Using the probabilistic evaluation tool for the analytical solution of large Markov models

Introduction Stochastic Petri net based Markov modeling is a potentially very powerful and generic approach for evaluating the performance and depend ability of many di erent systems such as computer systems communication networks manufacturing sys tems etc As a consequence of their general appli cability SPN based Markov models form the basic solution approach for several software packages that have been developed for the analytic solution of per formance and dependability models e g In these tools stochastic Petri nets are used to conve niently specify complicated models and an automatic mapping is carried out to an underlying Markov re ward model Subsequently this Markov reward model is solved by specialized solution algorithms appropri ately selected for the measure of interest