Journal of South China University of Technology(Natural Science) >

2025 , Vol. 53 >Issue 3: 88 - 96

DOI: https://doi.org/10.12141/j.issn.1000-565X.240262

Electronics, Communication & Automation Technology

Digital Twin Assisted Edge Computing Task Offloading and Resource Allocation Strategy in Industrial Internet of Things

  • LI Song ,
  • LI Yiming ,
  • LI Shun
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  • 1.School of Information and Control Engineering，China University of Mining and Technology，Xuzhou 221116，Jiangsu，China
    2.Xuzhou Engineering Research Center of Intelligent Industry Safety and Emergency Collaboration，Xuzhou 221116，Jiangsu，China
李松（1985—），男，博士，副教授，主要从事B5G/6G无线通信、智能工业物联网与应急通信研究。E-mail： lisong@cumt.edu.cn

Received date: 2024-05-27

  Online published: 2024-09-25

Supported by

the Natural Science Foundation of Jiangsu Province(BK20200650)

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Abstract

In the industrial Internet of Things, the reliability of mobile edge computing largely depends on the wireless channel conditions. In order to process the influence of imperfect channel state information to the system, this paper proposed a digital twin assisted mobile edge computing energy consumption optimization method. For the task offloading problem in industrial Internet of Things, a digital twin model of devices and channels in the edge computing system was established. Considering imperfect channel state information, the joint optimization of offloading decisions, transmission power, channel resources, and computational resources is performed with the aim of minimizing the total system energy consumption. To deal with the proposed nonlinear non convex problem of mixed integers, the probabilistic delay constraint was transformed and the original problem was decomposed into two sub-problems, and a joint optimization algorithm with the assistance of digital twins based on continuous convex approximation was proposed. Firstly, the original problem was relaxed to obtain resource allocation schemes and task offloading priorities. Then, the offloading priority of each terminal device was sorted in descending order. The complete task offloading scheme was obtained by solving the iterative optimization problem. Finally, simulation results show that, compared to other benchmark schemes, the proposed computational offloading optimization scheme significantly reduces the total energy consumption of the system.

Key words： mobile edge computing; task offloading; digital twin network; imperfect channel state information

Cite this article

LI Song , LI Yiming , LI Shun . Digital Twin Assisted Edge Computing Task Offloading and Resource Allocation Strategy in Industrial Internet of Things[J]. Journal of South China University of Technology(Natural Science), 2025 , 53(3) : 88 -96 . DOI: 10.12141/j.issn.1000-565X.240262

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