Skip to main content
SpringerLink
Log in

Fuzzy Immune Controller Synthesis for ABR Traffic Control in High-Speed Networks

  • Chapter
Book cover Aspects of Soft Computing, Intelligent Robotics and Control

Part of the book series: Studies in Computational Intelligence ((SCI,volume 241))

Abstract

An end-to-end congestion control design synthesis algorithm for the available-bit-rate traffic in high speed asynchronous-transfer-mode networks is studied via applying the synergy of fuzzy-based intelligence and immune control laws. A fuzzy immune controller is designed to overcome the adverse effects in the network caused by unavoidable uncertainties such as number of users, available bit-rate bandwidth, and propagated transmission delays. Also an algorithm is proposed that can guarantee the minimum cell rate in order to ensure the fair and full utilization of the bandwidth. Simulation investigation has been carried out and the results show the proposed control synthesis is robust and the system performs effectively in adaptive mode. Hence the network’s quality-of-service in is guaranteed too.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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. ATM Technical Committee: Traffic Management Specification, Version 4.1, af-tm-0121.000. ATM Forum, 43–55 (March 1999)

    Google Scholar 

  2. Stallings, W.: High-Speed Networks: TCP/IP and ATM Design Principles. Prentice-Hall, Upper Saddle River (1998)

    Google Scholar 

  3. Bertsekas, D., Galager, R.: Data Netwroks, 2nd edn. Prentice Hall, Englewood Cliffs (1992)

    Google Scholar 

  4. Jacobson, V.: Congestion Avoidance and Control. Computer Communications Review 18, 316–329 (1988)

    Article  Google Scholar 

  5. Jain, R.: Congestion Control and Traffic Management in ATM Networks: Recent Advance and A Survey. Computer Networks & ISDN Systems 28(13), 1723–1738 (1991)

    Article  Google Scholar 

  6. Ait-Hellal, O., Altman, E., Basar, T.: Rate-based Flow Control with Bandwidth Information. European Trans. on Telecommunications 8, 55–65 (1997)

    Article  Google Scholar 

  7. Imer, O.C., Basar, T.: Control of Congestion in High-Speed Networks. European J. Control, Spessial Issue 7, 132–144 (2001)

    Article  Google Scholar 

  8. Imer, O.C., Compans, S., Basar, T.R.: Srikant: ABR Congestion Control in ATM IEEE Control Systems Magazine 21, 38–56 (2001)

    Google Scholar 

  9. Xiao, X., Telkamp, T., Fineberg, V., Chen, C., Ni, L.M.: A Practical Approach for Providing QoS in the Internet Backbone. IEEE Communications Magazine 40, 56–62 (2002)

    Article  Google Scholar 

  10. Gervos, P., Crowcoft, J., Kirsten, P.S., Bhati, S.: Congestion Control Mechanisms and the Best effort Service Model. IEEE Network 15, 16–26 (2001)

    Article  Google Scholar 

  11. Ramakrishnan, K., Jain, R.: A Binary Feedback Scheme for Congestion Avoidance in Computer Networks with A Connectionless Network Layer. ACM Trans. on Computer Systems 8, 158–181 (1990)

    Article  Google Scholar 

  12. Bonomi, F., Mitra, D., Seery, J.B.: Adaptive Algorithms for Feedback-Based Flow Control in High-Speed, Wide-Area ATM Networks. IEEE J. on Selected Areas in Communications 13, 1267–1283 (1995)

    Article  Google Scholar 

  13. Benmohamed, L., Meerkov, S.M.: Feedback Control of Congestion in Packet Switching Networks: The Case of A Single Congested Node. IEEE/ACM Trans. on Networking 1, 693–707 (1993)

    Article  Google Scholar 

  14. Kolarov, A., Ramamurthy, G.: A Control-Theoretic Approach to the Design of An Explicit Rate Controller for ABR Service. IEEE/ACM Trans. on Networking 7, 741–753 (1999)

    Article  Google Scholar 

  15. Benmohamed, L., Wang, Y.T.: A Control-Theoretic ABR Explicit Rate Algorithm for ATM Switches with Per-VC Queuing. In: Proceedings of the1998 IEEE INFOCOM, San Diego, CA, vol. 1, pp. 183–191 (1998)

    Google Scholar 

  16. Mascolo, S., Cavendish, D., Gerla, M.: ATM Rate Based Congestion Control Using A Smith Predictor: An EPRCA Implementation. In: Proceedings of the 1996 IEEE INFOCOM, San Francisco, CA, pp. 569–576. The IEEE, Piscataway (1996)

    Chapter  Google Scholar 

  17. Mascolo, S.: Smith’s Principle for Congestion Control in High Speed ATM Networks. In: Proceedings of the 36th IEEE Conference on Decision and Control, San Diego, CA, pp. 4595–4600. The IEEE, Piscataway (1997)

