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Checkpointing for the RESTART problem in Markov networks

Part of: Markov processes Special processes

Published online by Cambridge University Press:  14 July 2016

Lester Lipsky ,
Derek Doran  and
Swapna Gokhale
Lester Lipsky
Affiliation:
University of Connecticut, Department of Computer Science and Engineering, University of Connecticut, 371 Fairfield Road, Storrs, CT 06269-2155, USA. Email address: [email protected]
Derek Doran
Affiliation:
University of Connecticut, Department of Computer Science and Engineering, University of Connecticut, 371 Fairfield Road, Storrs, CT 06269-2155, USA. Email address: [email protected]
Swapna Gokhale
Affiliation:
University of Connecticut, Department of Computer Science and Engineering, University of Connecticut, 371 Fairfield Road, Storrs, CT 06269-2155, USA. Email address: [email protected]
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Abstract

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We apply the known formulae of the RESTART problem to Markov models of software (and many other) systems, and derive new equations. We show how checkpoints might be included, with their resultant performance under RESTART. The result is a complete procedure for finding the mean, variance, and tail behavior of the job completion time as a function of the failure rate. We also provide a detailed example.

Keywords

Checkpointexponential failureMarkov modelRESTARTperformancepower-tailed distributionsubexponential distributionasymptotic behavior

MSC classification

Primary: 60J28: Applications of continuous-time Markov processes on discrete state spaces
Secondary: 60K10: Applications (reliability, demand theory, etc.)
Type
Part 4. Simulation
Information
Journal of Applied Probability , Volume 48 , Issue A: New Frontiers in Applied Probability (Journal of Applied Probability Special Volume 48A) , August 2011 , pp. 195 - 207
Copyright
Copyright © Applied Probability Trust 2011 

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