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    A Multifractal Wavelet Model with Application to Network Traffic

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    Author
    Riedi, Rudolf H.; Crouse, Matthew; Ribeiro, Vinay Joseph; Baraniuk, Richard G.
    Date
    1999-04-01
    Abstract
    In 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.
    Description
    Journal Paper
    Citation
    R. H. Riedi, M. Crouse, V. J. Ribeiro and R. G. Baraniuk, "A Multifractal Wavelet Model with Application to Network Traffic," IEEE Transactions on Information Theory, vol. 45, no. 3, 1999.
    Published Version
    http://dx.doi.org/10.1109/18.761337
    Keyword
    TCP Network traffic; Haar wavelet transform; multifractal wavelet model; TCP Network traffic; Haar wavelet transform; More... multifractal wavelet model Less...
    Type
    Journal article
    Citable link to this page
    https://hdl.handle.net/1911/20272
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    • DSP Publications [508]
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    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
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    Site Map