    Chapter  Google Scholar 

  18. Mascolo, S.: Congestion Control in High-Speed Communication Networks Using the Smith Principle. Automatica 35, 1921–1935 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  19. Habib, I., Tarraf, A., Saadawi, T.: A Neural Network Controller for Congestion Control in ATM Multiplexers. Computer Networks & ISDN Systems 29, 325–334 (1997)

    Article  Google Scholar 

  20. Lestas, M., Pitsilides, A., Ioannu, P., Hadjipollas, G.: Adaptive Congestion Protocol: A Congestion Control Protocol with Learning Capability. Computer Networks: Intl. J. of Computer & Telecommunications Networking 51, 3773–3798 (2007)

    MATH  Google Scholar 

  21. Kwang, K.S., Tan, S.W., Hsiao, M.C., Wu, C.S.: Cooperative Multiagent Congestion Control for High-speed Networks. IEEE Trans. on Systems, Man & Cyvernetics, Part B: Cybernetics 35, 255–268 (2005)

    Article  Google Scholar 

  22. Li, X., Zhou, Y.C., Dimirovski, G.M., Jing, Y.W.: Simulated Annnealing Q-learning Algoritam for ABR Traffic Control of ATM Networks. In: Proceedings of the 27th American Control Conference, Seaatle, WA, pp. 4462–4467. The AACC and IEEE, Piscataway (2008)

    Google Scholar 

  23. Hu, R.Q., Petr, D.W.: A Predictive Self-Tuning Fuzzy-Logic Feedback Rate Controller. IEEE/ACM Trans. on Networking 8, 697–709 (2000)

    Article  Google Scholar 

  24. Ding, Y.S.: A Nonlinear PID Controller Based on Fuzzy-Tuned Immune Feedback Law. In: Proceedings of the 3rd World Congress on Intelligent Control and Automation, Beijing, P.R. China, pp. 1576–1580 (2000)

    Google Scholar 

  25. Ren, T., Dimirovski, G.M., Jing, Y.W.: ABR Traffic Control over ATM Networks Using Fuzzy Immune PID Controller. In: Proceedings of the 25th American Control Conference, Minneapolis, MN, pp. 4876–4881 (2006)

    Google Scholar 

  26. Ren, T., Gao, Z., Kong, W., Jing, Y., Yang, M., Dimirovski, G.M.: Performance and Robustness Analysis of a Fuzzy Immune Flow Controller in ATM Networks with Time-varying Multiple Time-delays. J. Control Theory & Applications 6, 253–258 (2008)

    Article  MathSciNet  Google Scholar 

  27. Klir, G.J., Yuan, B.: Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice-Hall, Upper Saddle River (1995)

    MATH  Google Scholar 

  28. Ross, T.J.: Fuzzy Logic with Engineering Applications, 2nd edn. John Wiley & Sons, Chichester (2005)

    Google Scholar 

  29. Siler, W., Buckley, J.J.: Fuzzy Expert Systems and Fuzzy Reasoning. John Wiley & Sons Inc., Hoboken (2005)

    Google Scholar 

  30. Berenji, H.R.: Fuzzy Logic Controllers. In: Yager, R.R., Zadeh, L.A. (eds.) An Introduction to Fuzzy Logic Applications in Intelligent Systems, pp. 69–76. Kluwer Academic, Boston (1993)

    Google Scholar 

  31. Palm, R., Driankov, D., Hellendoorn, H.: Model Based Fuzzy Control. Springer, Heidelberg (1997)

    MATH  Google Scholar 

  32. Yen, J., Langari, R.: Fuzzy Logic: Intelligence, Control, and Information. Prentice Hall, Upper Saddle River (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dogus University, Computer Engineering Dept., Acibadem, Istanbul 34722, R. Turkey, and SS Cyril & Methodius University, FEIT, ASE, Karpos 2 BB, 1000 Skopje, R., Macedonia

    Georgi M. Dimirovski

  2. College of Information Science & Engineering, Northeastern University, Shenyang, Liaoning, 110004, P.R. China

    Yuanwei Jing & Tao Ren

Authors
  1. Georgi M. Dimirovski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuanwei Jing
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tao Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Intelligent Engineering Systems, John von Neumann Faculty of Informatics Budapest Tech, Bécsi út 96/b, H-1034, Budapest, Hungary

    János Fodor

  2. Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Dimirovski, G.M., Jing, Y., Ren, T. (2009). Fuzzy Immune Controller Synthesis for ABR Traffic Control in High-Speed Networks. In: Fodor, J., Kacprzyk, J. (eds) Aspects of Soft Computing, Intelligent Robotics and Control. Studies in Computational Intelligence, vol 241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03633-0_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-03633-0_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03632-3

  • Online ISBN: 978-3-642-03633-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation