **8.1.6 Core-edge agent functional component (CEA-FC)**
+
+The CEA-FC of core CEDS, collaborating with edge core agent functional components (ECA-FCs) of corresponding edge CEDSs (see clause 8.2.7), supports interactions between core CEDS and corresponding edge CEDS on demand.
+
+The CEA-FC of core CEDS provides functionalities as below:
+
+- Supporting interactions between core CEDS and corresponding edge CEDSs for synchronization and migration of data and services of cross edge DLT services;
+- Supporting service management of data and services of cross edge DLT services.
+
+#### **8.1.7 Core-core agent functional component (CCA-FC)**
+
+The CCA-FC of core CEDS supports collaborations with the core CEDSs of other CEDSs in the same or different core clouds.
+
+NOTE – Collaborations between core CEDSs of different CEDSs in core clouds are out of scope of this Recommendation.
+
+#### **8.1.8 Core-DLT agent functional component (CDA-FC)**
+
+The CDA-FC of core CEDS supports interactions between core CEDS and core DLT systems (see clause 8.1.9) in core clouds.
+
+The CDA-FC of core CEDS provides functionalities as below:
+
+- Supporting interactions between components of core CEDS and core DLT systems for cross edge DLT systems, including management for relevant data and services;
+- Supporting the maintenance of consistent data and services of cross edge DLT services.
+
+#### **8.1.9 Core DLT system**
+
+The core DLT systems deployed in core clouds and corresponding edge DLT systems (see clause 8.2.10) under the supporting of CEDSs (core CEDS and corresponding edge CEDSs), provide cross edge DLT services for IoT devices. Core DLT systems interact with components of core CEDS by using core-DLT agent functional component (CDA-FC).
+
+NOTE – Core DLT system itself is out of scope of this Recommendation.
+
+### **8.2 Functional components of edge CEDS**
+
+#### **8.2.1 Edge service management functional component (ESM-FC)**
+
+The ESM-FC of edge CEDS collaborates with corresponding core CEDS to manages cross edge DLT services, including data, services and resources in edge clouds and information of IoT devices, etc.
+
+The ESM-FC of edge CEDS provides functionalities as below:
+
+- Collaborating with corresponding core CEDS to manage cross edge DLT services;
+- Managing the profiles and policy of synchronization and migration of cross edge DLT services;
+- Supporting data and service synchronization of cross edge DLT services with corresponding core CEDS;
+- Supporting data and service migration of cross edge DLT services among corresponding edge CEDSs in the same or different edge clouds;
+
+- Collaborating with edge DLT systems to provide edge part of functionalities of cross edge DLT services in edge clouds;
+- Providing and managing resources (such as storage, computation, communication, etc.) for cross edge DLT services in edge clouds;
+- Collaborating with multi-access edge computing (MEC) mobility services (see clause 8.3.1) in edge clouds to follow mobility information of IoT devices (such as location) for cross edge DLT services.
+
+#### **8.2.2 Edge data synchronization functional component (EDS-FC)**
+
+The EDS-FC of edge CEDS supports synchronizing data of cross edge DLT service with corresponding core CEDS for IoT devices on demand, according to the profiles and policy of CEDSs and relevant national and regional data regulations.
+
+The EDS-FC of edge CEDS provides functionalities as below:
+
+- Collaborating with corresponding core CEDS (CDS-FC, see clause 8.1.2) to synchronize data of cross edge DLT services, including:
+ - Receiving data from corresponding core CEDS on demand;
+ - Sending data to corresponding core CEDS on demand;
+- Collaborating with edge service management functional component (ESM-FC) and edge DLT systems to manage the data for synchronization of cross edge DLT services, including:
+ - Storing relevant data into edge DLT systems;
+ - Retrieving relevant data from edge DLT systems;
+ - Keeping relevant data consistent between edge CEDS and the edge DLT systems.
+
+#### **8.2.3 Edge service synchronization functional component (ESS-FC)**
+
+The ESS-FC of edge CEDS supports dynamic seamless service synchronization of cross edge DLT services with corresponding core CEDS, according to the profiles and policy of CEDSs and relevant national and regional data regulations.
+
+The ESS-FC of edge CEDS provides functionalities as below:
+
+- Collaborating with corresponding core CEDS (CSS-FC, see clause 8.1.3) to synchronize dynamic and real-time service information of cross edge DLT services, including:
+ - Receiving relevant information from corresponding core CEDS on demand;
+ - Sending relevant service information to corresponding core CEDS on demand;
+- Collaborating with ESM-FC and edge DLT systems to manage dynamic and real-time service information for synchronization of cross edge DLT services, including:
+ - Storing relevant information into edge DLT systems;
+ - Retrieving relevant information from edge DLT systems;
+ - Keeping relevant information consistent between edge CEDS and the edge DLT systems.
+
+#### **8.2.4 Edge data migration functional component (EDM-FC)**
+
+The EDM-FC of edge CEDS supports data migration of cross edge DLT services between corresponding edge CEDSs, according to the profiles and policy of CEDSs and relevant national and regional data regulations.
+
+The EDM-FC of edge CEDS provides functionalities as below:
+
+- Collaborating with corresponding edge CEDSs to migrate data of cross edge DLT services, including:
+ - Validating the data migration requests;
+ - Supporting the transferring of data from one corresponding edge CEDS to other corresponding edge CEDS(s) on demand;
+- Collaborating with ESM-FC and edge DLT systems to manage the data for migration of cross edge DLT services, including:
+ - Storing relevant data into edge DLT systems;
+ - Retrieving relevant data from edge DLT systems;
+ - Keeping relevant data consistent between edge CEDS and the edge DLT systems.
+
+#### **8.2.5 Edge service migration functional component (EVM-FC)**
+
+The EVM-FC of edge CEDS supports dynamic seamless service migration between corresponding edge CEDSs on demand, according to the profiles and policy of CEDSs and relevant national and regional data regulations.
+
+The EVM-FC of edge CEDS provides functionalities as below:
+
+- Collaborating with corresponding edge CEDSs to migrate service of cross edge DLT services, including:
+ - Validating relevant service migration requests;
+ - Supporting the transferring of relevant information from one corresponding edge CEDS to other corresponding edge CEDS(s) on demand;
+- Collaborating with ESM-FC and edge DLT systems to manage the dynamic service information for migration of cross edge DLT services, including:
+ - Storing relevant information into edge DLT systems;
+ - Retrieving relevant information from edge DLT systems;
+ - Keeping relevant information consistent between edge CEDS and the edge DLT systems.
+
+#### **8.2.6 Edge-MEC agent functional component (EMA-FC)**
+
+The EMM-FC of edge CEDS interacts with the external MEC mobility service of a communication network in an edge cloud (see clause 8.3.1), to dynamically retrieve mobility information (such as location) of IoT devices.
+
+NOTE – Edge-MEC agent and the methods to interact with MEC mobility services in edge clouds are out of scope of this Recommendation.
+
+#### **8.2.7 Edge-core agent functional component (ECA-FC)**
+
+The ECA-FC of edge CEDS, collaborating with CEA-FCs of corresponding core CEDS (see clause 8.1.6), supports interactions between edge CEDS and corresponding core CEDS on demand.
+
+The ECA-FC of edge CEDS provides functionalities as below:
+
+- Supporting interactions between edge CEDS and corresponding core CEDS for synchronization and migration of data and services of cross edge DLT services;
+
+- Supporting service management of data and service synchronization of cross edge DLT services.
+
+#### **8.2.8 Edge-edge agent functional component (EEA-FC)**
+
+The EEA-FC of edge CEDS, collaborating with other components of edge CEDS and corresponding core CEDS, supports dynamic seamless service migration between edge CEDSs on demand.
+
+The EEA-FC of edge CEDS provides functionalities as below:
+
+- Supporting the migration of data and services to target corresponding edge CEDS(s) for cross edge DLT services, dynamically and seamlessly;
+- Supporting the migration of data and services from other corresponding edge CEDS(s) for cross edge DLT services, dynamically and seamlessly;
+- Supporting service management of data and service migration of cross edge DLT services.
+
+#### **8.2.9 Edge-DLT agent functional component (EDA-FC)**
+
+The EDA-FC of edge CEDS supports interactions between edge CEDS and edge DLT systems (see clause 8.2.10) in edge clouds.
+
+The EDA-FC of edge CEDS provides functionalities as below:
+
+- Supporting interactions between components of edge CEDS and edge DLT systems for cross edge DLT systems, including management for relevant data and services;
+- Supporting the maintenance of consistent data and services of cross edge DLT services.
+
+#### **8.2.10 Edge DLT system**
+
+The edge DLT systems deployed in edge clouds and corresponding core DLT systems (see clause 8.1.9) under the supporting of CEDSs (core CEDS and edge CEDSs), provide cross edge DLT services for IoT devices. Edge DLT systems interact with components of edge CEDS by using EDA-FC.
+
+NOTE – The edge DLT system itself is out of scope of this Recommendation.
+
+### **8.3 External entities**
+
+#### **8.3.1 MEC mobility services of communication network in edge clouds**
+
+The MEC mobility services of the communication network in edge clouds provide mobility information (such as location) of IoT devices on demand.
+
+#### **8.3.2 Local DLT clients in local area networks**
+
+The local DLT clients deployed in local area networks provide cross edge DLT-related functionalities in IoT devices, such as client location management, client configure, etc.
+
+## **8.4 Reference points**
+
+The CEDS exposes a group of reference points (R1 to R5) to support interactions between its core CEDS and corresponding edge CEDSs, and interactions with other functional components and entities, including:
+
+- R1: exposed by CEA-FC of core CEDS, to support interactions with ECA-FCs of corresponding edge CEDSs for cross edge DLT services, including supports of:
+ - Service management of cross edge DLT services for IoT devices;
+ - Service and data synchronization between core CEDS and corresponding edge CEDSs;
+ - Service and data migration between corresponding edge CEDSs.
+
+- R2: exposed by EEA-FC of edge CEDS, to support service and data migration with other corresponding edge CEDS in the same or different edge clouds for cross edge DLT services for mobile IoT devices, including supports of:
+ - Service management of cross edge DLT services for IoT devices.
+ - Service and data migration between corresponding edge CEDSs.
+- R3: exposed by edge DLT systems in edge clouds, for edge CEDS to interact with local DLT clients to provides cross edge DLT services to IoT devices in local area networks.
+- R4: exposed by EMA-FC of edge CEDS, for edge CEDS to interact with MEC mobility service in edge clouds to follow mobility information of IoT devices in local area networks.
+- R5: exposed by EEA-FC of core CEDS, for core CEDS to interact with other core CEDSs in the same or different core clouds to exchange information of IoT devices for cross edge DLT services.
+
+NOTE – Reference points R3, R4 and R5 are out of scope of this Recommendation.
+
+# 9 General procedures of the cross edge decentralized service by using DLT and edge computing technologies
+
+This clause provides general procedures of CEDS.
+
+## 9.1 Synchronization of data and service of DLT services between core cloud and edge cloud
+
+This procedure shows how a given CEDS performs data and service synchronization of a cross edge DLT service for an IoT device between its core CEDS and edge CEDS.
+
+The main steps reflecting a normal situation are described below (see Figure 9-1):
+
+- Step 1* A local DLT client hosted by an IoT device in a LAN (LAN A) requests access to a DLT service provided by an edge DLT system (edge DLT system A of edge CEDS A).
+The request is sent to the edge DLT system (edge DLT system A).
+- Step 2* The edge DLT system (edge DLT system A) forwards the request to related FCs of edge CEDS (edge CEDS A).
+The edge DLT system (edge DLT system A) collaborates with the related FCs of the edge CEDS (edge CEDS A) to manage the DLT service for the local DLT client.
+- Step 3* The related FCs of the edge CEDS (edge CEDS A) negotiates with a relevant MEC mobility service in the same edge cloud (edge cloud A) to validate mobility information (such as location) of the DLT client.
+The local DLT client may be in the edge cloud (edge cloud A) already, or may be roaming in this edge cloud (edge cloud A) from other edge cloud.
+If the local DLT client is already in the same edge cloud (edge cloud A), then it goes to step 5, otherwise, it goes to step 4.
+- Step 4* If the local DLT client is roaming from other edge cloud (such as edge cloud B), and then performs the procedures of data and service migration of DLT service between the two edge clouds (see clause 9.2).
+- Step 5* The FCs of edge CEDS (edge CEDS A) sends a request to FCs of core CEDS for synchronizing data and service of the DLT service.
+- Step 6* The FCs of core CEDS collaborate with related core DLT system to manage the DLT service inside of the core cloud.
+If not accepted by the core CEDS, it goes step 9 to stop the request of the local DLT client.
+
+**Step 7** If accepted by the core CEDS, then the edge CEDS (edge CEDS A) synchronizes data and service of the DLT service.
+
+The data and service of the DLT service may be from other edge CEDS.
+
+**Step 8** Similar to step 2, FCs of the edge CEDS (edge CEDS A) collaborate with the edge DLT system (edge DLT system A) to manage the DLT service for the local DLT client.
+
+**Step 9 and 10** The edge DLT system (edge DLT system A) provides the DLT service to the local DLT client accordingly, and synchronizes the data and service of the DLT service with the core CEDS.
+
+
+
+Y.4486(23)
+
+Sequence diagram showing the flow for data and service synchronization of cross edge DLT services. The diagram involves five main entities: LAN A (Local DLT client), Edge CEDS A (Edge DLT system A, FCs of edge CEDS A), Edge cloud A (MEC mobility service), Edge CEDS B (Edge DLT system B, FCs of edge CEDS B), and Core CEDS (Core DLT system, FCs of core CEDS). The process follows 10 steps: 1. Local DLT client requests DLT service from Edge DLT system A. 2. Service management between Edge DLT system A and FCs of edge CEDS A. 3. Mobility validation between FCs of edge CEDS A and MEC mobility service. 4. Data and service migration of DLT service from Edge cloud A to Edge CEDS B. 5. Data and service synchronization request from Edge CEDS B to Core CEDS. 6. Service management between Core DLT system and FCs of core CEDS. 7. Data and service synchronization response from Core CEDS to Edge CEDS B. 8. Service management between Edge DLT system B and FCs of edge CEDS B. 9. Local DLT client receives response from Edge DLT system B. 10. Data and service synchronization of DLT service between Edge CEDS B and Core CEDS.
+
+**Figure 9-1 – Flow for data and service synchronization of cross edge DLT services**
+
+## 9.2 Migration of data and service of DLT services between edge clouds
+
+This procedure shows how a given CEDS performs data and service migration of cross edge DLT service for an IoT device between different edge CEDSs.
+
+The main steps reflecting a normal situation are described below (see Figure 9-2):
+
+**Step 1** A local DLT client hosted in an IoT device firstly in a LAN (LAN A) accesses a DLT service performed by an edge DLT system (edge DLT system A).
+
+Afterwards when, the local DLT client roams to a new edge cloud (such as edge cloud B), the local DLT client will manage to continuously access the DLT service.
+
+**Step 2** The local DLT client manages to access the DLT service via edge CEDS in the new edge cloud (edge cloud B), and sends a request to the new target edge DLT system (edge DLT system B).
+
+**Step 3** The new target edge DLT system (edge DLT system B) forwards the request to related FCs of the edge CEDS (edge CEDS B).
+
+The new target edge DLT system (edge DLT system B) collaborates with related FCs of the edge CEDS (edge CEDS B) to manage the DLT service for the local DLT client.
+
+- Step 4* The related FCs of the edge CEDS (edge CEDS B) negotiates with a relevant MEC mobility service in the same edge cloud (edge cloud B) to validate mobility information of the local DLT client.
+- If the local DLT client is already in the same edge cloud (edge cloud B), then it goes to step 8, otherwise, it goes to step 12.
+- Step 5 and 6* The related FCs of the edge CEDS (edge CEDS B) negotiates with related core CEDS, and notifies the related core CEDS of the roaming information, and requests to provide the DLT service to the local DLT client.
+- The edge CEDS (edge CEDS B) collaborates with the related core CEDS to decide whether to provide the relevant DLT service to the local DLT client.
+- If not accepted, then it goes to step 12.
+- Step 7* The local DLT client stops accessing the DLT service via the old edge CEDS (edge CEDS A), then the old edge CEDS (edge CEDS A) collaborates with the related core CEDS to synchronize data and service of the DLT service for the IoT device (see clause 9.1).
+- Step 8,9,10 and 11* If the new target edge CEDS (edge CEDS B) accepts the request of the local DLT client, it sends a request to the old edge CEDS (edge CEDS A) to migrate data and service of the DLT service.
+- The edge DLT system and FCs of the old edge CEDS (edge CEDS A) check the request. If not accepted, it goes to step 12.
+- If accepted, the old edge CEDS (edge CEDS A) interacts with the new target edge CEDS (edge CEDS B) to migrate the data and service of the DLT service.
+- Step 12 and 13* The new target edge DLT system (edge DLT system B) provides the DLT service to the local DLT client accordingly to synchronize the data and service of the DLT service with the core CEDS.
+
+
+
+The diagram illustrates the flow for data and service migration of cross edge DLT services. It involves four main entities: LAN A -> LAN B (Local DLT client), Edge CEDS A (Edge DLT system A, FCs of edge CEDS A), Edge cloud B (MEC mobility service), Edge CEDS B (Edge DLT system B, FCs of edge CEDS B), and Core CEDS (Core DLT system, FCs of core CEDS).
+
+The sequence of steps is as follows:
+
+1. Interaction of DLT service (Old) between Local DLT client and Edge DLT system A.
+2. Interaction of DLT service (Request) from Edge DLT system A to MEC mobility service.
+3. Service management between MEC mobility service and Edge DLT system B.
+4. Mobility validation between MEC mobility service and Edge DLT system B.
+5. Roaming notification from Edge DLT system B to Core DLT system.
+6. Service management between Core DLT system and FCs of core CEDS.
+7. Data and service synchronization of DLT service (Old) between Edge DLT system A and Edge DLT system B.
+8. Data and service migration of DLT service (Request) from Edge DLT system A to Edge DLT system B.
+9. Service management between Edge DLT system A and FCs of edge CEDS A.
+10. Data and service migration of DLT service (Response) from Edge DLT system B to Edge DLT system A.
+11. Service management between Edge DLT system B and FCs of edge CEDS B.
+12. Interaction of DLT service (Response) from Edge DLT system A to Local DLT client.
+13. Data and service synchronization of DLT service between Edge DLT system B and Core DLT system.
+
+Y.4486(23)
+
+Sequence diagram showing the flow for data and service migration of cross edge DLT services between LAN A and LAN B, involving Edge CEDS A, Edge cloud B, Edge CEDS B, and Core CEDS.
+
+**Figure 9-2 – Flow for data and service migration of cross edge DLT services**
+
+## 10 Security considerations
+
+The data of IoT resources might be exposed to many security attacks, and third parties may exploit the data for illegal IoT services. To prevent these situations, the data should be secured during the interactions between users and service providers. The CEDS is responsible for the security of data during the synchronization and migration procedures from security threats (e.g., tampering of the communication, replay attack, distributed denial of service). The data security procedure should also follow local laws and regulations.
+
+# Appendix I
+
+## **Use case of the cross edge decentralized service for IoT devices by using DLT and edge computing technologies**
+
+(This appendix does not form an integral part of this Recommendation.)
+
+This appendix provides a use case to illustrate the concept of the cross edge decentralized service for IoT devices by using DLT and edge computing technologies.
+
+### **I.1 Cross edge traffic information sharing of Internet of vehicles enhanced by CEDS**
+
+This use case shows Internet of vehicles (IoV) using DLT-based IoV services enhanced by a given CEDS to share traffic information in cross edge environments.
+
+Without going into specifics, the core CEDS of the CEDS is deployed in the core cloud, and there is one edge CEDS of the CEDS in each of the edge clouds (see Figure I.1). The core CEDS and each of the edge CEDSs of the CEDS include a DLT-based IoV service. All of the DLT-based IoV services collaborate with each other to provide and speed up the seamless cross edge service for the IoV to share traffic information.
+
+When the IoV moves from one local area network (LAN) to other LANs, the DLT-based IoV services in the target edge clouds can obtain the mobility information of the IoV from the edge nodes of communication networks using the supports of the corresponding edge CEDSs, and can then prepare the service environment for the IoV, including migration of data and services of the DLT-based IoV services from the original edge CEDS. In this way the IoV can get seamless and uninterrupted service such as sharing traffic information provided by the DLT-based IoV services when it is roaming in different edge clouds.
