Aggregation and reduction techniques for hierarchical GCSPNs

The classes of stochastic well-formed colored nets (SWNs) and hierarchical generalized colored stochastic Petri nets (HGCSPNs) have been recently introduced for the specification and analysis of complex systems. SWNs allow the specification of models including symmetries in a very compact way and additionally can be used to generate a reduced Markov chain (MC) from the net specification by exploiting symmetries in the model. HGCSPNs allow a modular specification of a net using several smaller parts. This decomposition of the net specification can also be used to handle the state explosion of the underlying MC by describing the generator matrix using only much smaller subnet matrices. The author combines SWNs and HGCSPNs, allowing the automatic generation of a reduced MC from the hierarchical net specification. Approximative aggregation techniques for hierarchical nets are introduced