The paper presents the analysis of the applicability of alpha-stable processes in traffic modelling. This study is suggested by the goodness of alpha-stable processes in capturing not only the Long Range Dependence (LRD) of actual traffic, but also the heavy tailness of its marginal distribution. The relevance of this property is proved by means of discrete event simulations carried out considering two different data traffic sets, respectively related to a LAN-to-LAN interconnection and entertainment video service. Errors in the estimation of Hurst parameter and in the evaluation of queueing behaviour are highlighted either analytically and empirically by simulations. In particular the queueing simulations have emphasised the improvements in the performance forecasting introduced by the higher flexibility of alpha-stable model with respect to the widely used Fractional Brownian Motion (FBM).
Testing alpha-stable processes in modelling broadband teletraffic
GARROPPO, ROSARIO GIUSEPPE;GIORDANO, STEFANO;PROCISSI, GREGORIO
2000-01-01
Abstract
The paper presents the analysis of the applicability of alpha-stable processes in traffic modelling. This study is suggested by the goodness of alpha-stable processes in capturing not only the Long Range Dependence (LRD) of actual traffic, but also the heavy tailness of its marginal distribution. The relevance of this property is proved by means of discrete event simulations carried out considering two different data traffic sets, respectively related to a LAN-to-LAN interconnection and entertainment video service. Errors in the estimation of Hurst parameter and in the evaluation of queueing behaviour are highlighted either analytically and empirically by simulations. In particular the queueing simulations have emphasised the improvements in the performance forecasting introduced by the higher flexibility of alpha-stable model with respect to the widely used Fractional Brownian Motion (FBM).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.