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A genetic algorithm for the design of a fuzzy controller for active queue management

By Giuseppe Di Fatta, F. Hoffmann, G. Lo Re and A. Urso

Abstract

Active queue management (AQM) policies are those\ud policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the\ud hosts on the network borders, and the adoption of a suitable control\ud policy. This paper proposes the adoption of a fuzzy proportional\ud integral (FPI) controller as an active queue manager for Internet\ud routers. The analytical design of the proposed FPI controller is\ud carried out in analogy with a proportional integral (PI) controller,\ud which recently has been proposed for AQM. A genetic algorithm is\ud proposed for tuning of the FPI controller parameters with respect\ud to optimal disturbance rejection. In the paper the FPI controller\ud design metodology is described and the results of the comparison\ud with random early detection (RED), tail drop, and PI controller\ud are presented

Publisher: IEEE
Year: 2003
OAI identifier: oai:centaur.reading.ac.uk:4496

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Citations

  1. (1996). A 5.26 mflips programmable analogue fuzzy logic controller in a standard cmos 2.4 technology,”
  2. (2001). A control theoretic analysis of RED,” in
  3. (2002). A fuzzy approach for the network congestion problem,” in
  4. (2001). A fuzzy buffer management scheme for ATM and IP networks,” in
  5. A Quantitative Measure of Fairness and Discrimination for Resource Allocation in Shared Computer Systems,”,
  6. (2002). A robust active queue management algorithm based on sliding mode variable structure control,” in
  7. (1999). A self-configuring RED gateway,” in
  8. (2000). A web server’s view of the transport layer,”
  9. (2001). Analysis and design of an adaptive virtual queue (AVQ) algorithm for active queue management,” in
  10. (2002). Analysis and design of controllers for RED routers supporting
  11. (2001). Congestion avoidance and control,” in
  12. (1996). Design and analysis of a fuzzy proportional-integral-derivative controller,”
  13. (2002). Design of a fuzzy controller for active queue management,”
  14. (1998). Design of a hybrid fuzzy logic proportional plus conventional integral-derivative controller,”
  15. (2001). Difficulties in simulating the internet,”
  16. (2002). Dynamics of TCP/RED and scalable control,” in
  17. (2001). Evolutionary algorithms for fuzzy control system design,”
  18. (1996). Evolutionary Algorithms in Theory and Practice.
  19. (1999). Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED,” in
  20. (1996). Genetic algorithms for automated tuning of fuzzy controllers: A transportation application,” in
  21. (1989). Genetic Algorithms in Search, Optimization,
  22. (2001). Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases. Singapore: World Scientific,
  23. (2002). Internet congestion control,”
  24. (2001). Method for designing pi-type fuzzy controllers for induction motor drives,”
  25. (2000). Modeling TCP rena performance: A simple model and its empirical validation,”
  26. (1994). New design and stability analysis of fuzzy proportional-derivative control system,”
  27. (2001). On designing improved controllers for AQM routers supporting TCP flows,” in
  28. (1986). Optimization of control parameters for genetic algorithms,”
  29. (2000). Parallel structure and tuning of a fuzzy PID controller,”
  30. (1993). Random early detection gateways for congestion avoidance,”
  31. (1999). Reasons not to deploy RED,” in
  32. (1998). Recommendations on queue management and congestion avoidance in the Internet,”
  33. (2000). RED behavior with different packet sizes,” in
  34. (1999). Refined design of random early detection gateways,” in
  35. (2001). REM: Active queue management,”
  36. (1999). SRED: stabilized RED,” in
  37. (2002). The BLUE active queue management algorithms,”
  38. (2002). The Design of Innovation: Lessons from and for Competent Genetic Algorithms.
  39. (2001). The war between mice and elephants,” in
  40. (2000). Trends in wide area IP traffic patterns: A view from ames internet exchange,” in
  41. (1995). Wide area traffic: The failure of poisson modeling,”

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