Service Reliability Enhancement in Cloud by Checkpointing and Replication

Subrota K. Mondal (), Fumio Machida () and Jogesh K. Muppala ()
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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

A chapter in Principles of Performance and Reliability Modeling and Evaluation, 2016, pp 425-448 from Springer

Abstract: 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.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-319-30599-8_16

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DOI: 10.1007/978-3-319-30599-8_16

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