A method of forming a self-similar flow with a given Hurst parameter for network traffic modeling

This article addresses the problem of adequate network traffic modeling. A new method is proposed that enables the generation of self-similar packet flows with an arbitrarily specified degree of self-similarity. The method is based on the use of the Pareto distribution and the maximum likelihood met...

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Main Authors: P.E. Pustovoitov, V.O. Kompaniets
Format: Article
Language:English
Published: Zhytomyr Polytechnic State University 2024-12-01
Series:Технічна інженерія
Subjects:
Online Access:http://ten.ztu.edu.ua/article/view/319730
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author P.E. Pustovoitov
V.O. Kompaniets
author_facet P.E. Pustovoitov
V.O. Kompaniets
author_sort P.E. Pustovoitov
collection DOAJ
description This article addresses the problem of adequate network traffic modeling. A new method is proposed that enables the generation of self-similar packet flows with an arbitrarily specified degree of self-similarity. The method is based on the use of the Pareto distribution and the maximum likelihood method for estimating model parameters. The obtained results can be used to construct more realistic simulation models of computer networks. The authors propose a mathematical apparatus method for the procedure of forming self-similar traffic, which involves creating an accurate and efficient model that reflects the real properties of self-similarity in data flows. An effective tool for modeling complex network processes is proposed, allowing more accurate prediction of infocommunication network behavior and optimization of its operation. The proposed method can be applied to develop new data transmission protocols and analyze the efficiency of existing ones. A relationship has been obtained that allows calculating the appropriate value of the Pareto distribution parameter, which ensures the formation of a self-similar flow with the required Hurst parameter value. The procedure can be used to describe traffic when constructing a simulation model of computer network functioning.
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publishDate 2024-12-01
publisher Zhytomyr Polytechnic State University
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spelling doaj-art-d592a553fdff4be8941beda3acfd92c62025-08-20T02:42:00ZengZhytomyr Polytechnic State UniversityТехнічна інженерія2706-58472707-96192024-12-01942185190doi.org/10.26642/ten-2024-2(94)-185-190A method of forming a self-similar flow with a given Hurst parameter for network traffic modelingP.E. Pustovoitov0https://orcid.org/0000-0003-3884-0200V.O. Kompaniets1https://orcid.org/0000-0003-2909-6993National Technical University "Kharkiv Polytechnic Institute", UkraineNational Technical University "Kharkiv Polytechnic Institute", UkraineThis article addresses the problem of adequate network traffic modeling. A new method is proposed that enables the generation of self-similar packet flows with an arbitrarily specified degree of self-similarity. The method is based on the use of the Pareto distribution and the maximum likelihood method for estimating model parameters. The obtained results can be used to construct more realistic simulation models of computer networks. The authors propose a mathematical apparatus method for the procedure of forming self-similar traffic, which involves creating an accurate and efficient model that reflects the real properties of self-similarity in data flows. An effective tool for modeling complex network processes is proposed, allowing more accurate prediction of infocommunication network behavior and optimization of its operation. The proposed method can be applied to develop new data transmission protocols and analyze the efficiency of existing ones. A relationship has been obtained that allows calculating the appropriate value of the Pareto distribution parameter, which ensures the formation of a self-similar flow with the required Hurst parameter value. The procedure can be used to describe traffic when constructing a simulation model of computer network functioning.http://ten.ztu.edu.ua/article/view/319730self-similar traffichurstʼs parameterpareto distributionmathematical tools
spellingShingle P.E. Pustovoitov
V.O. Kompaniets
A method of forming a self-similar flow with a given Hurst parameter for network traffic modeling
Технічна інженерія
self-similar traffic
hurstʼs parameter
pareto distribution
mathematical tools
title A method of forming a self-similar flow with a given Hurst parameter for network traffic modeling
title_full A method of forming a self-similar flow with a given Hurst parameter for network traffic modeling
title_fullStr A method of forming a self-similar flow with a given Hurst parameter for network traffic modeling
title_full_unstemmed A method of forming a self-similar flow with a given Hurst parameter for network traffic modeling
title_short A method of forming a self-similar flow with a given Hurst parameter for network traffic modeling
title_sort method of forming a self similar flow with a given hurst parameter for network traffic modeling
topic self-similar traffic
hurstʼs parameter
pareto distribution
mathematical tools
url http://ten.ztu.edu.ua/article/view/319730
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AT vokompaniets amethodofformingaselfsimilarflowwithagivenhurstparameterfornetworktrafficmodeling
AT pepustovoitov methodofformingaselfsimilarflowwithagivenhurstparameterfornetworktrafficmodeling
AT vokompaniets methodofformingaselfsimilarflowwithagivenhurstparameterfornetworktrafficmodeling