计算机应用与软件2024,Vol.41Issue(2) :33-40,55.DOI:10.3969/j.issn.1000-386x.2024.02.005

基于无人机辅助边缘计算的收益策略优化研究

REVENUE STRATEGY OPTIMIZATION BASED ON UAV ASSISTED EDGE COMPUTING

蔡超 王俊义 梁海
计算机应用与软件2024,Vol.41Issue(2) :33-40,55.DOI:10.3969/j.issn.1000-386x.2024.02.005

基于无人机辅助边缘计算的收益策略优化研究

REVENUE STRATEGY OPTIMIZATION BASED ON UAV ASSISTED EDGE COMPUTING

蔡超 1王俊义 1梁海1
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作者信息

  • 1. 广西无线宽带通信与信号处理重点实验室 广西 桂林 541004
  • 折叠

摘要

在移动边缘计算场景下,为移动设备提供卸载机会的MEC处理器安装在无人驾驶飞行器(UAV)上,来帮助覆盖区域内的用户设备(UEs)任务卸载,然后将计算结果返回,无人机在服务区域根据最短距离原则确定悬停位置和高度.考虑到每架无人机计算资源和能量有限,该文目标是在资源受限情况下给资源定价.给出用户和服务器的收益模型,证明用户收益函数是凸函数;围绕计算资源定价进行Stackelberg博弈,以迭代的方式确定每个用户的卸载迁移率和最终资源定价.仿真结果表明,在服务器收益和系统总收益方面获得了显著的提高,但是牺牲了任务平均能耗与平均时延.

Abstract

In the mobile edge computing scenario,the MEC processor,which provides mobile devices with the opportunity of unloading,is installed on the unmanned aerial vehicle(UAV)to help users'devices(UES)in the coverage area unload their tasks,and then the calculation results are returned.The UAV determines the hovering position and height in the service area according to the principle of the shortest distance.Considering the limited computing resources and energy of each UAV,this paper aims to price the resources in the case of limited resources.The revenue model of users and servers was given,and it was proved that the revenue function of users was convex.Stackelberg game was used to determine the offload mobility and final resource pricing of each user iteratively.The simulation results show that compared with the existing methods,the server revenue and the total system revenue are significantly improved,but the average task energy consumption and average delay are sacrificed.

关键词

UAV/Stackelberg博弈/计算资源/服务器收益/系统总收益

Key words

UAV/Stackelberg game/Computing resources/Server revenue/Total system revenue

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基金项目

国家自然科学基金项目(61966007)

2018年主任基金项目(CRKL180106)

2018年开发基金项目(CRKL180201)

2019年主任基金项目(CRKL06190117)

广西自然科学基金面上项目(2020GXNSFAA159105)

出版年

2024
计算机应用与软件
上海市计算技术研究所 上海计算机软件技术开发中心

计算机应用与软件

CSTPCD北大核心
影响因子:0.615
ISSN:1000-386X
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