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Effective Algorithms To Estimate The Optimal Software Rejuvenation Schedule Under Censoring

In: Recent Advances In Stochastic Operations Research II

Author

Listed:
  • KOICHIRO RINSAKA

    (Faculty of Business Administration, Kobe Gakuin University, 1-3-1 Minatojima, Chuo-ku, Kobe 658-8586, Japan)

  • TADASHI DOHI

    (Department of Information Engineering, Graduate School of Engineering, Hiroshima University, Higashi-Hiroshima 739-8527, Japan)

Abstract

In this chapter, we consider the optimal software rejuvenation schedule which maximizes the steady-state system availability. We develop statistical algorithms to improve the estimation accuracy in the situation where randomly censored failure time data are obtained. More precisely, based on the kernel density estimation, we estimate the underlying failure time distribution. We propose the framework based on the kernel density estimation to estimate optimal software rejuvenation schedules from censored sample data. In simulation experiments, we show the improvement in the convergence speed to the real optimal solution in comparison with the conventional algorithm.

Suggested Citation

  • Koichiro Rinsaka & Tadashi Dohi, 2009. "Effective Algorithms To Estimate The Optimal Software Rejuvenation Schedule Under Censoring," World Scientific Book Chapters, in: Tadashi Dohi & Shunji Osaki & Katsushige Sawaki (ed.), Recent Advances In Stochastic Operations Research II, chapter 16, pages 225-242, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812791672_0016
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