Modelling GPRS data traffic

The paper presents results from an analysis of traffic measurements taken at the G_b interface of a GPRS network. Data was captured in one-week long data sets between November 2002 and March 2004. The paper provides new results, based on three of these data sets, and extends our previous work (Ivanovich, M. et al., 16th ITC Specialist Seminar, 2004). The data was analysed to characterise the aggregate workload statistics, including marginal distribution and autocorrelation, and identify any trends over this timeframe. A study of models that adequately characterise the traffic was also undertaken We find that the aggregate work process (bytes "departing" the SGSN) has a marginal distribution closely matching a negative exponential; however, this does not allow us to conclude that the packet arrival or departure processes are Poisson. The "burstiness" of the traffic (i.e. the coefficient of variation) was found to become smaller over time, i.e. the traffic became smoother. This occurred due to a greater level of aggregation, as a direct result of more "low traffic" users connecting to the network. This may be indicative of an increase in WAP and mobile e-mail usage. Four potential models for the aggregate work process were investigated. The latest data shows that the trend towards a more Gaussian-type marginal distribution model continues. Of the four models studied, the Poisson Pareto burst process gave the best fit to the queueing performance compared with the recorded traffic traces. The fit to the most recent data traffic measurements has substantially improved compared with the earlier results.