A hybrid, combinatorial-Markov method of solving performance and reliability models
A hybrid, combinatorial-Markov method of solving performance and reliability models
Performance and reliability analysis of computer systems: an example-based approach using the SHARPE software package
Performance Modelling of Communication Networks and Computer Architectures (International Computer S
Performance Modelling of Communication Networks and Computer Architectures (International Computer S
Semi-numerical Solution of Stochastic Process Algebra Models
ARTS '99 Proceedings of the 5th International AMAST Workshop on Formal Methods for Real-Time and Probabilistic Systems
Queueing models of RAID systems with maxima of waiting times
Performance Evaluation
Calibration of a Queueing Model of RAID Systems
Electronic Notes in Theoretical Computer Science (ENTCS)
A Fast Model for Evaluating the Detection of Selfish Nodes Using a Collaborative Approach in MANETs
Wireless Personal Communications: An International Journal
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This paper treats a practical problem that arises in the area of stochastic process algebras. The problem is the efficient computation of the mean value of the maximum of phase-type distributed random variables. The maximum of phase-type distributed random variables is again phase-type distributed, however, its representation grows exponentially in the number of considered random variables. Although an efficient representation in terms of Kronecker sums is straightforward, the computation of the mean value requires still exponential time, if carried out by traditional means. In this paper, we describe an approximation method to compute the mean value in only polynomial time in the number of considered random variables and the size of the respective representations. We discuss complexity, numerical stability and convergence of the approach.