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An improved arithmetic optimization algorithm for task offloading in mobile edge computing

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Abstract

The emergence of Mobile Edge Computing (MEC) not only provides low-latency computing services for the User Equipment (UE), but also extends the battery life of the UE. However, the computational resources of MEC servers are usually limited, and how to efficiently offload UE’s task and allocate the resources of MEC servers has become a research hotspot in MEC. In this paper, we develop an improved arithmetic optimization algorithm (IAOA) to optimize the convergence speed and convergence accuracy of the arithmetic optimization algorithm. Then a task offloading algorithm based on IAOA is designed to reduce the cost of offloading tasks in the framework including a single MEC server and multi-UE. The proposed algorithm jointly optimizes the task offloading strategy of the UEs and the resource allocation of the MEC server, meanwhile, models the weighted sum of delay and energy consumption as the system cost, with the goal of minimizing the system cost while satisfying the delay and energy consumption constraints of the tasks. Simulation results show that the proposed algorithm can effectively reduce the system cost and achieve a performance improvement of up to 20% compared with the benchmark algorithm.

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Data availability

The datasets generated during the current study are available from the corresponding author on reasonable request.

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Acknowledgement

This work was supported by Chongqing science and Technology Commission Project (Grant No: cstc2018jcyjAX0525), Key Research and Development Projects of Sichuan Science and Technology Department (Grant No: 2019YFG0107).

Funding

This work was supported by Chongqing science and Technology Commission Project (Grant No: cstc2018jcyjAX0525; Recipient: Hongjian Li), Key Research and Development Projects of Sichuan Science and Technology Department (Grant No: 2019YFG0107;Recipient: Hongjian Li).

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Authors and Affiliations

  1. Department of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Hongjian Li, Jiaxin Liu, Lankai Yang, Liangjie Liu & Hu Sun

Authors
  1. Hongjian Li
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  2. Jiaxin Liu
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  3. Lankai Yang
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  4. Liangjie Liu
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  5. Hu Sun
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Contributions

HL: Proposed an idea, Experiment, Wrote the manuscript. JL: Proposed an idea, Experiment, Wrote the manuscript. LY: Helped to wrote also several sections of the manuscript, Proof reading. LL: Helped to wrote also several sections of the manuscript, Proofreading. HS: Helped to wrote also several sections of the manuscript, Proof reading.

Corresponding author

Correspondence to Hongjian Li.

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None. The authors declare that they have no known conflict financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Li, H., Liu, J., Yang, L. et al. An improved arithmetic optimization algorithm for task offloading in mobile edge computing. Cluster Comput 27, 1667–1682 (2024). https://doi.org/10.1007/s10586-023-04048-0

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