Optimistic distributed execution of business process models

For the modeling of large and complex systems of business processes, a flow oriented, graphical modeling framework based on Petri nets has emerged taking the potentials of a qualitative and a quantitative analysis based on one and the same model. For the quantitative analysis of business process models (BPMs) representing realistically sized enterprise organizations, traditional evaluation techniques (like discrete event simulation) tend to become practically intractable. To be able to cope with very complex models, therefore, the author has developed a distributed execution mechanism based on the time warp distributed simulation protocol. A corresponding software tool was implemented based on the MPI communication library, thus portable to almost any distributed or parallel computing platform. In case studies performed on a 134 node Meiko CS-2 multiprocessor investigating real and hypothetical business or organizations, this work demonstrates that parallel/distributed simulation techniques make the execution of very large models feasible: in situations where the simulation model has reached a complexity prohibitive to an execution on a single processor computer (e.g. due to memory constraints), the decomposition into smaller submodels to be executed on a parallel processor or a network of workstations remains the only means to get the simulation done. As such, a whole new class of (complex) BPM simulations becomes practically tractable, and traditional simulations can be accelerated dramatically. As an example, a BPM of a document flow system comprising 64 offices with an average of 1000 documents per office gains a 250 to 300 fold acceleration of the overall execution speed using 32 processors of the CS-2