Skip to main content
Log in

Markov-modulated birth-death processes

  • Published:
Automatic Control and Computer Sciences Aims and scope Submit manuscript

Abstract

We consider the birth-death process, the parameters of which are determined according to the external environment. The latter is described by a continuous-time Markov chain. In the literature, such processes are designated as Markov-modulated. They allow making such processes time-dependent. Therefore, stochastic models that are based on them prove to correspond closer to the real processes of the Internet, insurance systems, etc. The article expounds the methodology for computing stationary state probabilities for the considered processes. As an example, we analyze a one-line queueing system functioning in a random environment. The numerical data demonstrate the presence of a dependence that significantly alters the efficiency factors of the system.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Feller, W., An Introduction to Probability Theory and Its Applications, New York: Wiley, 1971, vol. 1.

    MATH  Google Scholar 

  2. Feller, W., An Introduction to Probability Theory and Its Applications, New York: Wiley, 1971, vol. 2.

    MATH  Google Scholar 

  3. Andronov, A.M., Kopytov, E.A., and Gringlaz, L.Ya., Teoriya veroyatnostei i matematicheskaya statistika (Probability Theory and Mathematical Statistics. A Tutorial), St.-Petersburg: Piter, 2004.

    Google Scholar 

  4. Kijima, M., Markov Processes for Stochastic Modeling, London: Chapman and Hall, 1997.

    MATH  Google Scholar 

  5. Shneps, M.A., Sistema raspredeleniya informatsii. Metody rascheta (Systems of Distribution of Information. Methods of Calculation), Moscow: Svyaz’, 1979.

    Google Scholar 

  6. Vishnevskii, V.M., Teoreticheskie osnovy proektirovaniya vychmslitel’nykh setei (Theoretical Fundamentals of Computational Array Design), Moscow: Tekhnosfera, 2003.

    MATH  Google Scholar 

  7. Gelenbe, E. and Mitrani, I., Analyzing and Synthesis of Computer Systems, London: Academic, 1980.

    Google Scholar 

  8. Hernandez-Campos, F., Jeffay, K.F., Park, C., Marron, J.S., and Resnick, S.I., Extremal Dependence: Internet Traffic Applications, Stochastic Models, 2005, vol. 22, no. 1, pp. 1–35.

    Article  MathSciNet  Google Scholar 

  9. Zhang, Y., Breslay, L., Paxson, V., and Shenker, S., On the Characteristics and Origins of Internet ACM Flow Rates, Pittsburgh: SIGCOMM, 2002.

    Google Scholar 

  10. Breymann, W., Dias, A., and Embrechts, P., Dependence Structures for Multivariate High-Frequency Data in Finance, Quantitative Finance, 2003, vol. 3, no. 1, pp. 1–16.

    Article  MathSciNet  Google Scholar 

  11. Embrechts, P., Lindskog, F., and McNeil, A., Modelling Dependence with Copulas and Applications to Risk Management (Chapter 8). Handbook of Heavy Tailed Distributions in Finance, Amsterdam: Elsevier, 2003.

    Google Scholar 

  12. Dudin, A.N. and Klimenok, V.I., Sistemy massovogo obsluzhivaniya s korrelirovannymi potokami (Systems of Mass Service with Correlated Flows), Minsk: Belorus. Gos. Univ., 2000.

    Google Scholar 

  13. Pacheco, A., Tang, L.C., and Prabhu, U.N., Markov-Modulated Processes and Semiregenerative Phenomena, New Jersey: World Sci., 2009.

    Google Scholar 

  14. Kim, C.S., Dudin, A., Klimenok, V., and Khramova, V., Erlang Loss Queueing System with Batch Arrivals Operating in a Random Environment, Comp. Operat. Res., 2009, vol. 36, no. 3, pp. 674–697.

    Article  MATH  MathSciNet  Google Scholar 

  15. Kim, C.S., Klimenok, V., Mushko, V., and Dudin, A., The BMAP/PH/N Retrial Queueing System Operating in Markovian Random Environment, Comp. Operat. Res., 2010, vol. 37, no. 7, pp. 1228–1237.

    Article  MATH  MathSciNet  Google Scholar 

  16. Olivier, C. and Walrand, J., On the Existence of Finite-Dimensional Filters for Markov-Modulated Traffic, J. Applied Probabilities, 1994, vol. 31, pp. 515–525.

    Article  MATH  MathSciNet  Google Scholar 

  17. Turkington, D.A., Matrix Calculus and Zero-One Matrices. Statistical and Econometric Applications, Cambridge: Cambridge University Press, 2002.

    MATH  Google Scholar 

  18. Du, Q., A Monotonicity Result for a Single-Server Queue Subject to a Markov-Modulated Poisson Process, J. Applied Probability, 1995, vol. 32, pp. 1103–1111.

    Article  MATH  Google Scholar 

  19. Afanaseva, L. and Bulinskaya, E., Stoshastic Models of Transport Flows, Applied Stochastic Models and Data Analysis. Selected Papers (Proc. XIII Int. Conf.), Vilnius, 2009

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. M. Andronov.

Additional information

Original Russian Text © A.M. Andronov, 2011, published in Avtomatika i Vychislitel’naya Tekhnika, 2011, No. 3, pp. 5–18.

About this article

Cite this article

Andronov, A.M. Markov-modulated birth-death processes. Aut. Conrol Comp. Sci. 45, 123–132 (2011). https://doi.org/10.3103/S0146411611030035

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0146411611030035

Keywords

Navigation