Calculating Cumulative Operational Time Distributions of Repairable Computer Systems
IEEE Transactions on Computers - The MIT Press scientific computation series
Analysis of Performability for Stochastic Models of Fault-Tolerant Systems
IEEE Transactions on Computers
Performability Analysis: Measures, an Algorithm, and a Case Study
IEEE Transactions on Computers - Fault-Tolerant Computing
Journal of the ACM (JACM)
Performability Analysis Using Semi-Markov Reward Processes
IEEE Transactions on Computers
IEEE Transactions on Computers - Special issue on fault-tolerant computing
Performability Analysis: A New Algorithm
IEEE Transactions on Computers
IEEE Transactions on Computers
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
Computers and Operations Research
IEEE Transactions on Computers
Efficient implementations of the randomization method with control of the relative error
Computers and Operations Research
A performance model of highly available multicomputer systems
International Journal of Modelling and Simulation
Fast evaluation of the moments of the interval availability of large Markov models
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
Self-configuring algorithm for software fault tolerance in (n,k)-way cluster systems
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
A new availability concept for (n,k)-way cluster systems regarding waiting time
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
RAM analysis of repairable industrial systems utilizing uncertain data
Applied Soft Computing
A New General-Purpose Method for the Computation of the Interval Availability Distribution
INFORMS Journal on Computing
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Point availability and expected interval availability are dependability measures respectively defined by the probability that a system is in operation at a given instant and by the mean percentage of time during which a system is in operation over a finite observation period. We consider a repairable computer system and we assume, as usual, that the system is modeled by a finite Markov process. We propose in this paper a new algorithm to compute these two availability measures. This algorithm is based on the classical uniformization technique in which a test to detect the stationary behavior of the system is used to stop the computation if the stationarity is reached. In that case, the algorithm gives not only the transient availability measures, but also the steady state availability, with significant computational savings, especially when the time at which measures are needed is large. In the case where the stationarity is not reached, the algorithm provides the transient availability measures and bounds for the steady state availability. It is also shown how the new algorithm can be extended to the computation of performability measures.