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On the optimization of free resources using non-homogeneous Markov chain software rejuvenation model

Author

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  • Koutras, Vasilis P.
  • Platis, Agapios N.
  • Gravvanis, George A.

Abstract

Software rejuvenation is an important way to counteract the phenomenon of software aging and system failures. It is a preventive and proactive technique, which consists of periodically restarting an application at a clean internal state. Starting an application generally means that an amount of memory is captured and closing an application engenders the release of an amount of memory. In general, when an application is initiated an amount of memory is captured and when terminated an amount of memory is released. In this paper a model describing the amount of free memory on a system is presented. The modelling is formulated under a continuous time Markov chain framework. Additionally the cost of performing rejuvenation is also taken into consideration, a cost function for the model is produced and a rejuvenation policy is proposed. The contribution of this paper consists of using a cyclic non-homogeneous Markov chain in order to study the overall behaviour of the system capturing time dependence of the rejuvenation rates and deriving an optimal rejuvenation policy. Finally, a case study is presented in order to illustrate the results of the cost analysis.

Suggested Citation

  • Koutras, Vasilis P. & Platis, Agapios N. & Gravvanis, George A., 2007. "On the optimization of free resources using non-homogeneous Markov chain software rejuvenation model," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1724-1732.
    • Handle: RePEc:eee:reensy:v:92:y:2007:i:12:p:1724-1732
    DOI: 10.1016/j.ress.2006.09.017
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    Cited by:

    1. Zhaojun Hao & Francesco Di Maio & Enrico Zio, 2021. "Multi-State Reliability Assessment Model of Base-Load Cyber-Physical Energy Systems (CPES) during Flexible Operation Considering the Aging of Cyber Components," Energies, MDPI, vol. 14(11), pages 1-18, June.
    2. Tamás Bányai & Christian Landschützer & Ágota Bányai, 2018. "Markov-Chain Simulation-Based Analysis of Human Resource Structure: How Staff Deployment and Staffing Affect Sustainable Human Resource Strategy," Sustainability, MDPI, vol. 10(10), pages 1-21, October.
    3. Dhople, S.V. & DeVille, L. & Domínguez-García, A.D., 2014. "A Stochastic Hybrid Systems framework for analysis of Markov reward models," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 158-170.
    4. Zhe Liu & Shurong Li, 2022. "A numerical method for interval multi-objective mixed-integer optimal control problems based on quantum heuristic algorithm," Annals of Operations Research, Springer, vol. 311(2), pages 853-898, April.

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