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Article

Availability Analysis of Software Systems with Rejuvenation and Checkpointing

1
Department of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu 5258577, Japan
2
Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashihiroshima 7398527, Japan
*
Author to whom correspondence should be addressed.
Academic Editor: Vassilis C. Gerogiannis
Mathematics 2021, 9(8), 846; https://doi.org/10.3390/math9080846
Received: 15 March 2021 / Revised: 5 April 2021 / Accepted: 9 April 2021 / Published: 13 April 2021
(This article belongs to the Special Issue Mathematics in Software Reliability and Quality Assurance)
In software reliability engineering, software-rejuvenation and -checkpointing techniques are widely used for enhancing system reliability and strengthening data protection. In this paper, a stochastic framework composed of a composite stochastic Petri reward net and its resulting non-Markovian availability model is presented to capture the dynamic behavior of an operational software system in which time-based software rejuvenation and checkpointing are both aperiodically conducted. In particular, apart from the software-aging problem that may cause the system to fail, human-error factors (i.e., a system operator’s misoperations) during checkpointing are also considered. To solve the stationary solution of the non-Markovian availability model, which is derived on the basis of the reachability graph of stochastic Petri reward nets and is actually not one of the trivial stochastic models such as the semi-Markov process and the Markov regenerative process, the phase-expansion approach is considered. In numerical experiments, we illustrate steady-state system availability and find optimal software-rejuvenation policies that maximize steady-state system availability. The effects of human-error factors on both steady-state system availability and the optimal software-rejuvenation trigger timing are also evaluated. Numerical results showed that human errors during checkpointing both decreased system availability and brought a significant effect on the optimal rejuvenation-trigger timing, so that it should not be overlooked during system modeling. View Full-Text
Keywords: software rejuvenation; checkpointing; optimal rejuvenation-trigger timing; steady-state system availability; phase expansion; human-error factors software rejuvenation; checkpointing; optimal rejuvenation-trigger timing; steady-state system availability; phase expansion; human-error factors
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MDPI and ACS Style

Zheng, J.; Okamura, H.; Dohi, T. Availability Analysis of Software Systems with Rejuvenation and Checkpointing. Mathematics 2021, 9, 846. https://doi.org/10.3390/math9080846

AMA Style

Zheng J, Okamura H, Dohi T. Availability Analysis of Software Systems with Rejuvenation and Checkpointing. Mathematics. 2021; 9(8):846. https://doi.org/10.3390/math9080846

Chicago/Turabian Style

Zheng, Junjun, Hiroyuki Okamura, and Tadashi Dohi. 2021. "Availability Analysis of Software Systems with Rejuvenation and Checkpointing" Mathematics 9, no. 8: 846. https://doi.org/10.3390/math9080846

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