Additive and Multiplicative Mixture Trees for Network Traffic Modeling

dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)en_US
dc.citation.firstpageIV-4040en_US
dc.citation.lastpageIV4043en_US
dc.citation.locationOrlando, FLen_US
dc.citation.volumeNumber4en_US
dc.contributor.authorSarvotham, Shriramen_US
dc.contributor.authorWang, Xuguangen_US
dc.contributor.authorRiedi, Rudolf H.en_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T01:03:40Zen_US
dc.date.available2007-10-31T01:03:40Zen_US
dc.date.issued2002-05-01en_US
dc.date.modified2006-06-07en_US
dc.date.note2006-06-07en_US
dc.date.submitted2002-05-01en_US
dc.descriptionConference paperen_US
dc.description.abstractNetwork traffic exhibits drastically different statistics, ranging from nearly Gaussian marginals and long range dependence at very large time scales to highly non-Gaussian marginals and multifractal scaling on small scales. This behavior can be explained by forming two components of the traffic according to the speed of connections, one component absorbing most traffic and being mostly Gaussian, the other constituting virtually all the small scale bursts. Towards a better understanding of this phenomenon, we propose a novel tree-based model which is flexible enough to accommodate Gaussian as well as bursty behavior on different scales in a parsimonious way.en_US
dc.identifier.citationS. Sarvotham, X. Wang, R. H. Riedi and R. G. Baraniuk, "Additive and Multiplicative Mixture Trees for Network Traffic Modeling," vol. 4, 2002.en_US
dc.identifier.doihttp://dx.doi.org/10.1109/ICASSP.2002.5745544en_US
dc.identifier.urihttps://hdl.handle.net/1911/20317en_US
dc.language.isoengen_US
dc.subject.otherDSP for Communicationsen_US
dc.titleAdditive and Multiplicative Mixture Trees for Network Traffic Modelingen_US
dc.typeConference paperen_US
dc.type.dcmiTexten_US
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