Adaptive Decentralized Federated Learning in Energy and Latency Constrained Wireless Networks

arXiv:2403.20075v1 Announce Type: new
Abstract: In Federated Learning (FL), with parameter aggregated by a central node, the communication overhead is a substantial concern. To circumvent this limitation and alleviate the single point of failure within the FL framework, recent studies have introduced Decentralized Federated Learning (DFL) as a viable alternative. Considering the device heterogeneity, and energy cost associated with parameter aggregation, in this paper, the problem on how to efficiently leverage the limited resources available to enhance the model performance …

abstract arxiv communication cs.lg cs.sy decentralized eess.sy energy failure federated learning framework latency networks node studies type wireless