Semi-Markov resource flow as a bit-level model of traffic A. A. Nazarov, A. N. Moiseev, I. L. Lapatin [et al.]
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ArticleContent type: Текст Media type: электронный Subject(s): полумарковские потокии | асимптотический анализ | гауссовская аппроксимация | моделирование трафикаGenre/Form: статьи в сборниках Online resources: Click here to access online
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Distributed computer and communication networks : 24th International Conference, DCCN 2021, Moscow, Russia, September 20–24, 2021 : revised selected papers P. 220-232Abstract: In this paper, we consider semi-Markov flow as a bit-level model of traffic. Each request of the flow brings some arbitrary distributed amount of information to the system. The current paper aims to investigate the amount of information received in semi-Markov flow during time unit. We use the asymptotic analysis method under the limit condition of growing time of observation to derive the limiting probability distribution of the amount of information received in the flow and build the approximation of its prelimit distribution function.
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In this paper, we consider semi-Markov flow as a bit-level model of traffic. Each request of the flow brings some arbitrary distributed amount of information to the system. The current paper aims to investigate the amount of information received in semi-Markov flow during time unit. We use the asymptotic analysis method under the limit condition of growing time of observation to derive the limiting probability distribution of the amount of information received in the flow and build the approximation of its prelimit distribution function.
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