Towards reachability trees for high-level Petri nets
Advances in Petri Nets 1984
Bounds for quasi-lumpable Markov chains
Performance '93 Proceedings of the 16th IFIP Working Group 7.3 international symposium on Computer performance modeling measurement and evaluation
Stochastic Well-Formed Colored Nets and Symmetric Modeling Applications
IEEE Transactions on Computers
On Stochastic High-Level Petri Nets
PNPM '87 The Proceedings of the Second International Workshop on Petri Nets and Performance Models
Proceedings of the 10th International Conference on Applications and Theory of Petri Nets: Advances in Petri Nets 1990
Compositional approximate markov chain aggregation for PEPA models
EPEW'12 Proceedings of the 9th European conference on Computer Performance Engineering
Compositional approximate markov chain aggregation for PEPA models
EPEW'12 Proceedings of the 9th European conference on Computer Performance Engineering
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Structural symmetries in stochastic well-formed colored Petri nets (SWN's) lead to behavioral symmetries that can be exploited by using the symbolic reachability graph (SRG) construction algorithm. The SRC allows one to compute an aggregated reachability graph (RG) and a "lumped" continuous time Markov chain (CTMC) that contain all the information needed to study the qualitative properties and the performance of the modeled system, respectively. Some models exhibit qualitative behavioral symmetries that are not completely reflected at the CTMC level. We call them quasi-lumpable SWN models. In these cases, exact performance indices can be obtained by avoiding the aggregation of those markings that are qualitatively, but not quantitatively, equivalent. An alternative approach consists of aggregating all the qualitatively equivalent states and computing approximated performance indices. In this paper, a technique is proposed to compute bounds on the performance of SWN models of this kind, using the results we have presented elsewhere. The technique is based on the Courtois and Semal bounded aggregation method.