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.
- Sponsor Committee
- C/AISC - Artificial Intelligence Standards Committee
- Active PAR
- PAR Approval