Skip to main content
SpringerLink
Log in

A Fuzzy-Expert-System-Based Structure for Active Queue Management

  • Conference paper
Advances in Intelligent Computing (ICIC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3645))

Included in the following conference series:

Abstract

In this paper, we demonstrate an example of using artificial intelligent in solving problems with complex and uncertain features in communication networks. The concept of Fuzzy Expert System is used in the design of an Active Queue Management (AQM) algorithm. Expert System and Fuzzy Logic are commonly used methods in solving various kinds of uncertain problems. Network congestion control is a problem with large scale and complexity, where no accurate and reliable model has been proposed so far. We believe Fuzzy Expert System methods have the potential to be applied to congestion control and solve those problems with uncertainties. This research demonstrates the possibility of using Fuzzy Expert System in the network congestion control. In this paper, a fuzzy-expert-system-based structure is proposed for network congestion control and a novel AQM algorithm is introduced. Simulation experiments are designed to show that the fuzzy-expert-system-based AQM algorithm exhibits a better performance than conventional approaches.

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

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. Feng, W., Kandlur, D., Shin, K.: A self-configuring RED gateway. In: Proc. of INFOCOM 1999, March 1999, vol. 3, pp. 1280–1289 (1999)

    Google Scholar 

  2. Gurer, D., Lakshiminarayan, V., Sastry, A.: An Intelligent Agent-Based Architecture for the Management of Heterogeneous Networks. In: Proc. of DSOM 1998 (1998)

    Google Scholar 

  3. Floyd, S., Jacobson, V.: Random early detection gateways for congestion avoidance. IEEE/ACM Trans. on Networking 1(4), 397–413 (1993)

    Article  Google Scholar 

  4. Hollot, C.V., Misra, V., Towsley, D., Gong, W.-b.: On designing improving controllers for AQM Routers Supporting TCP Flows. In: Proc. of INFOCOM 1999, March 1999, vol. 3, pp. 1736- 34 (1999)

    Google Scholar 

  5. Park, Y.-K., Gyungho, L.: Intelligent congestion control in ATM networks. In: Proc. of the 5th Workshop on Future Trends of Distributed Computing Systems, August 1995, pp. 369–375 (1995)

    Google Scholar 

  6. Hoang, D.B., Yu, Q.: Performance of the fair intelligent congestion control for TCP applications over ATM networks: a simulation analysis. In: Proc. of ICATM 1999, pp. 390–395 (1999)

    Google Scholar 

  7. Huston, G.: The Future for TCP. The Internet Protocol Journal 3(3), 2–27 (2000)

    Google Scholar 

  8. Braden, B., et al.: Recommendations on Queue Management and Congestion Avoidance in the Internet. RFC 2309 (April 1998)

    Google Scholar 

  9. ns-2 Network Simulator, Obertain via, http://www.isi.edu/nsnam/ns/

  10. Pitsillides, A., Sekercioglu, A., Ramamurthy, G.: Effective Control of Traffic Flow in ATM Networks Using Fuzzy Explicit Rate Marking. IEEE JSAC 15(2), 209–225 (1997)

    Google Scholar 

  11. Hollot, C.V., Misra, V., Towsley, D., Gong, W.-B.: A Control Theoretic Analysis of RED. In: Proc. of INFOCOM 2001, April 2001, vol. 3, pp. 1510–1519 (2001)

    Google Scholar 

  12. Ott, T.J., Lakshman, T.V., Wong, L.H.: SRED: Stabilized RED. In: Proc. of IEEE INFOCOM 1999, March 1999, vol. 3, pp. 1346–1355 (1999)

    Google Scholar 

  13. May, M., Bolot, J., Diot, C., Lyles, B.: Reasons Not to Deploy RED. In: Proc. of IWQoS 1999 (June 1999)

    Google Scholar 

  14. Looking Over the Fence at Networks. National Academy Press (2001) ISBN 0-309-07613-7

    Google Scholar 

  15. Low, S.H.: A Duality Model of TCP and Queue Management Algorithms, under doing from: http://netlab.caltech.edu

  16. Low, S.H., Lapsley, D.: Optimization Flow Control. IEEE/ACM Transactions on Networking 7(6), 861–875 (1999)

    Article  Google Scholar 

  17. Lin, D., Morris, R.: Dynamics of random early detection. ACM Computer Communication Review 27, 127–137 (1997)

    Article  Google Scholar 

  18. Anjum, F., Tassiulas, L.: Fair Bandwidth sharing among adaptive and non-adaptive flows in the Internet. In: Proc. of INFOCOM 1999, March 1999, vol. 3, pp. 1412–1420 (1999)

    Google Scholar 

  19. Athuraliya, S., Low, S.H.: Simulation Comparison of RED and REM. In: Proc. of ICON 2000, September 2000, pp. 68–72 (2000)

    Google Scholar 

  20. Bonald, T., May, M.: Analytic evaluation of RED performance. In: Proc. of INFOCOM 2000, March 2000, vol. 3, pp. 1415–1424 (2000)

    Google Scholar 

  21. Padhye, J., Firoiu, V., Towsley, D., Kurose, J.: Modeling TCP Reno Performance: A Simple Model and Its Empirical Validation. IEEE/ACM Trans. on Networking 8(2) (April 2000)

    Google Scholar 

  22. Loukas, R., Kohler, S., Andreas, P., Phuoc, T.-G.: Fuzzy RED: Congestion Control for TCP/IP Diff-Serv. In: Proc. of IEEE the 10th Mediterranean Electrotechnical Conference, October 2000, vol. 1, pp. 19–22 (2000)

    Google Scholar 

  23. Sekercioglu, Y.A., Pitsillides, A.: Fuzzy Control of ABR Traffic Flow in ATM LANs. In: Proc. of IEEE Symposium on Computers and Communications, pp. 227–232 (1995)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Beihang University, 100083, Beijing, China

    Jin Wu

  2. Sino-German Joint Software Institute, Beihang University, 100083, Beijing, China

    Jin Wu

  3. School of Computing, University of Leeds, LS2 9JT, Leeds, United Kingdom

    Karim Djemame

Authors
  1. Jin Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karim Djemame
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Intelligent Computing Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, China

    De-Shuang Huang

  2. School of Computer & Information Technology, Beijing Jiaotong University, 100044, Beijing, P.R. China

    Xiao-Ping Zhang

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

    Guang-Bin Huang

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wu, J., Djemame, K. (2005). A Fuzzy-Expert-System-Based Structure for Active Queue Management. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538356_28

Download citation

  • DOI: https://doi.org/10.1007/11538356_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28227-3

  • Online ISBN: 978-3-540-31907-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation