Title :
A novel approach to the estimation of the Hurst parameter in self-similar traffic
Author :
Kettani, H. ; Gubner, John A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
Abstract :
We present a new method to estimate the Hurst parameter of the increment process in network traffic-a process that is assumed to be self-similar. The confidence intervals and biasedness are obtained for the estimates using the new method. This new method is then applied to pseudo-random data and to real traffic data. We compare the performance of the new method to that of the widely-used wavelet method, and demonstrate that the former is much faster and produces much smaller confidence intervals of the Hurst parameter estimate. We believe that the new method can be used as an on-line estimation tool for H and thus be exploited in the new TCP algorithms that exploit the known self-similar and long-range dependent nature of network traffic.
Keywords :
local area networks; parameter estimation; telecommunication traffic; Hurst parameter; TCP algorithms; biasedness; confidence intervals; increment process; network traffic; on-line estimation tool; pseudo-random data; real traffic data; Analysis of variance; Autocorrelation; Computer networks; Gaussian noise; Gaussian processes; Intelligent networks; Local area networks; Parameter estimation; Resonance light scattering; Telecommunication traffic;
Conference_Titel :
Local Computer Networks, 2002. Proceedings. LCN 2002. 27th Annual IEEE Conference on
Print_ISBN :
0-7695-1591-6
DOI :
10.1109/LCN.2002.1181780