Incoming traffic modeling of heterogeneous Public Safety Network

Accurate traffic models are necessary for a service provider of emergency communications to properly maintain the capacity planning of the network. To meet the necessity, the good traffic model must be developed that can capture characteristics including occurrences of few and large random incidents and accidents. These occurrences may be described as the unusual spikes and long tails in a probability model term of an actual network load. Therefore, the proposed mixed model for a peak period traffic brings significant results to capture the characteristics than other statistical models. We employ the Lognormal mixture model with high accuracy based on simulations with the real data set of emergency incoming traffic types. The results show that main traffic of a peak period is fitted reasonably by a mixture of Lognormal distributions with two or more components compared to well known statistical candidate distributions such as General Pareto, Weibull, and simple Lognormal.