Reputation-Aware Hedonic Coalition Formation for Efficient Serverless Hierarchical Federated Learning

• Published in: IEEE transactions on parallel and distributed systems Vol. 33; no. 11; pp. 2675 - 2686
• Main Authors: Ng, Jer Shyuan, Lim, Wei Yang Bryan, Xiong, Zehui, Cao, Xianbin, Jin, Jiangming, Niyato, Dusit, Leung, Cyril, Miao, Chunyan
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Base stations; Clusters; Collaborative work; Computational modeling; Computer architecture; Costs; decentralized edge intelligence; Efficiency; Federated learning; hedonic coalition formation; Machine learning; Magnetic heads; Mathematical models; Parameters; Privacy; Radio equipment; Relaying; Reputations; serverless federated learning; Servers; Training

Amid growing concerns on data privacy, Federated Learning (FL) has emerged as a promising privacy preserving distributed machine learning paradigm. Given that the FL network is expected to be implemented at scale, several studies have proposed system architectures towards improving the network scala...