Evaluation and parameterization of voice traffic models for disaster area scenarios

Abstract

Analyzing and modelling traffic is one important step in the performance evaluation of communication systems. In this paper we focus on evaluation and parameterization of traffic models for disaster area scenarios invented in our previous work. The goal is to provide scalable models for public safety scenarios as realistic and intuitive as possible. During our evaluation we examine synthetic traces for different parameters and levels of detail. As measures we examine traffic intensity, burstiness, and dependencies. The evaluation shows that the models are scalable without loosing specific characteristics. Finally, we provide an intuitive and scalable parameterization for our models that eases up using them.