Improving Accuracy of a Network Model Basing on the Case Study of a Distributed System with a Mobile Application and an API

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 718)


Nowadays, many IT products are created as distributed solutions that consist of many parts, such as mobile applications, web-based back-ends, as well as APIs that connect various parts of the system. It is a crucial task to apply a suitable architecture to provide users of mobile applications with satisfactory operation, especially when the Internet connection is necessary to get or send some data. The simulation of network architecture and configuration using a high-level model of the system described with dedicated Domain-Specific Language (DSL), enabled by the Timed Colored Petri Nets (TCPNs) formalism is a beneficial approach that could be applied in real case studies. The already proven research method has been applied to one of the scenarios regarding the system offered by TITUTO Sp. z o.o. [Ltd.] company (Rzeszow, Poland). The first obtained results were not sufficiently precise for detailed analysis of the system. Thus, the case study was used to improve the simulation method in order to more accurately model data transmissions over the network. After modifications were implemented in the simulation tool, significantly better results have been received, as discussed in the paper.


Simulation Petri Nets Performance Distributed system API Mobile application 


  1. 1.
    Riley, G.F., Henderson, T.R.: The ns-3 network simulator. In: Wehrle, K., Güneş, M., Gross, J. (eds.) Modeling and Tools for Network Simulation, pp. 15–34. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  2. 2.
    Gniewek, L.: Sequential control algorithm in the form of fuzzy interpreted Petri net. IEEE Trans. Syst. Man Cybern. Syst. 43(2), 451–459 (2013)CrossRefGoogle Scholar
  3. 3.
    Kounev, S.: Performance modeling and evaluation of distributed component-based systems using queueing Petri nets. IEEE Trans. Softw. Eng. 32(7), 486–502 (2006)CrossRefGoogle Scholar
  4. 4.
    Rak, T.: Response time analysis of distributed web systems using QPNs. Math. Probl. Eng. 2015, 1–10 (2015). doi: 10.1155/2015/490835. Article ID 490835MathSciNetCrossRefGoogle Scholar
  5. 5.
    Rak, T., Samolej, S.: Simulation and performance analysis of distributed internet systems using TCPNs. Informatica Int. J. Comput. Inform. 33(4), 405–415 (2009)Google Scholar
  6. 6.
    Szpyrka, M., Szmuc, T.: Integrated approach to modelling and analysis using RTCP-nets. In: Sacha, K. (ed.) Software Engineering Techniques: Design for Quality. IIFIP, vol. 227, pp. 115–120. Springer, Boston (2006). doi: 10.1007/978-0-387-39388-9_11 CrossRefGoogle Scholar
  7. 7.
    Gniewek, L.: Coverability graph of fuzzy interpreted Petri net. IEEE Trans. Syst. Man Cybern. Syst. 44(9), 1272–1277 (2014)CrossRefGoogle Scholar
  8. 8.
    Murata, T.: Petri nets: properties, analysis and applications. Proc. IEEE 77(4), 541–580 (1989)CrossRefGoogle Scholar
  9. 9.
    Szpyrka, M.: Analysis of RTCP-nets with reachability graphs. Fundamenta Informaticae 74(2), 375–390 (2006)MathSciNetzbMATHGoogle Scholar
  10. 10.
    Wells, L., Christensen, S., Kristensen, L.M., Mortensen, K.H.: Simulation based performance analysis of web servers. In: Proceedings 9th International Workshop on Petri Nets and Performance Models, pp. 59–68 (2001)Google Scholar
  11. 11.
    Girault, C., Valk, R.: Petri Nets for Systems Engineering. A Guide to Modelling Verification, and Applications. Springer, Heidelberg (2003)CrossRefzbMATHGoogle Scholar
  12. 12.
    Rząsa, W.: Simulation-based analysis of a platform as a service infrastructure performance from a user perspective. In: Gaj, P., Kwiecień, A., Stera, P. (eds.) CN 2015. CCIS, vol. 522, pp. 182–192. Springer, Cham (2015). doi: 10.1007/978-3-319-19419-6_17 CrossRefGoogle Scholar
  13. 13.
    Rząsa, W., Rzonca, D.: Event-driven approach to modeling and performance estimation of a distributed control system. In: Gaj, P., Kwiecień, A., Stera, P. (eds.) CN 2016. CCIS, vol. 608, pp. 168–179. Springer, Cham (2016). doi: 10.1007/978-3-319-39207-3_15 Google Scholar
  14. 14.
    Rząsa, W.: Predicting performance in a PaaS environment: a case study for a web application. Comput. Sci. [S.l.] 18(1), 21–39 (2017). CrossRefGoogle Scholar
  15. 15.
    Jensen, K., Kristensen, L.: Coloured Petri Nets. Modeling and Validation of Concurrent Systems. Springer, Heidelberg (2009)CrossRefzbMATHGoogle Scholar
  16. 16.
    Rząsa, W.: Timed colored Petri net based estimation of efficiency of the grid applications. Ph.D. thesis, AGH University of Science and Technology, Kraków, Poland (2011)Google Scholar
  17. 17.
    Jamro, M., Rzonca, D., Rząsa, W.: Testing communication tasks in distributed control systems with SysML and Timed Colored Petri Nets model. Comput. Ind. 71, 77–87 (2015). CrossRefGoogle Scholar
  18. 18.
    Rząsa, W.: Combining timed colored Petri nets and real TCP implementation to reliably simulate distributed applications. In: Kwiecień, A., Gaj, P., Stera, P. (eds.) CN 2009. CCIS, vol. 39, pp. 79–86. Springer, Heidelberg (2009). doi: 10.1007/978-3-642-02671-3_9 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer and Control EngineeringRzeszow University of TechnologyRzeszowPoland
  2. 2.TITUTO Sp. z o.o. [Ltd.]RzeszowPoland

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