In this paper, we present an approach for model transformation from Queueing Network Models (QNMs) into Queueing Petri Nets (QPNs). The performance of QPNs can be analyzed using a powerful simulation engine, SimQPN, designed to exploit the knowledge and behavior of QPNs to improve the efficiency of simulation. When QNMs are transformed into QPNs, their performance can be analyzed efficiently using SimQPN. To validate our approach, we apply it to analyze the performance of several queueing network models including a model of a database system. The evaluation results show that the performance analysis of the transformed QNMs has high accuracy and low overhead. In this context, model transformation enables the performance analysis of queueing networks using different ways that can be more efficient.
References
[1]
da Silva, A.R. (2015) Model-Driven Engineering: A Survey Supported by the Unified Conceptual Mode. Computer Languages, Systems & Structures, 43, 139-155.
https://doi.org/10.1016/j.cl.2015.06.001
Harchol-Balter, M. (2013) Performance Modeling and Design of Computer Systems: Queueing Theory in Action. Cambridge University Press, Cambridge.
[5]
Kounev, S. (2006) Performance Modeling and Evaluation of Distributed Component-Based Systems Using Queueing Petri Nets. IEEE Transactions on Software Engineering, 32, 486-502. https://doi.org/10.1109/TSE.2006.69
[6]
Kounev, S., Spinner, S. and Meier, P. (2012) Introduction to Queueing Petri Nets: Modeling Formalism, Tool Support and Case Studies. Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering, Boston, 22-25 April 2012, 9-18. https://doi.org/10.1145/2188286.2188290
[7]
QPME. http://qpme.sourceforge.net/
[8]
Kounev, S. and Buchmann, A. (2006) SimQPN: A Tool and Methodology for Analyzing Queueing Petri Net Models by Means of Simulation. Performance Evaluation, 63, 364-394. https://doi.org/10.1016/j.peva.2005.03.004
[9]
Brosig, F., Meier, P., Becker, S., Koziolek, A., Koziolek, H. and Kounev, S. (2015) Quantitative Evaluation of Model-Driven Performance Analysis and Simulation of Component-Based Architectures. IEEE Transactions on Software Engineering, 41, 157-175. https://doi.org/10.1109/TSE.2014.2362755
[10]
Al-Azzoni, I. (2017) ATL Transformation of Queueing Networks to Queueing Petri Nets. Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development (MODELSWARD), 261-268.
https://doi.org/10.5220/0006110002610268
[11]
Steinberg, D., Budinsky, F., Paternostro, M. and Merks, E. (2008) EMF: Eclipse Modeling Framework. 2nd Edition, Addison-Wesley Professional, Ch. 5.
Allilaire, F., Bézivin, J., Jouault, F. and Kurtev, I. (2006) ATL: Eclipse Support for Model Transformation. Proceedings of the Eclipse Technology Exchange Workshop of the European Conference on Object-Oriented Programming, Nantes, 4 July 2006.
[17]
Troya, J. and Vallecillo, A. (2014) Specification and Simulation of Queueing Network Models Using Domain-Specific Languages. Computer Standards & Interfaces, 36, 863-879. https://doi.org/10.1016/j.csi.2014.01.002
[18]
Osman, R., Awan, I. and Woodward, M.E. (2009) Application of Queueing Network Models in the Performance Evaluation of Database Designs. Electronic Notes in Theoretical Computer Science, 232, 101-124.
https://doi.org/10.1016/j.entcs.2009.02.053
[19]
Overview of the TPC-C Benchmark: The Order-Entry Benchmark.
http://www.tpc.org/tpcc/detail.asp
[20]
Java Modeling Tools. http://jmt.sourceforge.net/
[21]
Meier, P., Kounev, S. and Koziolek, H. (2011) Automated Transformation of Component-Based Software Architecture Models to Queueing Petri Nets. Proceedings of the Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems, Singapore, 25-27 July 2011, 339-348.
