数字孪生辅助的工业物联网边缘计算任务卸载和资源分配策略

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

华南理工大学学报(自然科学版) ›› 2025, Vol. 53 ›› Issue (3): 88-96.doi: 10.12141/j.issn.1000-565X.240262

• 电子、通信与自动控制 • 上一篇下一篇

数字孪生辅助的工业物联网边缘计算任务卸载和资源分配策略

李松¹^,²(), 李一鸣¹, 李顺¹

^1.中国矿业大学信息与控制工程学院，江苏徐州 221116
^2.徐州市智能安全与应急协同工程研究中心，江苏徐州 221116

收稿日期:2024-05-27 出版日期:2025-03-10 发布日期:2024-09-27
作者简介: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
基金资助:
江苏省自然科学基金项目(BK20200650);西安市网络融合通信重点实验室开放基金项目(2022NCC-N103);海南省省属科研院所技术创新项目(KYYSGY2024-005);工信部项目(CBG01N23-01-04)

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

LI Song¹^,²(), LI Yiming¹, LI Shun¹

^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

Received:2024-05-27 Online:2025-03-10 Published:2024-09-27
Supported by:
the Natural Science Foundation of Jiangsu Province(BK20200650)

摘要/Abstract

摘要：

在工业物联网中，移动边缘计算的可靠性很大程度上取决于无线信道条件。针对工业物联网中边缘计算任务卸载过程非完美信道状态信息对系统的影响，该文提出了一种数字孪生辅助的移动边缘计算能耗优化方法。对于工业物联网中的任务卸载问题，建立边缘计算系统中设备、信道的数字孪生模型，考虑非完美信道状态信息，联合优化卸载决策、发射功率、信道资源和计算资源，建立了系统总能耗最小化问题。为解决所提出的混合整数的非线性非凸问题，将概率时延约束进行转换，并将原问题分解为资源分配方案与卸载策略2个子问题，提出了一种基于连续凸逼近的联合优化算法，在数字孪生的辅助下联合优化卸载策略与资源分配方案。首先，将原问题进行松弛处理，以获得所有终端设备的资源分配方案与任务卸载优先级；然后，对各终端设备的卸载优先级进行降序排序，通过求解迭代优化问题获得完整的任务卸载方案。仿真结果表明，与其他基准方案相比，所提的计算卸载优化方案显著降低了系统的总能耗。

关键词: 移动边缘计算, 任务卸载, 数字孪生网络, 非完美信道状态信息

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

中图分类号:

TN929.5

李松, 李一鸣, 李顺. 数字孪生辅助的工业物联网边缘计算任务卸载和资源分配策略[J]. 华南理工大学学报(自然科学版), 2025, 53(3): 88-96.

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 Edition), 2025, 53(3): 88-96.

图/表 5

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数字孪生辅助的工业物联网边缘计算任务卸载和资源分配策略

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

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