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Joint optimization strategy of heterogeneous resources in multi-MEC-server vehicular network

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Abstract

As an important application scenario of Internet of Things in 5G, the vehicular network will produce a large number of computing tasks and data, which will bring huge pressures to the limited on-board resource, so shorter task processing delay is required. Mobile edge computing (MEC) is a promising paradigm to achieve low-latency and low-energy consumption by allowing Vehicle Users (VUs) to offload tasks to the MEC server. However, a single MEC server serves multiple VUs which is prone to resource congestion. In this paper, a scenario of multi-vehicle users and multi-MEC servers in vehicular networks composed of heterogeneous resources is built. In order to make full use of the resources and maximize the average system utility, the joint optimization problem of tasks offloading and heterogeneous resource allocation is formulated as a mixed integer nonlinear problem, where the transmission power allocation scheme, computing resource allocation scheme and optimal offloading policy are given. Then, the three-stage Multi-round combined offloading scheduling mechanism and joint resource allocation strategy is proposed, which decomposes the joint optimization problem of tasks offloading and heterogeneous resource allocation into three stages. Due to the coupling relationship between resource allocation and task offloading, a stable convergent solution can be obtained after several iterations. Finally, the simulation results show that with the increase of workloads and vehicle numbers, compared with other algorithms, the proposed algorithm has better performance on system utility.

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Funding

This study is funded by the following projects and foundations: National Natural Science Foundation of China (61801065, 61601071), Program for Chan-gjiang Scholars and Innovative Research Team in University (PCSIRT) of Ministry of Education of China (IRT16R72), Chongqing Innovation and Entrepreneurship Project for Returned Chinese Scholars (cx2020059), and General project on the foundation and cutting-edge research plan supported by Natural Science Foundation of Chongqing (No. cstc-2018jcyjAX0463).

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Author notes

  1. Ziqi Liu, Shamim Hasan and Yunfei Xu have contributed equally to this work.

Authors and Affiliations

  1. Chongqing Key Laboratory of Mobile Communications Technology, Engineering Research Center of Mobile Communications of the Ministry of Education, School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Haibo Zhang, Ziqi Liu, Shamim Hasan & Yunfei Xu

Authors
  1. Haibo Zhang
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  2. Ziqi Liu
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  3. Shamim Hasan
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  4. Yunfei Xu
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Correspondence to Ziqi Liu.

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Zhang, H., Liu, Z., Hasan, S. et al. Joint optimization strategy of heterogeneous resources in multi-MEC-server vehicular network. Wireless Netw 28, 765–778 (2022). https://doi.org/10.1007/s11276-021-02857-y

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