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Abstract

In the process of software performance modeling and analysis, although these two activities do not act in a strict pipeline, once generated/built (at whatever level of abstraction in the software lifecycle) a performance model has to be solved to get the values of performance indices of interest. It is helpful to recall here that the main targets of a performance model solution are the values of performance indices. The existing literature is rich of methodologies, techniques and tools for solving a wide variety of performance models. This is a very active research topic and, despite the complexity of problems encountered in this direction, in the last few decades very promising results have been obtained. Moreover, new tools have been developed to support this key step of software performance process. Therefore, the contents of this chapter are not limited to the basics of model solution techniques, and a short summary of the major tools for model solution is also provided.

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Notes

  1. 1.

    See Chap. 4 for relationships between performance modeling/analysis and software lifecycle.

  2. 2.

    Several seminal books have been published performance operational laws (see, for example, [79]). The description that follows has been taken from Jane Hillston’s class notes [3].

  3. 3.

    Bottleneck analysis can be a quite complex process, based on a well-assessed theory to study system bottlenecks. We do not report the whole theory in this chapter, but we only provide a sketch of it. Readers interested to a simple and complete presentation of this theory can refer to [79].

  4. 4.

    In a team race each team is as slow as its slowest runner.

  5. 5.

    Note, however, that modern definitions of resources widen their scope to complex combinations of hardware and software that provide certain services. In these cases the actions that decrease S i may also concern the software component of a resource.

  6. 6.

    Readers interested to EGs can refer to Smith’s book [110].

  7. 7.

    A database on (stochastic) Petri net tools can be found at [5].

  8. 8.

    Many excellent books have been published on (discrete event) simulation, whereas our intent here is only to mention it as a software performance modeling and analysis approach.

  9. 9.

    In this section we implicitly refer to Discrete Event Simulation [28], as the most widely used in the software performance domain.

  10. 10.

    We here only introduce the main mechanisms of simulation, and we assume that basic concepts (like virtual time) are known to the reader.

  11. 11.

    Note that most of this section contents comes from the web pages of the tools and only partially has been re-arranged for use in this book. The URL of each tool has been reported in the respective section for retrieving further information.

References

  1. Jane Hillston’s notes of lectures: Private communication

    Google Scholar 

  2. Petri Nets tools database. http://www.daimi.aau.dk/PetriNets

  3. Baccelli, F., Balbo, G., Boucherie, R.J., Campos, J.J., Chiola, G.: Annotated bibliography on stochastic petri nets. In: Tract, C. (ed.) Performance Evaluation of Parallel and Distributed Systems-Solution Methods, Amsterdam, 1994, pp. 1–24 (1994)

    Google Scholar 

  4. Baier, C., Haverkort, B.R., Hermanns, H., Katoen, J.-P., Siegle, M. (eds.): Validation of Stochastic Systems – A Guide to Current Research. Lecture Notes in Computer Science, vol. 2925. Springer, Berlin (2004)

    MATH  Google Scholar 

  5. Balbo, G., Bruell, S., Ghanta, S.: Combining queueing networks and generalized stochastic petri nets for the solution of complex models of system behavior. IEEE Transactions on Computers 37, 1251–1268 (1988)

    Article  MATH  Google Scholar 

  6. Balsamo, S., Bernardo, M., Simeoni, M.: Combining stochastic process algebras and queueing networks for software architecture analysis. In: Proceedings of the Third International Workshop on Software and Performance, WOSP02, pp. 190–202 (2002)

    Chapter  Google Scholar 

  7. Banks, J., Carson, J.S., Nelson, B.L., Nicol, D.M.: Discrete-Event System Simulation. Pearson Prentice Hall, Upper Saddle River (2004)

    Google Scholar 

  8. Bernardo, M.: TwoTowers 2.0 user manual. http://www.sti.uniurb.it/bernardo/twotowers (2002)

  9. Bernardo, M.: Twotowers 3.0: Enhancing usability. In: Proc. of the 11th IEEE/ACM Int. Symp. on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, Orlando, FL, pp. 188–193 (2003)

    Google Scholar 

  10. Chiola, G., Franceschinis, G., Gaeta, R., Ribaudo, M.: Greatspn 1.7: Graphical editor and analyzer for timed and stochastic petri nets. Perform. Eval. 24(1–2), 47–68 (1995)

    Article  MATH  Google Scholar 

  11. Coe, P.S., Howell, F.W., Ibbett, R.N., Williams, L.M.: Technical note: a hierarchical computer architecture design and simulation environment. ACM Transactions on Modelling and Computer Simulation 8(4), 431–446 (1998)

    Article  MATH  Google Scholar 

  12. Gilmore, S., Hillston, J.: The PEPA workbench: a tool to support a process algebra-based approach to performance modelling. In: Proceedings of the 7th International Conference on Modelling Techniques and Tools for Performance Evaluation, vol. 794, pp. 353–368. Springer, Berlin (1994)

    Google Scholar 

  13. Harrison, P.G., Hillston, J.: Exploiting quasi-reversible structures in Markovian process algebra models. Computer Journal 38(7), 510–520 (1995)

    Article  Google Scholar 

  14. Herzog, U., Klehmet, U., Mertsiotakis, V., Siegle, M.: Compositional performance modelling with the TIPPtool. Performance Evaluation 39(1–4), 5–35 (2000)

    MATH  Google Scholar 

  15. Hillston, J., Pooley, R.: Stochastic process algebras and their application to performance modelling. In: Proc. of TOOLS’98 Tutorials, 1998

    Google Scholar 

  16. Hillston, J., Thomas, N.: Product form solution for a class of PEPA models. Performance Evaluation 35(3), 171–192 (1999)

    Article  MATH  Google Scholar 

  17. Kemeny, J.G., Snell, J.L.: Finite Markov Chains. Springer, New York (1976)

    MATH  Google Scholar 

  18. Lazowska, E.D., Kahorjan, J., Graham, G.S., Sevcik, K.C.: Quantitative System Performance: Computer System Analysis Using Queueing Network Models. Prentice-Hall, Englewood Cliffs (1984)

    Google Scholar 

  19. Liu, X., Shenoy, P.J., Corner, M.D.: Chameleon: Application-level power management. IEEE Trans. Mob. Comput. 7(8), 995–1010 (2008)

    Article  Google Scholar 

  20. Pooley, R.J.: An Introduction to Programming in SIMULA. Blackwell Scientific Publications, Oxford (1987)

    MATH  Google Scholar 

  21. Sereno, M.: Towards a product form solution for stochastic process algebras. Computer Journal 38, 622–632 (1995)

    Article  Google Scholar 

  22. Smith, C.U., Williams, L.G.: Performance Solutions: A Practical Guide to Creating Responsive, Scalable Software. Addison-Wesley, Reading (2002)

    Google Scholar 

  23. Tijms, H.C.: Stochastic Models, An Algorithmic Approach. John Wiley and Sons Ltd, New York (1994)

    MATH  Google Scholar 

  24. Trivedi, K.S.: Probability and Statistics with Reliability, Queueing and Computer Science Applications. John Wiley and Sons, New York (2001)

    Google Scholar 

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Cortellessa, V., Di Marco, A., Inverardi, P. (2011). Performance Model Solution. In: Model-Based Software Performance Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13621-4_6

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  • DOI: https://doi.org/10.1007/978-3-642-13621-4_6

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