Edge Computing

This Recommendation provides functional requirements of edge cloud. Edge cloud is a cloud computing deployed to the edge of the network. It has small capacity resources enabling cloud service. It addresses the following subjects: - Overview of edge cloud; - Operation of edge cloud in distributed cloud; - Functional requirements of edge cloud; - Use cases of edge cloud in distributed cloud.

This Recommendation provides overview and requirements of edge computing. To provide requirements, this Recommendation defines terms and concept of edge computing, provides reference frameworks for edge computing based on fundamental characteristics and capabilities. Also, this Recommendation provides requirements through various use cases based on reference framework.

This draft Recommendation presents the use cases and technical requirements of application addressing in edge computing for future networks including IMT-2020. Application Addressing is the process to discover the IP address of the server which the application running on when UE intends to access the application This Recommendation specifies the following aspects of application addressing in edge computing in the context for future networks including IMT-2020: Use cases and requirements of application addressing in edge computing for future networks including IMT-2020. FMC architecture enhancement requirements.

Decentralized services (e.g., enabled by distributed ledger technologies, DLT) for IoT devices can be deployed in local area networks (e.g., in IoT devices or in local IoT gateways for constrained IoT devices) or in clouds (e.g., in remote IoT gateways or in cloud systems). When deployed in local area networks, the decentralized services will be affected by the local storage capability of peers and their computation capability and communication latency among peers. When deployed in clouds, the decentralized services will be affected by speed and efficiency of data access. With the popularization of the use of edge computing, part or whole of functionalities of DLT-based decentralized services can be deployed in edge nodes. This draft Recommendation introduces decentralized service by using DLT and edge computing technologies, which is an intermediate supporting service between decentralized services in local area networks and that in clouds. Decentralized service by using DLT and edge computing technologies is deployed in edge nodes and can facilitate interaction among peers of decentralized services, no matter where the peers are deployed (e.g., in local areas or in clouds). This draft Recommendation analyses characteristics and general requirements of decentralized service by using DLT and edge computing technologies, and provides its functional framework and relevant common capabilities, functionalities and general procedures.

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.

ISO/IEC 30163:2021 specifies the system requirements of an Internet of Things (IoT)/Sensor Network (SN) technology-based platform for chattel asset monitoring supporting financial services, including: - System infrastructure that describes functional components; - System and functional requirements during the entire chattel asset management process, including chattel assets in transition, in/out of warehouse, storage, mortgage, etc.; - Performance requirements and performance specifications of each functional component; - Interface definition of the integrated platform system. This document is applicable to the design and development of IoT/SN system for chattel asset monitoring supporting financial services.

IEC 62832-3:2020 specifies rules of the Digital Factory framework for managing information of a production system throughout its life cycle. It also defines how the information will be added, deleted or changed in the Digital Factory by the various activities during the life cycle of the production system.

IEC 62872-2:2022 presents an IoT application framework for industrial facility demand response energy management (FDREM) for the smart grid, enabling efficient information exchange between industrial facilities using IoT related communication technologies. This document specifies:<br /> - an overview of the price-based demand response program that serves as basic knowledge backbone of the IoT application framework;<br /> - a IoT-based energy management framework which describes involved functional components, as well as their relationships;<br /> - detailed information exchange flows that are indispensable between functional components;<br /> - existing IoT protocols that need to be identified for each protocol layer to support this kind of information exchange;<br /> - communication requirements that guarantee reliable data exchange services for the application framework.

IEC 61987-10:2009 provides a method of standardizing the descriptions of process control devices, instrumentation and auxiliary equipment as well as their operating environments and operating requirements (for example, measuring point specification data). The aims of this standard are:<br /> - to define a common language for customers and suppliers through the publication of Lists of Properties (LOPs),<br /> - to optimize workflows between customers and suppliers as well as in processes such as engineering, development and purchasing within their own organizations,<br /> - to reduce transaction costs.<br /> The standard describes industrial-process device types and devices using structured lists of properties and makes the associated properties available in a component data dictionary. This bilingual version, published in 2010-11, corresponds to the English version. The French version of this standard has not been voted upon.<br /> <br /> This publication is to be read in conjunction with <a href="http://webstore.iec.ch/webstore/webstore.nsf/ArtNum_PK/37363">IEC 61987-1:2006</a>.

IEC 61987-1:2006 defines a generic structure in which product features of industrial-process measurement and control equipment with analogue or digital output should be arranged, in order to facilitate the understanding of product descriptions when they are transferred from one party to another. It applies to the production of catalogues of process measuring equipment supplied by the manufacturer of the product and helps the user to formulate his requirements.

With the development of industry, cloud computing and edge computing are widely used. Especially in the industrial machine vision system, with the increase of data-intensive applications and computing-intensive applications, it is necessary to use the powerful computing capabilities and communication resources of cloud computing, collaborate with the short-time response capabilities of edge computing to realize and complete corresponding application requests. Through collaborative work, the value of edge computing and cloud computing will be maximized, thereby effectively improving the performance of industrial machine vision systems.
Cloud-edge collaboration technology is a collaborative method of cloud computing and edge computing, including data collaboration, resource collaboration, intelligent collaboration, service collaboration and application collaboration. At the same time, cloud-edge collaboration in industrial machine vision system will meet the needs of intelligent analysis and real-time response business in different scenarios.
This Recommendation specifies requirements and reference framework of cloud-edge collaboration in industrial machine vision system.

Under development