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- W142708085 abstract "During the last decades stochastic simulation methods have been utilized more and more in different research fields to describe complicated real-world phenomena. Reasons for the popularity are dramatic increase in processing power and significant decrease of price of computing systems. However, the main reason may be that the probability theory is a well-known tool for presentation and processing of stochastic information. In this article are described fundamental stochastic features of communication network simulation models. Especially, a concept of convergence time is considered and its numerical evaluation is defined by an example simulations. Network models considered here are event based discrete time models, which utilise Markov chain theory for state transitions and Monte Carlo method for duration times of events. Numerous reported case studies of stochastic simulations do not contain any information about a convergence time of the model. Therefore, it is possible that the reported results are randomly biased due to too short simulation (shorter than the convergence time) periods as illustrated in this article by examples." @default.
- W142708085 created "2016-06-24" @default.
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- W142708085 date "2006-04-16" @default.
- W142708085 modified "2023-09-26" @default.
- W142708085 title "Stochastic network simulation for reliable results" @default.
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