面向云应用系统的容错即服务优化提供方法
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作者简介:

杨娜(1991-),女,山东临沂人,硕士,主要研究领域为软件容错;刘靖(1981-),男,博士,副教授,CCF高级会员,主要研究领域为云计算,容错计算,软件测试.

通讯作者:

刘靖,E-mail:liujing@imu.edu.cn

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基金项目:

国家自然科学基金(61662051,61262017)


Optimized Fault Tolerance as Services Provisioning for Cloud Applications
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Fund Project:

National Natural Science Foundation of China (61662051, 61262017)

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    摘要:

    通过提供高效且持续可用的容错服务以保障云应用系统的可靠运行是至关重要的.采用容错即服务的模式,提出了一种优化的云容错服务动态提供方法,从云应用组件的可靠性及响应时间等方面描述云应用容错需求,以常用的复制、检查点和NVP(N-version programming)等容错技术为基础,充分考虑容错服务动态切换开销,分别针对支撑容错服务的底层云资源是否足够的场景,给出可用容错即服务提供方案的最优化求解方法.实验结果表明,所提方法降低了云应用系统支付的容错服务费用及支撑容错服务的底层云资源的开销,提高了容错服务提供商为多个云应用实施高效、可靠容错即服务的能力.

    Abstract:

    It is important to provide efficient and continuously available fault tolerant services for cloud applications to ensure their reliable executions. This study adopts the fault tolerance as a service scheme to propose an optimized fault tolerance services provisioning method. The fault tolerance requirements for cloud applications are specified from certain aspects of cloud service components, such as reliability and response time. Based on major fault tolerance technologies, i.e., replication, checkpoint, and NVP (N-Version Programming), with consideration of the dynamic switching overhead among fault tolerance services, a novel method to compute optimal solution of feasible fault tolerance service provisioning is proposed according to the fault tolerance as a service scheme. Two analysis scenarios are considered, that is, whether cloud infrastructure resources used to support fault tolerance service are sufficient or not. The experimental results show that the proposed method reduces the fault tolerant service expenses for cloud application system, reduces the cost of cloud infrastructure resources supporting fault tolerance service, and improves the service capacity of fault tolerance service providers to provide efficient and reliable fault tolerance as a service for cloud application systems.

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杨娜,刘靖.面向云应用系统的容错即服务优化提供方法.软件学报,2019,30(4):1191-1202

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历史
  • 收稿日期:2016-09-08
  • 最后修改日期:2017-01-18
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  • 在线发布日期: 2019-04-01
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