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Asymptotic analysis of a closed G-network of unreliable nodes

Rusilko Tatiana

Journal of Applied Mathematics and Computational Mechanics

2022

Vol. 21, nr 2

91--102

A closed exponential queueing G-network of unreliable multi-server nodes was studied under the asymptotic assumption of a large number of customers. The process of changing the number of functional servers in network nodes was considered as the birth-death process. The process of changing the number of customers at the nodes was considered as a continuous-state Markov process. It was proved that its probability density function satisfies the Fokker-Planck-Kolmogorov equation. The system of differential equations for the first-order and second-order moments of this process was derived. This allows us to predict the expectation, the variance and the pairwise correlation of the number of customers in the G-network nodes both in the transient and steady state.

Formulas for average transition times between states of the Markov birth-death process

Zhernovyi Yuriy, Kopytko Bohdan

Journal of Applied Mathematics and Computational Mechanics

2021

Vol. 20, nr 4

99--110

In this paper, we consider Markov birth-death processes with constant intensities of transitions between neighboring states that have an ergodic property. Using the exponential distributions properties, we obtain formulas for the mean time of transition from the state i to the state j and transitions back, from the state j to the state i. We found expressions for the mean time spent outside the given state i, the mean time spent in the group of states (0,...,i-1) to the left from state i, and the mean time spent in the group of states (i+1,i+2,...) to the right. We derive the formulas for some special cases of the Markov birth-death processes, namely, for the Erlang loss system, the queueing systems with finite and with infinite waiting room and the reliability model for a recoverable system.

Simulating an infinite mean waiting time

Bartoszek Krzysztof

Mathematica Applicanda

2019

Vol. 47, no. 1

93--102

We consider a hybrid method to simulate the return time to the initial state in a critical-case birth-death process. The expected value of this return time is infinite, but its distribution asymptotically follows a power-law. Hence, the simulation approach is to directly simulate the process, unless the simulated time exceeds some threshold and if it does, draw the return time from the tail of the power law.

W pracy rozważany jest mieszany sposób symulowania czasu powrotu do stanu początkowego określonego krytycznego procesu narodzin i śmierci. Ten czas powrotu ma nieskończoną wartość oczekiwaną przy czym jego asymptotyczny rozkład jest potęgowy. Zatem dopóki symulowany czas nie przekroczy pewnej granicznej wartości proces jest symulowany bezpośrednio. W chwili przekroczenia tej wartości granicznej czas powrotu jest losowany z ogona tego rozkładu potęgowego.