+
+When the IoV shares traffic information in one edge cloud using the supports of the CEDS, the entities of DLT-based IoV services in the core cloud and in the edge clouds can synchronize data and services of the DLT-based services for the IoV in order to speed up the sharing operations.
+
+
+
+## Bibliography
+
+- [b-ITU-T J.1303] Recommendation ITU-T J.1303 (2022), *Specification of a cloud-based converged media service to support Internet protocol and broadcast cable television – System specification on collaboration between production media cloud and cable service cloud.*
+- [b-ITU-T Q.1743] Recommendation ITU-T Q.1743 (2016), *IMT-Advanced references to Release 11 of LTE-Advanced evolved packet core network.*
+- [b-ITU-T X.1161] Recommendation ITU-T X.1161 (2008), *Framework for secure peer-to-peer communications.*
+- [b-ITU-T X.1400] Recommendation ITU-T X.1400 (2020), *Terms and definitions for distributed ledger technology.*
+- [b-ITU-T X.1409] Recommendation ITU-T X.1409 (2022), *Security services based on distributed ledger technology.*
+- [b-ITU-T Y.2091] Recommendation ITU-T Y.2091 (2011), *Terms and definitions for next generation networks.*
+- [b-ITU-T Y.3073] Recommendation ITU-T Y.3073 (2019), *Framework for service function chaining in information-centric networking.*
+- [b-ITU-T Y.3508] Recommendation ITU-T Y.3508 (2019), *Cloud computing – Overview and high-level requirements of distributed cloud.*
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation
+
+## **ITU-T Y.4496 (09/2025)**
+
+SERIES Y: Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+Internet of things and smart cities and communities –
+Frameworks, architectures and protocols
+
+---
+
+## **Requirements and reference architecture for a smart public health emergency information system**
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+## Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities
+
+| | |
+|---------------------------------------------------------|----------------------|
+| GLOBAL INFORMATION INFRASTRUCTURE | Y.100-Y.999 |
+| INTERNET PROTOCOL ASPECTS | Y.1000-Y.1999 |
+| NEXT GENERATION NETWORKS | Y.2000-Y.2999 |
+| FUTURE NETWORKS | Y.3000-Y.3499 |
+| CLOUD COMPUTING | Y.3500-Y.3599 |
+| BIG DATA | Y.3600-Y.3799 |
+| QUANTUM KEY DISTRIBUTION NETWORKS | Y.3800-Y.3999 |
+| INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES | Y.4000-Y.4999 |
+| General | Y.4000-Y.4049 |
+| Definitions and terminologies | Y.4050-Y.4099 |
+| Requirements and use cases | Y.4100-Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250-Y.4399 |
+| Frameworks, architectures and protocols | Y.4400-Y.4549 |
+| Services, applications, computation and data processing | Y.4550-Y.4699 |
+| Management, control and performance | Y.4700-Y.4799 |
+| Identification and security | Y.4800-Y.4899 |
+| Evaluation and assessment | Y.4900-Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4496
+
+## Requirements and reference architecture for a smart public health emergency information system
+
+## Summary
+
+Recommendation ITU-T Y.4496 provides the requirements and reference architecture for a smart public health emergency information system that can be implemented to address current and future potential public health risks.
+
+## History \*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T Y.4496 | 2025-09-23 | 20 | 11.1002/1000/15678 |
+
+## Keywords
+
+Functional module, public health emergency, reference architecture, requirement.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2025
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | | Page |
+|---|-----------------------------------------------------------------------------------------------------|------|
+| 1 | Scope..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| | 3.1 Terms defined elsewhere ..... | 1 |
+| | 3.2 Terms defined in this Recommendation..... | 1 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 2 |
+| 6 | Introduction of the smart public health emergency information system ..... | 2 |
+| 7 | Requirements of smart public health emergency information system..... | 3 |
+| | 7.1 Requirements for authorized health information collection module..... | 3 |
+| | 7.2 Requirements for a public health emergency information processing
module ..... | 4 |
+| | 7.3 Requirement for a public health emergency information analysis and
warning module ..... | 4 |
+| | 7.4 Requirements for public health emergency information exchange module... | 5 |
+| 8 | Reference architecture of the smart public health emergency information system..... | 6 |
+| | 8.1 Reference architecture of the smart public health emergency information
system..... | 6 |
+| | 8.2 Functional modules of the smart service for public health emergency
information system ..... | 6 |
+| | Bibliography..... | 11 |
+
+
+
+# Recommendation ITU-T Y.4496
+
+## Requirements and reference architecture for a smart public health emergency information system1
+
+# 1 Scope
+
+This Recommendation provides an architecture for a smart public health emergency information system.
+
+The scope of this Recommendation includes:
+
+- Introduction to the smart public health emergency information system;
+- Requirements of the smart public health emergency information system;
+- Reference architecture of the smart public health emergency information system.
+
+NOTE – The smart public health emergency information system needs to comply with different national regulations.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+None.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 Internet of things** [b-ITU-T Y.4000]: A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on, existing and evolving, interoperable information and communication technologies.
+
+**3.1.2 smart sustainable city (SSC)** [b-ITU-T Y.4900]: A smart sustainable city is an innovative city that uses information and communication technologies (ICTs) and other means to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social, environmental and cultural aspects.
+
+## 3.2 Terms defined in this Recommendation
+
+None.
+
+---
+
+1 In accordance with clause 9.5.4 of WTS Resolution 1, the following reservation has been appended to this Recommendation:
+
+– The following country has expressed a reservation and will not apply this Recommendation: United States.
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-----|------------------------------------------|
+| API | Application Programming Interface |
+| ICT | Information and Communication Technology |
+| IoT | Internet of Things |
+
+# 5 Conventions
+
+The following conventions are used in this Recommendation:
+
+The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted, if conformance to this Recommendation is to be claimed.
+
+The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+
+# 6 Introduction of the smart public health emergency information system
+
+The smart public health emergency information system is important for the safety and development of smart cities, as well as serving as a necessary foundation to promote the construction of smart cities. Given the occurrence or imminent threats of illnesses or health conditions caused by epidemic or pandemic diseases that pose substantial risk to a significant number of human facilities or incidents, information and communication technologies (ICTs) can play an important role in achieving highly efficient and reliable management of public health emergencies. In recent years, international, regional, and commercial public health emergency information systems have been established. The primary objective of the smart public health emergency information system is to provide early warning, precise epidemic prediction, and prompt response time to emergencies through the Internet of things (IoT) and other cutting-edge information technologies. The smart public health emergency information system can increase a city's or a community's resilience.
+
+The smart public health emergency information system, which is based on the integration of health information collection, public health emergency information processing, analysis and warning, as well as information exchange, aims to provide accurate predictive responses to various public emergencies by utilizing advanced algorithms and models. The system can effectively monitor potential risks, predict the development trend of emergencies, and provide decision-making support for relevant departments.
+
+In the absence of a current public health emergency, the smart public health emergency information system also serves in:
+
+- Preventing potential risks related to public health emergencies, such as infectious diseases, by continuously monitoring and analysing health data.
+- Establishing a reporting network among healthcare facilities, communities, and residences.
+
+During an actual public health emergency, the smart public health emergency information system is utilized for:
+
+- Triggering early warnings and providing accurate information to the general public.
+- Generating reliable predictions to support decision-making processes.
+
+Figure 1 shows an overview of the smart public health emergency information system.
+
+
+
+**Smart public health emergency information system**
+
+Public health emergency information exchange
+
+Public health emergency information processing → Public health emergency information analysis and warning
+
+Authorized health information collection
+
+Emergency response Intelligent decision support
+
+Thermometer Blood pressure monitor Blood glucose meter
+
+Health data collecting equipment e-health monitoring systems Public health knowledge system
+
+Y.4496(25)
+
+Figure 1: Overview of smart public health emergency information system. The diagram shows a central 'Smart public health emergency information system' box. Inside this box, 'Authorized health information collection' feeds into 'Public health emergency information processing', which then feeds into 'Public health emergency information analysis and warning'. This analysis and warning module feeds into 'Public health emergency information exchange'. Above the central box are 'Emergency response' and 'Intelligent decision support' modules, both connected to the 'Public health emergency information exchange' module. Below the central box are three categories of data sources: 'Health data collecting equipment' (including Thermometer, Blood pressure monitor, Blood glucose meter), 'e-health monitoring systems', and 'Public health knowledge system'. Arrows indicate data flow from these sources into the central system.
+
+**Figure 1 – Overview of smart public health emergency information system**
+
+# **7 Requirements of smart public health emergency information system**
+
+## **7.1 Requirements for authorized health information collection module**
+
+The authorized health information collection module requires managing devices and collecting data anonymously from Internet of things (IoT) devices and external systems.
+
+#### **7.1.1 Device and interface management**
+
+For device and interface management:
+
+- It is required to manage the registration, configuration, and de-registration of devices and interfaces involved in data collection.
+- It is required to support application programming interfaces (APIs) for data collection from IoT devices and external systems.
+
+#### **7.1.2 Data collection**
+
+For data collection:
+
+- It is required to support real-time data collection from connected IoT devices and external IoT systems.
+- It is required to handle structured, semi-structured, and unstructured data formats to accommodate diverse data sources.
+- It is required to automate the process to minimize human errors and ensure continuous data flow, even in the event of device failure.
+
+#### **7.1.3 Data filtering**
+
+For data filtering:
+
+- It is required to filter and cleanse data to eliminate duplicates, outliers, and inaccuracies, and to ensure high-quality data for processing.
+
+- It is required to implement validation techniques to ensure data consistency and completeness.
+
+#### **7.1.4 Data transfer**
+
+For data transfer:
+
+- It is required to use encrypted communication channels to ensure secure data transfer.
+- It is recommended to optimize data transmission for low-bandwidth environments and to synchronize data from multiple sources.
+
+#### **7.1.5 Data anonymization and authorization**
+
+For data anonymization and authorization:
+
+- It is recommended to anonymize personal health data to ensure full compliance with data regulations.
+- It is recommended to provide users the option to consent to or opt out of data collection.
+
+## **7.2 Requirements for a public health emergency information processing module**
+
+The public health emergency information processing module is required to process and storage collected data, as well as develop a knowledge base to enhance response efforts.
+
+#### **7.2.1 Data processing and aggregation**
+
+For data processing and aggregation:
+
+- It is required to aggregate data from multiple sources, applying cleansing techniques and normalizing the data to ensure consistency.
+- It is required to enrich raw data with metadata for deeper analysis.
+- It is required to perform data categorization to enable efficient retrieval and analysis.
+
+#### **7.2.2 Public health emergency data storage**
+
+For public health emergency data storage:
+
+- It is required to ensure scalability and reliability, with robust backup and recovery mechanisms.
+
+#### **7.2.3 Public health emergency knowledge base**
+
+For the public health emergency knowledge base:
+
+- It is required to integrate data from previous public health emergencies in order to identify patterns and trends, facilitating the prediction of future outbreaks for similar scenarios.
+- It is recommended to develop a comprehensive knowledge base with predictive models, risk assessments and practices, thereby supporting data prediction and analysis.
+
+### **7.3 Requirement for a public health emergency information analysis and warning module**
+
+The public health emergency information analysis and warning module is required to have the ability of predictive modelling, trend forecasting, risk assessment, simulation, early warning and data visualization to effectively respond to public health emergencies.
+
+#### **7.3.1 Predictive model development**
+
+For predictive model development:
+
+- It is required to combine multiple predictive models to enhance forecasting accuracy, adjusting model parameters in real-time based on updated epidemic data.
+
+#### **7.3.2 Epidemic trend prediction**
+
+For epidemic trend prediction:
+
+- It is required to forecast short-term and long-term epidemic trends, focusing on key indicators to assist decision-makers in managing responses.
+- It is recommended to predict peak epidemic times for optimal resource allocation.
+
+#### **7.3.3 Epidemic risk assessment**
+
+For epidemic risk assessment:
+
+- It is required to assess and rate risks for different regions and identify high-risk populations.
+- It is required to continuously update risk assessments based on evolving conditions.
+
+#### **7.3.4 Epidemic simulation and scenario analysis**
+
+For epidemic simulation and scenario analysis:
+
+- It is required to simulate various containment policies and scenarios to evaluate their impact on epidemic development.
+
+#### **7.3.5 Early warning**
+
+For early warning:
+
+- It is required to establish thresholds for key epidemic indicators and automatically trigger warning signals when these thresholds are met.
+- It is required to be implement a multi-tiered warning system to provide actionable information to decision-makers.
+
+#### **7.3.6 Data visualization**
+
+For data visualization:
+
+- It is required to provide real-time, interactive visualizations that allow users to explore epidemic data across dimensions such as time, region, and population.
+- It is required to provide customised dashboards and reports for different types of users.
+
+## **7.4 Requirements for public health emergency information exchange module**
+
+The public health emergency information exchange module is required to manage accounts, provide notification to external systems and offer decision support assistance.
+
+#### **7.4.1 Account management**
+
+For account management:
+
+- It is required to manage accounts with role-based access controls to ensure secure access, such as registration, login, permission settings, and so on.
+- It is required to log all operations for audit purposes.
+
+#### **7.4.2 Notification and data sharing**
+
+For notification and data sharing:
+
+- It is required to automatically generate alerts when key thresholds are exceeded, specifying the type of alert and the action recommendation.
+- It is required to support interoperable data formats and adopt international standards for data exchange.
+
+# 8 Reference architecture of the smart public health emergency information system
+
+## 8.1 Reference architecture of the smart public health emergency information system
+
+The reference architecture of the smart public health emergency information system is shown in Figure 2. Typically, the smart public health emergency information system consists of of four functional logical modules, based on the functionalities described in clause 6.
+
+
+
+External smart city platforms
+
+Public health emergency information exchange
+
+Account management
+
+Notification and data sharing
+
+Public health emergency information analysis and warning
+
+Predictive model development
+
+Epidemic trend prediction
+
+Epidemic risk assessment
+
+Epidemic simulation and scenario analysis
+
+Early warning
+
+Data visualization
+
+Public health emergency information processing
+
+Data processing and aggregation
+
+Public health emergency data storage
+
+Public health emergency knowledge base
+
+Authorized health information collection
+
+Device and interface management
+
+Data collection
+
+Data filtering
+
+Data transfer
+
+Data anonymization and authorization management
+
+Smart public health emergency information system
+
+External data sources (devices, IT systems)
+
+Y.4496(25)
+
+Figure 2: Reference architecture of the smart public health emergency information system. The diagram shows a central 'Smart public health emergency information system' block with four main functional layers. From top to bottom: 1. 'Public health emergency information exchange' containing 'Account management' and 'Notification and data sharing'. 2. 'Public health emergency information analysis and warning' containing 'Predictive model development', 'Epidemic trend prediction', 'Epidemic risk assessment', 'Epidemic simulation and scenario analysis', 'Early warning', and 'Data visualization'. 3. 'Public health emergency information processing' containing 'Data processing and aggregation', 'Public health emergency data storage', and 'Public health emergency knowledge base'. 4. 'Authorized health information collection' containing 'Device and interface management', 'Data collection', 'Data filtering', 'Data transfer', and 'Data anonymization and authorization management'. The system is connected to 'External smart city platforms' above and 'External data sources (devices, IT systems)' below via bidirectional arrows. A reference code 'Y.4496(25)' is at the bottom right.
+
+**Figure 2 – Reference architecture of the smart public health emergency information system**
+
+## 8.2 Functional modules of the smart service for public health emergency information system
+
+#### 8.2.1 Health information collection module
+
+The health information collection module is responsible for securely collecting and recording data relevant to public health emergencies. This information includes disease data, test results, and community reports. This module consists of the following functional components: device and interface management, data collection, data filtering, data transfer, and data anonymization and authorized management.
+
+##### 8.2.1.1 Device and interface management
+
+The functional component of device and interface management of the health information collection module provides functionalities, mainly as follows:
+
+- Manages the registration, configuration, and de-registration of devices and interfaces.
+- Queries device and interface details and issues alerts in the event of device malfunctions or disruptions in data collection.
+
+- Facilitates APIs for data collection from external systems, including public health emergency reporting systems, infectious disease surveillance systems, e-health monitoring systems [b-ITU-T Y.4408], and external knowledge bases or open data pools.
+
+##### **8.2.1.2 Data collection**
+
+The functional component of data collection of the health information collection module provides functionalities, mainly as follows:
+
+- Captures real-time health metrics from IoT devices and external health systems.
+- Supports diverse data formats, for compatibility with multiple data sources.
+- Automates the data collection process with comprehensive error-checking mechanisms to minimize human intervention and ensure data accuracy.
+- Establishes redundant data collection pathways to ensure continuous data flow in case of device or interface failure.
+- Implements robust data recovery procedures to restore lost or incomplete data, ensuring data integrity.
+
+##### **8.2.1.3 Data filtering**
+
+The functional component of data filtering of the health information collection module provides functionalities, mainly as follows:
+
+- Implements advanced data filtering techniques to eliminate noise, outliers, and inaccuracies from the collected data.
+- Detects and removes duplicate or redundant data entries to maintain dataset consistency.
+- Filters data based on predefined thresholds and conditions to exclude irrelevant or incomplete information.
+- Validates incoming data for accuracy, consistency, and completeness, ensuring only reliable data is processed.
+
+##### **8.2.1.4 Data transfer**
+
+The functional component of data transfer of the health information collection module provides functionalities, mainly as follows:
+
+- Transmits data using encrypted communication channels to protect the integrity and confidentiality of health information.
+- Optimizes data transfer processes to minimize bandwidth usage and ensure the timely delivery of large datasets, even in low-resources network environments.
+- Synchronizes data from multiple sources to maintain consistency across the system.
+
+##### **8.2.1.5 Data anonymization and authorization management**
+
+The functional component of data anonymization and authorization of the health information collection module provides functionalities, mainly as follows:
+
+- Implements anonymization techniques, such as those specified in [b-ISO/IEC 29100] and [b-ISO/IEC 27559], to safeguard user privacy while maintaining data integrity for analysis.
+- Supports APIs for IoT devices based on user consent, with an opt-out option for users.
+
+#### **8.2.2 Public health emergency information processing module**
+
+The public health emergency information processing module is responsible for aggregating, processing, storing, and managing data collected from various public health data sources to support effective decision-making. This module ensures data consistency, accessibility, and reliability while also organizing the data for knowledge extraction and future use. This module includes the following
+
+components: data processing and aggregation, public health emergency data storage, and a public health emergency knowledge base.
+
+##### **8.2.2.1 Data processing and aggregation**
+
+The functional component of the data processing and aggregation of public health emergency information processing module provides functionalities, mainly as follows:
+
+- Collects and aggregates data from multiple sources to ensure accuracy.
+- Normalizes and standardizes data to provide uniformity across datasets, facilitating easier analysis for different public health emergencies.
+- Enriches data with metadata and contextual information to enable deeper and more meaningful analysis.
+- Classifies data into specific categories, facilitating efficient retrieval and structured analysis based on the type of emergency or disease.
+
+##### **8.2.2.2 Public health emergency data storage**
+
+The functional component of the public health emergency data storage of public health emergency information processing module provides functionalities, mainly as follows:
+
+- Utilizes distributed data storage systems to enhance scalability, reliability, and fault tolerance, ensuring continuous access to critical public health information.
+- Implements robust data archiving mechanisms for long-term storage, supporting future analyses, and epidemiological studies.
+- Conducts regular backups and implements recovery mechanisms to system failure contingencies.
+
+##### **8.2.2.3 Public health emergency knowledge base**
+
+The functional component of the public health emergency knowledge base of information processing module provides functionalities, mainly as follows:
+
+- Aggregates and organizes structured and unstructured data from multiple sources, creating a centralized repository for public health emergency data.
+- Analyses past data from previous public health emergencies to identify trends and patterns.
+- Provides tools for data analysis and decision support, offering insights into best practices, epidemiological models, and risk management strategies.
+
+#### **8.2.3 Public health emergency information analysis and warning module**
+
+The public health emergency information analysis and warning module is responsible for constructing and utilizing predictive models to forecast epidemic trends, assess risks, simulate scenarios, provide early warnings and offer visualization services. This module serves as a critical decision support tool for public health authorities, facilitating timely and effective epidemic response.
