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research-article

BiLSTM-based Federated Learning Computation Offloading and Resource Allocation Algorithm in MEC

Authors:

Xiangjun Zhang,

Song LiuAuthors Info & Claims

ACM Transactions on Sensor Networks, Volume 19, Issue 3

Article No.: 68, Pages 1 - 20

https://doi.org/10.1145/3579824

Published: 01 March 2023 Publication History

Abstract

Mobile edge computing (MEC) driven by 5G cellular systems has recently emerged as a promising paradigm, enabling mobile devices (MDs) with limited computing resources to offload various computation-intensive tasks (such as autopilot, online game) to edge servers to enhance the data processing capabilities of MDs. However, the uncertainty of wireless channel state and data volume of offloading tasks, as well as the data security privacy of offloading tasks, bring serious challenges to computation offloading in MEC. In this article, we consider a time-varying MEC scenario and formalize the delay and energy consumption during the computation offloading process as a joint optimization problem. Then the optimization problem is decomposed into two sub-problems: intelligent task prediction and resource allocation. Different from traditional methods, we improve the federated learning (FL) algorithm and propose a thoughtful cloud-edge-client FL task prediction mechanism based on Bidirectional Long Short-Term Memory. Each participating MD trains the model locally without uploading data to the server, and periodically aggregates the model in the edge and in the cloud. The algorithm both eliminates the need to solve complex optimization problems and ensures user privacy security. Finally, experimental results show that our proposed algorithm significantly outperforms other benchmark algorithms in energy efficiency.

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BiLSTM-based Federated Learning Computation Offloading and Resource Allocation Algorithm in MEC

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Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 19, Issue 3

August 2023

597 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/3584865

Editor:
Yunhao Liu
Tsinghua University, China

Issue’s Table of Contents

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 01 March 2023

Online AM: 12 January 2023

Accepted: 27 December 2022

Revised: 08 December 2022

Received: 21 April 2022

Published in TOSN Volume 19, Issue 3

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National Natural Science Foundation of China
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Natural Science Basic Research Program of Shaanxi

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