Uniformization and hybrid simulation/analytic models of renewal processes
Operations Research
Modeling and analysis of computer system availability
IBM Journal of Research and Development
Importance sampling for stochastic simulations
Management Science
Discrete-time conversion for simulating finite-horizon Markov processes
SIAM Journal on Applied Mathematics
A Unified Framework for Simulating Markovian Models of Highly Dependable Systems
IEEE Transactions on Computers
WSC '92 Proceedings of the 24th conference on Winter simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Importance sampling for the simulation of highly reliable Markovian systems
Management Science
Fast transient simulation of Markovian models of highly dependable systems
Performance '93 Proceedings of the 16th IFIP Working Group 7.3 international symposium on Computer performance modeling measurement and evaluation
Efficient estimation of the mean time between failures in non-regenerative dependability models
WSC '93 Proceedings of the 25th conference on Winter simulation
Estimation of reliability and its derivatives for large time horizons in Markovian systems
WSC '93 Proceedings of the 25th conference on Winter simulation
Simulation and analysis of highly reliable systems
Simulation and analysis of highly reliable systems
Efficiency improvement and variance reduction
WSC '94 Proceedings of the 26th conference on Winter simulation
Fast simulation methods for highly dependable systems
WSC '94 Proceedings of the 26th conference on Winter simulation
Fast simulation of rare events in queueing and reliability models
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Rare event simulation in stochastic models
WSC '95 Proceedings of the 27th conference on Winter simulation
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ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue: Rare event simulation
SPNP: Stochastic Petri Nets. Version 6.0
TOOLS '00 Proceedings of the 11th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
SREPT: Software Reliability Estimation and Prediction Tool
TOOLS '00 Proceedings of the 11th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
Cybernetics and Systems Analysis
Fast Simulation of Unavailability of a Repairable System with a Bounded Relative Error of Estimate
Cybernetics and Systems Analysis
Fast Simulation of Unavailability of a Repairable System with a Bounded Relative Error of Estimate
Cybernetics and Systems Analysis
Estimation of Stationary Loss Probability in a Queuing System with Recurrent Input Flows
Cybernetics and Systems Analysis
Probability in the Engineering and Informational Sciences
Cybernetics and Systems Analysis
New measures of robustness in rare event simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Perwez Shahabuddin, 1962--2005: A professional appreciation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Rare events, splitting, and quasi-Monte Carlo
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Performance assessment for single echelon airport spare part management
Computers and Industrial Engineering
Exact and Efficient Simulation of Correlated Defaults
SIAM Journal on Financial Mathematics
Zero-Variance Importance Sampling Estimators for Markov Process Expectations
Mathematics of Operations Research
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This article deals with fast simulation techniques for estimating transient measures in highly dependable systems. The systems we consider of components with generally distributed lifetimes and repair times, with complex interaction among components. As is well known, standard simulation of highly dependable systems is very inefficient, and importance-sampling is widely used to improve efficiency. We present two new techniques, one of which is based on the uniformization approach to simulation, and the other is a natural extension of the uniformization approach which we call exponential transformation. We show that under certain assumptions, these techniques have the bounded relative error property, i.e., the relative error of the simulation estimate remains bounded as components become more and more reliable, unlike standard simulation in which it tends to infinity. This implies that only a fixed number of observations are required to achieve a given relative error, no matter how rare the failure events are.