Performance Analysis of M-NET using GSPN

Performance is a crucial factor in software system. For many software development groups, it remains easier to wait until a system has been built before evaluating its performance. Among the three most used techniques, measurement, simulation and analytic modeling , measurement is believed to be the most accurate method. But it is only feasible after system is implemented. Most organizations rely solely on performance testing and regularly incur the cost of redesign when performance problems arise. Situation would become better if we can evaluate system performance before we physically build up that system. That’s why simulation and analytic modeling become useful. Simulation tends to be expensive due to large computation time and can’t prove properties. Many analytic performance models are proposed by different researchers, including Queueing Network model, Markov chain model, and Markov reward models, etc.