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**Harvard**

Guerin, C., Nyberg, H., Perrin, O., Resnick, S., Rootzén, H. och Starica, C. (2003) *Empirical testing of the infinite source poisson data traffice model*.

** BibTeX **

@article{

Guerin2003,

author={Guerin, Charles-Antoine and Nyberg, Henrik and Perrin, Olivier and Resnick, Sidney and Rootzén, Holger and Starica, Catalin},

title={Empirical testing of the infinite source poisson data traffice model},

journal={Stochastic models},

volume={19},

pages={156-196},

abstract={The infinite source Poisson model is a fluid queue
approximation of network data transmission that
assumes that sources begin constant rate transmissions of data at Poisson
time points for random lengths of time. This model has been a popular
one as analysts attempt to provide explanations for observed features
in telecommunications data such as self-similarity, long range
dependence and heavy tails. We survey some features of this model
in cases where transmission length distributions have (a) tails so heavy
that means are infinite, (b) heavy tails with finite mean and
infinite variance and (c) finite variance. We survey the
self-similarity properties of various descriptor processes in this
model and then present analyses of four data sets which show that
certain features of the model are consistent with the data while
others are contradicted. The data sets are 1) the Boston University
1995 study of web sessions, 2) the UC Berkeley home IP HTTP
data collected in November 1996, 3) traces collected
in end of 1997 at a Customer Service Switch in Munich,
and 4) detailed data from a corporate Ericsson WWW server
from October 1998.},

year={2003},

keywords={data transmission modelling, internet traffic, heavy tails, regular variation, Pareto tails, self-similarity, scaling},

}

** RefWorks **

RT Journal Article

SR Electronic

ID 92891

A1 Guerin, Charles-Antoine

A1 Nyberg, Henrik

A1 Perrin, Olivier

A1 Resnick, Sidney

A1 Rootzén, Holger

A1 Starica, Catalin

T1 Empirical testing of the infinite source poisson data traffice model

YR 2003

JF Stochastic models

VO 19

SP 156

OP 196

AB The infinite source Poisson model is a fluid queue
approximation of network data transmission that
assumes that sources begin constant rate transmissions of data at Poisson
time points for random lengths of time. This model has been a popular
one as analysts attempt to provide explanations for observed features
in telecommunications data such as self-similarity, long range
dependence and heavy tails. We survey some features of this model
in cases where transmission length distributions have (a) tails so heavy
that means are infinite, (b) heavy tails with finite mean and
infinite variance and (c) finite variance. We survey the
self-similarity properties of various descriptor processes in this
model and then present analyses of four data sets which show that
certain features of the model are consistent with the data while
others are contradicted. The data sets are 1) the Boston University
1995 study of web sessions, 2) the UC Berkeley home IP HTTP
data collected in November 1996, 3) traces collected
in end of 1997 at a Customer Service Switch in Munich,
and 4) detailed data from a corporate Ericsson WWW server
from October 1998.

LA eng

LK http://www.math.chalmers.se/Math/Research/Preprints/2000/4.pdf

OL 30