Skip to main content
SpringerLink
Log in

Bio-Inspired Congestion Control: Conceptual Framework, Algorithm and Discussion

  • Chapter
Book cover Advances in Biologically Inspired Information Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 69))

We believe that future network applications will benefit by adopting key biological principles and mechanisms. This work propose that bio-inspired algorithms are best developed and analyzed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well founded analytical principles. We outline such a framework here, in the context of bio-inspired congestion control (BICC) models, and show that relations of those Internet entities that involved in congestion control mechanisms is similar to population interactions such as predator-prey. This similarity motivates us to map the predator-prey model to the Internet congestion control mechanism and design a bio-inspired congestion control scheme. The results show that using appropriately defined parameters, this model leads to a stable, fair and high performance congestion control algorithm. Key words: Communication Networks, Congestion Control, Biology, Predator-Prey

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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. P. D’haeseleer, S. Forrest, An Immunological Approach to Change Detection: Algorithms, Analysis and Implications, IEEE Symposium on Security and Privacy, Oakland, CA, USA, 1996.

    Google Scholar 

  2. S. Hofmeyer, An Immunological Model of Distributed Detection and Its Application to Computer Security, University of New Mexico, 1999.

    Google Scholar 

  3. F. Dressler, Efficient and Scalable Communication in Autonomous Networking using Bio-inspired Mechanisms - An Overview, informatica 29, 2005.

    Google Scholar 

  4. J. Wang, A Theoretical Study of Internet Congestion Control: Equilibrium and Dynamics, PhD thesis, University of Caltech, 2005.

    Google Scholar 

  5. S. Floyd, Connections with multiple congested gateways in packet-switched networks part 1: One-way traffic, Computer Communications Review, 1991.

    Google Scholar 

  6. T. V. Lakshman and U. Madhow, The performance of TCP/IP for networks with high bandwidth-delay products and random loss, IFIP Transactions, 1994.

    Google Scholar 

  7. T. Ott, J. Kemperman, and M. Mathis, The stationary behavior of ideal TCP congestion avoidance, 1998.

    Google Scholar 

  8. M. Mathis, J. Semke, J. Mahdavi, and T. Ott, The macroscopic behavior of the TCP congestion avoidance algorithm, Computer Communication Review, 1997.

    Google Scholar 

  9. J. Padhye, V. Firoiu, D. Towsley, and J. Kurose, Modeling TCP Reno performance: A simple model and its empirical validation, IEEE/ACM Transactions on Networking, 2000.

    Google Scholar 

  10. M. Handley, S. Floyd, J. Padhye, and J. Widmer, TCP Friendly Rate Control (TFRC): Protocol specification, RFC 3168, Internet Engineering Task Force, 2003.

    Google Scholar 

  11. V. Misra, W. Gong, and D. Towsley, Stochastic differential equation modeling and analysis of tcp-window size behavior, 1999.

    Google Scholar 

  12. V. Misra, W. Gong, and D. Towsley, Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED, ACM Sigcomm, 2000.

    Google Scholar 

  13. C. Hollot, V. Misra, D. Towsley, and W. Gong, A control theorietic analysis of RED, IEEE Infocom, 2001.

    Google Scholar 

  14. S. H. Low, F. Paganini, J. Wang, and J. C. Doyle, Linear stability of TCP/RED and a scalable control, Computer Networks Journal, 2003.

    Google Scholar 

  15. J. Aweya, M. Ouellette, and D. Y. Montuno, A control theoretic approach to active queue management, Computer Networks, 2001.

    Google Scholar 

  16. C. Hollot, V. Misra, D. Towsley, and W. Gong, On designing improved controller for AQM routers supporting TCP flows, IEEE Infocom, 2001.

    Google Scholar 

  17. K. B. Kim and S. H. Low, Analysis and design of aqm for stabilizing tcp, Technical Report, 2002.

    Google Scholar 

  18. H. Zhang, L. Baohong, and W. Dou, Design of a robust active queue management algorithm based on feedback compensation, ACM Sigcomm, 2003.

    Google Scholar 

  19. S. Ryu, C. Rump, and C. Qiao, Advances in active queue management (AQM) based TCP congestion control, Telecommunication System, 2004.

