Skip to main content
Log in

Abstract

In this paper, we show that a positive recurrent fluid queue is automatically V-uniformly ergodic for some function V ≥ 1 but never uniformly ergodic. This reveals a similarity of ergodicity between a fluid queue and a quasi-birth-and-death process. As a byproduct of V-uniform ergodicity, we derive computable bounds on the exponential moments of the busy period.

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. S Asmussen. Busy period analysis, rare events and transient behavior in fulidflow models, J Appl Math Stoch Anal, 1994, 7(3): 269–299.

    Article  MATH  MathSciNet  Google Scholar 

  2. A Badescu, L Breuer, G Latouche. Risk processes analyzed asfluid queues, J Scand Actuarial, 2005, 2: 127–141.

    Article  Google Scholar 

  3. B Cloez, M Hairer. Exponential ergodicity for Markov processes with random switching, Bernoul-li, 2015, 21(1): 505–536.

    Article  MathSciNet  MATH  Google Scholar 

  4. A da Silva Soares. Fluid queues: building upon the analogy with QBD processes. Doctoral Dissertation, Available at: http://theses.ulb.ac.be:8000/ETD-db/collection/available/ULBetd-03102005-160113/, 2005.

    Google Scholar 

  5. M Davis. Markov Models and Optimization, Chapman and Hall, London, 1993.

    Book  MATH  Google Scholar 

  6. S Dendievel, G Latouche, Y Liu. Poisson equation for discrete-time quasi-birth-and-death pro-cesses, Perform Eval, 2013, 70: 564–577.

    Article  Google Scholar 

  7. D Down, S P Meyn, R L Tweedie. Exponential and uniform ergodicity of Markov Processes, Ann Probab, 1995, 23(4): 1671–1691.

    Article  MathSciNet  MATH  Google Scholar 

  8. A I Elwalid, D Mitra. Analysis and design of rate-based congestion control of high speed net-works, I: stochasticfluid models, access regulation, Queueing Systems Theory Appl, 1991, 9: 19–64.

    Article  MATH  Google Scholar 

  9. M Govorun, G Latouche, MA Remiche. Stability forfluid queues: characteristic inequalities, Stoch Models, 2013, 29: 64–88.

    Article  MathSciNet  MATH  Google Scholar 

  10. S Jiang, Y Liu, S Yao. Poisson equation for discrete-time single-birth processes. Statistics and Probability Letters, 2014, 85, 78–83.

    Google Scholar 

  11. V G Kulkarni, E Tzenova. Mean first passage times influid queues, Oper Res Lett, 2002, 30: 308–318.

    Article  MathSciNet  MATH  Google Scholar 

  12. J Kushner. Stochastic Stability and Control Volume 33 of Mathematics in Science and Engi-neering, New York: Academic Press, 1967.

    Google Scholar 

  13. G Latouche, V Ramaswami. Introduction t. Matrix Analytic Methods in Stochastic Modeling, ASA-SIAM Series on Statistics and Applied Probability, SIAM, Philadelphia PA, 1999.

    Book  MATH  Google Scholar 

  14. Y Liu, Z Hou. Several types of ergodicity for M/G/1-type Markov chains and Markov processes, J Appl Probab, 2006, 43(1): 141–158.

    Article  MathSciNet  MATH  Google Scholar 

  15. Y Liu, Z Hou. Exponential and strong ergodicity for Jump processes with application to queuing theory, Chin Ann Math, 2008, 29B(2): 199–206.

    Google Scholar 

  16. Y Liu, Y Zhang. Central limit theorems for ergodic ontinuous-time Markov chains with appli-cations to single birth processes, Front Math China, 2015, 10(4): 933–947.

    Article  MathSciNet  Google Scholar 

  17. Y Mao, Y Tai, Y Q Zhao, J Zou. Ergodicity for the GI/G/1-type Markov chain, J Appl Probab Statist, 2014, 9(1): 1–44.

    Google Scholar 

  18. S P Meyn, R L Tweedie. Stability of Markovian processes III: Foster-Lyapunov criteria for continuous-time processes, Adv in Appl Probab, 1993, 25: 518–548.

    Article  MathSciNet  MATH  Google Scholar 

  19. V Ramaswami. Matrix analytic methods for stochasticfluidflows, Elsevie. Science B V, Edin-burgh, UK, pages, 1019–1030, 1999.

    Google Scholar 

  20. L C G Rogers. Fluid models in queueing theory and Wiener-Hopf factorization of Markov chains, Ann Appl Probab, 1994, 4(2): 390–413.

    Article  MathSciNet  MATH  Google Scholar 

  21. J Shao. Criteria for transience and recurrence of regime-switching diffusion processes, Electron J Probab, 2015, 20(63): 1–15.

    MathSciNet  MATH  Google Scholar 

  22. J Shao, F B Xi. Strong ergodicity of the regime-switching diffusion processes, Stoch Proc Appl, 2013, 123: 3903–3918.

    Article  MathSciNet  MATH  Google Scholar 

  23. T E Stern, A I Elwalid. Analysis of separable Markovmodulated rate models for information-handling systems, Adv Appl Probab, 1991, 23: 105–139.

    Article  MathSciNet  MATH  Google Scholar 

  24. N Va Foreest, M Mandjes, W Scheinhardt. Analysis of feedbackfluid model for heterogeneous TCP sources, Comm Statist Stoch Models, 2003, 19: 299–324.

    Article  MATH  Google Scholar 

  25. G Yin, F B Xi. Stability of regime-switching jump diffusions, SIAM J Contr Optim, 2010, 48: 4525–4549.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuan-yuan Liu.

Additional information

Supported by the National Natural Science Foundation of China (11571372, 11771452) and the Innovation Program of Central South University (10900-50601010).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, Yy., Li, Y. V-uniform ergodicity for fluid queues. Appl. Math. J. Chin. Univ. 34, 82–91 (2019). https://doi.org/10.1007/s11766-019-3543-2

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11766-019-3543-2

Keywords

MR Subject Classification

Navigation