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Skocz do pozycji: 1.

Tytuł:: Application of HM-networks with unreliable systems for finding the memory capacity in the information systems
Autorzy:: Matalytski, M.
Zajac, P.
Kopats, D.
Powiązania:: https://bibliotekanauki.pl/articles/122815.pdf
Data publikacji:: 2018
Wydawca:: Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:: HM-network
information systems
unreliable service
volumes of requests
pojemność pamięci
nadmierne buforowanie
sieci HM
sieci kolejkowe Howard-Matalytski
sieci kolejkowe
Opis:: To solve the problem of determining the memory capacity of the information systems (IS), it was proposed to use a stochastic model, based on the use of HM (Howard-Matalytski) - queueing networks with incomes. This model takes into account the servicing of requests along with their volumes, the ability to change the volumes of the requests over time and the possibility of damaging IS nodes and their repairs, so servicing of demands can be interrupted randomly. The expressions are generated for the mean (expected) values of total requests volumes in the IS nodes.
Źródło:: Journal of Applied Mathematics and Computational Mechanics; 2018, 17, 2; 51-63
2299-9965
Pojawia się w:: Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Diffusion approximation of the network with limited number of same type customers and time dependent service parameters
Autorzy:: Matalytski, M.
Kopats, D.
Powiązania:: https://bibliotekanauki.pl/articles/122463.pdf
Data publikacji:: 2016
Wydawca:: Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:: queueing network
birth and death process
asymptotic analysis
sieci kolejkowe
analiza asymptotyczna
proces losowy
Opis:: The article presents research of an open queueing network (QN) with the same types of customers, in which the total number of customers is limited. Service parameters are dependent on time, and the route of customers is determined by an arbitrary stochastic transition probability matrix, which is also dependent on time. Service times of customers in each line of the system is exponentially distributed. Customers are selected on the service according to FIFO discipline. It is assumed that the number of customers in one of the systems is determined by the process of birth and death. It generates and destroys customers with certain service times of rates. The network state is described by the random vector, which is a Markov random process. The purpose of the research is an asymptotic analysis of its process with a big number of customers, obtaining a system of differential equations (DE) to find the mean relative number of customers in the network systems at any time. A specific model example was calculated using the computer. The results can be used for modelling processes of customer service in the insurance companies, banks, logistics companies and other organizations.
Źródło:: Journal of Applied Mathematics and Computational Mechanics; 2016, 15, 2; 77-84
2299-9965
Pojawia się w:: Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Analysis of the queueing network with a random waiting time of negative customers at a non-stationary regime
Autorzy:: Naumenko, V.
Matalytski, M.
Kopats, D.
Powiązania:: https://bibliotekanauki.pl/articles/122923.pdf
Data publikacji:: 2016
Wydawca:: Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:: G-network
positive customers
negative customers
random waiting time
heavy-traffic regime
state probabilities
mean characteristics
non-stationary regime
sieci kolejkowe
sieć G
pozytywny klient
negatywny klient
czas oczekiwania
równania różniczkowe
Opis:: In the article a queueing network (QN) with positive customers and a random waiting time of negative customers has been investigated. Negative customers destroy positive customers on the expiration of a random time. Queueing systems (QS) operate under a heavy-traffic regime. The system of difference-differential equations (DDE) for state probabilities of such a network was obtained. The technique of solving this system and finding mean characteristics of the network, which is based on the use of multivariate generating functions was proposed.
Źródło:: Journal of Applied Mathematics and Computational Mechanics; 2016, 15, 3; 111-122
2299-9965
Pojawia się w:: Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:: Biblioteka Nauki

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