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Joint computation offloading and resource allocation in multi-cell MEC networks

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Abstract

A widely studied typical mobile edge computing (MEC) system consists of a cloud server, several edge servers, and some user equipment. Each MEC system is also referred to as a cell. In a multi-cell network, there are several different cells, and the cloud servers in different cells can be connected. In this paper, we consider the problem of offloading computing tasks crossing cells in a multi-cell network to improve the user’s quality of experience (QoE). We first investigate a cross-cell task binary computation offloading and resource allocation model for optimizing QoE and formulate this optimization problem as a mixed-integer nonlinear programming (MINLP). Then, for the offline case, we design an efficient exact algorithm (DGOSS) that can find the optimal computation offloading and resource allocation. For the online case, we devise an online algorithm (DTE-DOL) with a sub-linear bounded regret under dynamic computing task generation, dynamic server quota, and uncertain server-side information assumptions. The online algorithm adopts the multi-user Multi-Armed Bandit technique and distributed auction technique. Finally, we compare the performance of the proposed algorithms on different instances with previously existing algorithms. Experimental results show that for the offline case, the DGOSS algorithm can improve the QoE by approximately 5% with about 37.75% less running time, while for the online case, the DTE-DOL algorithm can significantly improve the QoE by around 18.75% with almost the same running time.

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Data availability

The device parameter data in the mobile edge computing network come from the server purchase website (https://ecs-buy.aliyun.com). The parameter data of the computation offloading task are set randomly. Please refer to the website (https://github.com/xiaoqimu/Multi-cell-MEC-networks) for details.

Notes

  1. https://cloud.tencent.com/document/product/213/6091.

  2. https://ecs-buy.aliyun.com.

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Funding

The work is supported by the National Natural Science Foundation of China, under the grant 61972070.

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  1. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China

    Qimu Xiao & Mingyu Xiao

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First author Qimu Xiao contributed the main idea of the model, experiments, and most writing. The second author Mingyu Xiao refined the model and algorithms and polished the presentation.

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Correspondence to Mingyu Xiao.

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Xiao, Q., Xiao, M. Joint computation offloading and resource allocation in multi-cell MEC networks. J Supercomput 81, 459 (2025). https://doi.org/10.1007/s11227-025-06921-8

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