SimGine: A simulation engine for stochastic discrete-event systems based on SDES description

Discrete-event systems have gained a lot of interest due to their wide range of applications, and discrete-event simulation is a useful method for the performance evaluation of such systems. In this domain, model-based evaluation methods play an important role and there are many formalisms and realistic experiments using these methods. In this paper, we introduce SimGine, a multi-formalism simulation engine for stochastic discrete-event systems based on SDES, which is a unified abstract description for stochastic discrete-event systems. The engine is also capable of rare-event simulation of models using the importance sampling technique, which makes it the first multi-formalism simulation tool with rare-event simulation capability. The XML-based input language of SimGine allows for definition of the required methods. The body of each method is expressed by codes in a high-level programming language and this provides a powerful and flexible approach for defining events with complex behavior. For the simulation of an existing model, a tool for translating models into the SimGine input language should be prepared. SimGine can be used as a stand-alone simulation tool or as a simulation engine in other tools.