Rare event simulation in stochastic models

We review fast simulation techniques used for estimating probabilities of rare events and related quantities in different types of stochastic models.

[1]  M. D. Wilkinson,et al.  Management science , 1989, British Dental Journal.

[2]  Juan A. Carrasco.  Efficient transient simulation of failure/repair Markovian models , 1991, [1991] Proceedings Tenth Symposium on Reliable Distributed Systems.

[3]  Elmer E Lewis,et al.  Monte Carlo simulation of Markov unreliability models , 1984 .

[4]  J.P.C. Kleijnen,et al.  Importance sampling in systems simulation : A practical failure? , 1979 .

[5]  José Villén-Altamirano,et al.  RESTART: a straightforward method for fast simulation of rare events , 1994, Proceedings of Winter Simulation Conference.

[6]  Jean C. Walrand,et al.  Quick simulation of ATM buffers with on-off multiclass Markov fluid sources , 1993, TOMC.

[7]  Jean Walrand,et al.  A quick simulation method for excessive backlogs in networks of queues , 1989 .

[8]  Philip Heidelberger,et al.  Bounded relative error in estimating transient measures of highly dependable non-Markovian systems , 1994, TOMC.

[9]  Philip Heidelberger,et al.  Fast Simulation of Highly Dependable Systems with General Failure and Repair Processes , 1993, IEEE Trans. Computers.

[10]  Philip Heidelberger,et al.  Efficient estimation of the mean time between failures in non-regenerative dependability models , 1993, WSC '93.

[11]  ArneAndersson LundUniversity.  Is Necessary and Sufficient# , 1996 .

[12]  P. Glynn.  Importance sampling for markov chains: asymptotics for the variance , 1994 .

[13]  Philip Heidelberger,et al.  Modeling and analysis of system dependability using the System Availability Estimator , 1994, Proceedings of IEEE 24th International Symposium on Fault- Tolerant Computing.

[14]  Cheng-Shang Chang,et al.  Stability, queue length, and delay of deterministic and stochastic queueing networks , 1994, IEEE Trans. Autom. Control..

[15]  Jie Wang,et al.  Monte Carlo summation and integration applied to multiclass queuing networks , 1994, JACM.

[16]  Philip Heidelberger,et al.  Fast simulation of rare events in queueing and reliability models , 1993, TOMC.

[17]  A. J. Bayes.  Statistical Techniques for Simulation Models , 1970, Aust. Comput. J..

[18]  Donald L. Iglehart,et al.  Importance sampling for stochastic simulations , 1989 .

[19]  Paul Glasserman,et al.  Rare-Event Simulation for Multistage Production-Inventory Systems , 1996 .

[20]  Perwez Shahabuddin,et al.  Fast Transient Simulation of Markovian Models of Highly Dependable Systems , 1994, Perform. Evaluation.

[21]  D. Siegmund.  Sequential Analysis: Tests and Confidence Intervals , 1985 .

[22]  Michael R. Frater,et al.  Optimally efficient estimation of the statistics of rare events in queueing networks , 1991 .

[23]  P. Shahabuddin,et al.  Estimation of reliability and its derivatives for large time horizons in Markovian systems , 1993, WSC '93.

[24]  R. F. Brown,et al.  PERFORMANCE EVALUATION , 2019, ISO 22301:2019 and business continuity management – Understand how to plan, implement and enhance a business continuity management system (BCMS).

[25]  V. F. Nicola,et al.  Techniques for Fast Simulation of Highly Dependable Systems , 1993 .

[26]  H. Kahn,et al.  Methods of Reducing Sample Size in Monte Carlo Computations , 1953, Oper. Res..

[27]  Perwez Shahabuddin,et al.  Importance sampling for the simulation of highly reliable Markovian systems , 1994 .

[28]  J. Sadowsky.  Large deviations theory and efficient simulation of excessive backlogs in a GI/GI/m queue , 1991 .

[29]  Michael A. Crane,et al.  Simulating Stable Stochastic Systems: III. Regenerative Processes and Discrete-Event Simulations , 1975, Oper. Res..

[30]  J. Keilson.  Markov Chain Models--Rarity And Exponentiality , 1979 .

[31]  Sigrún Andradóttir,et al.  On the Choice of Alternative Measures in Importance Sampling with Markov Chains , 1995, Oper. Res..

[32]  T. Lehtonen,et al.  SIMULATING LEVEL-CROSSING PROBABILITIES BY IMPORTANCE SAMPLING , 1992 .

[33]  Michel Mandjes,et al.  Finding the Conjugate of Markov Fluid Processes , 1995 .

[34]  Paul Glasserman,et al.  Analysis of an importance sampling estimator for tandem queues , 1995, TOMC.

[35]  Peter W. Glynn.  Likelihood Ratio Derivative Estimators For Stochastic Systems , 1989, 1989 Winter Simulation Conference Proceedings.

[36]  Marvin K. Nakayama.  Fast simulation methods for highly dependable systems , 1994, Proceedings of Winter Simulation Conference.

[37]  George S. Fishman,et al.  A Monte Carlo Sampling Plan for Estimating Network Reliability , 1984, Oper. Res..

[38]  Philip Heidelberger,et al.  A Unified Framework for Simulating Markovian Models of Highly Dependable Systems , 1992, IEEE Trans. Computers.

[39]  Philip Heidelberger,et al.  Effective Bandwidth and Fast Simulation of ATM Intree Networks , 1994, Perform. Evaluation.

[40]  M. Nakayama.  Asymptotics of likelihood ratio derivative estimators in simulations of highly reliable Markovian systems , 1995 .

[41]  William H. Sanders,et al.  Importance Sampling Simulation in UltraSAN , 1994, Simul..

[42]  Marvin K. Nakayama,et al.  General conditions for bounded relative error in simulations of highly reliable Markovian systems , 1996, Advances in Applied Probability.

[43]  Philip Heidelberger,et al.  Fast simulation of steady-state availability in non-Markovian highly dependable systems , 1993, FTCS-23 The Twenty-Third International Symposium on Fault-Tolerant Computing.

[44]  R. Cogburn.  A Uniform Theory for Sums of Markov Chain Transition Probabilities , 1975 .

[45]  Sandeep Juneja,et al.  Fast simulation of Markovian reliability/availability models with general repair policies , 1992, [1992] Digest of Papers. FTCS-22: The Twenty-Second International Symposium on Fault-Tolerant Computing.

[46]  Marie Cottrell,et al.  Large deviations and rare events in the study of stochastic algorithms , 1983 .

[47]  Juan A. Carrasco.  Failure distance-based simulation of repairable fault-tolerant systems , 1992 .

[48]  Michael Devetsikiotis,et al.  Statistical optimization of dynamic importance sampling parameters for efficient simulation of communication networks , 1993, TNET.

[49]  Michael Devetsikiotis,et al.  Importance Sampling Methodologies for Simulation of Communication Systems with Time-Varying Channels and Adaptive Equalizers , 1993, IEEE J. Sel. Areas Commun..

[50]  P. Heidelberger,et al.  Fast Simulation of Steady-state Availability in Non-markovian Systems , 1992 .