Stochastic Modeling and Analysis using QPME: Queueing Petri Net Modeling Environment v2.0
S. Spinner, S. Kounev, and P. Meier. Proceedings of the 33rd International Conference on Application and Theory of Petri Nets and Concurrency (Petri Nets 2012), volume 7347 of Lecture Notes in Computer Science (LNCS), page 388--397. Berlin, Heidelberg, Springer-Verlag, (June 2012)
Abstract
Queueing Petri nets are a powerful formalism that can be exploited for modeling distributed systems and analyzing their performance and scalability. By combining the modeling power and expressiveness of queueing networks and stochastic Petri nets, queueing Petri nets provide a number of advantages. In this paper, we present our tool QPME (Queueing Petri net Modeling Environment) for modeling and analysis using queueing Petri nets. QPME provides an Eclipse-based editor for building queueing Petri net models and a powerful simulation engine for analyzing these models. The development of the tool started in 2003 and since then the tool has been distributed to more than 120 organizations worldwide.
%0 Conference Paper
%1 SpKoMe2012-PETRINETS-QPME
%A Spinner, Simon
%A Kounev, Samuel
%A Meier, Philipp
%B Proceedings of the 33rd International Conference on Application and Theory of Petri Nets and Concurrency (Petri Nets 2012)
%C Berlin, Heidelberg
%D 2012
%E Haddad, Serge
%E Pomello, Lucia
%I Springer-Verlag
%K Analytical_and_simulation-based_analysis Formal_architecture_modeling Performance Prediction QPME QPME_Bibliography QPN Simulation Tool descartes t_short
%P 388--397
%T Stochastic Modeling and Analysis using QPME: Queueing Petri Net Modeling Environment v2.0
%U http://dx.doi.org/10.1007/978-3-642-31131-4_21
%V 7347
%X Queueing Petri nets are a powerful formalism that can be exploited for modeling distributed systems and analyzing their performance and scalability. By combining the modeling power and expressiveness of queueing networks and stochastic Petri nets, queueing Petri nets provide a number of advantages. In this paper, we present our tool QPME (Queueing Petri net Modeling Environment) for modeling and analysis using queueing Petri nets. QPME provides an Eclipse-based editor for building queueing Petri net models and a powerful simulation engine for analyzing these models. The development of the tool started in 2003 and since then the tool has been distributed to more than 120 organizations worldwide.
@inproceedings{SpKoMe2012-PETRINETS-QPME,
abstract = {Queueing Petri nets are a powerful formalism that can be exploited for modeling distributed systems and analyzing their performance and scalability. By combining the modeling power and expressiveness of queueing networks and stochastic Petri nets, queueing Petri nets provide a number of advantages. In this paper, we present our tool QPME (Queueing Petri net Modeling Environment) for modeling and analysis using queueing Petri nets. QPME provides an Eclipse-based editor for building queueing Petri net models and a powerful simulation engine for analyzing these models. The development of the tool started in 2003 and since then the tool has been distributed to more than 120 organizations worldwide.},
added-at = {2020-04-05T23:07:09.000+0200},
address = {Berlin, Heidelberg},
author = {Spinner, Simon and Kounev, Samuel and Meier, Philipp},
biburl = {https://www.bibsonomy.org/bibtex/2557bc6a22456d7f60c25ac1adacb2702/se-group},
booktitle = {Proceedings of the 33rd International Conference on Application and Theory of Petri Nets and Concurrency (Petri Nets 2012)},
editor = {Haddad, Serge and Pomello, Lucia},
interhash = {cf1e92a9a739c70750b0d751a6f56652},
intrahash = {557bc6a22456d7f60c25ac1adacb2702},
keywords = {Analytical_and_simulation-based_analysis Formal_architecture_modeling Performance Prediction QPME QPME_Bibliography QPN Simulation Tool descartes t_short},
month = {June},
pages = {388--397},
publisher = {Springer-Verlag},
series = {Lecture Notes in Computer Science (LNCS)},
timestamp = {2021-08-18T15:08:10.000+0200},
title = {{Stochastic Modeling and Analysis using QPME: Queueing Petri Net Modeling Environment v2.0}},
url = {http://dx.doi.org/10.1007/978-3-642-31131-4_21},
volume = 7347,
year = 2012
}