Skip to main content
SpringerLink
Log in

SPNP: Stochastic Petri Nets. Version 6.0

  • Conference paper
  • First Online:
Computer Performance Evaluation.Modelling Techniques and Tools (TOOLS 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1786))

Abstract

The Stochastic Petri Net Package (SPNP) [2] is a versatile modeling tool for solution of Stochastic Petri Net (SPN) models. The SPN models are described in the input language for SPNP called CSPL (C-based SPN Language) which is an extension of the C programming language [8] with additional constructs which facilitate easy description of SPN models. Moreover, if the user does not want to describe his model in CSPL, a Graphical User Interface (GUI) is available to specify all the characteristics as well as the parameters of the solution method chosen to solve the model.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. H. Choi et al. Markov Regenerative Stochastic Petri Nets. Performance Evaluation, 20(1–3):337–357, 1994.

    Article  MathSciNet  Google Scholar 

  2. G. Ciardo, J. K. Muppala, and K. S. Trivedi. SPNP: Stochastic Petri Net Package. Proc. of 3rd International Workshop on Petri Nets and Performance Models, pages 142–150, Kyoto, Japan, Dec. 1989.

    Google Scholar 

  3. G. Ciardo, D.M. Nicol, and K.S. Trivedi. Discrete-Event Simulation of Fluid Stochastic Petri-Nets. IEEE Trans. on Soft. Eng., 25(2):207–217, 1999.

    Article  Google Scholar 

  4. Computer Science Department. College of Willian and Mary. On the Simulation of Stochastic Petri Nets.

    Google Scholar 

  5. G.S. Fishman. Monte Carlo: Concepts, Algorithms and Applications. Springer-Verlag, 1997.

    Google Scholar 

  6. P. W. Glynn and D. L. Iglehart. Importance Sampling for Stochastic Simulations. Management Science, 35(11):1367–1392, November 1989.

    Article  MATH  MathSciNet  Google Scholar 

  7. A. Goyal et al. A Unified Framework for Simulating Markovian Models of Highly Dependable Systems. IEEE Trans. on Computers, 41(1):36–51, Jan. 1992.

    Article  Google Scholar 

  8. S. P. Harbison and G. L. Steele Jr. C — A Reference Manual. Prentice-Hall, 3 edition, 1991.

    Google Scholar 

  9. P. Heidelberger et al. Bounded Relative Error in estimating transient Measures of Highly Dependable Non-Markovian Systems. ACM Trans. on Modeling and Computer Simulation, 4(2):137–164, April 1994.

    Article  MATH  Google Scholar 

  10. P.A.W. Lewis and G.S. Shedler. Simulation of nonhomogeneous Poisson processes by thinning. Naval Res. Logist. Quart., 26:403–413, 1979.

    Article  MATH  MathSciNet  Google Scholar 

  11. M. Malhotra et al. Stiffness-tolerant methods for transient analysis of stiff Markov chains. Microelectron. & Rel., 34(11):1825–1841, 1994.

    Article  Google Scholar 

  12. V. F. Nicola et al. Fast Simulation of Highly Dependable Systems with General Failure and Repair Processes. IEEE Trans. on Computers, 42(12):1440–1452, December 1993.

    Article  Google Scholar 

  13. W. J. Stewart. Introduction to the Numerical Solution of Markov Chains. Princeton University Press, 1994.

    Google Scholar 

  14. B. Tuffin and K.S. Trivedi. Implementation of importance splitting techniques in stochastic petri net package. Computer performance evaluation: Modelling tools and techniques; 11th International Conference; TOOLS 2000, Schaumburg, Il., USA, March 2000.

    Google Scholar 

  15. W. B. van den Hout. The Power-Series Algorithm: A Numerical Approach to Markov Processes. Tilburg University, 1996.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Advanced Computing and Communication Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27708-0291, USA

    Christophe Hirel, Bruno Tuffin & Kishor S. Trivedi

Authors
  1. Christophe Hirel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bruno Tuffin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kishor S. Trivedi
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, RWTH Aachen, 52056, Aachen, Germany

    Boudewijn R. Haverkort  & Henrik C. Bohnenkamp  & 

  2. Performance Engineering Services Division, MS 110, L&S Computer Technology, Inc., P.O. Box 9802, Austin, TX, 78766, USA

    Connie U. Smith

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hirel, C., Tuffin, B., Trivedi, K.S. (2000). SPNP: Stochastic Petri Nets. Version 6.0. In: Haverkort, B.R., Bohnenkamp, H.C., Smith, C.U. (eds) Computer Performance Evaluation.Modelling Techniques and Tools. TOOLS 2000. Lecture Notes in Computer Science, vol 1786. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46429-8_30

Download citation

  • DOI: https://doi.org/10.1007/3-540-46429-8_30

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67260-9

  • Online ISBN: 978-3-540-46429-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation