On network traffic statistical analysis

On network traffic statistical analysis

The present article deals with statistical university network traffic, by applying the methods of self-similarity and chaos analysis. The object of measurement is Šiauliai University LitNet network node maintaining institutions of education of the northern Lithuania region. Time series of network t...

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Bibliographic Details
Main Authors: Liudas Kaklauskas, Leonidas Sakalauslas
Format: Article
Language:English
Published: Vilnius University Press 2020-05-01
Series:Lietuvos Matematikos Rinkinys
Subjects:
self-similarity
computer network
fractality
Online Access:https://www.journals.vu.lt/LMR/article/view/18116
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spelling doaj-05b7d6ca12a7407da83452e0d64d26ec2020-11-25T02:14:59ZengVilnius University PressLietuvos Matematikos Rinkinys0132-28182335-898X2020-05-0148proc. LMS10.15388/LMR.2008.18116On network traffic statistical analysisLiudas Kaklauskas 0Leonidas Sakalauslas1Institute of Mathematics and InformaticsInstitute of Mathematics and Informatics The present article deals with statistical university network traffic, by applying the methods of self-similarity and chaos analysis. The object of measurement is Šiauliai University LitNet network node maintaining institutions of education of the northern Lithuania region. Time series of network traffic characteristics are formed by registering amount of information packets in a node at different regimes of network traffic and different values of discretion of registered information are present. Measurement results are processed by calculating Hurst index and estimating reliability of analysis results by applying the statistical method. Investigation of the network traffic allowed us drawing conclusions that time series bear features of self-similarity when aggregated time series bear features of slowly decreasing dependence. https://www.journals.vu.lt/LMR/article/view/18116self-similaritycomputer networkfractality
collection DOAJ
language English
format Article
sources DOAJ
author Liudas Kaklauskas
Leonidas Sakalauslas
spellingShingle Liudas Kaklauskas
Leonidas Sakalauslas
On network traffic statistical analysis
Lietuvos Matematikos Rinkinys
self-similarity
computer network
fractality
author_facet Liudas Kaklauskas
Leonidas Sakalauslas
author_sort Liudas Kaklauskas
title On network traffic statistical analysis
title_short On network traffic statistical analysis
title_full On network traffic statistical analysis
title_fullStr On network traffic statistical analysis
title_full_unstemmed On network traffic statistical analysis
title_sort on network traffic statistical analysis
publisher Vilnius University Press
series Lietuvos Matematikos Rinkinys
issn 0132-2818
2335-898X
publishDate 2020-05-01
description The present article deals with statistical university network traffic, by applying the methods of self-similarity and chaos analysis. The object of measurement is Šiauliai University LitNet network node maintaining institutions of education of the northern Lithuania region. Time series of network traffic characteristics are formed by registering amount of information packets in a node at different regimes of network traffic and different values of discretion of registered information are present. Measurement results are processed by calculating Hurst index and estimating reliability of analysis results by applying the statistical method. Investigation of the network traffic allowed us drawing conclusions that time series bear features of self-similarity when aggregated time series bear features of slowly decreasing dependence.
topic self-similarity
computer network
fractality
url https://www.journals.vu.lt/LMR/article/view/18116
work_keys_str_mv AT liudaskaklauskas onnetworktrafficstatisticalanalysis
AT leonidassakalauslas onnetworktrafficstatisticalanalysis
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