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Long‐range dependence and performance in telecom networks
Author(s) -
Conti Pier Luigi,
Lijoi Antonio,
Ruggeri Fabrizio
Publication year - 2004
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.542
Subject(s) - range (aeronautics) , hurst exponent , fractional brownian motion , computer science , null hypothesis , bayesian probability , sampling (signal processing) , econometrics , brownian motion , statistics , mathematics , telecommunications , artificial intelligence , engineering , aerospace engineering , detector
Telecommunications systems have recently undergone significant innovations. These call for suitable statistical models that can properly describe the behaviour of the input traffic in a network. Here we use fractional Brownian motion (FBM) to model cumulative traffic network, thus taking into account the possible presence of long‐range dependence in the data. A Bayesian approach is devised in such a way that we are able to: (a) estimate the Hurst parameter H of the FBM; (b) estimate the overflow probability which is a parameter measuring the quality of service of a network: (c) develop a test for comparing the null hypothesis of long‐range dependence in the data versus the alternative of short‐range dependence. In order to achieve these inferential results, we elaborate an MCMC sampling scheme whose output enables us to obtain an approximation of the quantities of interest. An application to three real datasets, corresponding to three different levels of traffic, is finally considered. Copyright © 2004 John Wiley & Sons, Ltd.