EFFECTIVE ALGORITHMS TO ESTIMATE THE OPTIMAL SOFTWARE REJUVENATION SCHEDULE UNDER CENSORING

Koichiro Rinsaka and Tadashi Dohi
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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

Chapter 16 in Recent Advances in Stochastic Operations Research II, 2009, pp 225-242 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractIn 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.

Keywords: Operations Research; Uncertainty; Applied Probability; Stochastic Process; Optimization; Decision Science (search for similar items in EconPapers)
Date: 2009
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