Електронна бібліотека Житомирського державного університету: Ніяких умов. Результати впорядковані-Дата внесення. 2024-03-29T14:28:05ZEPrintshttp://eprints.zu.edu.ua/images/logo2.gifhttp://eprints.zu.edu.ua/2014-10-23T09:08:02Z2023-02-16T13:17:43Zhttp://eprints.zu.edu.ua/id/eprint/13296Цей елемент знаходиться в архіві з URL: http://eprints.zu.edu.ua/id/eprint/132962014-10-23T09:08:02ZStationary Effectiveness of an Information Server with a Single Buffer and Bursty Demands of Two Different CustomersIn this article we study the stationary efficiency of a system consisting of a finite capacity
buffer connected to two different customers with bursty on-off demands. We assume that the
buffer is filled up at a constant rate. The dynamic of the overall system is modeled using
a semi-Markov evolution environment and we derive design formulae involving the main
parameters. It has been shown that it is possible to use the phase merging algorithm (PMA) to
reduce the semi-Markov process to an approximated Markov process. We apply the PMA to the
analysis of two different semi-Markov cases.A. A. PogoruiRamón М. Rodríguez-DagnіnoR. D. Rodríguez-Saіd2014-10-21T07:23:19Z2023-02-16T13:18:13Zhttp://eprints.zu.edu.ua/id/eprint/13247Цей елемент знаходиться в архіві з URL: http://eprints.zu.edu.ua/id/eprint/132472014-10-21T07:23:19ZStationary probability distribution of a system with N equal customers with bursty demands connected to a single bufferIn this paper we study the stationary probability distribution of a system consisting of a finite capacity buffer connected to N equal customers with bursty on-off demands. We assume that the buffer is filled up at a constant rate and we analyze the case when this filling rate satisfies an optimization condition according to the customer demands. First, we consider semi-Markov on-off demands for the case N = 2 and we model the dynamics of the system using a semi-Markov evolution environment. We show that we can use the phase merging algorithm to reduce the problem to a Markov evolution environment case. Then, we generalize the results for any N using a birth-and-death process.R. D. Rodríguez-SaіdA. A. PogoruiRamón М. Rodríguez-Dagnіno