电子学报 ›› 2019, Vol. 47 ›› Issue (5): 1036-1043.DOI: 10.3969/j.issn.0372-2112.2019.05.009

• 学术论文 • 上一篇    下一篇

面向服务可靠性的云资源调度方法

周平1,2, 殷波3, 邱雪松1, 郭少勇1, 孟洛明1   

  1. 1. 北京邮电大学网络与交换技术国家重点实验室, 北京 100876;
    2. 中国电子技术标准化研究院 云计算标准与应用工业和信息化部重点实验室, 北京 100007;
    3. 清华大学信息技术研究院 网络大数据技术研究中心, 北京 100084
  • 收稿日期:2018-10-17 修回日期:2019-03-01 出版日期:2019-05-25
    • 作者简介:
    • 周平 男,1977年2月出生.2005年获清华大学软件工程硕士学位,现任中国电子技术标准化研究院云计算标准与应用工业和信息化部重点实验室主任.主持完成10余项包括"核高基"重大专项、重点研发计划、863、工业转型升级在内的重大项目,先后获中国电子学会电子信息科学技术奖二等奖1项、北京市科学技术奖三等奖1项.现为北京邮电大学网络与交换技术国家重点实验室博士研究生,主要从事通信与信息系统有关方面的研究.E-mail:zhouping@cesi.cn
    • 基金资助:
    • 国家自然科学基金 (No.61702048); 国家重点研发计划 (No.2018YFB1004200)

Service Reliability Oriented Cloud Resource Scheduling Method

ZHOU Ping1,2, YIN Bo3, QIU Xue-song1, GUO Shao-yong1, MENG Luo-ming1   

  1. 1. State Key Laboratory of Network and Switching Technology, BUPT, Beijing 100876, China;
    2. Key Laboratory of Cloud Computing Standards and Applications, Ministry of Industry and Information Technology, China Electronics Standardization Institute, Beijing 100007, China;
    3. Research Center of Network Big Data Technology, Institute of Information Technology, Tsinghua University, Beijing 100084, China
  • Received:2018-10-17 Revised:2019-03-01 Online:2019-05-25 Published:2019-05-25

摘要: 随着云计算成为重要的信息基础设施,越来越多的应用迁移到云上,云服务的可靠性日益重要,尤其是边缘计算新模式的引入,对云服务可靠性提出了更高的要求.如何通过资源调度保障服务可靠性成为了当前研究的热点.为此,针对云-边协同的应用场景,开展面向服务可靠性的云资源调度方法研究,提出基于马尔科夫预测模型的云资源调度算法,实现节点负载判断、待迁移任务和节点选择、迁移路由的决策,以解决云服务节点失效情况下的任务调度和负载均衡问题,实现快速的云服务故障恢复,提高云服务的可靠性.实验结果表明,本文所提方法能够有效保证节点失效情况下的服务可靠性.

关键词: 云服务, 可靠性, 资源调度, 马尔科夫过程

Abstract: As Cloud Computing becomes an important information infrastructure,more and more applications are being migrated to the cloud.Therefore,the reliability of cloud services becomes increasingly important.In particular,the introduction of new edge computing mode puts forward higher requirements on the reliability of cloud services.How to guarantee the reliability of services through resource scheduling has become a hot topic of current research.In Cloud-Edge collaborative application scenarios,we research on a service reliability oriented cloud resource scheduling method to support cloud service reliability.And the cloud resource scheduling algorithm based on markov prediction model is put forward to solve the problem of task scheduling and load balancing in cloud service node failure situation,including the judgment of node load degree,the selection of migrated task and nodes,and the decision of migration routing.The goal is to achieve rapid cloud service recovery and to improve the reliability of cloud services.The experimental results show that the proposed method can effectively guarantee the service reliability.

Key words: cloud service, reliability, resource scheduling, Markov process

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