Skip to main content

Effective Minimization of Acyclic Phase-Type Representations

  • Conference paper
Analytical and Stochastic Modeling Techniques and Applications (ASMTA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5055))

Abstract

Acyclic phase-type distributions are phase-type distributions with triangular matrix representations. They constitute a versatile modelling tool, since they (1) can serve as approximations to any continuous distributions, and (2) exhibit special properties and characteristics, which usually result in some ease in analysis. The size of the matrix representation has a strong influence on computational efforts needed when analyzing these distributions. This representation, however, is not unique, and two representations of the same distribution can differ drastically in size. This paper proposes an effective procedure to aggregate the size of the matrix representation without altering the distribution.

This work is supported by the German Research Council (DFG) as part of the Transregional Collaborative Research Center “Automatic Verification and Analysis of Complex Systems” (SFB/TR 14 AVACS). See www.avacs.org for more information.

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

Access this chapter

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. The GNU Multiple Precision Arithmetic Library (2008), http://gmplib.org/

  2. Asmussen, S.: Phase-type representations in random walk and queueing problems. Annals of Probability 20(2), 772–789 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  3. Baier, C., Hermanns, H.: Weak bisimulation for fully probabilistic processes. In: Grumberg, O. (ed.) CAV 1997. LNCS, vol. 1254, pp. 119–130. Springer, Heidelberg (1997)

    Google Scholar 

  4. Baier, C., Katoen, J.-P., Hermanns, H., Wolf, V.: Comparative branching-time semantics for Markov chains. Information and Computation 200(2), 149–214 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  5. Boudali, H., Crouzen, P., Stoelinga, M.: A compositional semantics for dynamic fault trees in terms of interactive Markov chains. In: Namjoshi, K.S., Yoneda, T., Higashino, T., Okamura, Y. (eds.) ATVA 2007. LNCS, vol. 4762, pp. 441–456. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  6. Bravetti, M.: Revisiting interactive Markov chains. Electronic Notes in Theoretical Computer Science 68(5) (2002)

    Google Scholar 

  7. Buchholz, P.: Exact and ordinary lumpability in finite Markov chains. Journal of Applied Probability 31, 59–75 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  8. Chakravarthy, S.R., Krishnamoorthy, A., Ushakumari, P.V.: A k-out-of-n reliability system with an unreliable server and phase type repairs and services: the (N,T) policy. Journal of Applied Mathematics and Stochastic Analysis 14(4), 361–380 (1992)

    Article  MathSciNet  Google Scholar 

  9. Chakravarthy, S.R., Ravi, K.: A Stochastic Model for a Computer Communication Network Node with Phase Type Timeout Periods, ch. 14. In: Numerical Solutions of Markov Chains, pp. 261–286. Marcel Dekker (1991)

    Google Scholar 

  10. Commault, C., Mocanu, S.: A generic property of phase-type representations. Journal of Applied Probability 39, 775–785 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  11. Cumani, A.: Canonical representation of homogeneous Markov processes modelling failure time distributions. Microelectronics and Reliability 2(3), 583–602 (1982)

    Article  MathSciNet  Google Scholar 

  12. Derisavi, S., Hermanns, H., Sanders, W.H.: Optimal state-space lumping in Markov chains. Information Processing Letters 87(6), 309–315 (2003)

    Article  MathSciNet  Google Scholar 

  13. Dugan, J.B., Bavuso, S.J., Boyd, M.A.: Dynamic fault-tree models for fault-tolerant computer systems. IEEE Transaction on Reliability 41(3), 363–377 (1992)

    Article  MATH  Google Scholar 

  14. Fackrell, M.W.: Characterization of Matrix-Exponential Distributions. PhD thesis, School of Applied Mathematics, The University of Brisbane (2003)

    Google Scholar 

  15. He, Q.-M., Zhang, H.: Spectral polynomial algorithms for computing bi-diagonal representations for phase type distributions and matrix-exponential distributions. Stochastic Models 2(2), 289–317 (2006)

    Article  MathSciNet  Google Scholar 

  16. He, Q.-M., Zhang, H.: An Algorithm for Computing Minimal Coxian Representations. INFORMS Journal of Computing, ijoc.1070.0228 (2007)

    Google Scholar 

  17. Henley, E.J., Kumamoto, H.: Probabilistic Risk Assessment. IEEE Computer Society Press, Los Alamitos (1992)

    Google Scholar 

  18. Hermanns, H.: Interactive Markov Chains: The Quest for Quantified Quality. LNCS, vol. 2428. Springer, Heidelberg (2002)

    Google Scholar 

  19. Hillston, J.: A compositional approach to performance modelling. Cambridge University Press, Cambridge (1996)

    Google Scholar 

  20. Johnson, M.A., Taaffe, M.R.: The denseness of phase distributions. Purdue School of Industrial Engineering Research Memoranda 88-20, Purdue University (1988)

    Google Scholar 

  21. Khayari, R.E.A., Sadre, R., Haverkort, B.R.: Fitting world-wide web request traces with the EM-algorithm. Performance Evaluation 52(2-3), 175–191 (2003)

    Article  Google Scholar 

  22. Manian, R., Dugan, J.B., Coppit, D., Sullivan, K.J.: Combining various solution techniques for dynamic fault tree analysis of computer systems. In: Proceedings of the 3rd IEEE International Symposium on High-Assurance Systems Engineering (HASE 1998), pp. 21–28. IEEE Computer Society Press, Los Alamitos (1998)

    Google Scholar 

  23. Neuts, M.F.: Matrix-Geometric Solutions in Stochastic Models: An Algorithmic Approach. Dover (1981)

    Google Scholar 

  24. O’Cinneide, C.A.: On non-uniqueness of representations of phase-type distributions. Communications in Statistics: Stochastic Models 5(2), 247–259 (1989)

    Article  MATH  MathSciNet  Google Scholar 

  25. O’Cinneide, C.A.: Characterization of phase-type distributions. Communications in Statistics: Stochastic Models 6(1), 1–57 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  26. O’Cinneide, C.A.: Phase-type distributions and invariant polytopes. Advances in Applied Probability 23(43), 515–535 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  27. O’Cinneide, C.A.: Triangular order of triangular phase-type distributions. Communications in Statistics: Stochastic Models 9(4), 507–529 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  28. Pulungan, R., Hermanns, H.: Effective minimization of acyclic phase-type representations. Reports of SFB/TR 14 AVACS 38, SFB/TR 14 AVACS (March 2008), ISSN: 1860-9821, http://www.avacs.org

  29. Pulungan, R., Hermanns, H.: The minimal representation of the maximum of Erlang distributions. In: Proceedings of the 14th GI/ITG Conference on Measuring, Modelling and Evaluation of Computer and Communication Systems (MMB 2008), pp. 207–221. VDE Verlag (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Khalid Al-Begain Armin Heindl Miklós Telek

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pulungan, R., Hermanns, H. (2008). Effective Minimization of Acyclic Phase-Type Representations. In: Al-Begain, K., Heindl, A., Telek, M. (eds) Analytical and Stochastic Modeling Techniques and Applications. ASMTA 2008. Lecture Notes in Computer Science, vol 5055. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68982-9_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-68982-9_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68980-5

  • Online ISBN: 978-3-540-68982-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics