Abstract
The probability of monotone failure of a system in a given time interval is investigated. A method of accelerated simulation based on the small parameter method and stratified sampling is proposed. Conditions are established under which estimates have a bounded mean-square error. A numerical example is considered.
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REFERENCES
I. N. Kovalenko, “Estimation of the reliability of complex systems,” Voprosy Radioelektroniki, 12, No.9, 50–68 (1965).
D. B. Gnedenko and A. D. Solov’yev, “Estimation of the reliability of complex restorable systems,” Pzv. Akad. Nauk SSSR, Tekh. Kibern., 12, No.3, 89–96 (1975).
D. G. Konstantinidis, “The principle of a monotone failure path of a complex restorable system,” Vestnik Moskovsk. Univ., Ser. 1, No. 3, 7–13 (1990).
A. D. Solov’yev and N. G. Karaseva, “Estimation of the mean life time of restorable systems,” Vestn. Moskovsk. Univ., Ser. 1, No. 5, 25–29 (1998).
I. N. Kovalenko, “Rare events in queueing systems: A survey,” Queueing Systems, 16, No.1, 1–49 (1994).
B. Blaszczyszyn, T. Rolski, and V. Schmidt, “Light traffic approximations in queues and related stochastic models,” in: J. H. Dshalalow (ed.), Advances in Queueing, CRC Press, Boca Raton (1995), pp. 379–406.
I. N. Kovalenko, “Approximations of queues via small parameter method,” in: J. H. Dshalalow (ed.), Advances in Queueing, CRC Press, Boca Raton (1995), pp. 481–506.
I. N. Kovalenko, “Estimation of the intensity of the flow of nonmonotone failures of a (≤λ)|G|m|r queuing system,” Ukr. Mat. Zh., 52, No.9, 1219–1225 (2000).
N. Yu. Kuznetsov, “Comparative analysis of the contribution to a system failure on a busy interval of monotone and nonmonotone paths,” Kibern. Sist. Anal., No. 5, 71–80 (2001).
I. N. Kovalenko, “Calculation of characteristics of highly reliable systems by an analytical-statistical method,” Elektronnoe Modelirovanie, 2, No.4, 5–8 (1980).
L. A. Zavadskaya, “An approach to the acceleration of simulation of systems with reservation,” Elektronnoe Modelirovanie, 6, No.6, 57–60 (1984).
N. Yu. Kuznetsov, “General approach to the determination of the reliability probability of structurally complex systems by an analytical-statistical method,” Kibernetika, No. 3, 86–94 (1985).
A. N. Nakonechnyi, “Representation of the probability of system fault-free operation as the mean of the w-functional of a terminating Markov process,” Kibernetika, No. 5, 91–94 (1985).
V. D. Shpak, “Analytical-statistical estimates for some reliability and efficiency measures of semi-Markov systems,” Kibernetika, No. 3, 103–107 (1991).
P. W. Glynn and D. L. Iglehart, “Importance sampling for stochastic simulations,” Manag. Science, 35, 1367–1392 (1989).
P. Heidelberger, P. Shahabuddin, and V. F. Nicola, “Bounded relative error in estimating transient measures of highly dependable non-Markovian systems,” ACM Trans. Modeling Comput. Simul., 4, 137–164 (1994).
S. Asmussen, R. J. Rubinstein, and C. L. Wang, “Regenerative rare events simulation via likelihood ratios,” J. Appl. Probab., 31, 797–815 (1994).
P. E. Lassila and J. T. Virtamo, “Efficient importance sampling for Monte Carlo simulation of loss systems,” in: Proc. ITC-16, Elsevier, Edinburgh (1999), pp. 787–796.
I. N. Kovalenko, N. Yu. Kuznetsov, and Ph. A. Pegg, Mathematical Theory of Reliability of Time Dependent Systems with Practical Applications, Wiley, Chichester (1997).
N. Yu. Kuznetsov, “Weighted modeling of the probability of monotone failure of a system with substantially different reliability characteristics of its elements,” Kibern. Sist. Anal., No. 2, 45–54 (2000).
A. A. Shumskaya, “Fast simulation of unavailability of a repairable system with a bounded relative error of estimate,” Kibern. Sist. Anal., No. 3, 45–58 (2003).
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Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 128–137, January–February 2005.
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Kuznetsov, N.Y., Shumskaya, A.A. Simulation of Monotone Failures of a System with Different Orders of Smallness of Random Variables That Determine Its Functioning. Cybern Syst Anal 41, 104–111 (2005). https://doi.org/10.1007/s10559-005-0045-4
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DOI: https://doi.org/10.1007/s10559-005-0045-4