Hierarchies are integrated in the class of Generalized Colored Stochastic Petri Nets (GCSPNs). The use of hierarchies supports the specification of nets describing large real-world systems. Moreover, the new model class can be analysed extremely efficient according to qualitative and quantitative results. Techniques for quantitative analysis, qualitative analysis and subnet aggregation are introduced. The usability of the approach is shown by means of a non-trivial example from literature.
CITATION STYLE
Buchholz, P. (1993). Hierarchies in colored GSPNs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 691 LNCS, pp. 106–125). Springer Verlag. https://doi.org/10.1007/3-540-56863-8_43
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