电子学报 ›› 2021, Vol. 49 ›› Issue (11): 2202-2207.DOI: 10.12263/DZXB.20201039

• 学术论文 • 上一篇    下一篇

一种面向移动边缘计算的多用户细粒度任务卸载调度方法

崔玉亚1,2, 张德干1,2, 张婷3, 杨鹏1,2, 朱浩丽1,2   

  1. 1.天津理工大学天津市智能计算及软件新技术重点实验室, 天津 300384
    2.天津理工大学计算机视觉与系统省部共建教育部 重点实验室, 天津 300384
    3.天津体育学院体育经济与管理学院,天津 301617
  • 收稿日期:2020-09-21 修回日期:2021-05-13 出版日期:2021-11-25 发布日期:2021-11-25
  • 作者简介:崔玉亚 男,1992年生,江苏淮安人,天津理工大学计算机科学与工程学院在读博士生,研究兴趣为网络通信、物联网、无线传感器网络、移动边缘计算等.E-mail:844511468@qq.com
    张德干 男,1970年生,湖北黄冈人,天津理工大学计算机科学与工程学院教授/博士,博导,研究兴趣为物联网、无线传感器网络、移动边缘计算、云计算等.E-mail:zhangdegan@tsinghua.org.cn
    张 婷(通信作者) 女,1972年,河北唐山人,天津体院学院体育经济与管理学院教授/博士,硕导,研究兴趣为物联网、无线传感器网络、移动边缘计算、大数据等.E-mail:zhangtingts@163.com
  • 基金资助:
    国家自然科学基金(61571328);天津市重大科技专项(15ZXDSGX00050);天津市科技支撑重点项目(17YFZCGX00360);天津市自然科学基金(18JCZDJC96800);天津市科技创新和131人才团队(TD13-5025)

A Multi-User Fine-Grained Task Offloading Scheduling Approach of Mobile Edge Computing

Yu-ya CUI1,2, De-gan ZHANG1,2, Ting ZHANG3, Peng YANG1,2, Hao-li ZHU1,2   

  1. 1.Tianjin Key Laboratory of Intelligent Computing & Novel Software Technology,Tianjin University of Technology,Tianjin 300384,China
    2.Ministry of Education Key Laboratory of Computer Vision and System,Tianjin University of Technology,Tianjin 300384,China
    3.School of Sports Economics and Management,Tianjin University of Sport,Tianjin 301617,China
  • Received:2020-09-21 Revised:2021-05-13 Online:2021-11-25 Published:2021-11-25

摘要:

在移动边缘计算中(Mobile Edge Computing, MEC),任务卸载可以有效地解决移动设备资源受限的问题,但是将全部任务都卸载到边缘服务器并非最优.本文提出一种面向移动边缘计算的多用户细粒度任务卸载调度新方法,把计算任务看作一个有向无环图(Directed Acyclic Graph, DAG),对节点的执行位置和调度顺序进行了优化决策.考虑系统的延迟把计算卸载看作一个约束多目标优化问题(Constrained Multi-object Optimization Problem, CMOP),提出了一个改进的NSGA-Ⅱ算法来解决CMOP.所提出的算法能够实现本地和边缘的并行处理从而减少延迟.实验结果表明,算法能够在实际应用程序中做出最优决策.

关键词: 移动边缘计算, 计算卸载, 约束多目标优化问题, 细粒度卸载调度, NSGA-Ⅱ

Abstract:

In mobile edge computing (MEC), task offloading can solve the problem of resource constraint on mobile devices effectively, but it is not optimal to offload all tasks to edge servers. In this paper, a multi-user fine-grained task offloading scheduling approach of mobile edge computation is proposed. The computation task is regarded as a directed acyclic graph (DAG), and task nodes’ execution location and scheduling order are optimized. Considering the delay of the system, the computation offloading is considered as a constrained multi-objective optimization problem (CMOP), and an improved NSGA -Ⅱ algorithm is proposed to solve the CMOP. The proposed algorithm can realize local and edge parallel processing to reduce delay. The experimental results show that the algorithm can make the optimal decision in practical applications.

Key words: mobile edge computing, computation offloading, constrained multi-objective optimization problem(CMOP), fine-grained task offloading scheduling, NSGA-Ⅱ

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