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Toward an Improved Understanding of Network Traffic Dynamics

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dc.contributor.author Riedi, Rudolf H.
Willinger, Walter
dc.contributor.editor Park and Willinger
dc.creator Riedi, Rudolf H.
Willinger, Walter
dc.date.accessioned 2007-10-31T01:01:34Z
dc.date.available 2007-10-31T01:01:34Z
dc.date.issued 2000-01-15
dc.date.submitted 2002-12-05
dc.identifier.uri http://hdl.handle.net/1911/20276
dc.description Book Chapter
dc.description.abstract Since the discovery of long range dependence in Ethernet LAN traces there has been significant progress in developing appropriate mathematical and statistical techniques that provide a physical-based, networking-related understanding of the observed fractal-like or self-similar scaling behavior of measured data traffic over time scales ranging from hundreds of milliseconds to seconds and beyond. These developments have helped immensely in demystifying fractal-based traffic modeling and have given rise to new insights and physical understanding of the effects of large-time scaling properties in measured network traffic on the design, management and performance of high-speed networks. However, to provide a complete description of data network traffic, the same kind of understanding is necessary with respect to the dynamic nature of traffic over small time scales, from a few hundreds of milliseconds downwards. Because of the predominant protocols and end-to-end congestion control mechanisms that determine the flow of packets, studying the fine-time scale behavior or local characteristics of data traffic is intimately related to understanding the complex interactions that exist in data networks. In this chapter, we first summarize the results that provide a unifying and consistent picture of the large-time scaling behavior of data traffic. We then report on recent progress in studying the small-time scaling behavior in data network traffic and outline a number of challenging open problems that stand in the way of providing an understanding of the local traffic characteristics that is as plausible, intuitive, appealing and relevant as the one that has been found for the global or large-time scaling properties of data traffic.
dc.description.sponsorship National Science Foundation
dc.language.iso eng
dc.publisher Wiley
dc.subject Self-similar
multifractal
network traffic
dc.subject.other Wavelet based Signal/Image Processing
Multiscale Methods
Signal Processing for Networking
Multifractals
dc.title Toward an Improved Understanding of Network Traffic Dynamics
dc.type Book Chapter
dc.citation.bibtexName inbook
dc.citation.journalTitle Self-similar Network Traffic and Performance Evaluation, eds Park and Willinger, Wiley
dc.date.modified 2002-12-05
dc.contributor.center Center for Multimedia Communications (http://cmc.rice.edu/)
dc.contributor.center Digital Signal Processing (http://dsp.rice.edu/)
dc.subject.keyword Self-similar
multifractal
network traffic
dc.citation.pageNumber 507-530
dc.type.dcmi Text
dc.identifier.citation R. H. Riedi and W. Willinger, "Toward an Improved Understanding of Network Traffic Dynamics," Self-similar Network Traffic and Performance Evaluation, eds Park and Willinger, Wiley, pp. 507-530, 2000.

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  • ECE Publications [1034 items]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508 items]
    Publications by Rice Faculty and graduate students in digital signal processing.
  • CMC Publications [275 items]
    Publications by Rice Faculty and graduate students in multimedia communications