+
+##### **8.2.3.1 Predictive model development**
+
+The functional component of the predictive model development in the analysis and warning module provides functionalities, mainly as follows:
+
+- Integrates a diverse array of predictive models, machine learning algorithms, and statistical methods, to improve the accuracy and robustness of epidemic forecasts.
+- Enables the models to ingest real-time epidemic data and dynamically adjust prediction parameters, ensuring that forecasts reflect the latest developments in the epidemic.
+- Utilizes historical data to train model parameters and applies optimization techniques, such as cross-validation, to improve prediction reliability and performance.
+
+##### **8.2.3.2 Epidemic trend prediction**
+
+The functional component of epidemic trend prediction in the analysis and warning module provides functionalities, mainly as follows:
+
+- Provides short-term forecasts for epidemic trends over the coming days and weeks, aiding decision-makers in managing immediate responses effectively.
+- Predicts long-term epidemic developments based on available epidemiological data and models, to support scenario-based strategic planning and resource allocation.
+- Forecasts the timing of the epidemic's peak, enabling public health authorities to prepare and allocate medical resources proactively.
+
+##### **8.2.3.3 Epidemic risk assessment**
+
+The functional component of epidemic risk assessment of the analysis and warning module provides functionalities, mainly as follows:
+
+- Evaluates and classifies epidemic risks for various regions, providing a comprehensive risk profile.
+- Identifies high-risk populations to guide targeted protective measures and resource allocation.
+- Updates risk assessments continuously based on real-time data and evolving epidemic conditions, facilitating timely adjustments in containment strategies.
+
+##### **8.2.3.4 Epidemic simulation and scenario analysis**
+
+The functional component of epidemic simulation and scenario analysis in the analysis and warning module provides functionalities, mainly as follows:
+
+- Simulates the effects of various containment measures to evaluate their potential impact on the epidemic's development, offering insights into the efficacy of different interventions.
+- Develops multiple epidemic scenarios based on different factors.
+- Analyses simulation outcomes to assess and compare the effectiveness of different containment strategies, ensuring data-driven decision-making.
+
+##### **8.2.3.5 Early warning**
+
+The functional component of early warning in the analysis and warning module provides functionalities, mainly as follows:
+
+- Monitors critical epidemic indicators and generates automated alerts when predefined thresholds are crossed.
+- Implements a tiered warning system to classify alerts by severity for tailored responses.
+
+##### **8.2.3.5 Data visualization**
+
+The functional component of data visualization in the information exchange module provides functionalities, mainly as follows:
+
+- Provides charts, maps, and dashboards for exploring epidemic data across geographic, temporal, and demographic dimensions.
+- Ensures that epidemic data and forecasts are continuously updated in real-time, maintaining the accuracy and relevance of the information presented to decision-makers.
+- Provides comprehensive views of epidemic data by displaying information across multiple dimensions, including geographic spread, temporal evolution, and population impact.
+
+#### **8.2.4 Public health emergency information exchange module**
+
+The public health emergency information exchange module is designed to support secure and efficient communication of epidemic-related data and notifications with external systems. This module includes the following components: account management, notification and data sharing.
+
+##### **8.2.4.1 Account management**
+
+The functional component of account management in the information exchange module provides functionalities, mainly as follows:
+
+- Implements and manages accounts and access control to ensure secure integration with external systems.
+- Monitors and logs all access activities to maintain an audit trail for security and compliance purposes.
+
+##### **8.2.4.2 Notification and data sharing**
+
+The functional component of notification and data sharing in the information exchange module provides functionalities, mainly as follows:
+
+- Automatically generates notifications to external systems upon receiving alert signals from the early warning component, ensuring proactivity.
+- Facilitates secure, standardized, and real-time data sharing from the smart public health emergency information system to external systems, ensuring timely and accurate information dissemination.
+- Supports the use of interoperable data formats and protocols to ensure seamless exchange of critical epidemic data and forecasts across different platforms.
+- Provides APIs for external systems to access, query, and contribute to the data and knowledge base, enhancing collaboration and information sharing between stakeholders.
+
+## Bibliography
+
+- [[b-ITU-T Y.4000](#)] Recommendation ITU-T Y.4000/Y.2060 (2012), *Overview of the Internet of things*.
+- [[b-ITU-T Y.4408](#)] Recommendation ITU-T Y.4408/Y.2075 (2015), *Capability framework for e-health monitoring services*.
+- [[b-ITU-T Y.4900](#)] Recommendation ITU-T Y.4900/L.1600 (2016), *Overview of key performance indicators in smart sustainable cities*.
+- [b-ISO/IEC 27559] ISO/IEC 27559 (2022), *Information security, cybersecurity and privacy protection – Privacy enhancing data de-identification framework*.
+- [b-ISO/IEC 29100] ISO/IEC 29100 (2024), *Information technology – Security techniques – Privacy framework*.
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# ITU-T
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+## Y.4500.12
+
+(03/2018)
+
+SERIES Y: GLOBAL INFORMATION
+INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS,
+NEXT-GENERATION NETWORKS, INTERNET OF
+THINGS AND SMART CITIES
+
+Internet of things and smart cities and communities –
+Frameworks, architectures and protocols
+
+# --- **oneM2M base ontology**
+
+Recommendation ITU-T Y.4500.12
+
+## ITU-T Y-SERIES RECOMMENDATIONS
+
+# GLOBAL INFORMATION INFRASTRUCTURE, INTERNET PROTOCOL ASPECTS, NEXT-GENERATION NETWORKS, INTERNET OF THINGS AND SMART CITIES
+
+## GLOBAL INFORMATION INFRASTRUCTURE
+
+| | |
+|-------------------------------------------|-------------|
+| General | Y.100–Y.199 |
+| Services, applications and middleware | Y.200–Y.299 |
+| Network aspects | Y.300–Y.399 |
+| Interfaces and protocols | Y.400–Y.499 |
+| Numbering, addressing and naming | Y.500–Y.599 |
+| Operation, administration and maintenance | Y.600–Y.699 |
+| Security | Y.700–Y.799 |
+| Performances | Y.800–Y.899 |
+
+## INTERNET PROTOCOL ASPECTS
+
+| | |
+|--------------------------------------------------------------------|---------------|
+| General | Y.1000–Y.1099 |
+| Services and applications | Y.1100–Y.1199 |
+| Architecture, access, network capabilities and resource management | Y.1200–Y.1299 |
+| Transport | Y.1300–Y.1399 |
+| Interworking | Y.1400–Y.1499 |
+| Quality of service and network performance | Y.1500–Y.1599 |
+| Signalling | Y.1600–Y.1699 |
+| Operation, administration and maintenance | Y.1700–Y.1799 |
+| Charging | Y.1800–Y.1899 |
+| IPTV over NGN | Y.1900–Y.1999 |
+
+## NEXT GENERATION NETWORKS
+
+| | |
+|-------------------------------------------------------------------|---------------|
+| Frameworks and functional architecture models | Y.2000–Y.2099 |
+| Quality of Service and performance | Y.2100–Y.2199 |
+| Service aspects: Service capabilities and service architecture | Y.2200–Y.2249 |
+| Service aspects: Interoperability of services and networks in NGN | Y.2250–Y.2299 |
+| Enhancements to NGN | Y.2300–Y.2399 |
+| Network management | Y.2400–Y.2499 |
+| Network control architectures and protocols | Y.2500–Y.2599 |
+| Packet-based Networks | Y.2600–Y.2699 |
+| Security | Y.2700–Y.2799 |
+| Generalized mobility | Y.2800–Y.2899 |
+| Carrier grade open environment | Y.2900–Y.2999 |
+
+## FUTURE NETWORKS
+
+| | |
+|-----------------|---------------|
+| CLOUD COMPUTING | Y.3000–Y.3499 |
+| | Y.3500–Y.3999 |
+
+## INTERNET OF THINGS AND SMART CITIES AND COMMUNITIES
+
+| | |
+|---------------------------------------------------------|----------------------|
+| General | Y.4000–Y.4049 |
+| Definitions and terminologies | Y.4050–Y.4099 |
+| Requirements and use cases | Y.4100–Y.4249 |
+| Infrastructure, connectivity and networks | Y.4250–Y.4399 |
+| Frameworks, architectures and protocols | Y.4400–Y.4549 |
+| Services, applications, computation and data processing | Y.4550–Y.4699 |
+| Management, control and performance | Y.4700–Y.4799 |
+| Identification and security | Y.4800–Y.4899 |
+| Evaluation and assessment | Y.4900–Y.4999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T Y.4500.12
+
+# oneM2M base ontology
+
+## Summary
+
+Recommendation ITU-T Y.4500.12 provides normative and informative specifications for the oneM2M base ontology and its instantiation into oneM2M resources.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|-----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T Y.4500.12 | 2018-03-01 | 20 | 11.1002/1000/13507 |
+
+## Keywords
+
+Interworking, ontology, oneM2M, semantics.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+NOTE – This Recommendation departs slightly from the usual editorial style of ITU-T Recommendations to preserve existing cross-referencing from external documents.
+
+© ITU 2018
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|------------------------------------------------------------------------------------------------------------------------------|-------------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere ..... | 1 |
+| 3.2 Terms defined in this Recommendation ..... | 1 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 3 |
+| 6 General information on the oneM2M base ontology ..... | 3 |
+| 6.1 Motivation and intended use of the ontology ..... | 3 |
+| 6.2 Insights into base ontology ..... | 8 |
+| 7 Description of classes and properties ..... | 13 |
+| 7.1 Classes ..... | 13 |
+| 7.2 Object properties ..... | 38 |
+| 7.3 Data Properties ..... | 42 |
+| 7.4 Annotation properties ..... | 47 |
+| 8 Instantiation of the base ontology and external ontologies to the oneM2M system .... | 48 |
+| 8.1 Instantiation rules for the base ontology ..... | 48 |
+| 8.2 Common mapping principles between the base ontology and external ontologies ..... | 55 |
+| 9 Functional specification of communication with the generic interworking IPE ..... | 56 |
+| 9.1 Usage of oneM2M resources for IPE communication ..... | 56 |
+| 9.2 Specification of the IPE for generic interworking..... | 58 |
+| 9.3 Specification of the behaviour of a communicating entity in message flows between IPE and the communicating entity ..... | 61 |
+| 10 FlexContainer specializations for generic interworking..... | 64 |
+| 10.1 Introduction ..... | 64 |
+| 10.2 Resource Type genericInterworkingService ..... | 64 |
+| 10.3 Resource Type genericInterworkingOperationInstance ..... | 68 |
+| Annex A – oneM2M specification update and maintenance control procedure..... | 74 |
+| Annex B – OWL representation of base ontology ..... | 75 |
+| Appendix I – Mappings of selected external ontologies to the base ontology ..... | 76 |
+| I.1 Mapping of SAREF ..... | 76 |
+| Bibliography..... | 86 |
+
+
+
+# Recommendation ITU-T Y.4500.12
+
+# oneM2M base ontology
+
+# 1 Scope
+
+This Recommendation specifies the oneM2M base ontology.
+
+This Recommendation also specifies an instantiation of the base ontology in oneM2M resources that is required for generic interworking.
+
+In addition this Recommendation contains the functional specification for an interworking proxy entity (IPE), the oneM2M resources and their usage for generic interworking.
+
+The Recommendation contains oneM2M Release 2 specification – oneM2M base ontology V2.0.0 and is equivalent to standards of oneM2M partners including ARIB, ATIS [b-ATIS.oneM2M.TS0012], CCSA [b-CCSA M2M-TS-0012], ETSI [b-ETSI TS 118 112], TTA, TSDSI [b-TSDSI STD T1.oneM2M TS-0012], TTA [b-TTAT.MM-TS.0012] and TTC [b-TTC TS-M2M-0012].
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T Y.4500.1] Recommendation ITU-T Y.4500.1 (2018), *oneM2M – Functional architecture*.
+
+[ITU-T Y.4500.11] Recommendation ITU-T Y.4500.11 (2018), *oneM2M – Common terminology*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+For the purposes of this Recommendation, the terms and definitions given in oneM2M TS-0011 [ITU Y.4500.11] apply.
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 application entity** [ITU Y.4500.11]: Represents an instantiation of application logic for end-to-end M2M solutions.
+
+**3.1.2 common services entity (CSE)** [ITU Y.4500.11]: Represents an instantiation of a set of common service functions of the M2M environments. Such service functions are exposed to other entities through reference points.
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 annotation property:** Property that can be used to add information (metadata or data about data) to classes, individuals and Object/Data properties.
+
+**3.2.2 concept:** Entity of an ontology that has an agreed, well-defined, meaning within the domain of interest of that ontology.
+
+NOTE 1 – A concept conceptually groups a set of individuals.
+
+NOTE 2 – Concepts are called "classes" as used in web ontology language (OWL) standard ontology language from the World Wide Web Consortium (W3C) (see [b-OWL]).
+
+**3.2.3 data property:** Property that relates an individual of a class to data of a specified type and range.
+
+**3.2.4 generic interworking:** Interworking with many types of non-oneM2M area networks and devices that are described in the form of a oneM2M compliant ontology that is derived from the oneM2M base ontology.
+
+NOTE – Generic interworking supports the interworking variant "full mapping of the semantic of the non-oneM2M data model to Mca" as indicated in clause F.2 of oneM2M TS-0001 [ITU-T Y.4500.1].
+
+**3.2.5 interworked device:** Non-oneM2M device (NoDN) for which communication with oneM2M entities can be achieved via an interworking proxy entity (IPE).
+
+**3.2.6 object property:** Property that relates an individual of a domain class to an individual of a range class.
+
+**3.2.7 ontology:** Formal specification of a conceptualization, i.e., defining concepts as objects with their properties and relationships versus other concepts.
+
+**3.2.8 property:** In web ontology language (OWL) standard ontology language, a property represents relations among individuals.
+
+NOTE – Properties can be subcategorized as object properties, data properties and annotation properties.
+
+**3.2.9 proxied device:** Virtual device [i.e., a set of oneM2M resources together with an interworking proxy entity (IPE)] that represents the interworked device in the oneM2M system.
+
+**3.2.10 relation; interrelation):** Stating a relationship among individuals.
+
+**3.2.11 restriction:** Describes a class of individuals based on the relationships that members of the class participate in.
+
+NOTE – Restrictions can be subcategorized as: existential restrictions, universal restrictions, cardinality restrictions and has value restrictions.
+
+# 4 Abbreviations and acronyms
+
+For the purposes of this Recommendation, the abbreviations given in oneM2M TS-0011 [ITU-T Y.4500.11] and the following apply:
+
+| | |
+|--------|-----------------------------------------|
+| AE | Application Entity |
+| CRUD | Create-Read-Update-Delete |
+| CSE | Common Services Entity |
+| IPE | Interworking Proxy Entity |
+| IRI | Internationalized Resource Identifier |
+| MAC | Media Access Control |
+| NoDN | Non-oneM2M Device |
+| OWL | Web Ontology Language |
+| OWL-DL | Web Ontology Language-Description Logic |
+| RDF | Resource Description Framework |
+
+| | |
+|--------|----------------------------------------|
+| RPC | Remote Procedure Call |
+| SAREF | Smart Appliances Reference |
+| SPARQL | SPARQL Protocol and RDF Query Language |
+| URI | Uniform Resource Identifier |
+
+# 5 Conventions
+
+The keywords "shall", "shall not", "may", "need not", "should", "should not" in this Recommendation are to be interpreted as described:
+
+Shall/shall not:
+
+## Requirements
+
+- 1) effect on this Recommendation: This Recommendation needs to describe the required feature (i.e., specify a technical solution for the requirement);
+- 2) effect on products: every implementation (M2M solution that complies with this Recommendation) must support it;
+- 3) effect on deployments: every deployment (M2M service based on this Recommendation) must use the standardized feature where applicable – otherwise, interoperability problems with other services could arise, for example.
+
+Should/should not:
+
+## Recommendation
+
+- 1) effect on this Recommendation: This Recommendation needs to describe a solution that allows the presence and the absence of the feature;
+- 2) effect on products: an implementation may or may not support it; however, support is recommended;
+- 3) effect on deployments: a deployment may or may not use it; however, usage is recommended.
+
+May/need not:
+
+## Permission/option
+
+- 1) effect on this Recommendation: This Recommendation needs to describe a solution that allows the presence and the absence of the required feature;
+- 2) effect on products: an implementation may or may not support it;
+- 3) effect on deployments: A deployment may or may not use it.
+
+# 6 General information on the oneM2M base ontology
+
+## 6.1 Motivation and intended use of the ontology
+
+### 6.1.1 Why use ontologies in oneM2M?
+
+#### 6.1.1.1 Introduction to ontologies
+
+In a nutshell, an ontology is a vocabulary with a structure. The vocabulary applies to a certain domain of interest (e.g., metering, appliances, medicine) and it contains concepts that are used within that domain of interest, similar to the terms defined in clause 3.
+
+An ontology should:
+
+- capture a shared understanding of a domain of interest;
+- provide a formal and machine interpretable model of the domain.
+
+The ontology lists and denominates those concepts that have agreed, well-defined, meanings within the domain of interest {e.g., the concept of "device" has an agreed, well-defined, meaning within the scope of the smart appliances reference (SAREF) ontology see [b-SAREFa]}.
+
+Example 1 follows of how external ontologies can be mapped to the base ontology. Example 1 uses the SAREF ontology [b-SAREFa].
+
+Concepts do not identify individuals, but classes of individuals. Therefore, in the OWL standard ontology language from the World Wide Web Consortium (W3C) (see [b-OWL]), concepts are called "classes".
+
+The structural part of the ontology is introduced through agreed, well-defined, relationships between its concepts. Such a relationship – in OWL called "object property" – links a *subject* concept to an *object* concept.
+
+*subject* concept → relationship → *object* concept
+
+in OWL:
+
+*domain* class → object property → *range* class
+
+*Example 1:* In SAREF, an object property "accomplishes" relates the "device" class to the "task" class:
+
+Device → accomplishes → task
+
+Also the relationships or object properties of an ontology have agreed, well-defined, meanings within the domain of interest. In Example 1, the "accomplishes" part of the relationship is well documented as part of SAREF (see [b-SAREFa]).
+
+A second type of property in OWL is called "data properties". A data property links a subject class to data. These data may be typed or untyped.
+
+*Example 2:* In SAREF the data property "hasManufacturer" links the class "device" with data of the type "literal":
+
+Device → hasManufacturer → literal
+
+Again, the data properties of an ontology have agreed, well-defined, meanings within the domain of interest. In Example 2, the data property "hasManufacturer" indicates that the Literal that is linked via this data property will indicate the manufacturer of the device.
+
+Data properties can be considered to be similar to attributes in oneM2M.
+
+A third type of property in OWL is called "annotation properties". An annotation property is used to provide additional information about ontology elements like classes and instances, which typically are external to the ontology and not used for reasoning. Example usages for such additional information are for providing a creator, a version or a comment. The object of an annotation property is either a data literal, a uniform resource identifier (URI) reference or an individual.
+
+In general, an individual of a certain class may or may not have a particular relation (object property, data property or annotation property) that is defined by the ontology. However, if such a relation exists for the individual, then that relation should be used with the meaning specified by the ontology.
+
+One additional, crucial aspect differentiates an ontology from a vocabulary with a structure. An ontology enables specified, allowed constructs (based on predicate logic) and can be represented in a formal, machine interpretable form, e.g., by the OWL standard ontology language. This allows the creation of queries [e.g., through the SPARQL (SPARQL Protocol and RDF query language)] that search for individuals of specified classes, having specified relationships, etc.
+
+The OWL flavour OWL-DL (where DL stands for "description logic") that is used in this Recommendation and that is supported by the ontology-editing tool, Protégé (see [b-Protégé]), has
+
+the additional advantage that it is underpinned by a description logic. For ontologies that fall into the scope of OWL-DL, a reasoner can be used to automatically check the consistency of classes, take what is explicitly stated in the ontology and use it to infer new information. OWL-DL ensures that queries are decidable.
+
+Additionally, OWL-DL allows the creation of intersection, union and complement classes, restrictions (e.g., on the required or allowed number of relationships for any individual of the class along this property) and other useful constructs.
+
+#### **6.1.1.2 The purpose of the oneM2M base ontology**
+
+##### **6.1.1.2.0 Introduction**
+
+Ontologies and their OWL representations are used in oneM2M to provide syntactic and semantic interoperability of the oneM2M system with external systems. These external systems are expected to be described by ontologies.
