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IEEE COMMUNICATIONS LETTERS, VOL. 8, NO. 9, SEPTEMBER 2004 591 A Sampling Technique for Variance Estimation of
 

Summary: IEEE COMMUNICATIONS LETTERS, VOL. 8, NO. 9, SEPTEMBER 2004 591
A Sampling Technique for Variance Estimation of
Long-Range Dependent Traffic
Javier Aracil, Member, IEEE
Abstract--Due to the long-range dependence of Internet traffic,
the sampling distribution of the variance is very hard to obtain and,
as a result, confidence intervals cannot be provided. Nevertheless,
we show that the -decimated variance sampling distribution can
be approximated by a 2 distribution. This sampling technique
can be used to provide a confidence interval for the variance, with
significant benefits for many applications in Internet dimensioning,
traffic forecasting and control.
Index Terms--Self-similarity, variance estimation.
I. INTRODUCTION AND PROBLEM STATEMENT
LONG-RANGE dependent traffic models constitute the
foundation for traffic forecasting algorithms [1] and also
for the analysis of buffer dynamics under long range dependent
traffic (Fractional Gaussian Noise -FGN-) [2]. However, all of
the above algorithms for network dimensioning and control de-
mand a priori knowledge of the traffic correlation and marginal

  

Source: Rico, Javier Aracil - Departamento de Ingeniería Informática, Universidad Autonoma de Madrid

 

Collections: Computer Technologies and Information Sciences