Designing fair flow fuzzy controller using genetic algorithm for computer networks

ABSTRACT

To utilize the link bandwidth efficiently in network, F.P.Kelly proposed the classic optimal model using utility function, which can converge to proportional fair point with asymptotic stability. However, the primal algorithm of Kelly model leads to the packet accumulation in the queue of the bottleneck link. By using heuristic fuzzy rules, this paper designs a fuzzy controller to adjust the additive increase parameter of the primal algorithm dynamically. Then genetic algorithm is used to optimize the scaling gains of the fuzzy controller, which is called GA-based fuzzy controller in this paper. The primal algorithm with the GA-based fuzzy controller can avoid the packet accumulation and keep the fairness and asymptotical stability. Thus it improves the performance of the primal algorithm.

REFERENCES

• 1: Fernando Paganini , Zhikui Wang , John C. Doyle , Steven H. Low, Congestion control for high performance, stability, and fairness in general networks, IEEE/ACM Transactions on Networking (TON), v.13 n.1, p.43-56, February 2005 [doi>10.1109/TNET.2004.842216]
• 2: Yueping Zhang , Seong-Ryong Kang , Dmitri Loguinov, Delayed stability and performance of distributed congestion control, Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications, August 30-September 03, 2004, Portland, Oregon, USA
• 3: K. Kar, S. Sarkar, and L. Tassiulas, "A Simple Rate Control Algorithm for Maximizing Total User Utility," IEEE INFOCOM, April 2001.
• 4: Srisankar Kunniyur , R. Srikant, End-to-end congestion control schemes: utility functions, random losses and ECN marks, IEEE/ACM Transactions on Networking (TON), v.11 n.5, p.689-702, October 2003 [doi>10.1109/TNET.2003.818183]
• 5: Ramesh Johari , David Kim Hong Tan, End-to-end congestion control for the internet: delays and stability, IEEE/ACM Transactions on Networking (TON), v.9 n.6, p.818-832, December 2001 [doi>10.1109/90.974534]
• 6: K. Kar, S. Sarkar, and L. Tassiulas, "A Simple Rate Control Algorithm for Maximizing Total User Utility," IEEE INFOCOM, April 2001.
• 7: C.W. Tao and J. S. Taur, "Design of fuzzy controllers with adaptive rule insertion," IEEE Trans. System, Man, Cybernetic, vol. SMC--29, no. 3, pp.389--397, Jun. 1999.
• 8: W. J. Wang and H. R. Lin, "Fuzzy control design for the trajectory tracking on uncertain nonlinear systems," IEEE Trans. Fuzzy Systems, vol.7, no. 1, pp. 53--62, Feb. 1999.
• 9: Y. Y. Cao and P. M. Frank, "Analysis and synthesis of nonlinear time delay systems via fuzzy control approach," IEEE Trans. Fuzzy Systems., vol.8, no. 2, pp. 200--211, Apr. 2000.
• 10: F. H. Hsiao, J. D. Hwang, C. W. Chen and Z. R. Tsai, "Robust stabilization of nonlinear multiple time-delay large-scale systems via decentralized fuzzy control," IEEE Trans. Fuzzy Systems, Vol 1.13, pp 152--163,Feb 2005.
• 11: B. R. Barmish, New Tools for Robustness of Linear Systems. New York: McMillan, 1994.
• 12: G. Feng , S. G. Cao , N. W. Rees , C. K. Chak, Design of fuzzy control systems with guaranteed stability, Fuzzy Sets and Systems, v.85 n.1, p.1-10, Jan. 1, 1997 [doi>10.1016/0165-0114(95)00375-4]
• 13: F. P. Kelly, A. K. Maulloo, and D. K. H. Tan, "Rate Control for Communication Networks: Shadow Prices, Proportional Fairness and Stability," Journal of the Operational Research Society, 49(3):237--252, March 1998.
• 14: F. P. Kelly, "Charging and Rate Control for Elastic Traffic," European Transactions on Telecommunications. 8(1):33--37, January 1997.
• 15: M. Gaid, A. Cela and Y. Hamam "Optimal integrated control and scheduling of networked control systems with communication constraints: application to a car suspension system," IEEE Transactions on Control Systems Technology, Vol 4.14 pp.776 -- 787, July 2006.
• 16: J. W. Lee, C. Mung and A. R. Calderbank, "Price-based distributed algorithms for rate-reliability tradeoff in network utility maximization," IEEE Journal on Selected Areas in Communications Vol 5.24, pp.962 -- 976, May 2006.
• 17: C. H. Chou, "Genetic algorithm--based optimal fuzzy controller design in the linguistic space," IEEE Transactions on Fuzzy Systems, Vol 3.14, pp.372 -- 385, June 2006.
• 18: Thomas Back , David B. Fogel , Zbigniew Michalewicz, Handbook of Evolutionary Computation, IOP Publishing Ltd., Bristol, UK, 1997
• 19: John R. Koza, Genetic programming: on the programming of computers by means of natural selection, MIT Press, Cambridge, MA, 1992
• 20: P. J. Fleming and R. C. Purshouse, "Evolutionary algorithms in control systems engineering: a survey," Control Eng. Pract., vol. 10, pp. 1223--1241, 2002.
• 21: P. T. Chan , W. F. Xie , A. B. Rad, Tuning of fuzzy controller for an open-loop unstable system: a genetic approach, Fuzzy Sets and Systems, v.111 n.2, p.137-152, April 2000 [doi>10.1016/S0165-0114(98)00044-X]
• 22: F. Hoffmann, "Evolutionary algorithms for fuzzy control system design," Proc. IEEE, vol. 89, no. 9, pp. 1318--1333, Sep. 2001.
• 23: C. H. Chou, "Optimal parametric fuzzy controller design by genetic algorithms," in Proc. IASTED Int. Conf. on Applied Modelling and Simulation, 1998, pp. 352--356.
• 24: Zbigniew Michalewicz, Genetic algorithms + data structures = evolution programs (2nd, extended ed.), Springer-Verlag New York, Inc., New York, NY, 1994
• 25: Joines J. and Houck C, "On the use of non-stationary penalty functions to solve constrained optimization problems with genetic algorithm," IEEE International Symposium Evolutionary Computation, Orlando,Fl, pp 579--584.1994.

INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.2 Network Protocols

General Terms:
Algorithms, Design, Experimentation, Performance, Theory

Keywords:
congestion control, fairness, fuzzy control, genetic algorithm