The qnetworks Toolbox: A Software Package for Queueing Networks Analysis

  • Moreno Marzolla
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6148)


Queueing Networks QNs are a useful performance modelling notation. They can be used to describe many kinds of systems, and efficient solution techniques have been developed for some classes of QN models. Despite the fact that QNs have been extensively studied, very few software packages for QN analysis are available today. In this paper we describe the qnetworks toolbox, a free software package for QN analysis for GNU Octave. qnetworks provides implementations of solution algorithms for single station queueing systems as well as for product and some non product form QN models. Exact, approximate and bound analysis can be performed. Additional utility functions and algorithms for Markov Chains analysis are also included. The qnetworks package is available as free and open source software, allowing users to study, modify and extend the code. This makes qnetworks a viable teaching tool.


Service Time Queueing Network Processor Share Closed Network Mixed Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Serazzi, G.: Performance Evaluation Modelling with JMT: learning by examples. Technical Report 2008.09, Politecnico di Milano (2008)Google Scholar
  2. 2.
    Bolch, G., Greiner, S., de Meer, H., Trivedi, K.: Queueing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications. Wiley, Chichester (1998)zbMATHGoogle Scholar
  3. 3.
    Eaton, J.W.: GNU Octave Manual. Network Theory Limited (2002)Google Scholar
  4. 4.
    The MathWorks Inc. Natick, Massachussets: MATLAB (2003)Google Scholar
  5. 5.
    Bertoli, M., Casale, G., Serazzi, G.: JMT: performance engineering tools for system modeling. SIGMETRICS Perform. Eval. Rev. 36(4), 10–15 (2009)CrossRefGoogle Scholar
  6. 6.
    Sauer, C.H., Reiser, M., MacNair, E.A.: RESQ: a package for solution of generalized queueing networks. In: AFIPS National Computer Conference. AFIPS Conference Proceedings, vol. 46, pp. 977–986. AFIPS Press (1977)Google Scholar
  7. 7.
    Chang, K.C., Gordon, R.F., Loewner, P.G., MacNair, E.A.: The Research Queuing Package Modeling Environment (RESQME). In: Winter Simulation Conference, pp. 294–302 (1993)Google Scholar
  8. 8.
    Véran, M., Potier, D.: QNAP2: A portable environment for queueing systems modelling. Technical Report 314, Institut National de Recherche en Informatique et en Automatique (June 1984)Google Scholar
  9. 9.
    Sahner, R., Trivedi, K.S., Puliafito, A.: Performance and Reliability Analysis of Computer Systems: An Example-Based Approach Using the SHARPE Software Package. Kluwer Academic Publishers, Dordrecht (1996)zbMATHGoogle Scholar
  10. 10.
    Jackson, J.R.: Jobshop-like queueing systems. Man. Science 10(1), 131–142 (1963)Google Scholar
  11. 11.
    Gordon, W.J., Newell, G.F.: Closed Queuing Systems with Exponential Servers. Operations Research 15(2), 254–265 (1967)zbMATHCrossRefGoogle Scholar
  12. 12.
    Baskett, F., Chandy, K.M., Muntz, R.R., Palacios, F.G.: Open, closed, and mixed networks of queues with different classes of customers. J. ACM 22(2), 248–260 (1975)zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Kleinrock, L.: Queueing Systems: Volume I–Theory. Wiley Interscience, New York (1975)Google Scholar
  14. 14.
    Lazowska, E.D., Zahorjan, J., Graham, G.S., Sevcik, K.C.: Quantitative System Performance: Computer System Analysis Using Queueing Network Models. Prentice Hall, Englewood Cliffs (1984)Google Scholar
  15. 15.
    Reiser, M., Lavenberg, S.S.: Mean-value analysis of closed multichain queuing networks. Journal of the ACM 27(2), 313–322 (1980)zbMATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Buzen, J.P.: Computational algorithms for closed queueing networks with exponential servers. Comm. ACM 16(9), 527–531 (1973)zbMATHCrossRefMathSciNetGoogle Scholar
  17. 17.
    Chandy, K.M., Sauer, C.H.: Computational algorithms for product form queueing networks. Comm. ACM 23(10), 573–583 (1980)zbMATHCrossRefMathSciNetGoogle Scholar
  18. 18.
    Schweitzer, P.: Approximate analysis of multiclass closed networks of queues. In: Proc. Int. Conf. on Stochastic Control and Optimization, June 1979, pp. 25–29 (1979)Google Scholar
  19. 19.
    Balsamo, S., De Nitto Personé, V., Onvural, R.: Analysis of Queueing Networks with Blocking. Kluwer Academic Publishers, Dordrecht (2001)zbMATHGoogle Scholar
  20. 20.
    Akyildiz, I.F.: Mean value analysis for blocking queueing networks. IEEE Transactions on Software Engineering 1(2), 418–428 (1988)CrossRefGoogle Scholar
  21. 21.
    Denning, P.J., Buzen, J.P.: The operational analysis of queueing network models. ACM Computing Surveys 10(3), 225–261 (1978)zbMATHCrossRefGoogle Scholar
  22. 22.
    Zahorjan, J., Sevcick, K.C., Eager, D.L., Galler, B.I.: Balanced job bound analysis of queueing networks. Comm. ACM 25(2), 134–141 (1982)CrossRefMathSciNetGoogle Scholar
  23. 23.
    Casale, G., Muntz, R.R., Serazzi, G.: Geometric bounds: a non-iterative analysis technique for closed queueing networks. IEEE Transactions on Computers 57(6), 780–794 (2008)CrossRefMathSciNetGoogle Scholar
  24. 24.
    Schwetman, H.: Testing network-of-queues software. Technical Report CSD-TR-330, Purdue University (January 1980)Google Scholar

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© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Moreno Marzolla
    • 1
  1. 1.Dipartimento di Scienze dell’InformazioneUniversità di BolognaBolognaItaly

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