Open access
2026
A Reinforcement Learning–Driven Latency Optimization Framework for Heterogeneous Federated Learning on Edge Devices
Heterogeneous federated learning (FL) over edge networks suffers from high end-to-end latency due to coupled delays in model distribution, on-device training and upload, and server-side aggregation. Existing latency-aware FL methods typically optimize only a single stage, such as client scheduling or communication comp...
De-Sheng Sun, Li-Xing Chen, Qi-Lin Wei et al.
· IEEE Access · 0 citations