A comparison of Markovian Arrival and ARMA/ARTA processes for the modeling of correlated input processes

The adequate modeling of input processes often requires that correlation is taken into account and is a key issue in building realistic simulation models. In analytical modeling Markovian Arrival Processes (MAPs) are commonly used to describe correlated arrivals, whereas for simulation often ARMA/ARTA-based models are in use. Determining the parameters for the latter input models is well-known whereas good fitting methods for MAPs have been developed only in recent years. Since MAPs may as well be used in simulation models, it is natural to compare them with ARMA/ARTA models according to their expressiveness and modeling capabilities for dependent sequences. In this paper we experimentally compare MAPs and ARMA/ARTA-based models.