计算机科学

计算机科学 ›› 2020, Vol. 47 ›› Issue (10): 240-246.doi: 10.11896/jsjkx.190900054

• 计算机网络 • 上一篇    下一篇

边缘计算环境下服务质量可信的任务迁移节点选择

王妍1,2, 韩笑1, 曾辉1, 刘荆欣1, 夏长清2,3,4   

  1. 1 辽宁大学信息学院 沈阳110036
    2 中国科学院沈阳自动化研究所机器人学国家重点实验室 沈阳110016
    3 中国科学院沈阳自动化研究所网络化控制系统重点实验室 沈阳110016
    4 中国科学院机器人与智能制造创新研究院 沈阳110169
  • 收稿日期:2019-09-07 修回日期:2020-01-06 出版日期:2020-10-15 发布日期:2020-10-16
  • 通讯作者: 夏长清(xiachangqing@sia.cn)
  • 作者简介:wang_yan@lnu.edu.cn
  • 基金资助:
    国家重点研发计划(2019YFB1406002);国家自然科学基金(61903356);机器人学国家重点实验室开放基金 (2019-O22);辽宁省自然科学基金计划重点项目(20180520029)

Task Migration Node Selection with Reliable Service Quality in Edge Computing Environment

WANG Yan1,2, HAN Xiao1, ZENG Hui1, LIU Jing-xin1, XIA Chang-qing2,3,4   

  1. 1 College of Information,Liaoning University,Shenyang 110036,China
    2 State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China
    3 Key Laboratory of Networked Control System,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China
    4 Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences,Shenyang 110169,China
  • Received:2019-09-07 Revised:2020-01-06 Online:2020-10-15 Published:2020-10-16
  • About author:WANG Yan,born in 1978,Ph.D,associa-te professor,is a member of China Computer Federation.Her main research interests include IIoT data processing,task scheduling and big data technology,etc.
    XIA Chang-qing,born in 1985,Ph.D,research assistant,is a member of China Computer Federation.His main research interests include industry network and task scheduling in Edge Computing,etc.
  • Supported by:
    National Key R&D Program of China (2019YFB1406002),National Natural Science Foundation of China (61903356),State Key Laboratory of Robotics(2019-O22) and National Natural Science Foundation of Liaoning province (20180520029)

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摘要： 随着物联网、大数据和5G网络的快速发展及应用,传统的云计算模式已无法高效处理网络边缘设备所产生的海量计算任务,边缘计算应运而生。边缘计算环境下,计算任务将被迁移到接近数据源的计算设备上执行,这为拓展终端节点资源以及缓解云中心负载提供了新的解决方案。现有的任务迁移决策均是在任务迁移节点确定的前提下制定的,并未考虑存在多个任务迁移节点可选的情景,而边缘计算下任务迁移节点的选择直接影响着任务迁移的服务质量,因此文中构建了服务质量可信模型,分别从时间可信、行为可信、资源可信3个维度对任务迁移节点进行评价。为了解决任务迁移节点数量巨大带来的选择效率低的问题,采用基于聚类编码的skyline查询算法对任务迁移节点进行筛选,并利用灰色关联分析法进行任务迁移节点的最终选择。实验结果表明,所提基于服务质量可信的任务迁移节点选择策略的任务迁移成功率平均提高了36%,任务完成吞吐量平均提高了18%。

关键词: skyline查询, 边缘计算, 灰色关联分析法, 迁移节点选择, 任务迁移

Abstract: With the rapid development and wide application of the Internet of things,big data and 5G network,the traditional cloud computing mode has been unable to efficiently handle the massive computing tasks generated by network edge devices,so edge computing came into being.Computing tasks in edge computing environments will be migrated to computing devices close to data sources for execution,providing new solutions for expanding terminal node resources and alleviating cloud center load.The existing task migration decisions are made on the premise that the task migration node is determined,without considering the si-tuation that multiple task migration nodes are available.The selection of the task migration node in edge computing directly affects the service quality of task migration,so,in this paper,a service quality trust model is constructed to evaluate the task migration nodes from three dimensions:time trust,behavior trust and resource trust.In order to avoid the problem of low selection efficiency caused by the large number of task migration nodes,a skyline query algorithm based on cluster coding is adopted to screen the task migration nodes,and grey relative analysis is used for the final selection of task migration nodes.The experimental results show that the proposed task migration node selection strategy based on reliable service quality can increase the success rate of task migration by 36% and the throughput of task completion by 18% on average.

Key words: Edge computing, Grey relative analysis method, Migration node selection, Skyline query, Task migration

中图分类号: 

  • TP302
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