Abstract
Software rejuvenation is a preventive maintenance technique that has been extensively studied in the recent literature. In this paper we extend the classical result by Huang et al. (1995), and in addition propose a modified stochastic model to generate the software rejuvenation schedule. More precisely, the software rejuvenation models are formulated via the semi-Markov process, and the optimal software rejuvenation schedule which minimizes the expected costs per unit time in the steady-state are derived analytically for respective cases. Further we develop non-parametric algorithms to estimate the optimal software rejuvenation schedules, provided that the statistical complete (unsensored) sample data of failure time is given. In numerical examples, we compare two models in terms of economic justification, and examine asymptotic properties for the statistical estimation algorithms.
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