Modeling and Characterization of Traffic in Public Safety Networks

Reliable communication and interoperability between public safety agencies play vital role for public safety. We analyze traffic data from a deployed trunked radio communication network operated by public safety wireless network service provider EComm. Traffic data span various periods in 2001, 2002, and 2003. OPNET model is created to evaluate the utilization of network resources and to locate network bottlenecks. Our analysis may be used to address existing and future network congestion problems. We also present statistical analysis of traffic data. We examine statistical distribution and autocorrelation function of call inter-arrival and call holding times during several busy hours. We find that call inter-arrival times are long-range dependent and may be modelled by both Weibull and gamma distributions. Call holding times follow the lognormal distribution and are uncorrelated. These findings indicate that traditional Erlang models for voice traffic may not be suitable for evaluating the performance of trunked radio networks.