NDLI: The modified Allan variance as time-domain analysis tool for estimating the Hurst parameter of long-range dependent traffic

Content Provider	IEEE Xplore Digital Library
Author	Bregni, S. Primerano, L.
Copyright Year	2004
Description	Author affiliation: Dept. of Electron. & Inf., Politecnico di Milano, Italy (Bregni, S.; Primerano, L.)
Abstract	Experimental measurements show that Internet traffic exhibits self-similarity and long-range dependence (LRD). A delicate issue is the estimation of traffic statistical quantities that characterize self-similarity and LRD, such as the Hurst parameter H. In this paper, we propose to use the modified Allan variance (MAVAR), a well-known time-domain tool originally studied for frequency stability characterization, for estimating the power-law spectrum and thus the H parameter of LRD traffic time series. This novel method is validated by comparison with one of the most widely adopted algorithms for analyzing LRD traffic: the log-scale diagram technique, based on wavelet analysis. Both methods are applied to a pseudo-random data series, generated with known values of H. MAVAR exhibits outstanding accuracy in estimating H, better than the classical log-scale method. Finally, both techniques are applied to a real IP traffic trace, providing a further example of the capabilities of MAVAR.
Starting Page	1406
Ending Page	1410
File Size	627898
Page Count	5
File Format	PDF
ISBN	0780387945
DOI	10.1109/GLOCOM.2004.1378215
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-11-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time domain analysis Parameter estimation Internet Algorithm design and analysis Frequency estimation Stability Communication system traffic control Fractals Wavelet analysis TCPIP
Content Type	Text
Resource Type	Article

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