Cited By
View all- Agha GPalmskog K(2018)A Survey of Statistical Model CheckingACM Transactions on Modeling and Computer Simulation10.1145/315866828:1(1-39)Online publication date: 31-Jan-2018
Efficient simulation of stochastic well-formed nets through symmetry exploitation
Article No.: 296, Pages 1 - 13
Abstract
Stochastic Well-Formed Nets (SWN) is a High-Level Stochastic Petri Net formalism supporting performability analysis. The symbolic marking and firing notions in SWNs allow to automatically aggregate states achieving significant reductions in highly symmetric models. If the reduced state space is still too large, simulation may be applied exploiting symbolic marking and firing to achieve more efficient handling of the Future Event List. This technique is implemented in the GreatSPN tool.
In this paper symmetry based simulation methods are presented, their strong and weak points are discussed, the issue of performance indices definition and computation is introduced, and an extension exploiting the most recent results on partial symmetries is proposed.
References
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Ajmone Marsan, M., G. Balbo, G. Conte, S. Donatelli, and G. Franceschinis. 1995. Modelling with Generalized Stochastic Petri Nets. New York, NY, USA: J. Wiley.
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Baarir, S., M. Beccuti, D. Cerotti, M. De Pierro, S. Donatelli, and G. Franceschinis. 2009. "The GreatSPN tool: recent enhancements". SIGMETRICS Performance Evaluation Review, Special Issue on Tools for Performance Evaluation 36 (4): 4--9.
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Baarir, S., M. Beccuti, C. Dutheillet, G. Franceschinis, and S. Haddad. 2011. "Lumping partially symmetrical stochastic models". Perform. Eval. 68 (1): 21--44.
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Balbo, G., M. Beccuti, M. De Pierro, and G. Franceschinis. 2011. "Computing first passage time distributions in stochastic well-formed nets". In ICPE, edited by S. Kounev, V. Cortellessa, R. Mirandola, and D. J. Lilja, 7--18: ACM.
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- Efficient simulation of stochastic well-formed nets through symmetry exploitation
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- IIE: Institute of Industrial Engineers
- INFORMS-SIM: Institute for Operations Research and the Management Sciences: Simulation Society
- SCS: Shanghai Computer Society
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
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Winter Simulation Conference
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Published: 09 December 2012
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Overall Acceptance Rate 3,413 of 5,075 submissions, 67%
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View all- Agha GPalmskog K(2018)A Survey of Statistical Model CheckingACM Transactions on Modeling and Computer Simulation10.1145/315866828:1(1-39)Online publication date: 31-Jan-2018
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