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A numerical approach for computing optimal dynamic checkpointing strategies for general rollback and recovery systems is presented. The system is modeled as a Markov renewal decision process. General failure distributions, random checkpointing durations, and reprocessing-dependent recovery times are allowed. The aim is to find a dynamic decision rule to maximize the average system availability
general failure distributions; optimal checkpointing strategies; rollback and recovery systems; numerical approach; Markov renewal decision process; dynamic decision rule; value-iteration stochastic dynamic programming; finite-element approximation; decision theory; dynamic programming; Markov processes; performance evaluation.

P. L'Ecuyer and J. Malenfant, "Computing Optimal Checkpointing Strategies for Rollback and Recovery Systems," in IEEE Transactions on Computers, vol. 37, no. , pp. 491-496, 1988.
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