The G-network as a stochastic data network model

  • Tatiana V. Rusilko Yanka Kupala State University of Grodno, 22 Azheshka Street, Grodna 230023, Belarus
DOI: https://doi.org/10.33581/2520-6508-2023-2-45-54

Abstract

The primary objective of this paper is the mathematical modelling of a data network consisting of terminal devices connected by routing devices and data links. A closed exponential G-network of single-server queueing nodes with positive requests and signals is used as a stochastic model. The model is studied in the asymptotic case of a large number of requests being processed. The mathematical approach used makes it possible to calculate the main statistical characteristics of a Markov process describing the model state, as well as to reconstruct analytically its normal probability density function based on the Gaussian approximation method. The results of the study allow us to analyse the data network performance in both transient and steady state. The areas of implementation of the research results are the pre-design of data networks and solving problems of their optimisation.

Author Biography

Tatiana V. Rusilko, Yanka Kupala State University of Grodno, 22 Azheshka Street, Grodna 230023, Belarus

PhD (physics and mathematics), docent; associate professor at the department of fundamental and applied mathematics, faculty of mathematics and informatics

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Published
2023-07-25
Keywords: G-network, data network, queueing network, asymptotic analysis, Gaussian approximation, mathematical modelling
Supporting Agencies The research was supported by the state programme of scientific research «Convergence-2025» (subprogramme «Mathematical models and methods», assignment 1.6.01).
How to Cite
Rusilko, T. V. (2023). The G-network as a stochastic data network model. Journal of the Belarusian State University. Mathematics and Informatics, 2, 45-54. https://doi.org/10.33581/2520-6508-2023-2-45-54
Issue
No 2 (2023): Journal of the Belarusian State University. Mathematics and Informatics
Section
Probability Theory and Mathematical Statistics

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