Edge Computing

The gateway is an important component of Internet of things (IoT) systems, enabling IoT devices to connect to communication networks. Edge computing technologies can benefit the IoT, providing computation, storage, networking and intelligence in proximity to IoT devices. Compared with the common gateway [ITU-T Y.4101], the edge-computing-enabled gateway in the IoT (EC-enabled IoT gateway) has additional capabilities supporting service layer interworking, and application layer interworking between IoT devices, IoT platforms and IoT application servers. In addition, the EC-enabled IoT gateway supports data transmission capabilities for IoT applications sensitive to time, latency, jitter and packet loss. Based on the common requirements and capabilities of a gateway for IoT applications [ITU-T Y.4101] and IoT requirements for support of edge computing [ITU-T Y.4208], additional capabilities and capability framework of the edge-computing-enabled gateway in the IoT are specified. Examples of applicability of the edge-computing-enabled gateway in the IoT are also given.

Recommendation ITU-T F.743.12 defines the requirements for edge computing in video surveillance. Edge computing is a distributed computing paradigm aimed at providing various computing services at the edge of the network, and it brings computation and data storage closer to the data source or the location where it is needed, to improve response time and save bandwidth. By using the edge computing technology, the video surveillance system can perform intelligent video analysis and store data near the network premises units. And the edge computing platform provides the management capabilities of the edge resources and functional components to the video surveillance system. It can improve the video processing efficiency and quality of services and reduce the infrastructure cost of the video surveillance system. This Recommendation describes the application scenarios and requirements for edge computing in the video surveillance system.

Recommendation ITU-T Y.3109 specifies quality of service (QoS) assurance-related requirements and a framework for virtual reality (VR) delivery using mobile edge computing (MEC) in International Mobile Telecommunications-2020 (IMT-2020). Recommendation ITU-T Y.3109 first provides an introduction to VR delivery using MEC supported by IMT-2020. It then specifies QoS assurance-related function and mechanism requirements and a framework. The QoS planning for VR services, typical VR user cases and guidelines for deployments of VR services are described in appendices.

Civilian unmanned aerial vehicle (CUAV) enabled mobile edge computing (MEC) utilizes CUAV as an MEC platform to realize a flexible, efficient and on-demand computing service that can be rapidly deployed and move according to the practical service needs of devices. Recommendation ITU-T F.749.11 describes the framework and specifies requirements for a CUAV-MEC system, including functional, service and security requirements.

Recommendation ITU-T F.743.10 specifies the general framework, scenarios and requirements for mobile edge computing- (MEC-)enabled content delivery networks (CDNs). Recommendation ITU_T F.743.10 also specifies the requirements for MEC functions on which a CDN edge node relies. The deployment of a CDN edge node with an MEC system is described in the general framework. Several use cases are introduced in Recommendation ITU-T F.743.10 to illustrate the usage of MEC-enabled CDN.

ISO/IEC 20005:2013 specifies services and interfaces supporting collaborative information processing (CIP) in intelligent sensor networks which includes:
CIP functionalities and CIP functional model,
common services supporting CIP,
common service interfaces to CIP.

This document specifies how to map IPv6 over DECT ULE inspired by [RFC4944], [RFC6282], [RFC6775], and [RFC7668].
Digital Enhanced Cordless Telecommunications (DECT) Ultra Low Energy (ULE) is a low-power air interface technology that is proposed by the DECT Forum and is defined and specified by ETSI. The DECT air interface technology has been used worldwide in communication devices for more than 20 years. It has primarily been used to carry voice for cordless telephony but has also been deployed for data-centric services.

This standard defines a protocol and procedures for the transport of timing over bridged and virtual bridged local area networks. It includes the transport of synchronized time, the selection of the timing source (i.e., best master), and the indication of the occurrence and magnitude of timing impairments (i.e., phase and frequency discontinuities). The PDF of this standard is available at the IEEEGET program. The "IEEE Get Program" grants public access to view and download individual PDFs of select standards at no charge. Visit http://standards.ieee.org/about/get/index.html for details.

The document focuses on the MEC Location Service. It describes the related application policy information including authorization and access control, information flows, required information and service aggregation patterns. The document specifies the necessary API with the data model and data format. It is to be noted that the actual data model and data format which is functional for the present API re-uses the definitions in "RESTful Network API for Zonal Presence" and "RESTful Network API for Terminal Location" published by the Open Mobile Alliance.

The document focuses on the Radio Network Information MEC service. It describes the message flows and the required information. The present document also specifies the RESTful API with the data model.

The document focuses on the functionalities enabled via the Mp1 reference point between MEC applications and MEC platform, which allows these applications to interact with the MEC system. Service related functionality includes registration/deregistration, discovery and event notifications. Other functionality includes application availability, traffic rules, DNS and time of day. It describes the information flows, required information, and specifies the necessary operations, data models and API definitions.

The document describes solutions that allow the deployment of MEC in an NFV environment. For each solution, it describes the motivation for the solution, its architectural impacts and the necessary work to enable it. The document provides recommendations as for where the specification work needs to be done.