DocumentCode :
2881684
Title :
Additive and multiplicative mixture trees for network traffic modeling
Author :
Sarvotham, Shriram ; Wang, Xin ; Riedi, Rudolf H. ; Baraniuk, Richard G.
Author_Institution :
Department of Electrical and Computer Engineering, Rice University, 6100 South Main Street, Houston, TX 77005, USA
Volume :
4
fYear :
2002
fDate :
13-17 May 2002
Abstract :
Network traffic exhibits drastically different statistics, ranging from nearly Gaussian marginals and Long range dependence at very large time scales to highly non-Gaussian marginals and multi fractal scaling on small scales. This behavior can be explained by forming two components of the traffic according to the speed of connections, one component absorbing most traffic and being mostly Gaussian, the other constituting virtually all the small scale bursts. Towards a better understanding of this phenomenon, we propose a novel tree-based model which is flexible enough to accommodate Gaussian as well as bursty behavior on different scales in a parsimonious way.
Keywords :
Estimation; Haar wavelet; Levy stable motion; Long range dependence; Network traffic modeling; fractional Brownian motion; multi fractals;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on
Conference_Location :
Orlando, FL, USA
ISSN :
1520-6149
Print_ISBN :
0-7803-7402-9
Type :
conf
DOI :
10.1109/ICASSP.2002.5745544
Filename :
5745544
Link To Document :
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