IEEE P2961

New IEEE Standard - Active - Draft.
This guide defines a machine learning framework that allows a computing task to be decomposed and distributed across edge and cloud nodes. This guide provides a blueprint for data usage, model learning, and computing collaboration in edge computing environments while meeting latency, privacy, security, and regulatory requirements. It defines the architectural framework and application guidelines for collaborative edge computing, including 1) description and definition of collaborative edge computing, 2) the types of collaborative edge computing, 3) the application scenarios to which each type applies, and 4) performance evaluation of collaborative edge computing in the real application system.

This guide provides a feasible solution for the industrial application of AI to learn an AI model for dynamically distributing computation and using data collectively without direct exchange. It promotes and facilitates computation collaboration and federated machine learning among both edge-edge and edge-cloud nodes, where low-latency service and data protection have become increasingly important.