    Google Scholar 

  20. H. Choe and S. H. Low, Stabilized Vegas, IEEE Infocom, April 2003.

    Google Scholar 

  21. S. H. Low, L. Peterson, and L.Wang, Understanding Vegas: a duality model, Journal of ACM, 2002.

    Google Scholar 

  22. C. Jin, D. X. Wei, and S. H. Low FAST TCP: motivation, architecture, algorithms, performance, IEEE Infocom, 2004.

    Google Scholar 

  23. J. Wang, D. X. Wei, and S. H. Low, Modeling and stability of FAST TCP, IEEE Infocom, 2005.

    Google Scholar 

  24. F. Kelly, Charging and rate control for elastic traffic, European Transactions on Telecommunications, 1997.

    Google Scholar 

  25. F. P. Kelly, A. Maulloo, and D. Tan, Rate control for communication networks: Shadow prices, proportional fairness and stability, Journal of Operations Research Society, 1998.

    Google Scholar 

  26. S. H. Low and D. E. Lapsley, Optimization flow control I: basic algorithm and convergence, IEEE/ACM Transactions on Networking, 1999.

    Google Scholar 

  27. M. Analoui, Sh. Jamali, A Conceptual Framework for Bio-Inspired Congestion Control In Communication Networks, IEEE/ACM BIONETICS, 2006.

    Google Scholar 

  28. M. Analoui, Sh. Jamali, Inspiring by predator-prey interaction for Congestion Control In Communication Networks, CSICC2006, Iran, Tehran, 2006.

    Google Scholar 

  29. S. Stepney, R. E. Smith, J. Timmis, A. M. Tyrrell, M. J. Neal, A. N. W. Hone. Conceptual Frameworks for Artificial Immune Systems. Int. J. Unconventional Computing, 1(3):315-338, 2005.

    Google Scholar 

  30. S. Elizabeth, John A. Rhodes, Mathematical Models in Biology: An Introduction, Cambridge press, 2003.

    Google Scholar 

  31. Lotka, A, Elements of Physical Biology, Williams and Wilkins, Baltimore, 1925.

    MATH  Google Scholar 

  32. H. Ohsaki, Y. Mera, M. Murata, and H. Miyahara, Steady state analysis of the RED gate-way: stability, transient behavior, and parameter setting, ACM SIGMETRICS, 2000.

    Google Scholar 

  33. T. J. Ott, T. V. Lakshman, and L.Wong, SRED: Stabilized RED, IEEE INFOCOM’99, 1999.

    Google Scholar 

  34. F. Kelly, Mathematical Modeling of the Internet, Mathematics Unlimited-2001 and Beyond, Springer-Verlag, Berlin, 2001.

    Google Scholar 

  35. M. Analoui, Sh. Jamali, TCP Fairness Enhancement Through a Parametric Mathematical Model, CCSP2005, IEEE International Conference, 2005.

    Google Scholar 

  36. M. Murata, Biologically Inspired Communication Network Control, International Workshop on Self- ∗ Properties in Complex Information Systems, 2004.

    Google Scholar 

  37. S. Athuraliya, V. H. Li, S. H. Low, and Q. Yin, REM: active queue management. IEEE Network, 2001.

    Google Scholar 

  38. J. D. Murray, Mathematical Biology: I. an Introduction, Third Edition, Springer press, 2002.

    Google Scholar 

  39. George f. Simmons, differential equations(with applications and historical notes), McGraw-Hill Inc., 1972.

    Google Scholar 

  40. K. Ramakrishna, S. Floyd, and D. Black, The addition of explicit congestion notification (ECN) to IP, RFC 3168, Internet Engineering Task Force, September 2001.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Iran University of Science & Technology, University Road, 16846-13114, 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

Editor information

Editors and Affiliations

  1. University of Erlangen, Martensstr. 3, 91058, Erlangen, Germany

    Falko Dressler

  2. CREATE-NET, Via Solteri 38, 38100, Trento, Italy

    Iacopo Carreras

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Analoui, M., Jamali, S. (2007). Bio-Inspired Congestion Control: Conceptual Framework, Algorithm and Discussion. In: Dressler, F., Carreras, I. (eds) Advances in Biologically Inspired Information Systems. Studies in Computational Intelligence, vol 69. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72693-7_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-72693-7_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72692-0

  • Online ISBN: 978-3-540-72693-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation