团队介绍：本成果由卢光跃教授团队的西邮低空经济研究院、西邮-铁塔“低空经济联合创新中心”的刘伯阳博士围绕低空经济展开研究，主要针对传统边缘计算网络中存在的用户到服务器信道质量差与服务器算力有限的问题，采用无人机对地面用户提供任务卸载辅助服务，并通过优化设计网络配置参数与无人机轨迹，最大化服务器对地面用户的服务完成率。通过探索低空经济发展的趋势和规律，推进关键技术攻关和成果转化应用，对空地一体化算力网络研究部署具有一定的指导意义。
无人机辅助多MEC服务器的任务完成率最大化方案
刘伯阳1,2,张浩然1,3,郭天润1,王丽平1,党儒鸽1
(1.西安邮电大学通信与信息工程学院,陕西 西安 710121; 2.陕西省信息通信网络及安全重点实验室,陕西 西安 710121; 3.爱生无人机试验测试靖边有限公司,陕西 榆林 718500)
摘要:针对传统移动边缘计算(Mobile Edge Computing,MEC)网络中的严重信道衰落以及单一MEC服务器计算资源有限的问题，提出一种无人机(Unmanned Aerial Vehicles,UAV)辅助多MEC服务器的任务完成率最大化方案。该方案联合优化任务卸载决策、计算和通信资源及UAV轨迹，在满足信息因果关系约束、任务约束和轨迹约束的前提下，建立任务完成率最大化和UAV与用户加权能耗最小化问题。为求解该问题，采用交替优化算法将高度复杂问题解耦为任务卸载问题、资源分配问题和UAV轨迹设计问题，利用变量替换与拉格朗日对偶算法对任务卸载和资源分配问题转换后的凸问题进行迭代求解，并通过连续凸近似算法优化UAV轨迹。仿真结果表明，所提方案可以有效提高任务完成率并降低系统能耗，能够有效缓解信道衰落以及单一MEC服务器计算资源有限的问题。
关键词:移动边缘计算；无人机；变量替换算法；拉格朗日对偶算法；连续凸近似算法
中图分类号:TN929.5 文献标识码:A 文章编号:2095-6533(2024)05-0019-11
Task completion maximization scheme for UAV-assisted multi-MEC servers
LIU Boyang1,2,ZHANG Haoran1,3,GUO Tianrun1,WANG Liping1,DANG Ruge1
(1.School of Communications and Information Engineering,xi’an University of posts and Telecommunications,xi’an 71012,China;2.Shaanxi Key Laboratory of Information Communication Network and Security,xi’an 710121,China;3.ASN UAS Flight Test and Research Jingbian Co.,Ltd,Yulin 718500,China)
Abstract:The problems of severe channel fading and limited computation capacity of a single MEC server in a traditional mobile edge computing (MEC) network are investigated.The task completion maximization scheme is proposed in an unmanned aerial vehicles (UAV) assisted multi-MEC server network.The scheme jointly optimizes task offloading decision,computation and communication resource,and UAV trajectory to formulate the task completion rate maximi-zation and the weighted energy consumption minimization problem between UAV and user,while satisfying the information causality constraint,task constraint,and trajectory constraint.In order to solve this problem,an alternating optimization algorithm is adopted to decouple the highly complex problem into a task offloading and resource allocation problem,as well as a UAV trajectory design problem.For the task offloading and resource allocation problems,the variable substitution algorithm and the Lagrangian dual algorithm are used to solve the transformed convex problems iteratively.The UAV trajectory is optimized with the successive convex approximation algorithm.Simulation results show that the proposed scheme can effectively improve the task completion rate and reduce the system energy consumption,and can effectively alleviate the prob lems of channel fading and limited computational capacity of a single MEC server.
Keywords:mobile edge computing;unmanned aerial vehicles;variable substitution algorithm;Lagrange dual algorithm;successive convex approximation algorithm
基金项目:国家自然科学基金项目(61901366);陕西省自然科学基础研究计划项目(2020JQ-851);陕西省普通高校青年杰出人才支持计划
作者简介:刘伯阳(1988—),男,陕西延安人,博士,西安邮电大学副教授,主要研究方向为边缘计算,认知无线电等.E-mail:liuboyang@xupt.edu.cn
张浩然(1999—),男,河南三门峡人,西安邮电大学硕士研究生,主要研究方向为无人机试验测试,边缘计算与反向散射通信等.E-mail:zhr@stu.xupt.edu.cn
引文格式:刘伯阳,张浩然,郭天润,等.无人机辅助多MEC服务器的任务完成率最大化方案[J].西安邮电大学学报,2024,29(5):19-29.
LIU B Y,ZHANG H R,GUO T R,et al.Task completion maximization scheme for UAV-assisted multi-MEC servers[J].Journal of xi’an University of posts and Telecommunications,2024,29(5):19-29.