A Multifractal Wavelet Model with Application to Network Traffic

dc.citation.bibtexNamearticleen_US
dc.citation.firstpage992en_US
dc.citation.issueNumber3en_US
dc.citation.journalTitleIEEE Transactions on Information Theoryen_US
dc.citation.lastpage1018en_US
dc.citation.volumeNumber45en_US
dc.contributor.authorRiedi, Rudolf H.en_US
dc.contributor.authorCrouse, Matthewen_US
dc.contributor.authorRibeiro, Vinay Josephen_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.orgCenter for Multimedia Communications (http://cmc.rice.edu/)en_US
dc.date.accessioned2007-10-31T01:01:21Zen_US
dc.date.available2007-10-31T01:01:21Zen_US
dc.date.issued1999-04-01en_US
dc.date.modified2006-06-21en_US
dc.date.submitted2001-09-04en_US
dc.descriptionJournal Paperen_US
dc.description.abstractIn this paper, we develop a new multiscale modeling framework for characterizing positive-valued data with long-range-dependent correlations (1/f noise). Using the Haar wavelet transform and a special multiplicative structure on the wavelet and scaling coefficients to ensure positive results, the model provides a rapid O(N) cascade algorithm for synthesizing N-point data sets. We study both the second-order and multifractal properties of the model, the latter after a tutorial overview of multifractal analysis. We derive a scheme for matching the model to real data observations and, to demonstrate its effectiveness, apply the model to network traffic synthesis. The flexibility and accuracy of the model and fitting procedure result in a close fit to the real data statistics (variance-time plots and moment scaling) and queuing behavior. Although for illustrative purposes we focus on applications in network traffic modeling, the multifractal wavelet model could be useful in a number of other areas involving positive data, including image processing, finance, and geophysics.en_US
dc.description.sponsorshipDefense Advanced Research Projects Agencyen_US
dc.description.sponsorshipOffice of Naval Researchen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.identifier.citationR. H. Riedi, M. Crouse, V. J. Ribeiro and R. G. Baraniuk, "A Multifractal Wavelet Model with Application to Network Traffic," <i>IEEE Transactions on Information Theory,</i> vol. 45, no. 3, 1999.en_US
dc.identifier.doihttp://dx.doi.org/10.1109/18.761337en_US
dc.identifier.urihttps://hdl.handle.net/1911/20272en_US
dc.language.isoengen_US
dc.subjectTCP Network trafficen_US
dc.subjectHaar wavelet transformen_US
dc.subjectmultifractal wavelet modelen_US
dc.subject.keywordTCP Network trafficen_US
dc.subject.keywordHaar wavelet transformen_US
dc.subject.keywordmultifractal wavelet modelen_US
dc.titleA Multifractal Wavelet Model with Application to Network Trafficen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
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