Analysis of f-ARIMA processes in the modelling of broadband traffic

The paper deals with the applicability of fractional AutoRegressive Integrated Moving Average (f-ARIMA) processes to traffic modelling. This study is suggested by the ability of f-ARIMA processes in separately capturing both the Long Range Dependence (LRD) and Short Range Dependence (SRD) features of actual traffic. Indeed, the f-ARIMA models permit to produce synthetic traces with a well-controlled LRD/SRD component ratio. The practical relevance of this feature is tested analysing, by means of discrete event simulations, the queueing performance in several working conditions for two different actual-traffic data sets, respectively related to a LAN-to-LAN interconnection and a videoconference service. In particular, the latter data set, characterised by a strong "low frequency" SRD component, emphasises the improvement on queueing performance evaluation introduced by a low-order f-ARIMA(p,d,0) model with respect to a pure LRD one. On the contrary, the inadequacy of the f-ARIMA model is highlighted when considering the LAN traffic characterised by a quite complex SRD component