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RenewKube: Reference Net Simulation Scaling with Renew and Kubernetes

  • Jan Henrik RöwekampEmail author
  • Daniel Moldt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11522)

Abstract

When simulating reference nets, the size (places, transitions; memory and CPU consumption) of the simulation is usually not known before actual runtime. This behavior originates from the concept of net instances, which are similar to objects in object-oriented programming. The simulator Renew supports very basic distribution but the manual infrastructural setup for simulations exceeding the capabilities of one machine is left up to the modeler until now. In this work the RenewKube tool, a ready to use Kubernetes and Docker based solution, is presented, that allows to control automated scaling of simulation instances from within the net running in the Renew simulator.

Keywords

Petri net tool High-level petri nets Reference nets Distributed computing Scalability Docker Kubernetes 

References

  1. 1.
    Bendoukha, S.: Multi-agent approach for managing workflows in an inter-cloud environment. Dissertation, University of Hamburg, Department of Informatics, Vogt-Kölln Str. 30, D-22527 Hamburg (2017)Google Scholar
  2. 2.
    Bernstein, D.: Containers and cloud: from LXC to Docker to Kubernetes. IEEE Cloud Comput. 1(3), 81–84 (2014)CrossRefGoogle Scholar
  3. 3.
    Buchs, D., Klikovits, S., Linard, A., Mencattini, R., Racordon, D.: A model checker collection for the model checking contest using docker and machine learning. In: Khomenko, V., Roux, O.H. (eds.) PETRI NETS 2018. LNCS, vol. 10877, pp. 385–395. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-91268-4_21CrossRefGoogle Scholar
  4. 4.
    Chiola, G., Ferscha, A.: Distributed simulation of Petri nets. IEEE Parallel Distrib. Technol. 1(3), 33–50 (1993)CrossRefGoogle Scholar
  5. 5.
    Christensen, S., Damgaard Hansen, N.: Coloured Petri Nets extended with channels for synchronous communication. In: Valette, R. (ed.) ICATPN 1994. LNCS, vol. 815, pp. 159–178. Springer, Heidelberg (1994).  https://doi.org/10.1007/3-540-58152-9_10CrossRefGoogle Scholar
  6. 6.
    Hauschildt, D.: A Petri net implementation. Fachbereichsmitteilung FBI-HH-M-145/87, University of Hamburg, Department of Computer Science, Vogt-Kölln Str. 30, D-22527 Hamburg (1987)Google Scholar
  7. 7.
    El Kaim, W., Kordon, F.: An integrated framework for rapid system prototyping and automatic code distribution. In: Proceedings of RSP, Grenoble, France, pp. 52–61. IEEE (1994)Google Scholar
  8. 8.
    Kordon, F.: Prototypage de systèmes parallèles à partir de réseaux de Petri colorés, application au langage Ada dans un environment centralisé ou réparti. Dissertation, Université P & M Curie, May 1992Google Scholar
  9. 9.
    Kummer, O.: Referenznetze. Logos Verlag, Berlin (2002)Google Scholar
  10. 10.
    Maier, C., Moldt, D.: Object coloured Petri nets - a formal technique for object oriented modelling. In: Agha, G.A., De Cindio, F., Rozenberg, G. (eds.) Concurrent Object-Oriented Programming and Petri Nets. LNCS, vol. 2001, pp. 406–427. Springer, Heidelberg (2001).  https://doi.org/10.1007/3-540-45397-0_16CrossRefzbMATHGoogle Scholar
  11. 11.
    Pitt, E., McNiff, K.: Java.Rmi: The Remote Method Invocation Guide. Addison-Wesley Longman Publishing Co., Inc, Boston (2001)Google Scholar
  12. 12.
    Pommereau, F., de la Houssaye, J.: Faster simulation of (coloured) Petri nets using parallel computing. In: van der Aalst, W., Best, E. (eds.) PETRI NETS 2017. LNCS, vol. 10258, pp. 37–56. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-57861-3_4CrossRefzbMATHGoogle Scholar
  13. 13.
    Röwekamp, J.H.: Investigating the Java Spring framework to simulate reference nets with Renew. Number 2018–02 in Reports/Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg, pp. 41–46. Universität Augsburg, Fachbereich Informatik (2018)Google Scholar
  14. 14.
    Röwekamp, J.H., Moldt, D., Feldmann, M.: Investigation of containerizing distributed Petri net simulations. In: Moldt, D., Kindler, E., Rölke, H. (eds.) Petri Nets and Software Engineering. International Workshop, PNSE 2018, Bratislava, Slovakia, 25–26 June 2018. Proceedings, volume 2138 of CEUR Workshop Proceedings, pp. 133–142. CEUR-WS.org (2018)Google Scholar
  15. 15.
    Röwekamp, J.H., Moldt, D., Simon, M.: A simple prototype of distributed execution of reference nets based on virtual machines. In: Proceedings of the Algorithms and Tools for Petri Nets (AWPN) Workshop 2017, pp. 51–57, October 2017Google Scholar
  16. 16.
    Simon, M., Moldt, D.: Extending Renew’s algorithms for distributed simulation. In: Cabac, L., Kristensen, L.M. Rölke, H. (eds.) Petri Nets and Software Engineering. International Workshop, PNSE 2016, Toruń, Poland, 20–21 June 2016. Proceedings, volume 1591 of CEUR Workshop Proceedings, pp. 173–192. CEUR-WS.org (2016)Google Scholar
  17. 17.
    Taubner, D.: On the implementation of Petri nets. In: Rozenberg, G. (ed.) APN 1987. LNCS, vol. 340, pp. 418–439. Springer, Heidelberg (1988).  https://doi.org/10.1007/3-540-50580-6_40CrossRefGoogle Scholar
  18. 18.
    Valk, R.: Petri nets as token objects - an introduction to elementary object. In: Desel, J., Silva, M. (eds.) ICATPN 1998. LNCS, vol. 1420, pp. 1–24. Springer, Heidelberg (1998).  https://doi.org/10.1007/3-540-69108-1_1CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Mathematics, Informatics and Natural Sciences, Department of InformaticsUniversity of HamburgHamburgGermany

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