| 引用本文： |
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杜利俊,李陶深,黄翊芯,漆治君.基于SWIPT的D2D通信辅助移动边缘计算任务卸载策略[J].广西科学,2023,30(4):754-763. [点击复制]
- DU Lijun,LI Taoshen,HUANG Yixin,QI Zhijun.Task Offloading Strategy of D2D Communication Assisted MEC Based on SWIPT[J].Guangxi Sciences,2023,30(4):754-763. [点击复制]
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| 摘要: |
| 为解决5G移动通信系统中移动用户计算能力不足、能量消耗多、无线资源缺乏等问题，本文构建一种基于无线携能通信(Simultaneous Wireless Information and Power Transfer，SWIPT)的多用户设备间(Device to Device，D2D)通信辅助移动边缘计算(Mobile Edge Computation，MEC)系统模型，提出一种D2D-MEC联合卸载策略。该策略以系统中请求用户总能耗最小化为目标，采用二进制卸载模式和功率分流模式对请求用户进行任务卸载和能量收集。针对能耗最小化问题为非线性混合整数规划问题，根据整数变量和实数变量将原问题解耦为功率分配和计算任务卸载两个独立子问题，并分别采用Dinkelbach方法和匈牙利算法求出两个子问题的最优解。仿真实验结果表明，本文所提策略优于传统的D2D卸载策略和MEC卸载策略，有效降低了请求用户的总能耗，提高了任务执行效率。 |
| 关键词: 无线携能通信 移动边缘计算 设备间通信 任务卸载 功率分配 |
| DOI：10.13656/j.cnki.gxkx.20230928.015 |
| 投稿时间：2022-03-08修订日期：2022-04-21 |
| 基金项目:国家自然科学基金项目(61762010)和广西科技计划项目(桂科AD20297125)资助。 |
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| Task Offloading Strategy of D2D Communication Assisted MEC Based on SWIPT |
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DU Lijun1, LI Taoshen1,2, HUANG Yixin1, QI Zhijun1
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| (1.School of Computer, Electronics and Information, Guangxi University, Nanning, Guangxi, 530004, China;2.China-ASEAN International Join Laboratory of Integrate Transport, Nanning University, Nanning, Guangxi, 530200, China) |
| Abstract: |
| In order to solve the problems of insufficient calculate capability,high energy consumption and scarce wireless resources of mobile users in 5G mobile communication system,a multi-user Device to Device (D2D) communications assisted Mobile Edge Computation (MEC) system model based on Simultaneous Wireless Information and Power Transfer (SWIPT) is constructed,and a D2D-MEC joint offloading strategy is proposed.The strategy aims to minimize the total energy consumption of the requesting users in the system,and uses binary offloading mode and power splitting mode to offload tasks and collect energy for the requesting users.For the problem of energy consumption minimization is a nonlinear mixed integer programming problem,the original problem is decoupled into two independent sub-problems: power allocation and computing task offloading according to integer variables and real variables,and then the optimal solutions of the two sub-problems are obtained by Dinkelbach method and Hungarian algorithm.The simulation results show that the proposed strategy is superior to the traditional D2D offloading strategy and MEC offloading strategy,which effectively reduces the total energy consumption of the requesting users and improves the efficiency of task execution. |
| Key words: simultaneous wireless information and power transfer mobile edge computing D2D communications task offloading power allocation |
