A network traffic prediction approach based on multifractal modeling

This work extends the notion of the widely mentioned and used fractional Brownian traffic model in the literature. Extensive experimental investigations indicate that the proposed traffic model, named extended fractional Brownian traffic, can capture not only the self-similar properties, but also th...

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Bibliographic Details
Published inJournal of high speed networks Vol. 17; no. 2; pp. 83 - 96
Main Authors Vieira, Flávio Henrique Teles, Bianchi, Gabriel Rocon, Lee, Luan Ling
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.05.2010
Subjects
Algorithms
Communication networks
High speed
Mathematical models
Networks
Self-similarity
Traffic engineering
Traffic flow
multifractal model
Network traffic
traffic prediction
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ISSN0926-6801
1875-8940
DOI10.3233/JHS-2010-0334

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Summary:This work extends the notion of the widely mentioned and used fractional Brownian traffic model in the literature. Extensive experimental investigations indicate that the proposed traffic model, named extended fractional Brownian traffic, can capture not only the self-similar properties, but also the inherent multifractal characteristics of those traffic flows found in modern communication networks. Additionally, the structure of this traffic model is taken into account in a traffic prediction algorithm that benefits from the more accurate traffic modeling. The experimental results clearly point out the advantages of using the proposed model in traffic modeling as well as in traffic prediction.
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ISSN:0926-6801
1875-8940
DOI:10.3233/JHS-2010-0334