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Service Reliability Enhancement in Cloud by Checkpointing and Replication

In: Principles of Performance and Reliability Modeling and Evaluation

Author

Listed:
  • Subrota K. Mondal

    (The Hong Kong University of Science and Technology)

  • Fumio Machida

    (Laboratory for Analysis of System Dependability)

  • Jogesh K. Muppala

    (The Hong Kong University of Science and Technology)

Abstract

Virtual machines (VMs) are used in cloud computing systems to handle user requests for service. A user’s request cannot be completed if the VM fails. Replication mechanisms can be used to mitigate the impact of VM failures. In this chapter, we are primarily interested in characterizing the failure–recovery behavior of a VM in the cloud under different replication schemes. We use a service-oriented dependability metric called Defects Per Million (DPM), defined as the number of user requests dropped out of a million due to VM failures. We present an analytical modeling approach for computing the DPM metric in different replication schemes on the basis of the checkpointing method. The effectiveness of replication schemes are demonstrated through experimental results. To verify the validity of the proposed analytical modeling approach, we extend the widely used cloud simulator CloudSim and compare the simulation results with analytical solutions.

Suggested Citation

  • Subrota K. Mondal & Fumio Machida & Jogesh K. Muppala, 2016. "Service Reliability Enhancement in Cloud by Checkpointing and Replication," Springer Series in Reliability Engineering, in: Lance Fiondella & Antonio Puliafito (ed.), Principles of Performance and Reliability Modeling and Evaluation, pages 425-448, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-319-30599-8_16
    DOI: 10.1007/978-3-319-30599-8_16
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