[22]
Becker, S., Koziolek, H. and Reussner, R. (2009) The Palladio Component Model for Model-Driven Performance Prediction. Journal of Systems and Software, 82, 3-22.
https://doi.org/10.1016/j.jss.2008.03.066
[23]
Koziolek, H. and Reussner, R. (2008) A Model Transformation from the Palladio Component Model to Layered Queueing Networks. Proceedings of the SPEC International Performance Evaluation Workshop, Darmstadt, 27-28 June 2008, 58-78.
https://doi.org/10.1007/978-3-540-69814-2_6
[24]
Smith, C.U., Lladó, C.M. and Puigjaner, R. (2010) Performance Model Interchange Format (PMIF 2): A Comprehensive Approach to Queueing Network Model Interoperability. Performance Evaluation, 67, 548-568.
https://doi.org/10.1016/j.peva.2010.01.006
[25]
The e-Motions Tool.
http://atenea.lcc.uma.es/index.php/Main_Page/Resources/E-motions
[26]
Clavel, M., Durán, F., Eker, S., Lincoln, P., Mart-Oliet, N., Meseguer, J. and Talcott, C. (2007) All About Maude—A High-Performance Logical Framework: How to Specify, Program and Verify Systems in Rewriting Logic. Springer-Verlag, Berlin.
[27]
Rygielski, P. and Kounev, S. (2014) Data Center Network Throughput Analysis Using Queueing Petri Nets. Proceedings of the Conference on Distributed Computing Systems Workshops, Madrid, 30 June-3 July 2014, 100-105.
https://doi.org/10.1109/ICDCSW.2014.11
[28]
Rygielski, P., Zschaler, S. and Kounev, S. (2013) A Meta-Model for Performance Modeling of Dynamic Virtualized Network Infrastructures. Proceedings of the Conference on Performance Engineering, Prague, 21-24 April 2013, 327-330.
https://doi.org/10.1145/2479871.2479918
[29]
Lladó, C.M., Bonet, P. and Smith, C.U. (2013) Towards a Multi-Formalism Multi-Solution Framework for Model-Driven Performance Engineering. In: Gribaudo, M. and Iacono, M., Eds., Theory and Application of Multi-Formalism Modeling, IGI Global, Ch. 3, 34-55.
[30]
Bause, F. and Kritzinger, P.S. (2002) Stochastic Petri Nets: An Introduction to the Theory. 2nd Edition, Springer, Berlin. https://doi.org/10.1007/978-3-322-86501-4
[31]
Smith, C. and Williams, L. (1999) A Performance Model Interchange Format. Journal of Systems and Software, 49, 63-80.
https://doi.org/10.1016/S0164-1212(99)00067-9
[32]
Dingle, N.J., Knottenbelt, W.J. and Suto, T. (2009) PIPE2: A Tool for the Performance Evaluation of Generalised Stochastic Petri Nets. SIGMETRICS Performance Evaluation Review, 36, 34-39. https://doi.org/10.1145/1530873.1530881
[33]
OMG: The Object Constraint Language Specification v. 2.4.
http://www.omg.org/spec/OCL/2.4/
[34]
Warmer, J. and Kleppe, A. (2003) The Object Constraint Language: Getting Your Models Ready for MDA. 2nd Edition, Addison-Wesley, Boston.
[35]
Buettner, F., Egea, M., Cabot, J. and Gogolla, M. (2012) Verification of ATL Transformations Using Transformation Models and Model Finders. Proceedings of the Conference on Formal Engineering Methods, Kyoto, 198-213.
https://doi.org/10.1007/978-3-642-34281-3_16
[36]
González, C.A. and Cabot, J. (2012) ATL Test: A White-Box Test Generation Approach for ATL Transformations. Proceedings of the Conference on Model Driven Engineering Languages and Systems, Innsbruck, 1-5 October 2012, 449-464.
https://doi.org/10.1007/978-3-642-33666-9_29
[37]
Fleurey, F., Baudry, B., Muller, P.-A. and Traon, Y.L. (2009) Qualifying Input Test Data for Model Transformations. Software and Systems Modeling, 8, 185-203.
https://doi.org/10.1007/s10270-007-0074-8