Skip to main content
Log in

Large Deviations for Small Buffers: An Insensitivity Result

  • Published:
Queueing Systems Aims and scope Submit manuscript

Abstract

This article focuses on a queue fed by a large number of “semi-Markov modulated fluid sources”, e.g., on/off sources with on and off-times that have general distributions. The asymptotic regime is considered in which the number of sources grows large, and the buffer and link rate are scaled accordingly. We aim at characterizing the exponential decay rate of the buffer overflow probability for the regime of small buffers. An insensitivity result is proven: the decay rate depends on the distributions of the on and off-times only through their means. The efficiency gain to be achieved by using small buffers is significant, as the decay rate grows fast: proportionally to the square root of the buffer size.

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.

Institutional subscriptions

Similar content being viewed by others

References

  1. D. Anick, D. Mitra and M. Sondhi, Stochastic theory of a data-handling system with multiple sources, Bell System Tech. J. 61 (1982) 1871-1894.

    Google Scholar 

  2. D. Botvich and N. Duffield, Large deviations, the shape of the loss curve and economies of scale in large multiplexers, Queueing Systems 20 (1995) 293-320.

    Google Scholar 

  3. O. Boxma and V. Dumas, Fluid queues with long-tailed activity period distributions, Comput. Commun. 21 (1998) 1509-1529.

    Google Scholar 

  4. C. Courcoubetis and R. Weber, Buffer overflow asymptotics for a buffer handling many traffic sources, J. Appl. Probab. 33 (1996) 886-903.

    Google Scholar 

  5. A. Dembo and O. Zeitouni, Large Deviations Techniques and Applications (Jones and Bartlett, Boston, 1993).

    Google Scholar 

  6. N. Duffield, Queueing at large resources driven by long-tailed M/G/∞-modulated processes, Queueing Systems 28 (1998) 245-266.

    Google Scholar 

  7. V. Dumas and A. Simonian, Asymptotic bounds for the fluid queue fed by sbexponential on-off sources, preprint.

  8. A. Elwalid, D. Mitra and R. Wentworth, A new approach for allocating buffers and bandwidth to heterogeneous, regulated traffic in an ATM node, IEEE J. Selected Areas Commun. 13 (1995) 1115-1127.

    Google Scholar 

  9. M. Grossglauser and J.-C. Bolot, On the relevance of long-range dependence in network traffic, IEEE/ACM Trans. Networking 7 (1999) 629-640.

    Google Scholar 

  10. D. Heyman and T. Lakshman, What are the implications of long-range dependence for VBR traffic engineering?, IEEE/ACM Trans. Networking 4 (1996) 301-317.

    Google Scholar 

  11. J. Hui, Resource allocation for broadband networks, IEEE J. Selected Areas Commun. 6 (1988) 1598-1608.

    Google Scholar 

  12. W. Leland, M. Taqqu, W. Willinger and D. Wilson, On the self-similar nature of Ethernet traffic, IEEE/ACM Trans. Networking 2 (1994) 1-15.

    Google Scholar 

  13. N. Likhanov and R. Mazumdar, Cell loss asymptotics in buffers fed with a large number of independent stationary sources, J. Appl. Probab. 36 (1999) 86-96.

    Google Scholar 

  14. M. Mandjes and S. Borst, Overflow behavior in queues with many long-tailed inputs, to appear in Adv. Appl. Probab., CWI report PNA-R9911, available at http://www.cwi.nl/static/publications/reports/PNA-1999.html.

  15. V. Paxson and S. Floyd, Wide area traffic: The failure of Poisson modeling, IEEE/ACM Trans. Networking 3 (1995) 226-244.

    Google Scholar 

  16. B. Ryu and A. Elwalid, The importance of long-range dependence of VBR video traffic in ATMtraffic engineering: Myths and realities, Comput. Commun. Rev. 26 (1996) 3-14.

    Google Scholar 

  17. A. Shwartz and A. Weiss, Large Deviations for Performance Analysis, Queues, Communication and Computing (Chapman and Hall, New York, 1995).

    Google Scholar 

  18. A. Simonian and J. Guibert, Large deviations approximation for fluid queues fed by a large number of on/off sources, IEEE J. Selected Areas Commun. 13 (1995) 1017-1027.

    Google Scholar 

  19. A. Weiss, A new technique of analyzing large traffic systems, Adv. Appl. Probab. 18 (1986) 506-532.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mandjes, M., Kim, J.H. Large Deviations for Small Buffers: An Insensitivity Result. Queueing Systems 37, 349–362 (2001). https://doi.org/10.1023/A:1010837416603

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1010837416603

Navigation