移动边缘计算中分布式异构任务卸载算法

夏士超; 姚枝秀; 鲜永菊; 李云

doi:10.11999/JEIT190728

移动边缘计算中分布式异构任务卸载算法

doi: 10.11999/JEIT190728

重庆邮电大学移动通信技术重庆市重点实验室重庆 400065

基金项目: 国家自然科学基金(61671096)，重庆市“科技创新领军人才支持计划”(CSTCCXLJRC201710)，重庆市基础科学与前沿技术研究项目(cstc2017jcyjBX0005)，重庆邮电大学博士研究生高端人才培养项目(BYJS201806)

详细信息

作者简介:
夏士超：男，1991年生，博士生，研究方向为物联网、边缘计算

姚枝秀：女，1994年生，硕士生，研究方向为物联网、边缘计算

鲜永菊：女，1973年生，副教授，主要研究领域为无线移动通信、物联网和边缘计算

李云：男，1974年生，教授，博士生导师，主要研究领域为无线移动通信、物联网和边缘计算

通讯作者:
李云　liyun@cqupt.cn

中图分类号: TN92
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出版历程
- 收稿日期: 2019-09-19
- 修回日期: 2020-05-30
- 网络出版日期: 2020-07-09
- 刊出日期: 2020-12-08

A Distributed Heterogeneous Task Offloading Methodology for Mobile Edge Computing

Chongqing Key Laboratory of Mobile Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (61671096), The Chongqing Science and Technology Innovation Leading Talent Support Program (CSTCCXLJRC201710), The Chongqing Research Program of Basic Science and Frontier Technology (cstc2017jcyjBX0005), The Chongqing University of Posts and Telecommunications PhD High-end Talent Training Project (BYJS201806)

摘要

摘要:
随着物联网(IoT)迅速发展，移动边缘计算(MEC)在提供高性能、低延迟计算服务方面的作用日益明显。然而，在面向IoT业务的MEC(MEC-IoT)时变环境中，不同边缘设备和应用业务在时延和能耗等方面具有显著的异构性，对高效的任务卸载及资源分配构成严峻挑战。针对上述问题，该文提出一种动态的分布式异构任务卸载算法(D2HM)，该算法利用分布式博弈机制并结合李雅普诺夫优化理论，设计了一种资源的动态报价机制，并实现了对不同业务类型差异化控制和计算资源的弹性按需分配，仿真结果表明，所提的算法可以满足异构任务的多样化计算需求，并在保证网络稳定性的前提下降低系统的平均时延。
- 边缘计算 /
- 物联网 /
- 博弈论 /
- 李雅普诺夫优化 /
- 异构任务卸载
Abstract:
With the rapid development of the Internet of Things (IoT), Mobile Edge Computing (MEC) becomes increasingly effective in improving processing capacity and providing low-latency computing services. However, in the time-varying MEC-IoT environment, heterogeneous devices and applications cause serious challenges on efficient task offloading and resource allocation. A Distributed Dynamic Heterogeneous task offloading Methodology (D2HM) algorithm is proposed in this paper by exploiting game theory and Lyapunov optimization, which can achieves heterogeneous control and allocation of computation resources by dynamic quote price mechanism. Simulation results show that the proposed algorithm can meet the diverse computing needs of heterogeneous tasks and reduce the average delay of the system while ensuring network stability.
- Mobile Edge Computing (MEC) /
- Internet of Things (IoT) /
- Game theory /
- Lyapunov optimization /
- Heterogeneous task offloading

HTML全文

图 1 一种典型的异构任务卸载模型

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图 2 CPU计算频率动态报价过程

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图 3 队列积压及CPU频率的按需分配

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图 4 不同算法性能对比

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