Towards Fast and Energy-Efficient Hierarchical Federated Edge Learning: A Joint Design for Helper Scheduling and Resource Allocation

Wanli Wen, Howard H. Yang, Wenchao Xia, Tony Q.S. Quek

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

Hierarchical federated edge learning (H-FEEL) has been recently proposed to enhance the federated learning model. Such a system generally consists of three entities, i.e., the server, helpers, and clients. Each helper collects the trained gradients from users nearby, aggregates them, and sends the result to the server for model update. Due to limited communication resources, only a portion of helpers can upload their aggregated gradients to the server, thereby necessitating a well design for helper scheduling and communication resources allocation. In this paper, we develop a training algorithm for H-FEEL which involves local gradient computing, weighted gradient uploading, and model updating phases. By characterizing these phases mathematically and analyzing the one-round convergence bound of the training algorithm, we formulate a problem to achieve the scheduling and resource allocation scheme. To solve the problem, we first transform it into an equivalent problem and then decompose the transformed problem into two subproblems: bit and sub-channel allocation problem and helper scheduling problem. For the first subproblem, we obtain a low-complexity suboptimal solution by using a four-stage method. For the second subproblem, we obtain a stationary point by using the penalty convex-concave procedure. The efficacy of our scheme is demonstrated via simulations, and the analytical framework is shown to provide valuable insights for the design of practical H-FEEL system.

原文English
主出版物標題ICC 2022 - IEEE International Conference on Communications
發行者Institute of Electrical and Electronics Engineers Inc.
頁面5378-5383
頁數6
ISBN(電子)9781538683477
DOIs
出版狀態Published - 2022
事件2022 IEEE International Conference on Communications, ICC 2022 - Seoul, Korea, Republic of
持續時間: 2022 5月 162022 5月 20

出版系列

名字IEEE International Conference on Communications
2022-May
ISSN(列印)1550-3607

Conference

Conference2022 IEEE International Conference on Communications, ICC 2022
國家/地區Korea, Republic of
城市Seoul
期間22-05-1622-05-20

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 電氣與電子工程

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