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A phase expansion for non-Markovian availability models with time-based aperiodic rejuvenation and checkpointing

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  • Junjun Zheng
  • Hiroyuki Okamura
  • Tadashi Dohi

Abstract

This paper presents a stochastic framework, consisting of stochastic reward net (SRN) for capturing the transient behaviors of the system and its related non-Markovian state transition diagram, to model an operational software system that undergoes aperiodic time-based rejuvenation and checkpointing schemes, and further to investigate whether there exists the optimal rejuvenation schedule that maximizes the system steady-state availability. A phase expansion approach is adopted to solve the non-Markovian availability models, which are actually neither the semi-Markov processes nor the Markov regenerative processes. Our numerical results show an appropriate rejuvenation trigger timing range, resulting in the positive improvement effect on the system availability of a database system, and that there exists the optimal rejuvenation trigger timing maximizing the system availability.

Suggested Citation

  • Junjun Zheng & Hiroyuki Okamura & Tadashi Dohi, 2020. "A phase expansion for non-Markovian availability models with time-based aperiodic rejuvenation and checkpointing," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(15), pages 3712-3729, August.
    • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:15:p:3712-3729
    DOI: 10.1080/03610926.2019.1708400
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    Cited by:

    1. Junjun Zheng & Hiroyuki Okamura & Tadashi Dohi, 2021. "Availability Analysis of Software Systems with Rejuvenation and Checkpointing," Mathematics, MDPI, vol. 9(8), pages 1-15, April.

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