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Input Modeling with Phase-Type Distributions and Markov Models

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Abstract

Quantitative analysis of man-made systems like computer systems, communication networks, manufacturing plants, logistics networks, to mention only few examples, is often done by means of discrete event models that are analyzed numerically [152] or by simulation [105]. One key issue in these models is the adequate modeling of the load which describes the occurrence of events, let it be customer arrivals in queueing networks, failure times in reliability models or packet lengths in simulation models of computer networks. In more abstract terms one can think of arrival, service or failure times that are part of a model. We will use the term inter-event times to capture the different quantities in a model. Inter-event times are characterized by random variables or stochastic processes generating non-negative numbers.

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  1. Department of Computer Science, Technical University of Dortmund, Dortmund, Germany

    Peter Buchholz, Jan Kriege & Iryna Felko

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  1. Peter Buchholz
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  2. Jan Kriege
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  3. Iryna Felko
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© 2014 Peter Buchholz, Jan Kriege, Iryna Felko

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Buchholz, P., Kriege, J., Felko, I. (2014). Introduction. In: Input Modeling with Phase-Type Distributions and Markov Models. SpringerBriefs in Mathematics. Springer, Cham. https://doi.org/10.1007/978-3-319-06674-5_1

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