Information Age-Based Task Splitting Scheme for Edge Computing-Enabled Networks

This letter focuses on data freshness-based task splitting in edge computing (EC)-enabled networks, where a user’s subtasks are offloaded to EC servers through radio access networks (RANs). A control tower (CT) receives information of available computing resources from EC servers and channel information. Considering the freshness of received information at CT, we define a successful offloading probability (SOP), then formulate the SOP maximization problem by optimizing the task splitting. We propose an alternative algorithm by decomposition with approximation and bisection methods. Numerical results demonstrate the proposed algorithm outperforms a baseline, emphasizing the importance of data freshness on the optimization.

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Publication Details

Journal
IEEE Wireless Communications Letters
Published
2024-11-15
DOI
https://doi.org/10.1109/lwc.2024.3492095
Citations
1
Primary Topic
Age of Information Optimization
Type
article
Field-Weighted Citation Impact
0.35
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article

Information Age-Based Task Splitting Scheme for Edge Computing-Enabled Networks

Jemin Lee, Jinwoong Kim
1 citations
IEEE Wireless Communications Letters
Age of Information Optimization
0.35
article

Information Age-Based Task Splitting Scheme for Edge Computing-Enabled Networks

Jemin Lee, Jinwoong Kim
article en
1 citations

Abstract

This letter focuses on data freshness-based task splitting in edge computing (EC)-enabled networks, where a user’s subtasks are offloaded to EC servers through radio access networks (RANs). A control tower (CT) receives information of available computing resources from EC servers and channel information. Considering the freshness of received information at CT, we define a successful offloading probability (SOP), then formulate the SOP maximization problem by optimizing the task splitting. We propose an alternative algorithm by decomposition with approximation and bisection methods. Numerical results demonstrate the proposed algorithm outperforms a baseline, emphasizing the importance of data freshness on the optimization.

IEEE Wireless Communications LettersVol. 14(2)
Daegu Gyeongbuk Institute of Science and Technology (KR), Yonsei University (KR)
Openalex Percentile: Top 37%
Age of Information Optimization
0.35
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Information Age-Based Task Splitting Scheme for Edge Computing-Enabled Networks — Jemin Lee, Jinwoong Kim · IEEE Wireless Communications Letters (2024) | TGRS Research Map | TGRS