Multiscale Queuing Analysis

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dc.citation.bibtexNamearticleen_US
dc.citation.journalTitleIEEE Transactions on Networkingen_US
dc.contributor.authorRibeiro, Vinay Josephen_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.accessioned2007-10-31T01:00:48Zen_US
dc.date.available2007-10-31T01:00:48Zen_US
dc.date.issued2006-10-01en_US
dc.date.modified2006-06-28en_US
dc.date.submitted2006-02-23en_US
dc.descriptionJournal Paperen_US
dc.description.abstractThis paper introduces a new multiscale framework for estimating the tail probability of a queue fed by an arbitrary traffic process. Using traffic statistics at a small number of time scales, our analysis extends the theoretical concept of the critical time scale and provides practical approximations for the tail queue probability. These approximations are non-asymptotic; that is they apply to any finite queue threshold. While our approach applies to any traffic process, it is particularly apt for long-range-dependent (LRD) traffic. For LRD fractional Brownian motion, we prove that a sparse exponential spacing of time scales yields optimal performance. Simulations with LRD traffic models and real Internet traces demonstrate the accuracy of the approach. Finally, simulations reveal that the marginals of traffic at multiple time scales have a strong influence on queuing that is not captured well by its global second-order correlation in non-Gaussian scenarios.en_US
dc.description.sponsorshipTexas Advanced Technology Programen_US
dc.description.sponsorshipDefense Advanced Research Projects Agencyen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.identifier.citationV. J. Ribeiro, R. H. Riedi and R. G. Baraniuk, "Multiscale Queuing Analysis," <i>IEEE Transactions on Networking,</i> 2006.en_US
dc.identifier.doihttp://dx.doi.org/10.1109/TNET.2006.882987en_US
dc.identifier.urihttps://hdl.handle.net/1911/20259en_US
dc.language.isoengen_US
dc.subjectlong-range-dependenceen_US
dc.subjectself-similarityen_US
dc.subjectqueuingen_US
dc.subjectwaveletsen_US
dc.subjectmultifractalsen_US
dc.subjectcritical time-scaleen_US
dc.subjectmultiscaleen_US
dc.subjecttreesen_US
dc.subjectfractioanl Gaussian noiseen_US
dc.subjectfractional Brownian motionen_US
dc.subjectrelevant time-scalesen_US
dc.subject.keywordlong-range-dependenceen_US
dc.subject.keywordself-similarityen_US
dc.subject.keywordqueuingen_US
dc.subject.keywordwaveletsen_US
dc.subject.keywordmultifractalsen_US
dc.subject.keywordcritical time-scaleen_US
dc.subject.keywordmultiscaleen_US
dc.subject.keywordtreesen_US
dc.subject.keywordfractioanl Gaussian noiseen_US
dc.subject.keywordfractional Brownian motionen_US
dc.subject.keywordrelevant time-scalesen_US
dc.subject.otherSignal Processing for Networkingen_US
dc.titleMultiscale Queuing Analysisen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
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