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Replica Selection Strategy Based on Individual QoS Sensitivity Constraints in Cloud Environment

  • Chao Lou
  • Mingchun Zheng
  • Xuan Liu
  • Xiao Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8351)

Abstract

In order to solve the problem of replica selection for a kind of user with individual QoS sensitivity in cloud environment, a strategy is presented based on individual QoS sensitivity constraints with comprehensive consideration of the system loading, transmission cost, user’s QoS preference and historical evaluation information. On the basis of it, the strategy considers the similarity of current demanding environment and the historical replica credibility evaluated envrionment, and then selects the special replica. Simulation experiment results testify that the selection strategy is feasible and effective.

Keywords

Cloud environment QoS preference Replica credibility Replica selection 

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References

  1. 1.
    Xiong, L.S.J.: QoS preference-aware replica selection strategy in cloud computing. J. Computer Simulation 32, 93–102 (2011)Google Scholar
  2. 2.
    Vazhkudai, S., Jennifer, M.S.: Using regression techniques to predict large data transfers. J. International Journal of High Performance Computing Application 17, 249–268 (2003)CrossRefGoogle Scholar
  3. 3.
    Zhang, W.X.-D.: The strategy of replica management based on genetic algorithm. J. Computer Simulation 26, 197–263 (2009)Google Scholar
  4. 4.
    Sun, S., Lu, E., Yu, C.: Research of replica selection scheme based on ant algorithm in data grid. J. Computer Engineering and Applications 43, 145–147 (2007)Google Scholar
  5. 5.
    Liu, L.H.: Artificial neural network and particle swarm optimization. M. Beijing Publishing House of University of Posts and Telecommunications (2008)Google Scholar
  6. 6.
    Xiao, F.W.L.: Replica placement methods of QoS on data grid. J. Information Science 39, 1063–1071 (2009)Google Scholar
  7. 7.
    Gong, C.Z.: A research of dynamic replication management strategy based on data grid. J. Journal of Yunnan University 31, 470–476 (2009)Google Scholar
  8. 8.
    Feng, Research and design the load balancing algorithm in cloud computing. D. University of Posts and Telecommunications (2012)Google Scholar
  9. 9.
    Martin, D.L.: A comparative study into distributed load balancing algorithms for cloud computing. C. IEEE. 24 4, 551–556 (2010)Google Scholar
  10. 10.
    Zhao.: Replica selection strategy based on similar scene recommendation in data grid environment. J. Microelectronics & Computer 29, 23–26 (2012)Google Scholar
  11. 11.
    Hong, Y.: Key technology of cloud computing and cloud computing model based on Hadoop study. J. Software Guide 9, 9–11 (2010)Google Scholar
  12. 12.
    Deng.: Topology design and Hadoop research in cloud computing. D. University of Science and Technology of China (2009)Google Scholar
  13. 13.
    Xu, P.Y.D.: Strategy of replica selection based on grey Markov chain prediction model in HDFS. J. Journal of Computer Applications 31, 39–42 (2011)CrossRefGoogle Scholar
  14. 14.
    Tehmina, M.A.D.: A survey of dynamic replication strategies for improving data availability in data grids. J. Future Generation Computer Systems. 28, 337–349 (2012)CrossRefGoogle Scholar
  15. 15.
    Fu.: Research on TOPSIS method. J. Journal of Xian University of Science and Tecnology 28, 190–193 (2008)Google Scholar
  16. 16.
    Zha, Y.: Cloud computing simulation platform CloudSim in resource allocation research applications. Software Guide 11, 57–59 (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Chao Lou
    • 1
  • Mingchun Zheng
    • 1
  • Xuan Liu
    • 1
  • Xiao Li
    • 1
  1. 1.College of Management Science and EngineeringShandong Normal UniversityJinanChina

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