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- W2765606180 abstract "Abstract Uniformization, also referred to as randomization, is a well-known performance evaluation technique to model and analyse continuous-time Markov chains via an easier to performance measures via iteration of the one-step transition matrix of the discrete-time Markov chain. The number of iterations has a Poisson distribution with rate dominating the maximum exit rate from the states of the continuous-time Markov chain. This paper contains an expository presentation of uniformization techniques to increase awareness and to provide a formal and intuitive justification of several exact and approximate extensions, including: • exact uniformization for reward models, • exact uniformization for time-inhomogeneous rates, • a numerical comparison with simple time-discretization, • approximate uniformization for unbounded transition rates, and • exact uniformization for continuous state variables for non-exponential networks. Furthermore, several of these results are numerically illustrated for a processor sharing web server tandem model of practical interest." @default.
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- W2765606180 date "2018-02-01" @default.
- W2765606180 modified "2023-10-18" @default.
- W2765606180 title "Uniformization: Basics, extensions and applications" @default.
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- W2765606180 doi "https://doi.org/10.1016/j.peva.2017.09.008" @default.
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