+
+The only ontology that is specified by oneM2M is the oneM2M base ontology, as described in this Recommendation. However, external organizations and companies are expected to contribute their own ontologies that can be mapped (e.g., by subclassing, equivalence) to the oneM2M base ontology. A formal OWL representation of the base ontology can be found at [b- oneM2M Ontologies used for oneM2M].
+
+Such external ontologies might describe specific types of devices (e.g., like the SAREF ontology) or, more generally, they might describe real-world things (like buildings, rooms, cars, cities) that should be represented in a oneM2M implementation. The value for external organizations and companies to provide their ontologies to oneM2M consists in supplementing oneM2M data with information on the meaning or purpose of these data. The OWL representation of that ontology provides a common format across oneM2M.
+
+The oneM2M base ontology is the minimal ontology (i.e., mandating the least number of conventions) that is required such that other ontologies can be mapped into oneM2M.
+
+##### **6.1.1.2.1 Syntactic interoperability**
+
+Syntactic interoperability is mainly used for interworking with NoDNs in area networks. In this case, an ontology – represented as an OWL file – that contains the area network-specific types of communication parameters (names of operations, input/output parameter names, their types and structures, etc.) is used to configure an interworking proxy entity (IPE).
+
+With the help of this OWL file, the IPE is able to allocate oneM2M resources (AEs, containers) that are structured along the area network-specific parameters and procedures. This enables oneM2M entities to read/write from/into these resources, so that the IPE can serialize the data and send/receive them from/to the devices in the area network.
+
+The semantic meaning of these resources is implicitly given by the interworked area network technology.
+
+Each ontology that describes a specific type of interworked area network needs to be derived from the oneM2M base ontology. In particular, the device types of an ontology of an interworked area network need to be mapped (e.g., by sub-typing) into the concept "Interworked Device" of the oneM2M base ontology.
+
+##### **6.1.1.2.2 Semantic interoperability**
+
+Semantic interoperability is mainly used to describe functions provided by oneM2M compliant devices (M2M Devices).
+
+*Example:* Different, oneM2M compliant types of washing machine may all perform a function like "washing-function", "drying-function", "select wash temperature"; however, the oneM2M resources
+
+(containers) through which these functions can be accessed can have different resourceNames, child-structures and type of content.
+
+In this case, an ontology – represented as an OWL file – contains the specific types of the M2M application service or common service of the M2M device [e.g., Create-Read-Update-Delete (CRUD) operation, resourceNames, child-structures and type of content] together with the function of that service (e.g., "washing-function").
+
+Each ontology that describes a specific type of M2M device needs to be derived from the oneM2M base ontology. In particular, the device type needs to be mapped (e.g., by subtyping) into the concept "Device" of the oneM2M base ontology.
+
+### **6.1.2 How are the base ontology and external ontologies used?**
+
+#### **6.1.2.1 Overview**
+
+This clause describes how an external ontology that is compatible with the base ontology can be used in a joint fashion.
+
+NOTE – Further use of external ontologies is left to subsequent releases.
+
+#### **6.1.2.2 Introduction to usage of classes, properties and restrictions**
+
+An ontology consists of properties and classes.
+
+Properties represent relationships, and link individuals from the specified domain (a class) to individuals from the specified range (another class). There are two main types of properties in the base ontology: object properties and data properties. An object property describes a relationship between two object individuals. A data property describes a relationship between an object individual and a concrete data value that may be typed or untyped.
+
+Classes are interpreted as sets of individuals and sometimes classes are also seen as a concrete representation of concepts. In the base ontology, a class can be directly defined by the class name and class hierarchy or defined by the property characteristics of the individuals in the class. The latter method is known as restriction. The classes defined by restriction can be anonymous, which contains all of the individuals that satisfy the restriction.
+
+In the base ontology, the restrictions can be divided into existential restrictions, universal restrictions and cardinality restrictions.
+
+- Existential restrictions describe classes of individuals that participate in at least one (some) relationship along a given property to individuals that are members of the class, e.g., since a device (Class: Device) has at least one function (Object Property: hasFunction) (Class: Function) that this device accomplishes, then (Class: Device) is a subclass of the anonymous class of (Object Property: hasFunction) *some* (Class: Function).
+- Universal restrictions describe classes of individuals that for a given property only have relationships along this property to individuals that are members of the class. For example, since a subclass "Watervalue" of (Class: Device) only has a function (Object Property: hasFunction) subclass "Open\_or\_Close\_Valve" of (Class: Function), then (Class:Watervalue) is a superclass of the anonymous class of (Object Property: hasFunction) *only* (Class: Open\_or\_Close\_Valve).
+- Cardinality restrictions describe classes of individuals that, for a given property, only have a specified number of relationships along this property to individuals that are members of the class.
+
+#### 6.1.2.3 Methods for jointly using the base ontology and external ontologies
+
+If the base ontology is available and the external ontologies are compatible with the base ontology, the base ontology and the external ontologies can be jointly used in the following ways.
+
+##### 1) Classes and properties mapping:
+
+- The names of the class and properties in different ontologies may be totally different, but the meanings of the class and properties can be relevant. Class and property mapping is used to link the relevant classes and properties in different ontologies.
+- The descriptions for the class and property mapping relationship of the base ontology and external ontologies can be given in an ontology or a semantic rule depending on the frequency of the usage. For frequent cases, it is better to give the mapping description in an ontology, even in the base ontology.
+- Class and property mapping can be based on the properties defined in OWL and resource description frameworks (RDFs), e.g., `rdfs:subClassOf`, `owl:equivalentClass`, for classifying the hierarchy of the classes and properties in base ontology and external ontologies. The inheritance from upper properties and classes will be implied according to the mapped hierarchy. For example, when a class A in an external ontology is mapped as a subclass of the class B in the base ontology, it implies that the properties of class B in the base ontology will be inherited by the class A in the external ontology.
+
+Table 1 gives a simple example for class and property mapping between two ontologies.
+
+**Table 1 – An example of class and property mapping between two ontologies**
+
+| Property mapping | | | Class mapping | | |
+|----------------------|-------------------------------------|----------------------------|----------------------|----------------------------------|---------------------|
+| property I | mapping relationship | property II | class I | mapping relationship | Class II |
+| OntologyB: hasSwitch | rdfs:subPropertyOf | OntologyA: hasOperation | OntologyB: appliance | rdfs:subClassOf | OntologyA:device |
+| OntologyA: hasPower | owl:equivalentProperty | OntologyB: hasPower | OntologyB: lamp | owl:equivalentClass | OntologyA:light |
+| OntologyA: hasVendor | owl:equivalentProperty | OntologyB: hasManufacturer | OntologyB: Switch | rdfs:subClassOf | OntologyA:Operation |
+
+##### 2) Individual annotation across multiple ontologies:
+
+- Though the names of classes and properties in different ontologies may be totally different, the semantic annotation for individuals can be done based on these different ontologies, respectively and independently. In this way, knowledge from different ontologies is used together to describe the individuals.
+
+Table 2 gives a simple example of individual annotation across two ontologies.
+
+**Table 2 – An example of individual annotation across two ontologies**
+
+| Individuals | Semantic annotation based on ontology A | | Semantic annotation based on ontology B | |
+|--------------------------------------------------------------|-----------------------------------------|------------------------------------------------------|-----------------------------------------|------------------------------------------------------|
+| | Properties | Classes | Properties | Classes |
+| Light A | rdf:type | Ontology A: Light | rdf:type | Ontology B:ledLight |
+| | OntologyA: hasOperation | Ontology A:Open | OntologyB: hasColor | rdf:datatype="&xsd:string">'red' |
+| | OntologyA: hasStatus | rdf:datatype="&xsd:boolean">true | OntologyB: hasSwitch | OntologyB:Switch |
+| NOTE – The two methods can be used jointly or independently. | | | | |
+
+The compatibility of two ontologies depends on their class hierarchies. When the class hierarchy of one ontology can be mapped as a part or an external part of the class hierarchy of the other ontology, they are compatible. When multiple ontologies are pairwise compatible, they are compatible.
+
+## **6.2 Insights into base ontology**
+
+### **6.2.1 General design principles of the base ontology**
+
+#### **6.2.1.1 General principle**
+
+The base ontology has been designed to provide a minimal number of concepts, relations and restrictions that are necessary for semantic discovery of entities in the oneM2M system. To make such entities discoverable in the oneM2M system, they need to be semantically described as classes (concepts) in a – technology/vendor/other-standard specific – ontology and these classes (concepts) need to be related to some classes of the base ontology as subclasses.
+
+Additionally, the base ontology enables non-oneM2M technologies to build derived ontologies that describe the data model of the non-oneM2M technology for the purpose of interworking with the oneM2M system.
+
+The base ontology only contains classes and properties, but not instances, because the base ontology and derived ontologies are used in oneM2M to only provide a semantic description of the entities they contain.
+
+Instantiation (i.e., data of individual entities represented in the oneM2M system – e.g., devices, things) is done via oneM2M resources
+
+The base ontology is available at [b-oneM2M-Ontologies], which contains the latest version of the ontology and individual versions of the ontology (see Annex A).
+
+#### **6.2.1.2 Essential classes and properties of the base ontology**
+
+Figure 1 shows the essential classes and properties of the base ontology. The nodes (bubbles) denote classes whereas edges (arrows) denote object properties.
+
+
+
+Legend: A class shown with grey shading indicates that the same class appears multiple times in the figure.
+
+Y.4500.12(18)\_F01
+
+Figure 1 – The oneM2M base ontology diagram. This is a complex class diagram showing the relationships between various entities in the oneM2M system. Classes are represented by ovals, and relationships by directed arrows with labels. Key classes include Thing, Device, Service, Function, Command, Operation, DataPoint, Variable, Aspect, and MetaData. Relationships include 'hasThingRelation', 'hasThingProperty', 'is-a', 'isPartOf', 'hasService', 'hasFunction', 'exposes Function', 'hasCommand', 'hasOperation', 'hasInput DataPoint', 'hasOutput DataPoint', 'hasSub Service', 'hasSub Structure', 'describes', 'hasMetaData', and 'hasInput'. Some classes like 'Variable' and 'Aspect' are shaded grey, indicating they are used multiple times. A legend at the bottom left explains this shading. The diagram is identified as Y.4500.12(18)\_F01.
+
+**Figure 1 – The oneM2M base ontology**
+
+Figure 1 can be read as follows:
+
+- A **Thing** in oneM2M (Class: Thing) is an entity that can be identified in the oneM2M system. A Thing may have properties (Object Property: hasThingProperty). A Thing can have relations to other things (object Property: hasThingRelation). For example, a room that is modelled in oneM2M would be a Thing that could have a room-temperature as a ThingProperty (via hasThingProperty) and could have a hasThingRelation "isAdjacentTo" another room. In general, it is assumed that a Thing is not able to communicate electronically with its environment. However, the subclass of Thing that *is* able to interact electronically is called a "Device".
+- A **ThingProperty** (Class: ThingProperty) denotes a property of a Thing. A Thing can be described with (the values of) ThingProperties, but in general the Thing cannot influence that value or being influenced by it. A human or a computer or a device could set the value of a
+
+ThingProperty of a Thing and possibly read it. A ThingProperty can be retrieved or updated by an entity of the oneM2M system. For example, the indoor temperature of a room could be a value of a Thing "Room", or the manufacturer could be a ThingProperty of a Thing "Car". A ThingProperty of a Thing can describe a certain aspect, e.g., the indoor temperature describes the aspect "Temperature" that could be measured by a temperature sensor. A ThingProperty of a Thing can have metadata.
+
+- **Variable** (Class: Variable) constitutes a superclass to the following classes: ThingProperty, OperationInput, OperationOutput, OperationState, InputDataPoint, OutputDataPoint. Its members are entities that have some data (integers, text, etc. or structured data) that can change over time. These data of the Variable usually describe some real-world aspects (e.g., a temperature) and can have MetaData (e.g., units, precision). A Variable can be structured, i.e., it can consist of (sub-)Variables.
+- One subclass is defined in the base ontology:
+ - **SimpleTypeVariable** (Class: SimpleTypeVariable) is a subclass of Variable that only consists of Variables of simple XML types like xsd:integer, xsd:string..., potentially including restrictions.
+ - **MetaData** (Class: MetaData) contain data (units, precision-ranges, etc.) about the Values of a Thing or about an Aspect, e.g., the indoor temperature could have MetaData: "Degrees Celsius".
+ - A **Device** (Class: Device) is a Thing (a subclass of class:Thing) that is designed to accomplish a particular task via the Functions the Device performs. A Device can be able to interact electronically with its environment via a network. A Device contains some logic and is a producer or consumer of data that are exchanged via its Services with other entities (Devices, Things) in the network. A Device interacts through the DataPoints or Operations of its Services. In the context of oneM2M, a Device is always assumed to be capable of communicating electronically via a network (oneM2M or interworked non-oneM2M network) as follows.
+ - In order to accomplish its task, the device performs one or more Functions (Object Property: hasFunction) (Class: Function). These Functions are exposed in the network as Services of the Device.
+ - A Device can be composed of several (sub-)Devices (Object Property: consistsOf) (Class: Device). => consistsOf only Device.
+ - Each Device (including sub-Devices) needs to be individually addressable in the network.
+
+For example, a light switch would be a Device, a combined fridge-freezer would be a Device that consists of a sub-Device Fridge and a sub-Device Freezer.
+
+- A **Function** (Class: Function) represents the Function necessary to accomplish the task for which a Device is designed. A device can be designed to perform more than one Function. The Class: Function exhibits the – humanly understandable – meaning of what the Device "*does*":
+- A Function refers to (e.g., observes or influences) a certain Aspect.
+
+
+For example, considering a light switch, then a related Function could be "Controlling\_ON\_OFF". These Functions would refer to an Aspect "lighting" that is influenced by the Device Light switch.
+- Two subclasses of class Function are defined in the base ontology:
+ - **ControllingFunction** (Class: ControllingFunction) is a subclass of Function that only controls or influences real world Aspects that the Function relates to.
+
+- **MeasuringFunction** (Class: MeasuringFunction) is a subclass of Function that only measures or senses real world Aspects that the Function relates to.
+- An **Aspect** (Class: Aspect) describes the real-world aspect that a Function relates to. Aspect is also used to describe a quality or kind of OperationInput or OperationOutput variables. The Aspect could be a (physical or non-physical) entity or it could be a quality.
+- A **Command** (Class: Command) represents an action that can be performed to support the Function. An Operation exposes a Command to the network. OperationInput and OperationOutput of the related Operation can parameterize the command, for example, the Function "Dimming-Function" could have a Command "setPercentage", with a parameter that has values 0-100.
+- A **Service** (Class: Service) is a representation of a Function to a network that makes the Function discoverable, registerable, remotely controllable in the network. A Service can represent one or more Functions. A Service is offered by a device that wants (a certain set of) its Functions to be discoverable, registerable and remotely controllable by other devices in the network:
+ - while a Function describes the meaning of the device's Function the Service (Class: Service) is used to describe how such Function is represented in a communication network and is therefore dependent on the technology of the network.
+
+For example., the Function: "turn\_light\_On\_or\_Off" could be exposed in the network by a Service "Binary Value Actuator".
+
+ - A Service may be composed of smaller, independent (sub)Services, e.g., re-usable service modules.
+- An **OutputDataPoint** (Class: OutputDataPoint) is a Variable of a Service that is set by a RESTful Device in its environment and that provides state information about the Service. The Device updates the OutputDataPoint autonomously (e.g., at periodic times). To enable a third party to retrieve the current value of an OutputDataPoint (out of schedule) devices often also offer a SET\_OutputDataPoint Operation to trigger the device to update the data of the OutputDataPoint.
+- An **InputDataPoint** (Class: InputDataPoint) is a Variable of a Service that is set by a RESTful Device in its environment and that the Device reads out autonomously (e.g., at periodic times). To enable a third party to instruct the device to retrieve (out of schedule) the current value of an InputDataPoint. Devices often also offer a GET\_InputDataPoint Operation to trigger the device to retrieve the data from the InputDataPoint.
+
+NOTE 1 – Input and Output DataPoints are usually used by Devices (AEs) that communicate in a RESTful way, while Operations are the procedures that are used for remote procedure-based communication. Operations are, however, also needed in RESTful systems to correlate output that is produced by a device, to the input that triggered the production of that output.
+
+- An **Operation** (Class: Operation) is the means of a Service to communicate in a procedure-type manner over the network (i.e., transmit data to or from other devices). An Operation is a representation of a Command to a network:
+ - An Operation can have OperationInput (data consumed by the Device) and OperationOutput (Data produced by the Device), as well as a Method that describes how the Operation is invoked over the network.
+ - An Operation shall have a Data Property "OperationState" that indicates how the operation has progressed in the device.
+ - An Operation is transient, i.e., an Operation can be invoked, possibly produces output and is finished.
+
+- An Operation correlates the output data of the Operation to the input data that were used at Operation invocation.
+- Two subclasses of class Operation are defined in the base ontology:
+ - **GET\_InputDataPoint** (Class: GET\_InputDataPoint) is a subclass of Operation that may be offered by a Device to trigger the device to retrieve the data of an InputDataPoint. (e.g., outside the schedule when the device normally retrieves that DataPoint).
+ - **SET\_OutputDataPoint** (Class: SET\_OutputDataPoint) is a subclass of Operation that may be offered by a Device to trigger the device to update the data of an OutputDataPoint (e.g., outside the schedule when the device normally updates that DataPoint).
+- **OperationInput** (Class: OperationInput) describes the type of input of an Operation to a service of the device. The OperationInput class represents all possible values for that input (data types and ranges or a list of enumerated individuals). An Operation can have multiple OperationInputs or OperationOutputs. If an instance of an Operation is executed, then the input value to that Operation is an instance of its OperationInput classes (e.g., enumerated instances like "ON" or "OFF" for an OperationInput class that sets the state of a switch or a real number within a certain range for a "Temperature" OperationInput class for a thermostat).
+- **OperationOutput** (Class: OperationOutput) describes the type of output of an Operation from a service of the device. The OperationOutput class represents all possible values for that OperationOutput (data types and ranges or a list of enumerated individuals). An Operation can have multiple OperationInputs or OperationOutputs. If an instance of an Operation is executed then the output values of that Operation are instances of its OperationOutput classes.
+- **OperationState** (Class: OperationState) describes the current state during the lifetime of an Operation. The OperationState class represents all possible values for that state (enumerated individuals). The OperationState is set during the progress of the operation by the entity invoking the operation, the entity that is the target of the operation, e.g., a device (or for interworked devices by the IPE) and the CSE. It takes values like "data\_received\_by\_application", "operation\_ended", "operation\_failed", "data\_transmitted\_to\_interworked\_device".
+- **Area network** (Class: AreaNetwork):
+ - An area network (see oneM2M TS-0001 [ITU-T Y.4500.1]) is characterized by its technology:
+ - physical properties (e.g., IEEE\_802\_15\_4\_2003\_2\_4GHz);
+ - communication protocol (e.g., ZigBee\_1\_0); and
+ - potentially a profile (e.g., ZigBee\_HA).
+- **Interworked Device** (Class: InterworkedDevice):
+ - Is part of an AreaNetwork.
+
+NOTE 2 – An Interworked Device is not a oneM2M Device and can be only accessed from the oneM2M system by communicating with a "proxied" (virtual) device that has been created by an IPE. The InterworkedDevice class describes the "proxied" (virtual) device that is represented in the oneM2M system as an individual resource or a child resource of the of its IPE.
+
+### 6.2.2 Use of ontologies for generic interworking with area networks
+
+#### 6.2.2.1 General principle
+
+Interworking with area networks is accomplished in oneM2M through a Function provided by IPEs.
+
+The IPE creates "proxied" devices as oneM2M Resources (e.g., AEs) in the oneM2M Solution that can be accessed by oneM2M Applications in the usual way.
+
+To accomplish the creation of "proxied" devices the IPE uses an ontology that describes the type of interworked area network and its entities (device types, their operations, etc.). For example, in Figure 2, an ontology that describes a KNX area network and its entities would be needed.
+
+To achieve the flexibility for the IPE to create "proxied" Devices for many different types of area networks each ontology that describes a specific type of interworked area network needs to be derived from the base ontology that is specified in this Recommendation, e.g., the OWL representation of an ontology that describes the entities of an area network of type KNX needs to:
+
+- a) contain an "include" statement which includes the base ontology;
+- b) the KNX Nodes class needs to be a subclass of the Device class of the oneM2M base ontology;
+- c) the KNX Communication Objects class needs to be a subclass of the Service class of the base ontology;
+- d) etc.
