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Optimization of partial software rejuvenation policy

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  • Levitin, Gregory
  • Xing, Liudong
  • Huang, Hong-Zhong

Abstract

This paper models a real-time software system performing state-based partial rejuvenations for counteracting performance deterioration effects caused by software aging. The decision on performing each rejuvenation, recovery state and corresponding rejuvenation time depend on both the system degradation level (state) and task operations completed immediately before the rejuvenation action. Full rejuvenations where the system performance is recovered to the peak level appear as a special case of the considered rejuvenation model when the recovery state after performing the rejuvenation is the initial perfect state. We suggest an iterative numerical method based on event transitions for assessing the successful completion probability of a real-time task performed by the considered software system. The proposed method has no limitation on the distribution type of any state sojourn time (or state transition time). We further optimize the state-based partial rejuvenation policy for maximizing the probability of completing a particular real-time task. Impacts of different parameters on the optimization solution are demonstrated through examples, including the discretization parameter used in the suggested numerical algorithm, real-time task deadline, and rejuvenation time parameter.

Suggested Citation

  • Levitin, Gregory & Xing, Liudong & Huang, Hong-Zhong, 2019. "Optimization of partial software rejuvenation policy," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 289-296.
    • Handle: RePEc:eee:reensy:v:188:y:2019:i:c:p:289-296
    DOI: 10.1016/j.ress.2019.03.011
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    References listed on IDEAS

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    1. Machida, Fumio & Miyoshi, Naoto, 2017. "Analysis of an optimal stopping problem for software rejuvenation in a deteriorating job processing system," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 128-135.
    2. Levitin, Gregory & Xing, Liudong & Ben-Haim, Hanoch, 2018. "Optimizing software rejuvenation policy for real time tasks," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 202-208.
    3. Meng, Haining & Liu, Jianjun & Hei, Xinhong, 2015. "Modeling and optimizing periodically inspected software rejuvenation policy based on geometric sequences," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 184-191.
    4. Levitin, Gregory & Xing, Liudong & Luo, Liang, 2019. "Joint optimal checkpointing and rejuvenation policy for real-time computing tasks," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 63-72.
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    Citations

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    Cited by:

    1. Wen, Tao & Deng, Yong, 2020. "The vulnerability of communities in complex networks: An entropy approach," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    2. Levitin, Gregory & Xing, Liudong & Xiang, Yanping, 2020. "Cost minimization of real-time mission for software systems with rejuvenation," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    3. Levitin, Gregory & Xing, Liudong & Xiang, Yanping, 2020. "Optimizing software rejuvenation policy for tasks with periodic inspections and time limitation," Reliability Engineering and System Safety, Elsevier, vol. 197(C).

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