Committed to connecting the world

  •  
ITU GSR 2024

ITU-T work programme

[2017-2020] : [SG20] : [Q3/20]

[Declared patent(s)]  - [Publication]

Work item: Y.CDML-arc
Subject/title: Reference architecture of collaborative decentralized machine learning for intelligent IoT services
Status: [Carried to next study period]
Approval process: AAP
Type of work item: Recommendation
Version: New
Equivalent number: -
Timing: -
Liaison: IEEE, ISO/IEC JTC1 SC42
Supporting members: China Mobile, ZTE, China Unicom, BUPT, NUPT
Summary: A collaborative decentralized machine learning (CDML) architecture can support ML model distributed training and inference across highly heterogeneous and resource-constrained IoT devices, which results in less latency, higher reliability, lower energy consumption, and saving bandwidth resources. With using CDML, spare resources across decentralized IoT devices can be fully used to perform computation-intensive ML tasks collaboratively with high performance. This Recommendation introduces collaborative decentralized machine learning (CDML) for intelligent IoT services, and provides the characteristics and reference architecture of CDML for intelligent IoT services.
Comment: -
Reference(s):
  Historic references:
Contact(s):
Wei Qu, Editor
Kai Wang, Editor
ITU-T A.5 justification(s):
Generate A.5 drat TD
-
[Submit new A.5 justification ]
See guidelines for creating & submitting ITU-T A.5 justifications
First registration in the WP: 2020-11-18 19:07:31
Last update: 2021-10-29 12:29:47