FLC: A Novel Dynamic Buffer Tuner for Shortening Service Roundtrip Time over the Internet by Eliminating User-Level Buffer Overflow on the Fly

  • Wilfred W. K. Lin
  • Allan K. Y. Wong
  • Tharam S. Dillon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3756)


The proposed Fuzzy Logic Controller (FLC) is for dynamic buffer tuning at the user/server level. It eliminates buffer overflow on-line by ensuring that the buffer length always cover the queue length adaptively. The FLC contributes to prevent the AQM (active queue management) resources dished out at the system level from being wasted and to shorten the service roundtrip time (RTT) by reducing retransmission caused by user-level buffer overflow at the reception side. Combining fuzzy logic and the conventional PIDC model creates the FLC that operates with the {0, Δ}2 objective function. The fuzzy logic maintains the given safety margin about the reference point, which is symbolically represented by “0” in {0, Δ}2. The short execution time of the FLC makes it suitable for supporting time-critical applications over the Internet.


Queue Length Clock Cycle Fuzzy Logic Controller Buffer Overflow Active Queue Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Braden, B., et al.: Recommendation on Queue Management and Congestion Avoidance in the Internet, RFC2309 (April 1998)Google Scholar
  2. 2.
    Wong, A.K.Y., Lin, W.W.K., Ip, M.T.W., Dillon, T.S.: Genetic Algo-rithm and PID Control Together for Dynamic Anticipative Marginal Buffer Management: An Effective Approach to Enhance Dependability and Performance for Distributed Mobile Object-Based Real-time Computing over the Internet. Journal of Parallel and Distributed Computing (JPDC) 62, 1433–1453 (2002)zbMATHCrossRefGoogle Scholar
  3. 3.
    Mitchell, E.: An Introduction to Genetic Algorithms. MIT Press, Cambridge (1999)Google Scholar
  4. 4.
    Wong, A.K.Y., Dillon, T.S.: A Fault-Tolerant Data Communication Setup to Improve Reliability and Performance for Internet-Based Distributed Applications. In: Proc. of the 1999 Pacific Rim International Symposium on Dependable Computing (PRDC 1999), Hong Kong SAR, December 1999, pp. 268–275 (1999)Google Scholar
  5. 5.
    M.T.W., Ip, W.W.K., Lin, A.K.Y., Wong, T.S.: An Adaptive Buffer Management Algorithm for Enhancing Dependability and Performance in Mobile-Object-Based Real-time Computing. In: Proc. of the IEEE ISORC 2001, Magden-burg, Germany, May 2001, pp. 138–144 (2001)Google Scholar
  6. 6.
    Mitsuru, O., Guenter, K., Kouichi, O.: IBM Aglets Specification (1998),
  7. 7.
    Tsybakov, B., Georganas, N.D.: Self-Similar Processes in Communications Networks. IEEE Transactions on Information Theory 44(5), 1713–1725 (1998)zbMATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Generator of Self-Similar Network Traffic,
  9. 9.
    Pareto DistributionGoogle Scholar
  10. 10.
  11. 11.
    Karagiannis, T., Faloutsos, M., Molle, M.: A User-friendly Self-similarity Analysis Tool. ACM SIGCOMM Computer Communication Review 33(3), 81–93 (2003), CrossRefGoogle Scholar
  12. 12.
    Molnar, S., Dang, T.D., Vidacs, A.: Heavy-Tailedness, Long-Range Dependence and Self-Similarity in Data Traffic. In: Proc. of the 7th Int’l Conference on Telecommunication Systems, Modelling and Analysis, Nashville, USA, pp. 18–21 (1999)Google Scholar
  13. 13.
    Intel’s VTune Performance Analyzer,

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Wilfred W. K. Lin
    • 1
  • Allan K. Y. Wong
    • 1
  • Tharam S. Dillon
    • 2
  1. 1.Department of ComputingThe Hong Kong Polytechnic UniversityKowloon, Hong Kong S.A.R.P.R.C.
  2. 2.Faculty of Information TechnologyUniversity of Technology SydneySydneyAustralia

Personalised recommendations