A decentralized game theoretic approach for energy-aware resource management in federated learning

Chit Wutyee Zaw, Choong Seon Hong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The resource management in Federated Learning (FL) system has been a challenging issue since mobile users can save the energy consumption by limiting their computing resources and dataset in training their local models in which users have the energy limitation. We analyze the performance of the global model on the size of dataset and computing resources used for the local training. The performance of the final model is significantly influenced by the resource management of users. Moreover, the decisions of the users on the communication, computing resources and size of dataset can affect the time taken for one computing round. Since a large number of mobile users participate in the FL, a centralized resource management is not practical. Thus, we formulate an energy-aware resource management problem for FL in which users are interested in minimizing the time taken for one computing round with the constraints of energy consumption, communication resources and performance of the training model. Due to the coupling in the communication resource allocation, we formulate the resource management problem as a Generalized Nash Equilibrium Problem (GNEP) and propose a decentralized algorithm. In addition, we analyze the performance of the proposed algorithm on the resource management, energy and time consumption.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE International Conference on Big Data and Smart Computing, BigComp 2021
EditorsHerwig Unger, Jinho Kim, U Kang, Chakchai So-In, Junping Du, Walid Saad, Young-guk Ha, Christian Wagner, Julien Bourgeois, Chanboon Sathitwiriyawong, Hyuk-Yoon Kwon, Carson Leung
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages133-136
Number of pages4
ISBN (Electronic)9781728189246
DOIs
Publication statusPublished - Jan 2021
Event2021 IEEE International Conference on Big Data and Smart Computing, BigComp 2021 - Jeju Island, Korea, Republic of
Duration: 17 Jan 202120 Jan 2021

Publication series

NameProceedings - 2021 IEEE International Conference on Big Data and Smart Computing, BigComp 2021

Conference

Conference2021 IEEE International Conference on Big Data and Smart Computing, BigComp 2021
Country/TerritoryKorea, Republic of
CityJeju Island
Period17/01/2120/01/21

Keywords

  • Decentralized approach
  • Energy-aware resource management
  • Federated learning
  • Generalized nash equilibrium problem

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