Open AccessApplication of EM-Algorithm for Approximation of Correlated Traffic Probabilities Density by Hyperexponents
Author(s) -
Marina Buranova,
Igor Kartashevskiy
Publication year - 2021
Publication title -
trudy učebnyh zavedenij svâzi
Language(s) - English
Resource type - Journals
eISSN - 2712-8830
pISSN - 1813-324X
DOI - 10.31854/1813-324x-2021-7-4-10-17
Subject(s) - computer science , algorithm , task (project management) , uncorrelated , simple (philosophy) , traffic flow (computer networking) , probability distribution , quality (philosophy) , probability density function , flow (mathematics) , mathematical optimization , mathematics , statistics , engineering , philosophy , geometry , computer security , systems engineering , epistemology
An accurate assessment of the quality of service parameters in modern information communication networks is a very important task. This paper proposes the use of hyperexponential distributions to solve the problem of approxi-mating an arbitrary probability density in the G/G/1 system for the case when the approximation by a system of the type H2/H2/1 is assumed. To determine the parameters of the probability density of the hyperexponential distribu-tion, it is proposed to use EM- algorithm that provides fairly simple use cases for uncorrelated flows. In this paper, we propose a variant of the EM algorithm implementation for determining the parameters of the hyperexponential distribution in the presence of correlation properties of the analyzed flow.