Comparison of LRD and SRD traffic models for the performance evaluation of finite buffer systems

Abstract

The paper presents a comparison of several traffic models in order to investigate their adequacy to approximate the behaviour of actual traffic in a single server queue under realistic working conditions. Hence, considering queueing systems with finite buffers, models parsimoniously fitting the long range dependence (LRD) property are compared to intrinsically short range dependent models and to flexible ones, capturing both LRD and short range dependence (SRD). The paper highlights an optimistic queueing behaviour evaluated by means of models capturing only LRD property, when realistic buffer sizes are considered and a strong SRD correlation component is present. The simulation results point out that the circulant modulated Poisson processes (CMPP) and fractional autoregressive integrated moving average (p,d,0) (f-ARIMA(p,d,0)) are suitable models to estimate the performance of the queueing system under heavy load conditions. On the contrary, when the system works under low-medium load conditions, the relevance of the marginal distribution to queueing performance and the inaccuracy of the CMPP model on fitting this statistic in the case of actual traffic data lead to a reduction of the accuracy of this model on system performance evaluation.