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Darryl Veitch

Researcher at University of Technology, Sydney

Publications -  133
Citations -  5791

Darryl Veitch is an academic researcher from University of Technology, Sydney. The author has contributed to research in topics: Network packet & The Internet. The author has an hindex of 35, co-authored 132 publications receiving 5607 citations. Previous affiliations of Darryl Veitch include RMIT University & AT&T.

Papers
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Journal ArticleDOI

Wavelet analysis of long-range-dependent traffic

TL;DR: A wavelet-based tool for the analysis of long-range dependence and a related semi-parametric estimator of the Hurst parameter is introduced and is shown to be unbiased under very general conditions, and efficient under Gaussian assumptions.
Journal ArticleDOI

A wavelet-based joint estimator of the parameters of long-range dependence

TL;DR: A joint estimator is presented for the two parameters that define the long-range dependence phenomenon in the simplest case and is found to be unbiased and of minimum or close to minimum variance for the scale parameter, and asymptotically unbiased and efficient for the second parameter.
Book ChapterDOI

Wavelets for the Analysis, Estimation, and Synthesis of Scaling Data

TL;DR: Long-range dependence-Scaling phenomena-(Multi)fractal-Wavelet analysis Scaling analysis-Sc scaling parameters estimation-Robustness-Fractional Brownian motion synthesis-Fano factor-Aggregation procedure-Allan variance.
Journal ArticleDOI

Multiscale nature of network traffic

TL;DR: The state of the art in scaling behavior in teletraffic is overview, focusing on the capabilities of the wavelet transform as a key tool for unraveling the mysteries of traffic statistics and dynamics.
Proceedings ArticleDOI

Inverting sampled traffic

TL;DR: In this paper, the spectral density, a second order statistic, and the distribution of the number of packets per flow per flow were investigated for a Poisson cluster process, and it was shown that in practice this cannot be done using the traditional packet-based sampling, even for high sampling rate.