© 2001 by British Computer Society
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Estimating Software Rejuvenation Schedules in High-Assurance Systems
eva-Popstojanova21 Department of Industrial and Systems Engineering, Hiroshima University, Higashi-Hiroshima 739-8527, Japan Email: dohi@gal.sys.hiroshima-u.ac.jp 2 Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506-6109, USA 3 Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708-0294, USA
Software rejuvenation is a preventive maintenance technique that has been extensively studied in 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 reward process, and the optimal software rejuvenation schedules are derived analytically in terms of the reward rate. In particular, we consider the two special cases: steady-state availability and expected cost per unit time in the steady state. Further, we develop non-parametric algorithms to estimate the optimal software rejuvenation schedules, provided that the statistically complete (unsensored) sample data of failure time is given. In numerical examples, we compare two models from the viewpoints of system availability and economic justification, and examine asymptotic properties for the statistical estimation algorithms.
Received 2 November, 2000. Revised 2 May, 2001.
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