Summary

A collaborative decentralized machine learning (CDML) architecture can support machine learning (ML) model distributed training and inference across highly heterogeneous and resource-constrained Internet of things (IoT) devices, which results in less latency, higher reliability, lower energy consumption and saving bandwidth resources. Using CDML, spare resources across decentralized IoT devices can be fully used to perform computation-intensive ML tasks collaboratively with high performance.

Recommendation ITU-T Y.4494 introduces CDML for intelligent IoT services, and provides the characteristics and reference architecture of CDML for intelligent IoT services.