Resource consumption for supporting federated learning in wireless networks

Liu, Y.-J., Qin, S., Sun, Y. and Feng, G. (2022) Resource consumption for supporting federated learning in wireless networks. IEEE Transactions on Wireless Communications, (doi: 10.1109/TWC.2022.3181611) (Early Online Publication)

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Abstract

Federated learning (FL) has recently become one of the hottest focuses in wireless edge networks with the ever-increasing computing capability of user equipment (UE). In FL, UEs train local machine learning models and transmit them to an aggregator, where a global model is formed and then sent back to UEs. In wireless networks, local training and model transmission can be unsuccessful due to constrained computing resources, wireless channel impairments, bandwidth limitations, etc., which degrades FL performance in model accuracy and/or training time. Moreover, we need to quantify the benefits and cost of deploying edge intelligence, as model training and transmission consume certain amount of resources. Therefore, it is imperative to deeply understand the relationship between FL performance and multiple-dimensional resources. In this paper, we construct an analytical model to investigate the relationship between the FL model accuracy and consumed resources in FL empowered wireless edge networks. Based on the analytical model, we explicitly quantify the model accuracy, available computing resources and communication resources. Numerical results validate the effectiveness of our theoretical modeling and analysis, and demonstrate the trade-off between the communication and computing resources for achieving a certain model accuracy.

Item Type:Articles
Status:Early Online Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Sun, Dr Yao
Authors: Liu, Y.-J., Qin, S., Sun, Y., and Feng, G.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
Journal Name:IEEE Transactions on Wireless Communications
Publisher:IEEE
ISSN:1536-1276
ISSN (Online):1558-2248
Published Online:16 June 2022
Copyright Holders:Copyright © 2022 IEEE
First Published:First published in IEEE Transactions on Wireless Communications 2022
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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