Modelling and Performance Evaluation with TimeNET 4.4

  • Armin Zimmermann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10503)


The paper presents the current status of the software tool TimeNET. It supports modeling and performance evaluation of stochastic models, including extended deterministic and stochastic Petri nets, colored stochastic Petri nets, and Markov chains as well as UML extensions. Among its main characteristics are simulation and analysis modules for stationary and transient evaluation of Petri nets including non-exponentially distributed delays, as well as a simulation module for complex colored models. Recent enhancements include algorithms for the efficient rare-event simulation of Petri nets, a new multi-trajectory hybrid simulation/analysis algorithm, and a net class for Markov chains.


Modeling tool TimeNET Stochastic Petri nets Colored Petri nets Performance evaluation 


  1. 1.
    Bernardi, S., Bertoncello, C., Donatelli, S., Franceschinis, G., Gaeta, G., Gribaudo, M., Horvàth, A.: GreatSPN in the new millenium. In: International Multiconference on Measurement, Modelling and Evaluation of Computer-Communication Systems, Research Report 760, 2001, Universität Dortmund, Germany: tools of Aachen 2001, pp. 17–23 (2001)Google Scholar
  2. 2.
    Bodenstein, C., Zimmermann, A.: TimeNET optimization environment - batch simulation and heuristic optimization of SCPNs with TimeNET 4.2. In: 8th International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS 2014), Bratislava, Slovakia, December 2014Google Scholar
  3. 3.
    Courtney, T., Gaonkar, S., Keefe, K., Rozier, E., Sanders, W.: Möbius 2.3: an extensible tool for dependability, security, and performance evaluation of large and complex system models. In: IEEE/IFIP International Conference on Dependable Systems Networks, pp. 353–358 (2009)Google Scholar
  4. 4.
    Hirel, C., Tuffin, B., Trivedi, K.S.: SPNP: stochastic Petri nets. Version 6.0. In: Haverkort, B.R., Bohnenkamp, H.C., Smith, C.U. (eds.) TOOLS 2000. LNCS, vol. 1786, pp. 354–357. Springer, Heidelberg (2000). doi: 10.1007/3-540-46429-8_30 CrossRefGoogle Scholar
  5. 5.
    Jensen, K., Kristensen, K.L., Wells, L.: Coloured Petri nets and CPN tools for modelling and validation of concurrent systems. Int. J. Softw. Tools Technol. Transf. (STTT) 9(3–4), 213–254 (2007)CrossRefGoogle Scholar
  6. 6.
    Reijsbergen, D., de Boer, P.-T., Scheinhardt, W., Haverkort, B.: Automated rare event simulation for stochastic Petri nets. In: Joshi, K., Siegle, M., Stoelinga, M., D’Argenio, P.R. (eds.) QEST 2013. LNCS, vol. 8054, pp. 372–388. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-40196-1_31 CrossRefGoogle Scholar
  7. 7.
    Shorin, D., Zimmermann, A.: Extending the software tool TimeNET by power consumption estimation of UML MARTE models. In: Proceeding of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2014), pp. 83–91, Vienna, Austria, August 2014Google Scholar
  8. 8.
    Zimmermann, A.: Stochastic Discrete Event Systems. Springer, Heidelberg (2007). doi: 10.1007/978-3-540-74173-2 Google Scholar
  9. 9.
    Zimmermann, A.: Modeling and evaluation of stochastic Petri nets with TimeNET 4.1. In: Proceeding 6th International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS), pp. 54–63, Corse, France (2012)Google Scholar
  10. 10.
    Zimmermann, A., Hotz, T., Canabal Lavista, A.: A hybrid multi-trajectory simulation algorithm for the performance evaluation of stochastic Petri nets. In: Bertrand, N., Bortolussi, L. (eds.) QEST 2017. LNCS, vol. 10503, pp. 107–122. Springer, Cham (2017)Google Scholar
  11. 11.
    Zimmermann, A., Jäger, S., Geyer, F.: Towards reliability evaluation of AFDX avionic communication systems with rare-event simulation. In: Proceeding Probabilistic Safety Assessment & Management Conference 2014 (PSAM 12), pp. 1–12, Honolulu, Hawaii, USA, June 2014Google Scholar
  12. 12.
    Zimmermann, A., Maciel, P.: Importance function derivation for RESTART simulations of Petri nets. In: 9th International Workshop on Rare Event Simulation (RESIM 2012), pp. 8–15, Trondheim, Norway, June 2012Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer Science and Automation, Systems and Software Engineering GroupTU IlmenauIlmenauGermany

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