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移动边缘计算中基于Lyapunov的任务卸载与资源分配算法
引用本文:唐伦,胡彦娟,刘通,陈前斌. 移动边缘计算中基于Lyapunov的任务卸载与资源分配算法[J]. 计算机工程, 2021, 47(3): 29-36. DOI: 10.19678/j.issn.1000-3428.0058268
作者姓名:唐伦  胡彦娟  刘通  陈前斌
作者单位:重庆邮电大学 通信与信息工程学院 移动通信技术重点实验室, 重庆 400065
基金项目:重庆市技术创新与应用发展专项重大主题专项项目;重庆市教委科学技术研究项目;国家自然科学基金
摘    要:移动边缘计算(MEC)通过将计算和存储资源部署在无线网络边缘,使得用户终端可将计算任务卸载到边缘服务器进行处理,从而缓解终端设备资源受限与高性能任务处理需求之间的冲突.但随着任务卸载规模的不断增加,执行任务所产生的功耗急剧上升,严重影响了MEC系统的收益.建立任务队列动态调度模型,以队列上溢概率为约束构建最大化系统平均...

关 键 词:移动边缘计算  任务卸载  资源分配  Lyapunov理论  任务队列
收稿时间:2020-05-08
修稿时间:2020-07-08

Task Offloading and Resource Allocation Algorithm Based on Lyapunov in Mobile Edge Computing
TANG Lun,HU Yanjuan,LIU Tong,CHEN Qianbin. Task Offloading and Resource Allocation Algorithm Based on Lyapunov in Mobile Edge Computing[J]. Computer Engineering, 2021, 47(3): 29-36. DOI: 10.19678/j.issn.1000-3428.0058268
Authors:TANG Lun  HU Yanjuan  LIU Tong  CHEN Qianbin
Affiliation:Key Laboratory of Mobile Communication Technology, School of Communication and Information Engineering, Chongqing University of Post and Telecommunications, Chongqing 400065, China
Abstract:By deploying computing and storage resources at the edge of wireless network,Mobile Edge Computing(MEC)enables mobile devices to offload computing tasks to the MEC servers for processing,thereby effectively alleviating the contradiction between the limited resources of mobile devices and the high-performance task processing demands.However,with the increasing size of offloaded tasks,the power consumption generated by task execution rises dramatically,which significantly affects the profit of MEC systems.To solve the problem,this paper designs a dynamic scheduling model for task queue,and builds a resource optimization model to maximize the average revenue of the MEC system with the queue overflow probability as a constraint.Considering that the resource optimization problem is a coupling problem under different time slots,this paper uses the Lyapunov optimization theory to design a resource allocation algorithm based on a single time slot,and thus converts the optimization problem into three sub-problems:local computing resource allocation,power and bandwidth resource allocation,and MEC server computing resource allocation.Simulation results show that the proposed algorithm improves the time-average revenue of the MEC system while satisfying the QoS requirements of users.
Keywords:Mobile Edge Computing(MEC)  task offloading  resource allocation  Lyapunov theory  task queue
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