+
+NOTE – For the purpose of generic interworking with area networks,, the base ontology is only used to describe type information and not for describing instances of these types, e., the base ontology describes the type "Device", but does not contain information about a specific device. The base ontology therefore only contains classes and properties, but not instances.
+
+
+
+The diagram is divided into two main sections: a light blue section on the left labeled 'Area network (e.g., KNX)' and an orange section on the right labeled 'oneM2M compliant solution'. In the blue section, several small circles representing 'real devices in area network' are connected by lines to a central box labeled 'Interworking proxy entity'. In the orange section, several small circles representing '"proxied" devices in the oneM2M system technology' are connected by lines to the same 'Interworking proxy entity' box. Below the proxy entity, in the orange section, is a box labeled 'OneM2M AE'. A curved arrow labeled 'REST-full resource access' points from the 'OneM2M AE' box towards the proxied devices.
+
+Y.4500.12(18)\_F02
+
+Diagram illustrating Interworking between an Area network (e.g., KNX) and a oneM2M compliant solution. The Area network contains real devices. The oneM2M compliant solution contains proxied devices. An Interworking proxy entity connects the real devices to the proxied devices. A OneM2M AE is shown with REST-full resource access.
+
+**Figure 2 – Interworking**
+
+# 7 Description of classes and properties
+
+## 7.1 Classes
+
+### 7.1.1 Class: Thing
+
+See Figure 3.
+
+
+
+**Class: Thing**
+
+Class: Thing
+
+... an OWL class
+
+... an Object property
+
+... a Data property
+
+... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F03
+
+Diagram of the 'Thing' class in an ontology. The 'Thing' class is represented by an oval. It has a self-loop labeled 'hasThingRelation'. It has an outgoing arrow labeled 'hasThingProperty' pointing to a 'Thing Property' oval. It has an incoming arrow labeled 'is-a' from a 'Device' oval. It has an outgoing arrow labeled 'hasThing Description' (in a green box) pointing to a dashed 'rdfs: Literal' box. Below the diagram is a legend: 'Class' (oval) ... an OWL class; 'objectProperty' (grey arrow) ... an Object property; 'dataProperty' (green arrow) ... a Data property; 'is-a' (blue arrow) ... indicates an inheritance (sub-Class/sub-Property).
+
+**Figure 3 – Thing**
+
+#### Description
+
+- A **Thing** in oneM2M (Class: Thing) is an entity that can be identified in the oneM2M system. A Thing that is not a Device is not able to communicate electronically with its environment. However, the subclass of Thing that *is* able to interact electronically is called a "Device". A Thing may have ThingProperties (Object Property: hasThingProperty). A Thing can have relations to other things (Object Property: hasThingRelation). Since a Thing that is not a Device is not able to communicate electronically, it cannot influence the value of its ThingProperties or being influenced by it. Similarly a Thing cannot document its – real-world – relationships (via hasThingRelation) to other Things.
+- For example, a room that is modelled in oneM2M would be a Thing that could have a room-temperature as a ThingProperty and could have a relationship "isAdjacentTo" another room.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- hasThingProperty (range Class: ThingProperty)
+- hasThingRelation (range Class: Thing)
+
+This class is the range Class of Object Property:
+
+- hasThingRelation (domain Class: Thing)
+
+#### Data Properties
+
+- hasThingAnnotation (range datatype: rdfs:Literal)
+
+#### Superclass-subclass Relationships
+
+This class is a subclass of:
+
+- none
+
+This class is a superclass of:
+
+- device
+
+#### Restrictions
+
+This class is an anonymous subclass of:
+
+- hasThingRelation only Thing (Universal restriction: a Thing can *only* have a relationship "hasThingRelation" to other Things)
+- hasThingProperty only ThingProperty
+
+### 7.1.2 Class: ThingProperty
+
+See Figure 4.
+
+
+
+Class: ThingProperty
+
+Class: ThingProperty
+
+ThingProperty is-a Variable
+
+ThingProperty hasThingProperty Thing
+
+ThingProperty hasMetaData (inherited) MetaData
+
+ThingProperty Describes (inherited) Aspect
+
+Class ... an OWL class
+
+objectProperty ... an Object property
+
+dataProperty ... a Data property
+
+is-a ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F04
+
+Figure 4: Class diagram for ThingProperty. It shows ThingProperty as a subclass of Variable (indicated by a blue 'is-a' arrow). ThingProperty has an outgoing 'hasThingProperty' relationship to Thing (indicated by a black arrow with a grey 'objectProperty' label). ThingProperty also has two outgoing relationships: 'hasMetaData (inherited)' to MetaData (indicated by a brown arrow with a grey label) and 'Describes (inherited)' to Aspect (indicated by a brown arrow with a grey label). A legend below explains the symbols: a grey oval for 'Class' (an OWL class), a grey rectangle for 'objectProperty' (an Object property), a green rectangle for 'dataProperty' (a Data property), and a blue rectangle for 'is-a' (indicates inheritance).
+
+Figure 4 – ThingProperty
+
+#### Description
+
+- A **ThingProperty** (Class: ThingProperty) denotes a property of a Thing. A ThingProperty can be observed or influenced by devices, or constitute static data about a Thing, for example, the indoor temperature of the room could be a ThingProperty of a Thing "room". A ThingProperty of a Thing can describe a certain Aspect, e.g., the indoor temperature describes the Aspect "Temperature" that could be measured by a temperature sensor. A ThingProperty of a Thing can have metadata.
+- The class ThingProperty is a subclass of the Variable class.
+
+#### Object Properties
+
+This class is the domain Class of Object Property:
+
+- describes (range Class: Aspect) (inherited from Class: Variable)
+- hasMetaData (range Class: MetaData) (inherited from Class: Variable)
+
+This class is the range Class of Object Property:
+
+- hasThingProperty (domain Class: Thing)
+
+#### Data Properties
+
+This class is part of the domain Class of Data Property:
+
+- Inherited from Class: Variable and possibly Class SimpleTypeVariable (see clauses 6.1.17 and 6.1.18)
+
+#### Superclass-subclass Relationships
+
+This class is a subclass of:
+
+- Variable
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- None
+
+### 7.1.3 Class: Aspect
+
+See Figure 5.
+
+
+
+Class: Aspect
+
+```
+graph LR; Variable((Variable)) -- describes --> Aspect((Aspect)); Function((Function)) -- refersTo --> Aspect; Aspect -- hasMetadata --> Metadata((Metadata))
+```
+
+Legend:
+
+- Class ... an OWL class
+- objectProperty ... an Object property
+- dataProperty ... a Data property
+- is-a ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F05
+
+Figure 5: Class: Aspect. A diagram showing the relationships between Class: Aspect, Variable, Function, and Metadata. Variable describes Aspect, Function refers to Aspect, and Aspect has Metadata.
+
+Figure 5 – Aspect
+
+#### Description
+
+- An **Aspect** (Class: Aspect) describes the real-world aspect that a Function relates to. Aspect is also used to describe the quality or kind of a Variable. The Aspect could be a (physical or non-physical) entity or it could be a quality.
+
+#### Object Properties
+
+This class is the domain Class of Object Property:
+
+- hasMetadata (range Class: Metadata)
+
+This class is the range Class of Object Property:
+
+- refersTo (domain Class: Function)
+- describes (domain Class: Variable)
+
+#### Data Properties
+
+- None
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- None
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- None
+
+### 7.1.4 Class: MetaData
+
+See Figure 6.
+
+
+
+Class: MetaData
+
+```
+graph BT; Variable((Variable)) -- hasMetaData --> MetaData((MetaData)); Aspect((Aspect)) -- hasMetaData --> MetaData;
+```
+
+... an OWL class
+
+... an Object property
+
+... a Data property
+
+... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F06
+
+Figure 6: MetaData class diagram. The diagram shows a central 'MetaData' class (oval) with two incoming arrows from 'Variable' and 'Aspect' classes (ovals). Both arrows are labeled 'hasMetaData'. Below the diagram is a legend: 'Class' (oval) points to '... an OWL class'; 'objectProperty' (grey rectangle) points to '... an Object property'; 'dataProperty' (green rectangle) points to '... a Data property'; 'is-a' (blue rectangle) points to '... indicates an inheritance (sub-Class/sub-Property)'. The text 'Y.4500.12(18)\_F06' is at the bottom right.
+
+**Figure 6 – MetaData**
+
+#### Description
+
+- **MetaData** (Class: MetaData) contain data (like units, precision-ranges ...) about a Variable or about an Aspect, for example, the indoor temperature could have as metadata an individual "Celsius\_Scale" specifying that the temperature needs to be understood as degrees Celsius.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- None
+
+This class is the range Class of Object Property:
+
+- hasMetaData (domain Class: Variable)
+- hasMetaData (domain Class: Aspect)
+
+#### Data properties
+
+- None
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- None
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- None
+
+### 7.1.5 Class: Device
+
+See Figure 7.
+
+
+
+Class: Device
+
+... an OWL class
+
+... an Object property
+
+... a Data property
+
+... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F07
+
+Figure 7: Class: Device. An OWL class diagram showing the 'Device' class and its relationships. 'Device' is a subclass of 'Thing' (indicated by a blue 'is-a' arrow) and a superclass of 'Interworked Device' (indicated by a blue 'is-a' arrow). 'Device' has a self-referencing 'consistsOf' property. It also has three outgoing object properties: 'hasThingProperty' pointing to 'Thing Property', 'hasService' pointing to 'Service', and 'hasFunction' pointing to 'Function'. A legend below the diagram defines the symbols: 'Class' (oval), 'objectProperty' (grey arrow), 'dataProperty' (green arrow), and 'is-a' (blue arrow).
+
+**Figure 7 – Device**
+
+#### Description
+
+- A **Device** (Class: Device) is a Thing (a subclass of class:Thing) that is designed to accomplish a particular task via the Functions the Device performs. A Device can interact electronically with its environment via a network. A Device contains some logic and is a producer or consumer of data that are exchanged via its Services with other oneM2M entities (Devices, Things) in the network. A Device may be a physical or non-physical entity. A Device interacts through the DataPoints or Operations of its Services:
+ - in order to accomplish its task, the device performs one or more Functions;
+ - these Functions are exposed in the network as Services of the Device;
+ - a Device can be composed of several (sub-)Devices;
+ - each Device (including sub-Devices) needs to be individually addressable in the network.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- consistsOf (range Class: Device)
+- hasService (range Class: Service)
+- hasFunction (range Class: Function)
+- hasThingProperty (range Class: ThingProperty) (inherited from Class:Thing)
+
+This class is the range Class of Object Property:
+
+- consistsOf (domain Class: Device)
+
+#### Data properties
+
+- None
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- Thing
+
+This class is a superclass of:
+
+- InterworkedDevice
+
+#### Restrictions
+
+This class is an anonymous subclass of:
+
+- consistsOf only Device (Universal restriction: a Device can have a relationship "consistsOf" *only* to other Devices).
+- hasFunction min 1 Function (Universal restriction: a Device needs to have a relationship "hasFunction" to at least 1 Function).
+- hasService only Service (Universal restriction: a Device can have a relationship "hasService" *only* to Services).
+
+### 7.1.6 Class: InterworkedDevice
+
+See Figure 8.
+
+
+
+Class: InterworkedDevice
+
+Area Network
+
+Interworked Device
+
+Device
+
+isPartOf
+
+is-a
+
+Class ... an OWL class
+
+objectProperty ... an Object property
+
+dataProperty ... a Data property
+
+is-a ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F08
+
+Figure 8: InterworkedDevice. A diagram showing class relationships. 'InterworkedDevice' is a subclass of 'Device' (indicated by a blue arrow labeled 'is-a'). 'InterworkedDevice' is also an instance of 'Area Network' (indicated by a black arrow labeled 'isPartOf'). A legend below explains the symbols: 'Class' (grey oval) for an OWL class, 'objectProperty' (grey rectangle) for an Object property, 'dataProperty' (green rectangle) for a Data property, and 'is-a' (blue arrow) for inheritance.
+
+**Figure 8 – InterworkedDevice**
+
+#### Description
+
+- An **InterworkedDevice** (Class: InterworkedDevice) is a Device – e.g., in an area network – that does not support oneM2M interfaces and can only be accessed from the oneM2M system by communicating with a "proxied" (virtual) device that has been created by an IPE.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- isPartOf (range Class: AreaNetwork)
+
+This class is the range Class of Object Property:
+
+- None
+
+#### Data properties
+
+- None
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- Device
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- None
+
+### 7.1.7 Class: AreaNetwork
+
+See Figure 9.
+
+
+
+Class: AreaNetwork
+
+Area Network
+
+Interworked Device
+
+isPartOf
+
+netTechnologyPhysicalStandard
+
+netTechnology communication Protocol
+
+netTechnology Profile
+
+rdf: PlainLiteral
+
+rdf: PlainLiteral
+
+rdf: PlainLiteral
+
+Class ... an OWL class
+
+objectProperty ... an Object property
+
+dataProperty ... a Data property
+
+is-a ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F09
+
+Figure 9: Class diagram for AreaNetwork. The diagram shows 'Area Network' as a class (oval) with an 'isPartOf' relationship (grey arrow) to 'Interworked Device' (oval). 'Area Network' has three data properties (green arrows) pointing to 'netTechnologyPhysicalStandard', 'netTechnology communication Protocol', and 'netTechnology Profile' (all green rectangles). Each of these data properties points to an 'rdf: PlainLiteral' (dashed rectangle). A legend at the bottom explains the symbols: 'Class' (oval), 'objectProperty' (grey arrow), 'dataProperty' (green arrow), and 'is-a' (blue arrow).
+
+Figure 9 – AreaNetwork
+
+#### Description
+
+- An **AreaNetwork** (Class: AreaNetwork) is a Network that provides data transport services between an Interworked Device and the oneM2M system. Different area Networks can use heterogeneous network technologies that may or may not support IP access.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- None
+
+This class is the range Class of Object Property:
+
+- isPartOf (domain Class: InterworkedDevice)
+
+#### Data properties
+
+- netTechnologyPhysicalStandard (range datatype: rdf:PlainLiteral) which serves for Identification of the physical properties of an area network technology (e.g., IEEE\_802\_15\_4\_2003\_2\_4GHz)
+- netTechnologyCommunicationProtocol (range datatype: rdf:PlainLiteral) which serves for Identification of a communication protocol (e.g., ZigBee\_1\_0)
+
+- netTechnologyProfile (range datatype: rdf:PlainLiteral) which serves for Identification of a profile (e.g., ZigBee\_HA) of an area network technology
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- None
+
+This Class is super-class of:
+
+- None
+
+#### Restrictions
+
+- None
+
+### 7.1.8 Class: Service
+
+See Figure 10.
+
+
+
+**Class: Service**
+
+Class ... an OWL class
+
+objectProperty ... an Object property
+
+dataProperty ... a Data property
+
+is-a ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F10
+
+Figure 10: Service class diagram. The diagram shows a central 'Service' class (oval) with several relationships. 'Device' (oval) has a 'hasService' relationship (grey arrow) pointing to 'Service'. 'Service' has a 'hasSubService' relationship (grey arrow) pointing to itself. 'Service' has an 'exposes Function' relationship (grey arrow) pointing to 'Function' (oval). 'Service' has a 'hasInputDataPoint' relationship (grey arrow) pointing to 'Input DataPoint' (oval). 'Service' has a 'hasOutputDataPoint' relationship (grey arrow) pointing to 'Output DataPoint' (oval). 'Service' has a 'hasOperation' relationship (grey arrow) pointing to 'Operation' (oval). A legend below the diagram defines the symbols: 'Class' (oval) is an OWL class; 'objectProperty' (grey arrow) is an Object property; 'dataProperty' (green arrow) is a Data property; 'is-a' (blue arrow) indicates inheritance. The diagram is labeled Y.4500.12(18)\_F10.
+
+**Figure 10 – Service**
+
+#### Description
+
+- A **Service** (Class: Service) is an electronic representation of a Function in a network. The Service exposes the Function to the network and makes it discoverable, registerable and remotely controllable in the network. A Service is offered by a device that wants (a certain set of) its Functions to be discoverable, registerable or remotely controllable by other devices in the network. A Service can expose one or more Functions and a Function can be exposed by one or more Services.
+- The Input and Output DataPoints and Operations of a Service may have the same names as for a different Service; however, the Service to which they belong differentiates how they are addressed in the Device (e.g., via a port specific to the Service).
+
+NOTE – While a Function describes the – humanly understandable – meaning of a Service of the device, the Service is used to describe how such Function is represented in a communication network and can be accessed by electronic means. The Service and its Operations is therefore dependent on the technology of the network, hard- and software of the device.
+
+- For example., the Function: "turn\_light\_On\_or\_Off" could be exposed in the network by a Service "UPDATE Binary Value".
+
+- Object Property "hasSubService" expresses the fact that Services can be composed of independent (sub)Services, for example, a Service could be composed out of multiple (reusable) service modules. A Dimmer could contain a module "binaryActuator" to turn on/off and additionally "setInteger0-255Actuator" to set the dimming level.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- exposesFunction (range Class: Service)
+- hasOperation (range Class: Operation)
+- hasInputDataPoint (range Class: InputDataPoint)
+- hasOutputDataPoint (range Class: OutputDataPoint)
+- hasSubService (range Class: Service)
+
+If, for a Service, an Operation, Input-, OutputDataPoint or sub-Service is mandatory, then the related Object Property (hasOperation, hasInputDataPoint, hasOutputDataPoint, hasSubService) shall have a Property Restriction with cardinality "min 1".
+
+This class is the range Class of Object Property:
+
+- hasService (domain Class: Device)
+- hasSubService (domain Class: Service)
+
+#### Data properties
+
+- None
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- None
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- hasSubService only Service (Universal restriction: a Service can have a relationship "hasSubService" *only* to other Service)
+- hasOperation only Operation
+- exposesFunction some Function (Universal restriction: at least one of the relationship "exposesFunction" of a Service needs to point of a Function)
+- hasInputDataPoint only InputDataPoint
+- hasOutputDataPoint only OutputDataPoint
+
+### 7.1.9 Class: Function
+
+#### 7.1.9.0 General description
+
+See Figure 11.
+
+Class: Function, Controlling-, Measuring-
+
+
+
+Class: Function, Controlling-, Measuring-
+
+... an OWL class
+
+... an Object property
+
+... a Data property
+
+... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F11
+
+Figure 11 – Function: A diagram showing the relationships between various classes and properties. The central class is 'Function'. It is connected to 'Device' via 'hasFunction', to 'Service' via 'exposesFunction', to 'Command' via 'hasCommand', and to 'Aspect' via 'refersTo'. Additionally, 'Controlling Function' and 'Measuring Function' are shown as subclasses of 'Function' via 'is-a' relationships. A legend below the diagram defines the symbols: 'Class' (oval), 'objectProperty' (grey arrow), 'dataProperty' (green arrow), and 'is-a' (blue arrow).
+
+Figure 11 – Function
+
+##### Description
+
+- A **Function** (Class: Function) represents a particular function necessary to accomplish the task for which a Device is designed. A device can be designed to perform more than one Function. The Function exhibits the – humanly understandable – meaning of what the device "does".
+- A Function refers to (e.g., observes or influences) some real-world aspect(s) that can be modelled as a Class: Aspect.
+- For example, considering a "light switch", then a related Function could be "Controlling\_ON\_OFF" or "Controlling Brightness". These Functions would refer to an Aspect "light-control".
+- A Function of a Device can be influenced or observed by a human user through the Commands that this Function has and that are offered to the user.
+
+##### Object properties
+
+This class is the domain Class of Object Property:
+
+- hasCommand (range Class: Command)
+- refersTo (range Class: Aspect)
+
+This class is the range Class of Object Property:
+
+- exposesFunction (domain Class: Service)
+- hasFunction (domain Class: Device)
+
+##### Data properties
+
+- None
+
+##### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- None
+
+This class is a superclass of:
+
+- ControllingFunction
+- MeasuringFunction
+
+##### **Restrictions**
+
+- None
+
+#### **7.1.9.1 Class: ControllingFunction**
+
+##### **Description**
+
+- A **ControllingFunction** (Class: ControllingFunction) represents a Function that has impacts on the real world, but does not gather data. In general a ControllingFunction has Commands (or Operations of its related Services) that receive input data.
