无线供电MEC中基于S-PSO的任务卸载策略研究

Research on task offloading strategy based on S-PSO in wireless powered MEC

随着5G技术和物联网的快速发展,大量的物联网设备接入到无线通信网络中,由于物联网设备计算和能量资源有限,将移动边缘计算(MEC)和无线供电技术(WPT)集成,可以给移动设备(MD)提供能量和计算任务处理服务。首先构建了多用户设备多服务器的任务卸载模型,然后在粒子群优化算法的基础上,加入Levy飞行策略和改进的权重更新方法,提出了S-PSO算法来优化系统的时延与能耗,最后仿真结果表明,S-PSO算法与其他基准方案相比较,有效降低了系统的时延与能耗,提高了计算网络的性能。

With the rapid development of 5G technology and the Internet of Things(IoT),a large number of IoT devices are connected to wireless communication networks.Due to the limited computing and energy resources of IoT devices,the integration of Mobile Edge Computing(MEC)and Wireless Power Technology(WPT)can provide energy and computing task processing service for Mobile Device(MD).This article firstly constructs a task offloading model for multi-user devices and multi-servers.Then,based on the particle swarm optimization algorithm,Levy flight strategy and improved weight update method are added to propose the S-PSO algorithm to optimize the system’s latency and energy consumption.Finally,simulation results show that the S-PSO algorithm effectively reduces the system’s latency and energy consumption compared to other benchmark schemes,and improves the performance of the computing network.