计算机科学 ›› 2017, Vol. 44 ›› Issue (7): 61-67.doi: 10.11896/j.issn.1002-137X.2017.07.011

• 2016 年全国理论计算机科学学术年会 • 上一篇    下一篇

融合容错需求和资源约束的云容错服务适配方法

杨娜,刘靖   

  1. 内蒙古大学计算机学院 呼和浩特010021,内蒙古大学计算机学院 呼和浩特010021
  • 出版日期:2018-11-13 发布日期:2018-11-13
  • 基金资助:
    本文受国家自然科学基金项目(61262017,61662051)资助

Cloud Fault Tolerance Services Adaption Method Based on Requirement and Resource Constriction

YANG Na and LIU Jing   

  • Online:2018-11-13 Published:2018-11-13

摘要: 云计算环境下,失效成为一种常态行为,可靠性保障能力不足不仅成为云计算应用推广的主要障碍,而且还促使云计算环境下的容错服务研究成为一个亟待解决的问题。针对目前云计算容错服务研究中存在的用户容错需求定义无法直接反映用户关心的可靠性问题,以及云容错服务供应商资源得不到灵活利用等问题,提出了一种融合容错需求和资源约束的云容错服务适配方法。从用户的角度,以组件为单位,基于可靠性对用户的容错需求进行定义。从云容错服务供应商的角度,分别在其资源充足和资源不足的情况下研究最佳的容错服务适配方法,并使用最优化理论求解该适配方法下的容错服务。实验结果表明,所提出的容错服务适配方法生成的容错服务能更好地满足用户和云容错服务供应商的需求。

关键词: 云计算,容错即服务,副本容错,检查点容错,最优化

Abstract: In the environment of cloud computing,faults have become a normal behavior and the shortage of reliability safeguard not only has become the main obstacle of application promotions in cloud computing,but also has made fault tolerance services in cloud computing become a problem that need to be solved urgently.Aiming at solving the shortage study of fault tolerance services in cloud computing that the definition of user fault tolerance requirements can’t reflect reliability which was concerned by the users directly and the inflexible usage of the resources of cloud fault tolerance service providers,this paper proposed an adaption method of cloud fault tolerance services which was based on user requirement and resource constriction.This paper first defined the fault tolerance requirements of users from the prospective of users,which was conducted by taking a component as a unit and reliability as a basis.Then the optimal adaption method of fault tolerance services was studied from the perspective of cloud fault tolerance services providers under the condition of that the resources of fault tolerance service providers is insufficient or sufficient.This paper solved the fault tolerance services generated by the optimal adaption method using optimization theory.The results of the experiments showed that the fault tolerance services which were generated by our adaption method can better satisfy the requirements of users and cloud fault tolerance service providers.

Key words: Cloud computing,Fault tolerance as a service,Replication fault tolerance,Checkpoint fault tolerance,Optimization

[1] JHAWAR R,PIURI V.Fault Tolerance and Resilience in Cloud Computing Environments(2nd Edition)[M]∥Jhawar R,PiuriV.Computer and Information Security Handbook.SanFrancisco:Morgan Kaufmann,2013:1-28.
[2] SUN D W,CHANG G R,MIAO C S,et al.Analyzing,Modeling and Evaluating Dynamic Adaptive Fault Tolerance Strategies in Cloud ComputingEnvironments[J].Journal of Super Computing,2013,66(1):193-228.
[3] YI H Z,WANG F,ZUO K,et al.Asynchronous Checkpoint/Restart Based on Memory Buffer[J].Journal of Computer Research and Development,2014,1(6):1229-1239.(in Chinese) 易会战,王锋,左克,等.基于内存缓存的异步检查点容错技术[J].计算机研究与发展,2014,51(6):1229-1239.
[4] GAO Y,GUPTA S K,WANG Y Z,et al.An Energy-AwareFault Tolerance Scheduling Framework for Soft Error Resilient Cloud Computing Systems[C]∥Design,Automation and Test in Europe Conference and Exhibition.2014:1-6.
[5] HAMID B,RADERMACHER A,VANUXEEM P,et al.AFault-Tolerance Framework for Distributed Component Systems[C]∥34th Euromicro Conference Software Engineering and Advanced Applications.2008:84-91.
[6] CHEN S H,CHEN T,WEI H,et al.A Study of Suitable Fault Tolerance Frameworks for an Energy-efficient Storage System[C]∥Collaboration Technologies and Systems(CTS).2015:220-225.
[7] JHAWAR R,SANTAMBROGIO M.Fault Tolerance Manage-ment in Cloud Computing:A System-Level Perspective[J].IEEE System Journal,2013,7(2):288-297.
[8] NANDI B B,PAUL H S,BANERJEE A,et al.Fault Tolerance as a Service[C]∥IEEE 6th International Conference on Cloud Computing.2013:446-453.
[9] WU X G.Minimun-cost Based Data Replication Strategy in C-loud Computing Environment[J].Computer Science,2014,41(10):154-159.(in Chinese) 吴修国.云计算环境下面向最小成本的数据副本策略[J].计算机科学,2014,41(10):154-159.
[10] YUAN S,GUO Y B,LIU W.Research on voting algorithm in NMR and NVP system [J].Application Research of Compu-ters,2008,5(11):3463-3467.(in Chinese) 袁顺,郭渊博,刘伟.NMR及NVP系统中表决算法分析与研究[J].计算机应用研究,2008,25(11):3463-3467.
[11] DENG W P.Research on checkpointing in mobile computing environment and modeling with petri nets[D].Harbin:Harbin Institute of Technology,2008.(in Chinese) 邓文平.移动计算环境下检查点技术研究与Petri网建模[D].哈尔滨:哈尔滨工业大学,2008.
[12] ZHAO L H.Search of Cloud Task Allocation Strategy Based on Cloudsi[D].Hohhot:Inner Mongolia University of Technology,2013.(in Chinese) 赵立慧.基于CLOUDSIM平台的云任务分配策略研究[D].呼和浩特:内蒙古工业大学,2013.
[13] 赵东方.数学模型与计算[M].北京:科学出版社,2007:249-274.
[14] REN J Z,TAN S Y,DONG L C,et al.Lingo optimization software and its application on optimization of chemical process[J].Computers and Applied Chemistry,2010,7(7):975-978.(in Chinese) 任竞争,谭世语,董立春,等.LINGO及其在化工过程优化中的应用[J].计算机应用化学,2010,27(7):975-978.
[15] ZHENG Z B,LYU M R.Fault Tolerance Management in Cloud Computing:Selecting an optimal fault tolerance strategy for re-liable service-oriented system with local and global constraints[J].IEEE Transactions on Computers,2015,64(1):219-232.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!