The modified allan variance as time-domain analysis tool for estimating the hurst parameter of long-range dependent traffic

S. Bregni, L. Primerano
IEEE Global Telecommunications Conference, 2004. GLOBECOM '04.  
 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
more » ... of LRD traffic time series. This novel method is validated by comparison to 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 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. Index Terms  Fractals, fractional noise, Internet, long-range dependence, self-similarity, traffic control (communication).
doi:10.1109/glocom.2004.1378215 dblp:conf/globecom/BregniP04 fatcat:g5rfsege7fde5lsffx5iohyitm