+- For example., a thermostat would have "temperature-adjustment" as a ControllingFunction.
+
+##### **Object properties**
+
+This class is the domain Class of Object Property:
+
+- None
+
+This class is the range Class of Object Property:
+
+- None
+
+##### **Data properties**
+
+- None
+
+##### **Superclass-subclass relationships**
+
+This class is a subclass of:
+
+- Function
+
+This class is a superclass of:
+
+- None
+
+##### **Restrictions**
+
+- None
+
+#### **7.1.9.2 Class: MeasuringFunction**
+
+##### **Description**
+
+- A **MeasuringFunction** (Class: MeasuringFunction) represents a Function that has no impacts on the real world, but only gathers data. In general, a MeasuringFunction has Commands (or Operations of its related Services) that generate output data.
+- For example., a temperature sensor would have "temperature-sensing" as a MeasuringFunction.
+
+##### **Object properties**
+
+This class is the domain Class of Object Property:
+
+- None
+
+This class is the range Class of Object Property:
+
+- None
+
+##### **Data properties**
+
+- None
+
+##### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- Function
+
+This class is a superclass of:
+
+- None
+
+##### Restrictions
+
+- None
+
+### 7.1.10 Class: Operation
+
+#### 7.1.10.0 General description
+
+See Figure 12.
+
+
+
+**Class: Operation**
+
+... an OWL class
+
+... an Object property
+
+... a Data property
+
+... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F12
+
+Figure 12: Operation class diagram. The diagram shows the 'Operation' class as a central entity. It is a subclass of 'Get\_Input DataPoint' and 'Get\_Out DataPoint'. It has a 'hasOperation' relationship with 'Device' and an 'exposes Command' relationship with 'Command'. It has two data properties: 'oneM2M TargetURI' (restricted to 'rdfs: Literal') and 'oneM2M Method' (restricted to 'rdf: PlainLiteral'). It has five object properties: 'hasInput' (leading to 'Operation Input'), 'hasOutput' (leading to 'Operation Output'), 'hasOperation State' (leading to 'Operation State'), 'hasInput DataPoint' (leading to 'Input DataPoint'), and 'hasOutput DataPoint' (leading to 'Output DataPoint'). A legend at the bottom explains the symbols: Class (oval), objectProperty (grey rectangle), dataProperty (green rectangle), and is-a (blue arrow).
+
+**Figure 12 – Operation**
+
+##### Description
+
+- An **Operation** (Class: Operation) is the means of a Service to communicate in a procedure-type manner over the network (i.e., transmit data to/from other devices). It is the – machine interpretable – exposure of a –humanly understandable– Command to a network. An Operation is transient. I.e., an Operation can be invoked, possibly produces output and is finished:
+ - An NoDN or a oneM2M entity [e.g., an application entity (AE)] can invoke an Operation of the Device (oneM2M Device or InterworkedDevice) and that invocation can trigger some action in the Device. If an Operation has input data it may receive input data from:
+ - InputDataPoints (persistent entities), or
+ - OperationInput (transient entities, that are deleted when the Operation finishes);and potentially produce output data into:
+ - OutputDataPoints (persistent entities), or
+ - OperationOutput (transient entities that are deleted when the Operation finishes);
+
+- An Operation correlates the output data of the Operation to the input data that were used at Operation invocation.
+- An Operation has an OperationState that allows a oneM2M entity to be informed on the progress of that operation.
+
+NOTE – The OperationState – which provides information of an ongoing or finished operation – should not be confused with state information about the Device or Service, which potentially could be obtained as output data of some operation.
+
+##### Object properties
+
+This class is the domain Class of Object Property:
+
+- exposesCommand (range Class: Command)
+- hasInput (range Class: OperationInput)
+- hasInputDataPoint (range Class: InputDataPoint)
+- hasOutput (range Class: OperationOutput)
+- hasOutputDataPoint (range Class: OutputDataPoint)
+- hasOperationState (range Class: OperationState)
+
+If for an Operation an OperationInput, OperationOutput, Input-, or OutputDataPoint is mandatory then the related Object Property (hasInput, hasOutput, hasInputDataPoint, hasOutputDataPoint) shall have a Property Restriction with cardinality "min 1".
+
+If for an Operation the OperationState is mandatory then the related Object Property (hasOperationState) shall have a Property Restriction with cardinality "exactly 1".
+
+This class is the range Class of Object Property:
+
+- hasOperation (range Class: Service)
+
+##### Data properties
+
+- oneM2MMethod (range data type: rdf:PlainLiteral)
+- oneM2MTargetURI (range data type: rdfs:Literal)
+
+##### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- None
+
+This class is a superclass of:
+
+- GET\_InputDataPoint
+- SET\_OutputDataPoint
+
+##### Restrictions
+
+- exposesCommand only Command
+- hasInput only OperationInput
+- hasOperationState only OperationState
+- hasOutput only OperationOutput
+
+#### 7.1.10.1 Class: GET\_InputDataPoint
+
+##### Description
+
+- **GET\_InputDataPoint** (Class: GET\_InputDataPoint) is an Operation that may be offered by a Device to trigger the device to retrieve the data of an InputDataPoint (e.g., outside the schedule when the device normally retrieves data from that DataPoint)
+
+##### **Object properties**
+
+This class is the domain Class of Object Property:
+
+- hasInputDataPoint (range Class: InputDataPoint)
+
+This class is the range Class of Object Property:
+
+- None
+
+##### **Data properties**
+
+- None
+
+##### **Superclass-subclass relationships**
+
+This class is a subclass of:
+
+- Operation
+
+This class is a superclass of:
+
+- None
+
+##### **Restrictions**
+
+- None
+
+#### **7.1.10.2 Class: SET\_OutputDataPoint**
+
+##### **Description**
+
+- **SET\_OutputDataPoint** (Class: SET\_OutputDataPoint) is an Operation that may be offered by a Device to trigger the device to update the data of an OutputDataPoint (e.g., outside the schedule when the device normally updates that DataPoint)
+
+##### **Object properties**
+
+This class is the domain Class of Object Property:
+
+- hasOutputDataPoint (range Class: OutputDataPoint)
+
+This class is the range Class of Object Property:
+
+- None
+
+##### **Data properties**
+
+- None
+
+##### **Superclass-subclass relationships**
+
+This class is a subclass of:
+
+- Operation
+
+This class is a superclass of:
+
+- None
+
+##### **Restrictions**
+
+- None
+
+### **7.1.11 Class: Command**
+
+See Figure 13.
+
+
+
+Class: Command
+
+Functionality
+
+Operation
+
+Input DataPoint
+
+Output DataPoint
+
+Command
+
+Operation Input
+
+Operation Output
+
+Class ... an OWL class
+
+objectProperty ... an Object property
+
+dataProperty ... a Data property
+
+is-a ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F13
+
+Figure 13 – Command: An OWL diagram showing the relationships between classes and properties. The 'Class: Command' is central. 'Functionality' has a 'hasCommand' property pointing to 'Command'. 'Operation' has an 'exposesCommand' property pointing to 'Command'. 'InputDataPoint' and 'OutputDataPoint' also have 'exposesCommand' properties pointing to 'Command'. 'Command' has 'hasInput' and 'hasOutput' properties pointing to 'OperationInput' and 'OperationOutput' respectively. A legend below explains the symbols: Class (oval), objectProperty (grey rectangle), dataProperty (green rectangle), and is-a (blue arrow).
+
+**Figure 13 – Command**
+
+#### Description
+
+- A **Command** (Class: Command) represents an action that can be performed to support the Function. A Command is the humanly understandable name of that action invoked in a device or reported by the device. An Operation exposes a Command to the network. OperationInput and OperationOutput of the related Operation can parameterize the command, for example, the Function "dimming-Function" of a light switch that remotely controls a light could have a Command "setLightIntensity", with a parameter that has values 0-100%.
+
+Also InputDataPoints and OutputDataPoints expose Commands to the network. When a Device communicates in a RESTful way then changing (UPDATEing) an InputDataPoint triggers an action in the Device once the Device has read out the data from the InputDataPoint. Similarly, when a Device sets the data of an OutputDataPoint then it provides state information about the Device.
+
+NOTE – In RESTful systems, the names of Input and Output DataPoints are usually chosen in such a way that they express the Command, i.e., the human-understandable meaning (e.g., a binary InputDataPoint of a light switch could have a name "Set\_Light\_Status"). Updating a DataPoint can be interpreted as executing a Command.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- isExposedByOperation (range Class: Operation)
+- hasInput (range Class: OperationInput)
+- hasOutput (range Class: OperationOutput)
+
+This class is the range Class of Object Property:
+
+- hasCommand (domain Class: Function)
+- exposesCommand (domain Class: Operation OR InputDataPoint OR OutputDataPoint)
+
+#### Data properties
+
+- None
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- None
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- hasInput only OperationInput (Universal restriction: a Command can have a relationship "hasInput" *only* to OperationInput)
+- hasOutput only OperationOutput
+- hasInputDataPoint only InputDataPoint
+- hasOutputDataPoint only OutputDataPoint
+
+### 7.1.12 Class: OperationInput
+
+See Figure 14.
+
+
+
+**Class: OperationInput**
+
+```
+graph TD; Operation([Operation]) -- hasInput --> OperationInput([Operation Input]); Command([Command]) -- hasInput --> OperationInput; OperationInput -- is-a --> Variable([Variable]);
+```
+
+Class ... an OWL class
+
+objectProperty ... an Object property
+
+dataProperty ... a Data property
+
+is-a ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F14
+
+Figure 14: OperationInput class diagram and legend. The diagram shows 'Operation' and 'Command' classes pointing to 'OperationInput' via a 'hasInput' property. 'OperationInput' is shown as a subclass of 'Variable' via an 'is-a' relationship. A legend below explains the symbols: 'Class' (grey oval), 'objectProperty' (grey arrow), 'dataProperty' (green arrow), and 'is-a' (blue arrow).
+
+**Figure 14 – OperationInput**
+
+#### Description
+
+- **OperationInput** (Class: OperationInput) describes an input of an Operation of a Service. OperationInput also describes the input of a Command:
+ - OperationInput is transient. An instance of OperationInput is deleted when the instance of its Operation is deleted.
+ - An Operation/Command may have multiple OperationInputs or OperationOutputs. If an instance of an Operation is invoked then the input value to that Operation shall be an instance of its OperationInput class.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- hasMetaData (range Class: MetaData) (inherited from class:Variable)
+- describes (range Class: Aspect) (inherited from class:Variable)
+
+This class is the range Class of Object Property:
+
+- hasInput (domain Class: Operation)
+- hasInput (domain Class: Command)
+
+#### Data properties
+
+This class is part of the domain Class of Data Property:
+
+- Inherited from Class: Variable and possibly Class SimpleTypeVariable (see clauses 6.1.17 and 6.1.18)
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- Variable
+
+NOTE – Since class:SimpleTypeVariable is a sub-class of class:Variable a specific instance of OperationInput may also be a SimpleTypeVariable.
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- None
+
+### 7.1.13 Class: OperationOutput
+
+See Figure 15.
+
+
+
+**Class: OperationOutput**
+
+```
+graph TD; Operation([Operation]) -- hasOutput --> OperationOutput([Operation Output]); Command([Command]) -- hasOutput --> OperationOutput; OperationOutput -- is-a --> Variable([Variable]);
+```
+
+Class ... an OWL class
+
+objectProperty ... an Object property
+
+dataProperty ... a Data property
+
+is-a ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F15
+
+Figure 15: OperationOutput. A diagram showing the relationships between classes and properties. At the top, 'Operation' and 'Command' are connected to 'Operation Output' via a 'hasOutput' property. 'Operation Output' is connected to 'Variable' via an 'is-a' property. A legend at the bottom explains the symbols: 'Class' for an OWL class, 'objectProperty' for an Object property, 'dataProperty' for a Data property, and 'is-a' for inheritance (sub-Class/sub-Property).
+
+**Figure 15 – OperationOutput**
+
+#### Description
+
+- **OperationOutput** (Class: OperationOutput) describes an output of an Operation. OperationOutput also describes the output of a Command:
+ - OperationOutput is transient. An instance of OperationOutput is deleted when the instance of its Operation is deleted
+ - An Operation/Command may have multiple OperationInputs or OperationOutputs
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- hasMetaData (range Class: MetaData) (inherited from class:Variable)
+- describes (range Class: Aspect) (inherited from class:Variable)
+
+This class is the range Class of Object Property:
+
+- hasOutput (domain Class: Operation)
+- hasOutput (domain Class: Command)
+
+#### Data properties
+
+This class is part of the domain Class of Data Property:
+
+- Inherited from Class: Variable and possibly Class SimpleTypeVariable (see clauses 6.1.17 and 6.1.18)
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- Variable
+
+NOTE – Since class:SimpleTypeVariable is a sub-class of class:Variable a specific instance of OperationOutput may also be a SimpleTypeVariable
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- None
+
+### 7.1.14 Class: OperationState
+
+See Figure 16.
+
+
+
+Class: OperationState
+
+The diagram illustrates the class hierarchy and relationships for OperationState. It features three classes represented by ovals: 'Operation' at the top, 'Operation State' in the middle, and 'SimpleType Variable' at the bottom. A vertical arrow points from 'Operation' to 'Operation State', labeled 'hasOperationState'. Another vertical arrow points from 'Operation State' to 'SimpleType Variable', labeled 'is-a'. To the left of the diagram is a legend with four entries, each consisting of a colored box with a label and a corresponding description:
+
+- Class** (grey oval) ... an OWL class
+- objectProperty** (grey rectangle) ... an Object property
+- dataProperty** (green rectangle) ... a Data property
+- is-a** (blue rectangle) ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F16
+
+Figure 16: OperationState diagram showing class relationships and a legend.
+
+Figure 16 – OperationState
+
+#### Description
+
+- **OperationState** (Class: OperationState) describes the current state of an Operation. The OperationState class represents all possible values for that state (enumerated individuals). The OperationState is set during the progress of the operation by the CSE and, optionally, the entity that is the target of the operation, e.g., a device (or for interworked devices by the IPE).
+
+This class contains a text string that is provided by the AE (e.g., an IPE). Values for that text that are specified in oneM2M are:
+
+- "data\_received\_by\_application"
+- "operation\_ended"
+- "operation\_failed"
+- "data\_transmitted\_to\_interworked\_device"
+
+Additional values for the text string of the *operationState* attribute are permissible.
+
+#### Object properties
+
+This class is the range Class of Object Property:
+
+- hasOperationState (domain Class: Operation)
+
+#### Data properties
+
+This class is part of the domain Class of Data Property:
+
+- inherited from Class: Variable (see clause 6.1.17)
+- hasDataType (range data type: xsd:string) (inherited from Class: SimpleTypeVariable, see clause 6.1.18)
+- hasDataRestriction\_Pattern (range data type: xsd:string{"data received by application", "operation ended", "operation failed", "data transmitted to interworked device"}) (inherited from Class: SimpleTypeVariable, see clause 6.1.18)
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- SimpleTypeVariable
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- hasDataRestriction\_pattern exactly 1 xsd:string
+- (hasDataRestriction\_pattern value "data\_received\_by\_application"^^xsd:string) or (hasDataRestriction\_pattern value "data\_transmitted\_to\_interworked\_device"^^xsd:string) or (hasDataRestriction\_pattern value "operation\_ended"^^xsd:string) or (hasDataRestriction\_pattern value "operation\_failed"^^xsd:string)
+
+NOTE – An OperationState has a Data Property "hasDataRestriction" with a pattern of exactly 1 xsd:string. The value of that xsd:string can be: "data\_received\_by\_application", "data\_transmitted\_to\_interworked\_device", "operation\_ended" or "operation\_failed".
+
+### 7.1.15 Class: InputDataPoint
+
+See Figure 17.
+
+
+
+**Class: InputDataPoint**
+
+Class: InputDataPoint
+
+Operation Service
+
+hasInputDataPoint
+
+Input DataPoint
+
+exposes Command
+
+Command
+
+is-a
+
+Variable
+
+Class ... an OWL class
+
+objectProperty ... an Object property
+
+dataProperty ... a Data property
+
+is-a ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F17
+
+UML diagram for Class: InputDataPoint. It shows 'Operation' and 'Service' classes with arrows pointing to 'InputDataPoint' labeled 'hasInputDataPoint'. 'InputDataPoint' has an arrow pointing to 'Command' labeled 'exposes Command'. 'InputDataPoint' also has a blue arrow pointing to 'Variable' labeled 'is-a'. A legend below explains the symbols: 'Class' (grey oval), 'objectProperty' (grey arrow), 'dataProperty' (green arrow), and 'is-a' (blue arrow).
+
+**Figure 17 – InputDataPoint**
+
+#### Description
+
+- **InputDataPoint** (Class: InputDataPoint) is a Variable of a Service that is accessed by a RESTful Device in its environment, which the Device reads out autonomously (e.g., at periodic times). To enable a third party to instruct the device to retrieve (out of schedule) the current value of an InputDataPoint. Devices often also offer a GET\_InputDataPoint Operation to trigger the device to retrieve the data from the InputDataPoint:
+ - An InputDataPoint is a persistent entity.
+
+NOTE 1 – Input and Output DataPoints are usually used by Devices (AEs) that communicate in a RESTful way, while Operations are the procedures that are used for remote procedure based communication. Operations are, however, also needed in RESTful systems to correlate output that is produced by a device to the input that triggered the production of that output.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- hasMetaData (range Class: MetaData) (inherited from class:Variable)
+- describes (range Class: Aspect) (inherited from class:Variable)
+
+This class is the range Class of Object Property:
+
+- hasInputDataPoint (domain Class: Operation)
+- hasInputDataPoint (domain Class: Command)
+
+#### Data properties
+
+This class is part of the domain Class of Data Property:
+
+- Inherited from Class: Variable and possibly Class SimpleTypeVariable (see clauses 6.1.17 and 6.1.18)
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- Variable
+
+NOTE 2 – Since class:SimpleTypeVariable is a sub-class of class:Variable a specific instance of InputDataPoint may also be a SimpleTypeVariable.
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- None
+
+### 7.1.16 Class: OutputDataPoint
+
+See Figure 18.
+
+
+
+**Class: OutputDataPoint**
+
+```
+
+classDiagram
+ class Operation
+ class Service
+ class OutputDataPoint
+ class Command
+ class Variable
+
+ Operation --> OutputDataPoint : hasOutputDataPoint
+ Service --> OutputDataPoint : hasOutputDataPoint
+ OutputDataPoint --> Command : exposes Command
+ OutputDataPoint --|> Variable : is-a
+
+```
+
+Legend:
+
+- Class (oval) ... an OWL class
+- objectProperty (grey rectangle) ... an Object property
+- dataProperty (green rectangle) ... a Data property
+- is-a (blue arrow) ... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F18
+
+Figure 18: Class diagram for OutputDataPoint. It shows classes Operation, Service, OutputDataPoint, Command, and Variable. Operation and Service have arrows pointing to OutputDataPoint labeled 'hasOutputDataPoint'. OutputDataPoint has an arrow pointing to Command labeled 'exposes Command'. OutputDataPoint has a blue arrow pointing to Variable labeled 'is-a'. A legend below explains the symbols: Class (oval), objectProperty (grey rectangle), dataProperty (green rectangle), and is-a (blue arrow).
+
+**Figure 18 – OutputDataPoint**
+
+#### Description
+
+- **OutputDataPoint** (Class: OutputDataPoint) is a Variable of a Service that is set by a RESTful Device in its environment and that the Device updates autonomously (e.g., at periodic times). To enable a third party to instruct the device to update (out of schedule) the current value of an OutputDataPoint. Devices often also offer a SET\_OutputDataPoint Operation to trigger the device to update the data of the OutputDataPoint:
+ - An OutputDataPoint is a persistent entity.
+
+NOTE 1 – Input and Output DataPoints are usually used by Devices (AEs) that communicate in a RESTful way, while Operations are the procedures that are used for remote procedure-based communication. Operations are, however, also needed in RESTful systems to correlate output that is produced by a device to the input that triggered the production of that output.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- hasMetaData (range Class: MetaData) (inherited from class:Variable)
+- describes (range Class: Aspect) (inherited from class:Variable)
+
+This class is the range Class of Object Property:
+
+- hasOutputDataPoint (domain Class: Operation)
+
+- hasOutputDataPoint (domain Class: Command)
+
+#### Data properties
+
+This class is part of the domain Class of Data Property:
+
+- Inherited from Class: Variable and possibly Class SimpleTypeVariable (see clauses 6.1.17 and 6.1.18)
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- Variable
+
+NOTE 2 – Since class:SimpleTypeVariable is a sub-class of class:Variable a specific instance of OutputDataPoint may also be a SimpleTypeVariable.
