Skip to main content
SpringerLink
Log in

Congestion Control in the Internet: Inspiration from Balanced Food Chains in the Nature

  • Thresholds Edited by Lawrence Bernstein
  • Published:
Journal of Network and Systems Management Aims and scope Submit manuscript

Abstract

Congestion in the Internet is the main reason for reduced performance and poor quality of service; therefore, a good congestion control system is essential. The current work proposes that the congestion control problem in the Internet can be inspired from natural population control tactics. Toward this idea, the congestion window size of each connection is viewed as population size of a species and then congestion control problem is redefined as population control of these windows species (W). This paper defines a three-trophic food chain and gives a model to control population size of W species within this food chain. Simulation results show that the proposed algorithm leads to a fair, stable and high-performance congestion control scheme.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Floyd, S., Jacobson, V.: Random early detection gateways for congestion avoidance. IEEE/ACM Trans. Netw. 1, 397–413 (1993)

    Article  Google Scholar 

  2. Floyd, S.: High speed TCP for large congestion windows. Internet draft, June 2002

  3. D’haeseleer, P., Forrest, S.: An immunological approach to change detection: algorithms, analysis and implications. IEEE (1996)

  4. Dressler, F.: Efficient and scalable communication in autonomous networking using bio-inspired mechanisms—an overview. Informatica 29, 183–188 (2005)

    Google Scholar 

  5. Analoui, M., Jamali, Sh.: A conceptual framework for bio-inspired congestion control in communication networks. IEEE/ACM BIONETICS (2006)

  6. Murray, J.D.: Mathematical Biology: I. An Introduction, 3rd edn. Springer press (2002)

  7. Analoui, M., Jamali, Sh.: Bio-inspired Congestion Control: Conceptual Framework, Algorithm and Discussion, Book chapter. Springer SCI series (2007, to appear)

  8. Analoui, M., Jamali, Sh.: Equation-based congestion control in the internet biologic environment. J LNCS Trans. Comput. Syst. Biol. (TCSB) (2007, to appear)

  9. Takeuchi, Y., Adachi, N.: Global stability of ecosystem of the generalized volterra type. Math. BioSci. 42, 119–136 (1978)

    Article  MATH  MathSciNet  Google Scholar 

  10. Ramakrishna, K., Floyd, S., Black, D.: The addition of explicit congestion notification (ECN) to IP, RFC 3168 (2001)

  11. Analoui, M., Jamali, Sh.: TCP fairness enhancement through a parametric mathematical model. IEEE CCSP2005 (2005)

Download references

Acknowledgement

This work has been supported by Iran Telecommunication Research Center.

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Iran University of Science and Technology (IUST), P.O. Box 16846, Tehran, Iran

    Morteza Analoui & Shahram Jamali

Authors
  1. Morteza Analoui
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shahram Jamali
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shahram Jamali.

Additional information

Morteza Analoui and Shahram Jamali present an interesting way of treating network congestion. In its simplest form it amounts to finding the flow hogging the most bandwidth, I mean data rate, and killing it. Their approach seems to provide network justice and dispenses with the notion fairness to those who abuse it.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Analoui, M., Jamali, S. Congestion Control in the Internet: Inspiration from Balanced Food Chains in the Nature. J Netw Syst Manage 16, 1–10 (2008). https://doi.org/10.1007/s10922-007-9093-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10922-007-9093-6

Keywords

Search

Navigation