Testing alpha-stable processes in capturing the queuing behavior of broadband teletraffic

The paper analyzes the applicability of α-stable processes in traffic modelling. This study is suggested by the ability of α-stable processes in capturing not only the self-similarity of actual traffic, but also the heavy tails of its marginal distribution. The relevance of this property is proven by means of discrete event simulations carried out considering two different traffic data sets, related to a LAN-to-LAN interconnection and to an entertainment video service, respectively. The performance of the α-stable model is evaluated in terms of the ability in capturing the queuing behavior of actual traffic, in cases of realistic systems (i.e. with finite buffer) and ideal models (i.e. with infinite buffer). In both cases, the analysis is mainly carried out by means of discrete event simulations; in addition to this, in the infinite buffer scenario, a theoretical lower bound is also given and its tightness is discussed. The queuing simulations emphasize the improvements in the performance prediction introduced by the higher flexibility of the α-stable model with respect to the widely used fractional Brownian motion.