+
+This class is a superclass of:
+
+- None
+
+#### Restrictions
+
+- None
+
+### 7.1.17 Class: Variable
+
+See Figure 19.
+
+**Class: Variable**
+
+
+
+Class: Variable
+
+... an OWL class
+
+... an Object property
+
+... a Data property
+
+... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F19
+
+Figure 19: Class: Variable. A diagram showing the relationships of the Variable class. The central node is 'Variable'. It has five subclasses: 'Input DataPoint', 'Output DataPoint', 'Operation Input', 'Operation Output', and 'Thing property', all connected by 'is-a' relationships. 'SimpleType Variable' is also a subclass of 'Variable'. 'Variable' has a self-referencing 'hasSub Structure' relationship. It has two data properties: 'oneM2M TargetURI' (pointing to 'rdf: PlainLiteral') and 'oneM2M Method' (pointing to 'rdfs: Literal'). It also has two object properties: 'describes' (pointing to 'Aspect') and 'hasMetaData' (pointing to 'MetaData'). A legend at the bottom explains the symbols: 'Class' (oval), 'objectProperty' (grey rectangle), 'dataProperty' (green rectangle), and 'is-a' (blue arrow).
+
+**Figure 19 – Variable**
+
+#### Description
+
+- A **Variable** (Class: Variable) constitutes a superclass to the following classes: ThingProperty, OperationInput, OperationOutput, OperationState, InputDataPoint, OutputDataPoint, SimpleTypeVariable. Its members are entities that store some data (e.g., integers, text, etc., or structured data) that can change over time. These data of the
+
+Variable usually describe some real-world Aspects (e.g., a temperature) and can have MetaData (e.g., units, precision)
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- hasMetaData (range Class: MetaData)
+- describes (range Class: Aspect)
+- hasSubStructure (range Class: Variable)
+
+If a Variable has a substructure for which certain parts (i.e., Variables of the substructure) are mandatory, then the related Object Property (hasSubStructure) shall have a Property Restriction with cardinality "min 1".
+
+This class is the range Class of Object Property:
+
+- hasSubStructure (domain Class: Variable)
+
+#### Data properties
+
+- oneM2MMethod (range datatype: rdf:PlainLiteral)
+This data property contains a oneM2M Method through which the oneM2M instantiation of the value of the Variable can be manipulated by the communicating entity:
+ - It contains the string "RETRIEVE" for retrieving the variable when the oneM2M resource is of type or . This applies to subclasses: OperationOutput, OutputDatapoint, ThingProperty and OperationState.
+ - It contains the string "CREATE" for updating the variable when the oneM2M resource is of type . This applies to subclasses: OperationInput, InputDatapoint, ThingProperty.
+ - It contains the string "UPDATE" for updating the variable when the oneM2M resource is of type . This applies to subclasses: OperationInput, InputDatapoint, ThingProperty.
+- oneM2MTargetURI (range data type: rdfs: Literal)
+This data property contains the URI of a oneM2M resource ( or ) through which the oneM2M instantiation of the value of the Variable can be manipulated by the communicating entity. It can contain an absolute address or an address relative to the resource that holds the RDF description of the Variable. That address could be, e.g., the value of the parentID for the or of a Input or Output DataPoint that has a child resource of the type that holds the RDF description of the DataPoint.
+
+#### Superclass-subclass relationships
+
+This class is a subclass of:
+
+- None
+
+This class is a superclass of:
+
+- ThingProperty
+- OperationInput, OperationOutput
+- OperationState
+- InputDataPoint
+- OutputDataPoint
+- SimpleTypeVariable
+
+#### Restrictions
+
+- hasSubStructure only Variable
+
+### 7.1.18 Class: SimpleTypeVariable
+
+See Figure 20.
+
+
+
+Class: SimpleTypeVariable
+
+```
+classDiagram
+ class SimpleTypeVariable
+ class Variable
+ class OperationState
+ class rdfsLiteral["rdfs: Literal"]
+ class rdfsLiteral2["rdfs: Literal"]
+ class rdfPlainLiteral["rdf: PlainLiteral"]
+ class rdfPlainLiteral2["rdf: PlainLiteral"]
+
+ SimpleTypeVariable --|> Variable : is-a
+ SimpleTypeVariable --> rdfsLiteral : hasValue
+ SimpleTypeVariable --> rdfsLiteral2 : hasData Restriction
+ SimpleTypeVariable --> rdfPlainLiteral : oneM2M DataType
+ SimpleTypeVariable --> rdfPlainLiteral2 : oneM2M Attribute
+ OperationState --|> SimpleTypeVariable : is-a
+```
+
+... an OWL class
+... an Object property
+... a Data property
+... indicates an inheritance (sub-Class/sub-Property)
+
+Y.4500.12(18)\_F20
+
+UML class diagram for SimpleTypeVariable. The diagram shows SimpleTypeVariable as a subclass of Variable (indicated by an 'is-a' arrow). SimpleTypeVariable has several associations: 'hasValue' to 'rdfs: Literal', 'hasData Restriction' to 'rdfs: Literal', 'oneM2M DataType' to 'rdf: PlainLiteral', and 'oneM2M Attribute' to 'rdf: PlainLiteral'. There is also an 'Operation State' entity with an 'is-a' relationship to SimpleTypeVariable. A legend at the bottom explains the symbols: Class (oval), objectProperty (grey arrow), dataProperty (green arrow), and is-a (blue arrow).
+
+Figure 20 – SimpleTypeVariable
+
+#### Description
+
+- **SimpleTypeVariable** (Class: SimpleTypeVariable) is a subclass of class:Variable that only consists of Variables of simple XML types like xsd:integer, xsd:string, etc., potentially including restrictions
+
+The simple datatypes and -restrictions contained in [b-OWL] are supported.
+
+#### Object properties
+
+This class is the domain Class of Object Property:
+
+- None
+
+This class is the range Class of Object Property:
+
+- None
+
+#### Data properties
+
+This class is part of the domain Class of Data Property:
+
+- Inherited from Class: Variable. (See clause 6.1.17.)
+- hasValue (range data type: rdfs: Literal)
+
+This data property contains the value of the Variable if that value is part of the semantic description and is not contained in a different resource (identified by the oneM2MTargetURI data property). Storing the value of a Variable in a semantic description (i.e., as part of the RDF description in the semanticDescriptor resource) is useful for values that are relatively static (e.g., the name of the manufacturer):
+
+- Data properties "hasValue" and "oneM2MTargetURI" are mutually exclusive. Only one of the two shall be instantiated.
+- oneM2MAttribute (range data: rdf:PlainLiteral)
+This Data Property contains the name of the attribute of the oneM2M resource (of type or ) that is referenced with the oneM2MTargetURI and that stores the value of the SimpleTypeVariable.
+- hasDataType (range datatype: rdf:PlainLiteral)
+This Data Property contains the datatype of the SimpleTypeVariable as text string.
+- hasDataRestriction (range datatype: rdf:PlainLiteral)
+This Data Property contains a restriction of value of the SimpleTypeVariable.
+
+#### **Superclass-subclass relationships**
+
+This class is a subclass of:
+
+- Variable
+
+This class is a superclass of:
+
+- OperationState
+
+#### **Restrictions**
+
+- hasDataType exactly 1 rdf:PlainLiteral
+- hasDataRestriction only rdf:PlainLiteral
+- hasSubStructure exactly 0 Variable
+
+NOTE – A Simple Type Variable has a data type but no other variables as substructure.
+
+## **7.2 Object properties**
+
+### **7.2.1 Void**
+
+### **7.2.2 Void**
+
+### **7.2.3 Object Property: consistsOf**
+
+#### **Description**
+
+- A Device can consist (i.e., be composed) of several (sub-)Devices
+
+#### **Domain Class**
+
+- Device
+
+#### **Range Class**
+
+- Device
+
+### **7.2.4 Object Property: describes**
+
+#### **Description**
+
+- A Variable describes an Aspect (a quality or kind)
+
+#### **Domain Class**
+
+- Variable
+
+#### **Range Class**
+
+- Aspect
+
+### **7.2.5 Object Property: exposesCommand**
+
+#### **Description**
+
+- A – machine interpretable – Operation or an Input/OutputDataPoint of a Service exposes a – humanly understandable – Command to a network.
+
+#### **Domain Class**
+
+- Operation
+
+#### **Range Class**
+
+- Command
+
+### **7.2.6 Object Property: exposesFunction**
+
+#### **Description**
+
+- A Service exposes a Function to the network and makes it discoverable, registerable and remotely controllable in the network.
+
+#### **Domain Class**
+
+- Service
+
+#### **Range Class**
+
+- Function
+
+### **7.2.7 Object Property: hasCommand**
+
+#### **Description**
+
+- A Function of a Device can be influenced or observed by a human user through the Commands that this Function has and which are offered to the user
+
+#### **Domain Class**
+
+- Function
+
+#### **Range Class**
+
+- Command
+
+### **7.2.8 Object Property: hasFunction**
+
+#### **Description**
+
+- In order to accomplish its task, a Device performs one or more Functions
+
+#### **Domain Class**
+
+- Device
+
+#### **Range Class**
+
+- Function
+
+### **7.2.9 Object Property: hasInput**
+
+#### **Description**
+
+- An Operation of a Service of the Device or a Command of a Function of the Device can have OperationInput data.
+
+#### **Domain Class**
+
+- Operation
+
+- Command
+
+#### **Range Class**
+
+- OperationInput
+
+### **7.2.10 Object Property: hasInputDataPoint**
+
+#### **Description**
+
+- A Service or an Operation of a Service of the Device can have InputDataPoints. Communicating entities write data into InputDataPoints and the Device retrieves the data at times according to an internal schedule. An InputDataPoint can also contain the data that are used as input to an Operation.
+
+#### **Domain Class**
+
+- Operation
+- Service
+
+#### **Range Class**
+
+- InputDataPoint
+
+### **7.2.11 Object Property: hasMetaData**
+
+#### **Description**
+
+- A Variable can have MetaData (units, precision ranges, etc.)
+
+#### **Domain Class**
+
+- Variable
+
+#### **Range Class**
+
+- MetaData
+
+### **7.2.12 Void**
+
+### **7.2.13 Object Property: hasOperation**
+
+#### **Description**
+
+- A Service communicates by means of Operations over the network to transmit data to/from other devices
+
+#### **Domain Class**
+
+- Service
+
+#### **Range Class**
+
+- Operation
+
+### **7.2.14 Object Property: hasOperationState**
+
+#### **Description**
+
+- An Operation may have an OperationState that is exposed
+
+#### **Domain Class**
+
+- Operation
+
+#### **Range Class**
+
+- OperationState
+
+### **7.2.15 Void**
+
+### **7.2.16 Object Property: hasOutput**
+
+- An Operation of a Service of the Device or a Command of a Function of the Device can have OperationOutput data
+
+#### **Domain Class**
+
+- Operation
+- Command
+
+#### **Range Class**
+
+- OperationOutput
+
+### **7.2.17 Object Property: hasOutputDataPoint**
+
+#### **Description**
+
+- A Service or an Operation of a Service of the Device can have OutputDataPoints. The Device writes data into OutputDataPoints at times according to an internal schedule and the communicating entities retrieve the data. An OutputDataPoint can also contain the data that are created as output of an Operation.
+
+#### **Domain Class**
+
+- Operation
+- Service
+
+#### **Range Class**
+
+- OutputDataPoint
+
+### **7.2.18 Object Property: hasService**
+
+#### **Description**
+
+- The Functions of a Device are exposed in the network as Services of the Device
+
+#### **Domain Class**
+
+- Device
+
+#### **Range Class**
+
+- Service
+
+### **7.2.19 Object Property: hasSubStructure**
+
+#### **Description**
+
+- A structured Variable can be composed of (sub-)Variables
+
+#### **Domain Class**
+
+- Variable
+
+#### **Range Class**
+
+- Variable
+
+### **7.2.20 Object Property: hasThingProperty**
+
+#### **Description**
+
+- A Thing may have properties that can be described by Values
+
+#### **Domain Class**
+
+- Thing
+
+#### **Range Class**
+
+- Value
+
+### **7.2.21 Object Property: hasThingRelation**
+
+#### **Description**
+
+- A Thing may have relations to itself or to other Things
+
+#### **Domain Class**
+
+- Thing
+
+#### **Range Class**
+
+- Thing
+
+### **7.2.22 Void**
+
+### **7.2.23 Void**
+
+### **7.2.24 Void**
+
+### **7.2.25 Object Property: isPartOf**
+
+#### **Description**
+
+- An InterworkedDevice consist a part of an AreaNetwork
+
+#### **Domain Class**
+
+- InterworkedDevice
+
+#### **Range Class**
+
+- AreaNetwork
+
+### **7.2.26 Object Property: refersTo**
+
+#### **Description**
+
+- A Function of a Device can refer to a certain Aspect (a quality or kind) that is measured or controlled by that Function. e.g., a temperature sensor would refer to the Aspect "Temperature" that it measures
+
+#### **Domain Class**
+
+- Function
+
+#### **Range Class**
+
+- Aspect
+
+## **7.3 Data Properties**
+
+### **7.3.1 Data Property: hasDataType**
+
+Note that in this Recommendation the name space identifier for:
+
+- '' shall be referred to using the prefix: xsd
+- '' shall be referred to using the prefix: owl
+- '' shall be referred to using the prefix: rdf
+
+#### Description
+
+- This Data Property specifies the data type of the SimpleTypeVariable as URI
+
+#### Domain Class
+
+- SimpleTypeVariable
+
+#### Range Datatype
+
+- *xsd:anyURI*
+
+Permissible URIs are:
+
+- for Numbers types (possible restrictions: *xsd:minInclusive*, *xsd:maxInclusive*, *xsd:minExclusive*, *xsd:maxExclusive*):
+ - *owl:real*
+ - *owl:rational*
+ - *xsd:decimal*
+ - *xsd:integer*
+ - *xsd:nonNegativeInteger*
+ - *xsd:nonPositiveInteger*
+ - *xsd:positiveInteger*
+ - *xsd:negativeInteger*
+ - *xsd:long*
+ - *xsd:int*
+ - *xsd:short*
+ - *xsd:byte*
+ - *xsd:unsignedLong*
+ - *xsd:unsignedInt*
+ - *xsd:unsignedShort*
+ - *xsd:unsignedByte*
+- for PlainLiteral – contains all String types (possible restrictions: *xsd:length*, *xsd:minLength*, *xsd:maxLength*, *xsd:pattern*, *rdf:langRange*):
+ - *rdf:PlainLiteral*
+- for String types (possible restrictions: *xsd:length*, *xsd:minLength*, *xsd:maxLength*, *xsd:pattern*):
+ - *xsd:string*
+ - *xsd:normalizedString*
+ - *xsd:token*
+ - *xsd:language*
+ - *xsd:Name*
+ - *xsd:NCName*
+ - *xsd:NMTOKEN*
+- for Boolean Values (no restrictions):
+ - *xsd:boolean*
+- for Binary Data types (possible restrictions: *xsd:minLength*, *xsd:maxLength*, *xsd:length*):
+ - *xsd:hexBinary*
+
+- *xsd:base64Binary*
+- for internationalized resource identifiers (IRIs; possible restrictions: *xsd:minLength*, *xsd:maxLength*, *xsd:length*, *xsd:pattern*):
+ - *xsd:anyURI*
+- for Time Instants (possible restrictions: *sd:minInclusive*, *xsd:maxInclusive*, *xsd:minExclusive*, *xsd:maxExclusive*):
+ - *xsd:dateTime*
+ - *xsd:dateTimeStamp*
+- for Literals:
+ - *rdf:XMLLiteral*
+
+### **7.3.2 Data Property: *hasDataRestriction***
+
+#### **7.3.2.0 General description**
+
+##### **Description**
+
+- This Data Property specifies the restrictions on the data type of the SimpleTypeVariable.
+
+##### **Domain Class**
+
+- SimpleTypeVariable
+
+##### **Range Datatype**
+
+- *rdf:PlainLiteral*
+
+The Data Property "*hasDataRestriction*" shall always be subclassed as one of the following specializations.
+
+The range of a sub-classed Data Property "*hasDataRestriction*" shall be instantiated as the value restricting the data, for example, a value 100 in the range of Data Property: *hasDataRestriction\_minInclusive* specifies that the SimpleTypeVariable can only take values greater or equal to 100.
+
+#### **7.3.2.1 Data Property: *hasDataRestriction\_minInclusive***
+
+For applicability of this subclass of data property: *hasDataRestriction*, see clause 6.3.1.
+
+#### **7.3.2.2 Data Property: *hasDataRestriction\_maxInclusive***
+
+For applicability of this subclass of data property: *hasDataRestriction*, see clause 6.3.1.
+
+#### **7.3.2.3 Data Property: *hasDataRestriction\_minExclusive***
+
+For applicability of this subclass of data property: *hasDataRestriction*, see clause 6.3.1.
+
+#### **7.3.2.4 Data Property: *hasDataRestriction\_maxExclusive***
+
+For applicability of this subclass of data property: *hasDataRestriction*, see clause 6.3.1.
+
+#### **7.3.2.5 Data Property: *hasDataRestriction\_length***
+
+For applicability of this subclass of data property: *hasDataRestriction*, see clause 6.3.1.
+
+#### **7.3.2.6 Data Property: *hasDataRestriction\_minLength***
+
+For applicability of this subclass of data property: *hasDataRestriction*, see clause 6.3.1.
+
+#### **7.3.2.7 Data Property: *hasDataRestriction\_maxLength***
+
+For applicability of this subclass see of data property: *hasDataRestriction*, see clause 6.3.1.
+
+#### **7.3.2.8 Data Property: hasDataRestriction\_pattern**
+
+For applicability of this subclass of data property: hasDataRestriction, see clause 6.3.1.
+
+#### **7.3.2.9 Data Property: hasDataRestriction\_langRange**
+
+For applicability of this subclass of data property: hasDataRestriction, see clause 6.3.1.
+
+### **7.3.3 Data property: hasValue**
+
+#### **Description**
+
+- This data property contains the value of the Variable if that value is part of the semantic description and is not contained in a different resource (identified by the oneM2MTargetURI data property). Storing the value of a Variable in a semantic description (i.e., as part of the RDF description in the semanticDescriptor resource) is useful for values that are relatively static (e.g., the name of the manufacturer):
+ - Data properties "hasValue" and "oneM2MTargetURI" are mutually exclusive. Only one of the two shall be instantiated.
+
+#### **Domain Class**
+
+- SimpleTypeVariable
+
+#### **Range Datatype**
+
+- rdfs: Literal
+
+### **7.3.4 Data Property: netTechnologyCommunicationProtocol**
+
+#### **Description**
+
+- Identifies a communication protocol (e.g., ZigBee\_1\_0)
+
+#### **Domain Class**
+
+- AreaNetwork
+
+#### **Range Datatype**
+
+- netTechnologyCommunicationProtocol rdf:PlainLiteral
+
+### **7.3.5 Data Property: netTechnologyPhysicalStandard**
+
+#### **Description**
+
+- netTechnologyPhysicalStandardIdentification of the physical properties of an area network technology (e.g., IEEE\_802\_15\_4\_2003\_2\_4GHz).
+
+#### **Domain Class**
+
+- AreaNetwork
+
+#### **Range Datatype**
+
+- rdf:PlainLiteral
+
+### **7.3.6 Data Property: netTechnologyProfile**
+
+#### **Description**
+
+- netTechnologyProfileIdentification of a profile (e.g., ZigBee\_HA) of an area network technology
+
+#### **Domain Class**
+
+- AreaNetwork
+
+#### Range Datatype
+
+- rdf:PlainLiteral
+
+### 7.3.7 Data Property: oneM2MTargetURI
+
+#### Description
+
+- oneM2MTargetURI (range data type: rdfs: Literal)
+This data property contains the URI of a oneM2M resource ( or ) through which the oneM2M instantiation of the value of the Variable can be manipulated by the communicating entity. It can contain an absolute address or an address relative to the resource that holds the RDF description of the Variable.
+That address could be e.g.:
+ - The value of the parentID for the or of an Input or Output DataPoint which has child resource of type that holds the RDF description of the DataPoint.
