A Model Driven Engineering Approach to Reduce Large Queueing Networks

Modeling complex systems, including discrete event systems, remains a challenge. The complexity and the size of such systems prevent understanding their models. This article proposes an approach for reducing queuing networks large models into smaller ones. The objective is to reduce the analysis as well as the simulation times in addition to the better understanding of the system under study. The basic idea is to divide the model into a set of smaller, hierarchically organized and more manageable sub-models, which are analyzed in isolation. The key contributions of this work are the substitution of each sub-model by a single M/G/∞ station and the automation of the decomposition process using model transformation techniques. The main conclusion is that the reduction approach provides exact results for the global mean number of clients and mean residence time at the whole network. KEywoRDS Decomposition and Aggregation Approach, Hierarchical Modeling, Model Driven Engineering, Model Transformation, Queueing Networks