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Open Access

Utility Aware Offloading for Mobile-Edge Computing

Ran Bi( ), Qian Liu, Jiankang Ren, Guozhen Tan
School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.
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Abstract

Mobile-edge computing casts the computation-intensive and delay-sensitive applications of mobile devices onto network edges. Task offloading incurs extra communication latency and energy cost, and extensive efforts have focused on offloading schemes. Many metrics of the system utility are defined to achieve satisfactory quality of experience. However, most existing works overlook the balance between throughput and fairness. This study investigates the problem of finding an optimal offloading scheme in which the objective of optimization aims to maximize the system utility for leveraging between throughput and fairness. Based on Karush-Kuhn-Tucker condition, the expectation of time complexity is analyzed to derive the optimal scheme. A gradient-based approach for utility-aware task offloading is given. Furthermore, we provide an increment-based greedy approximation algorithm with 1+1e-1 ratio. Experimental results show that the proposed algorithms can achieve effective performance in utility and accuracy.

Keywords

utilityapproximation algorithmquality of experiencemobile edge computing

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Tsinghua Science and Technology
Volume 26 Issue 2,
April 2021
Pages 239-250
DOI: 10.26599/TST.2019.9010062
Cite this article:
Bi R, Liu Q, Ren J, et al. Utility Aware Offloading for Mobile-Edge Computing. Tsinghua Science and Technology, 2021, 26(2): 239-250. https://doi.org/10.26599/TST.2019.9010062

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Received: 09 December 2019
Accepted: 16 December 2019
Published: 24 July 2020
© The author(s) 2021.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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