+
+#### Domain Class
+
+- Operation
+- Variable
+
+#### Range Datatype
+
+- rdfs:Literal
+
+### 7.3.8 Data Property: oneM2MAttribute
+
+#### Description
+
+- This Data Property contains the name of the attribute of the oneM2M resource of type or the child resource of the oneM2M resource of type that is referenced with the oneM2MTargetURI and that stores the value of the SimpleTypeVariable:
+ - if the resource-type of the oneM2M resource that is referenced with the oneM2MTargetURI is then this Data Property shall contain the text string "#latest".
+
+#### Domain Class
+
+- SimpleTypeVariable
+
+#### Range Datatype
+
+- rdf:PlainLiteral
+
+### 7.3.9 Data Property: oneM2MMethod
+
+#### Description
+
+- This data property contains a oneM2M CRUD Method through which the oneM2M instantiation of the value of the Variable can be manipulated by the communicating entity:
+ - It contains the string "RETRIEVE" for retrieving the variable when the oneM2M resource is of type or . This applies to subclasses: OperationOutput, OutputDatapoint, ThingProperty and OperationState.
+ - It contains the string "CREATE" for updating the variable when the oneM2M resource is of type . This applies to subclasses: OperationInput, InputDatapoint, ThingProperty.
+
+- It contains the string "UPDATE" for updating the variable when the oneM2M resource is of type . This applies to subclasses: OperationInput, InputDatapoint, ThingProperty.
+
+#### Domain Class
+
+- Variable
+- Operation
+
+#### Range Datatype
+
+- rdf:PlainLiteral
+
+### 7.3.10 Data Property: hasThingAnnotation
+
+#### Description
+
+- This data property contains a description of a Thing.
+- Note: Data Property: hasThingAnnotation should be used in cases where the annotation data do not change very often or where they are usually not the subject of semantic operations (e.g., semantic discovery). Otherwise Object Property: hasThingProperty should be used.
+- For example., a certain type of Device could have the model (as a numeric description) or the name of the manufacturer (as a textual annotation).
+
+#### Domain Class
+
+- Thing
+
+#### Range Datatype
+
+- rdfs: Literal
+
+## 7.4 Annotation properties
+
+### 7.4.1 Annotation Property: resourceDescriptorLink
+
+#### Description
+
+- The *resourceDescriptorLink* annotation property is used to refer to a *semanticDescriptor* resource that contains more information about its subject. Its subject may be any individual and the range shall be the data literal or URI reference that represents the address of the *semanticDescriptor*:
+ - For a oneM2M instantiation of the base ontology the *resourceDescriptorLink* annotation property is used to annotate instances that appear in the range of object properties. The URI points to the *semanticDescriptor* that contains more information about the instance of that class.
+
+NOTE – In OWL DL the definition of property axioms based on annotation properties is not allowed, i.e., it is not possible to define a domain and a range within the ontology itself.
+
+#### Domain Class
+
+- owl:Thing
+
+#### Range Datatype
+
+- xsd:anyURI
+
+# 8 Instantiation of the base ontology and external ontologies to the oneM2M system
+
+## 8.1 Instantiation rules for the base ontology
+
+### 8.1.1 Instantiation of classes of the oneM2M base ontology and derived external ontologies in the oneM2M system
+
+#### 8.1.1.1 General on instantiating classes of the base ontology in the oneM2M system
+
+Clause 8.1.1 describes how the base ontology shall be instantiated in the oneM2M system.
+
+NOTE 1 – Apart from semantically describing oneM2M Solutions, a standardized oneM2M instantiation of the base ontology is also needed for the purpose of Interworking with full semantic mapping when the non-oneM2M data model is described by a oneM2M compliant ontology as described in clause F.5 of oneM2M TS-0001 [ITU-T Y.4500.1].
+
+NOTE 2 – Other instantiations of the base ontology are permissible if interworking according to clause F.5 of oneM2M TS-0001 [ITU-T Y.4500.1] is not required.
+
+Every instantiation of a class of the base ontology (or a subclass thereof) shall be instantiated in a *descriptor* attribute of a oneM2M resource of type **. A ** resource may instantiate multiple classes.
+
+That ** resource shall:
+
+- a) Contain instantiations of classes in the RDF data [b-RDF] of its *descriptor* attribute:
+ - Every instance of a class shall be globally identified within the oneM2M Solution using the *rdf:about* attribute that contains a URI [e.g., based on a media access control (MAC) address of a Device] that is unique within the oneM2M Solution.
+
+NOTE 3 – The choice of a suitable unique URI is outside the scope of oneM2M.
+
+- a) Contain an Ontology-Ref attribute that identifies the class whose instantiation is described in the *descriptor* attribute. Depending on the instantiation, this is a class in the base ontology or a class of another ontology that is a subclass of (includes equals to) a class in the base ontology as defined in clause 6.1.2.2.
+
+The ** shall also contain:
+
+- a) the instantiated Object Properties for which the instantiated class is the domain class;
+- b) the instantiated Data Properties for which the instantiated class is the domain class.
+
+NOTE 4 – Instantiations of the domain class and the range class of an object property may be contained in ** different ** resources.
+
+If the range class of an object property is instantiated in a ** resource that is different to the ** resource in which the domain class is instantiated, then the ** of the instance of the domain class shall contain:
+
+- a) an instance of the *resourceDescriptorLink* annotation property that contains the URI of the *semanticDescriptor* of the instance of the range class.
+
+For specific classes that are indicated in clause 8.1.1.2 (in particular class:OperationState and classes that are derived from class:Variable) the values of Data Properties may be stored in the parent resource of that ** instead of the RDF data [b-RDF] of the *descriptor* attribute.
+
+Any class of a derived external ontology shall be either:
+
+- a subclass of a class of the base ontology; or
+- the range class of some Object Property whose domain class is a class (e.g., class:Thing) or subclass of the base ontology.
+
+If a class of a derived external ontology is a subclass of a class of the base ontology, then it shall be instantiated in the same way as the class of the base ontology.
+
+If a class of a derived external ontology is not a subclass of the base ontology, but is the range class of some Object Property whose domain class is a class or subclass of the base ontology, then it shall be instantiated in the data of the *descriptor* attribute of the ** child resource of the oneM2M resource that instantiates the subclass of the base ontology.
+
+#### 8.1.1.2 Instantiation of individual classes of the base ontology
+
+An overview of the oneM2M resources for instantiating the classes of the oneM2M base ontology is shown in the Figure 21. Different colours indicate different resource types.
+
+
+
+*oneM2M resource for instantiating the oneM2M Base Ontology*
+
+Legend: oneM2M resource types
+
+- , or
+- specialization: genericInterworkingService
+- specialization: genericInterworkingOperationInstance
+
+Y.4500.12(18)\_F21
+
+Figure 21: oneM2M instantiation of the base ontology. This diagram illustrates the relationships between various classes in the oneM2M base ontology, categorized by resource types indicated by background colors. The classes are represented as ovals, and their relationships are shown as directed arrows with labels. The categories are: , or (grey); specialization: genericInterworkingService (yellow); specialization: genericInterworkingOperationInstance (green); and specialization: genericInterworkingDataPoint (light grey). Key relationships include: 'Thing' (grey) has 'ThingProperty' (grey) via 'hasThingProperty' and 'is-a' to 'Variable' (grey); 'Device' (yellow) has 'Interworked Device' (yellow) via 'isPartOf' and 'is-a', and 'Area Network' (grey) via 'isPartOf'; 'Service' (yellow) has 'Function' (yellow) via 'hasFunction' and 'exposes Function', and 'Command' (yellow) via 'hasCommand'; 'Operation' (green) has 'Operation State' (green) via 'hasOperation State' and 'exposes Command'; 'Output DataPoint' (light grey) has 'Input DataPoint' (light grey) via 'hasInputDataPoint' and 'is-a' to 'Variable' (grey); 'Operation Output' (light grey) has 'Operation Input' (light grey) via 'hasInput' and 'is-a' to 'Variable' (grey); 'Variable' (grey) has 'Aspect' (grey) via 'describes' and 'hasMetaData' to 'Meta Data' (grey); 'SimpleType Variable' (grey) has 'Variable' (grey) via 'is-a' and 'hasSub Structure'.
+
+Figure 21 – oneM2M instantiation of the base ontology
+
+- The **Device** class of the oneM2M base ontology (or a subclass thereof that is not an InterworkedDevice) shall be instantiated in the data of the *descriptor* attribute of a resource of type ** that is a child resource of an **.
+
+The Device instance is identified using the *rdf:about* attribute that contains a URI (e.g., the MAC address) that is unique within the oneM2M Solution.
+
+The application logic (identified by its APP-ID of the Device instance) is provided by the Application Entity (AE) of that Device.
+
+NOTE 1 – The *resourceID* of a ** resource that stores the node specific information where this AE resides is contained in the *nodeLink* attribute of the ** of the Device.
+
+- The **InterworkedDevice** class of the oneM2M base ontology (or a subclass) shall be instantiated in the data of the *descriptor* attribute of a resource of type ** that is a child resource of:
+ - an ** resource of its IPE; or
+ - a ** or ** resource that is a child resource of the ** resource of its IPE.
+
+The InterworkedDevice instance is identified using the *rdf:about* attribute that contains a URI (e.g., the device identifier of the device in the interworked system) that is unique within the oneM2M Solution.
+
+The APP-ID of the ** that is the parent (or grand-parent) of the ** which contains an instance of an InterworkedDevice, shall be the APP-ID of the IPE of the InterworkedDevice.
+
+NOTE 2 – The reason for the different instantiation of Device and InterworkedDevice is the following:
+
+Case 1 – native oneM2M Device:
+
+- A oneM2M Device (ASN, ADN – and potentially MN) always has an AE and an ** resource. Therefore the Device class for a oneM2M Device needs to be instantiated in the *descriptor* attribute of the ** child resource of that **.
+
+Case 2 – interworked (non-oneM2M) device:
+
+- In the case of an interworked (non-oneM2M) device the IPE may
+ - Instantiate the InterworkedDevice class for the interworked (non-oneM2M) devices in the *descriptor* attribute of the ** child resource of the ** of the IPE.
+ - The IPE can create multiple ** resources, one for each interworked device. In this case, each interworked device needs to be instantiated in the *descriptor* attribute of the ** child resource of that newly created **.
+ - The IPE can create multiple ** or ** resources as child resources of the ** resource of its IPE, one for each interworked device. In this case, each interworked (non-oneM2M) device needs to be instantiated in the *descriptor* attribute of the ** child resource of that ** or **.
+- The **AreaNetwork** class (or a subclass) shall be instantiated in the data of the *descriptor* attribute of the ** child resource of the oneM2M resource that instantiates the InterworkedDevice class:
+ - The Data Properties "anTechnologyCommunicationProtocol", "anTechnologyPhysicalStandard" and "anTechnologyProfile" are instantiated in the *descriptor* attribute of the ** child resource of the oneM2M resource that instantiates the InterworkedDevice class.
+- The **Service** class (or a subclass) shall be instantiated in the data of the *descriptor* attribute of the ** child resource of a *genericInterworkingService* (specialization of **) resource.
+
+The instance is identified using the *rdf:about* attribute that contains the URI of the Device concatenated with an asterisk "\*" and the class name of the Service (e.g., 00:11:2F:74:2C:8F\*MyService).
+
+The *genericInterworkingService* resource shall be a child resource of the (, or ) resource that contains the that instantiates the Device class. It contains references to the or resources that represent Input or Output Datapoints of the Service.
+
+The **Function** class (or subclass) shall be instantiated in the data of the *descriptor* attribute of the child resource of the oneM2M resource that instantiates the Device class.
+
+The instance is identified using the *rdf:about* attribute that contains the URI of the Device concatenated with an asterisk "\*" and the class name of the Function (e.g., 00:11:2F:74:2C:8F\*MyFunction).
+
+- The **Command** class (or subclass) shall be instantiated in the data of the *descriptor* attribute of the child resource of the oneM2M resource that instantiates the Device class.
+
+The instance is identified using the *rdf:about* attribute that contains the URI of the Device concatenated with an asterisk "\*" and the class name of the Command (e.g., 00:11:2F:74:2C:8F\*MyCommand).
+
+- The **Operation** class (or subclasses) shall be instantiated in the *descriptor* attribute of the child resource of a *genericInterworkingOperationInstance* (specialization of ) resource.
+
+The instance is identified using the *rdf:about* attribute that contains the URI of the Device concatenated with an asterisk "\*" and the class name of the Service, concatenated with an asterisk "\*" and a combination of the class name of the Operation with a number that makes the instance unique within its Service instance during the operation's lifetime (e.g., at a certain point in time a Service instance might have Operation instances with OperationInstances with IDs:
+
+- "00:11:2F:74:2C:8F\*MyService\*MyOperation1",
+"00:11:2F:74:2C:8F\*MyService\*MyOperation5";
+- "00:11:2F:74:2C:8F\*MyService\*MyOtherOperation1";
+- "00:11:2F:74:2C:8F\*MyService\*MyThirdOperation8").
+
+The *genericInterworkingOperationInstance* resource shall be a child resource of the *genericInterworkingService* resource that contains the that instantiates the Service class:
+
+- The range instance of Object Property "hasOperation" that links the instance of the Service to the instance of the Operation shall be annotated with an Annotation Property: resourceDescriptorLink , which shall contain a reference to the resource of type that instantiates the Operation.
+- The **OperationInput** and **OperationOutput** class (or subclass) shall be instantiated in the data of the *descriptor* attribute of the child resource of a or .
+
+The instance is identified using the *rdf:about* attribute that contains the URI of the OperationInstance concatenated with an asterisk "\*" and the class name of the OperationInput and OperationOutput (e.g., 00:11:2F:74:2C:8F\*MyService\*MyThirdOperation8\*MyOperationOutput).
+
+The ** or **, whose ** child resource contains the instance of the OperationInput or OperationOutput shall be a child resource of the *genericInterworkingOperationInstance* resource:
+
+- The range of an instantiation of Object Properties "hasInput" and "hasOutput" that link the instance of the Operation to the instance of the OperationInput and OperationOutput shall be annotated with an Annotation Property: resourceDescriptorLink, which shall contain a reference to the resource of type ** that instantiates the OperationInput and OperationOutput.
+
+- The **InputDataPoint** and **OutputDataPoint** class (or subclass) shall be instantiated in the data of the *descriptor* attribute of the ** child resource of a ** or **.
+
+The instance is identified using the *rdf:about* attribute that contains the URI of the Device concatenated with an asterisk "\*" and the class name of the InputDataPoint or OutputDataPoint (e.g., 00:11:2F:74:2C:8F\*MyInputDataPoint).
+
+The ** or ** resource shall be a child resource of the (**, ** or **) resource, which contains the ** that instantiates the Device class or InterworkedDevice class:
+
+- The range of an instantiation of Object Properties "hasInputDataPoint" and "hasOutputDataPoint" that link the instance of a Service or Operation to the instance of the InputDataPoint and OutputDataPoint shall be annotated with an Annotation Property: resourceDescriptorLink which shall contain a reference to the resource of type ** that instantiates the InputDataPoint and OutputDataPoint.
+
+- ** The **OperationState** class (or subclass) shall be instantiated in the data of the *descriptor* attribute of the ** child resource of the *genericInterworkingOperationInstance* resource that is related via the "hasOperationState" Object Property.
+
+The instance is identified using the *rdf:about* attribute that contains the URI of the OperationInstance concatenated with an asterisk "\*" and "OperationState" (i.e., the class name of the OperationState) (e.g., 00:11:2F:74:2C:8F\*MyService\*MyThirdOperation8\*OperationState):
+
+- The data property "oneM2MTargetURI" shall contain the URI of the *genericInterworkingOperationInstance* resource.
+- The data property "oneM2MAttribute" shall obtain the value "OperationState" (i.e., the name of the Attribute of the OperationState in the *genericInterworkingOperationInstance* resource).
+
+- ** The **Aspect** class (or subclasses) may be instantiated in the data of the *descriptor* attribute of the ** child resource of any resource type that allows a ** child resource.
+
+The instance is identified using the *rdf:about* attribute that contains a URI that is unique within the oneM2M Solution.
+
+NOTE 3 – The choice of a suitable unique URI is outside the scope of oneM2M.
+
+- The **Thing** class (or subclasses) may be instantiated in the data of the *descriptor* attribute of the ** child resource of any resource type that allows a ** child resource:
+
+- The instance is identified using the *rdf:about* attribute that contains a URI that is unique within the oneM2M Solution.
+
+NOTE 4 – The choice of a suitable unique URI is outside the scope of oneM2M.
+
+- The range of an instantiation of Object Property "hasThingRelation" that links the instance of the Thing to the instance of a second Thing shall be annotated with an Annotation Property: resourceDescriptorLink, which shall contain a reference to the resource of type ** that instantiates the second Thing.
+
+NOTE 5 – This reference could refer to Thing, or a Device (as a subclass of Thing).
+
+- The range of an instantiation of an Object Property "hasThingProperty" that links the instance of the Thing to an instance of a ThingProperty shall be annotated with an Annotation Property: resourceDescriptorLink, which shall contain a reference to the resource of type ** that instantiates the ThingProperty**.
+- The **ThingProperty** class (or subclass) shall be instantiated in the data of the *descriptor* attribute of the ** of the Thing or of a separate ** or **.
+The instance is identified using the *rdf:about* attribute that contains the URI of the Thing concatenated with an asterisk "\*" and the class name of the ThingProperty (e.g., *[some out of scope Thing URI]\*MyThingProperty*):
+ - If the ThingProperty is a SimpleTypeVariable and contains in its data property "hasValue", the value of the ThingProperty, then it can be instantiated in the data of the *descriptor* attribute of the ** of the Thing.
+ - Otherwise the ThingProperty shall be instantiated in the data of the *descriptor* attribute of a separate ** or **, which shall be a child resource of the parent resource of ** that instantiates the Thing class. In this case, the range of an Object Property "hasThingProperty" that links an instance of a Thing to the instance of the ThingProperty shall be annotated with an Annotation Property: resourceDescriptorLink, which shall contain a reference to the resource of type ** that instantiates the ThingProperty.
+- The subclasses of the **Variable** class shall be instantiated in the data of the *descriptor* attribute of the ** child resource of resources of a ** or **. If the Variable has a structure (if it is composed of (sub-)Variables) – i.e., it is not a SimpleTypeVariable then:
+ - The ** shall have instances of Object Property "hasSubStructure" and each instance contains in its range an instance of a (sub-)Variable. If that (sub-)Variable is part of a different ** resource then the range of an Object Property "hasSubStructure" shall be annotated with an annotation property: "resourceDescriptorLink", which shall contain a reference to the resource of type ** that instantiates the (sub-)Variable.
+ - The ** shall contain an instance of data property "oneM2MTargetURI", which shall contain the URI of the parent ** or ** resource.
+ - The ** shall have instances of the data property "oneM2MMethod", which indicates a oneM2M CRUD Method through which the oneM2M instance of the value of the Variable can be manipulated by the communicating entity:
+ - It contains the string "RETRIEVE" for retrieving the variable when the oneM2M resource is of type ** or **. This applies to subclasses: OperationOutput, OutputDatapoint, ThingProperty and OperationState.
+ - It contains the string "CREATE" for updating the variable when the oneM2M resource is of type **. This applies to subclasses: OperationInput, InputDatapoint, ThingProperty.
+
+- It contains the string "UPDATE" for updating the variable when the oneM2M resource is of type **. This applies to subclasses: OperationInput, InputDatapoint, ThingProperty.
+- The subclasses of the **SimpleTypeVariable** class shall be instantiated in the data of the *descriptor* attribute of the ** child resource of resources of a ** or **. The data properties are the same as for instances of the Variable class.
+
+In addition:
+
+- The data property "hasValue" contains the value of the Variable if that value is part of the semantic description and is not contained in a different resource (identified by the oneM2MTargetURI data property).
+
+NOTE 6 – Storing the value of a Variable in a semantic description (i.e., as part of the RDF description in the ** resource) is useful for values that are relatively static (e.g., the name of the manufacturer).
+
+- Data properties "hasValue" and "oneM2MTargetURI" are mutually exclusive. Only one of the two shall be instantiated for a SimpleTypeVariable.
+- If data property "oneM2MTargetURI" is instantiated then the data property "oneM2MAttribute" shall also be instantiated and contain:
+ - In the case of a *