International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Lyapunov-based Fuzzy Queue Scheduling for Internet Routers

  • Cho, Hyun-Cheol (Dept. of Electrical Engineering, Dong-A University) ;
  • Fadali, M. Sami (Dept. of Electrical Engineering, Univ. of Nevada-Reno) ;
  • Lee, Jin-Woo (Dept. of Electrical Engineering, Dong-A University) ;
  • Lee, Young-Jin (Dept. of Avionics Electrical Eng., Korea Aviation Polytechnic) ;
  • Lee, Kwon-Soon (Dept. of Electrical Engineering, Dong-A University)
  • Published : 2007.06.30
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Abstract

Quality of Service (QoS) in the Internet depends on queuing and sophisticated scheduling in routers. In this paper, we address the issue of managing traffic flows with different priorities. In our reference model, incoming packets are first classified based on their priority, placed into different queues with different capacities, and then multiplexed onto one router link. The fuzzy nature of the information on Internet traffic makes this problem particularly suited to fuzzy methodologies. We propose a new solution that employs a fuzzy inference system to dynamically and efficiently schedule these priority queues. The fuzzy rules are derived to minimize the selected Lyapunov function. Simulation experiments show that the proposed fuzzy scheduling algorithm outperforms the popular Weighted Round Robin (WRR) queue scheduling mechanism.

Keywords

References

  1. S. Floyd, 'A report on recent developments in TCP congestion control,' IEEE Communications Magazine, vol. 39, no. 4, pp. 84-90, 2001 https://doi.org/10.1109/35.917508
  2. Z. Wang, Internet QoS: Architectures and Mechanisms for Quality of Service, Morgan Kaufmann Publishers, 2001
  3. J. Nagle, 'On packet switches with infinite storage,' IEEE Trans. on Communications, vol. 35, no. 4, pp. 435-438, 1987 https://doi.org/10.1109/TCOM.1987.1096782
  4. A. Demers, S. Keshav and S. Shenker, 'Analysis and simulation of a Fair-Queuing algorithm,' Proc. ACM SIGCOMM, pp. 1-12, 1989
  5. F. Risso and P. Gevros, 'Operational and performance issue of a CBQ router,' Computer Communication Review (ACM SIGCOMM), vol. 29, no. 5, pp. 47-58, 1999
  6. J. Joutsensalo, G. Gomzikov, and T. Hamalainen, 'Enhancing revenue maximization with adaptive WRR,' Proc. of the 8th IEEE Int. Symposium on Computers and Communication, vol. 1, pp. 175-180, 2003
  7. K. M. Passino and S. Yurkovich, Fuzzy Control, Addison-Wesley, 1998
  8. M. Margaliot and G. Langholz, New Approaches to Fuzzy Modeling and Control: Design and Analysis, World Scientific, 2000
  9. J. R. Perkins and P. R. Kumark, 'Stable, distributed, real-time scheduling of flexible manufacturing /assembly /disassembly systems,' IEEE Trans. on Automatic Control, vol. 34, no. 2, pp. 139-148, 1989 https://doi.org/10.1109/9.21085
  10. J.-J. E. Slotine and W. Li, Applied Nonlinear Control, Prentice Hall, 1991
  11. C. V. Hollot, V. Misra, D. Towsley, and W. Gong, 'Analysis and design of controllers for AQM routers supporting TCP flows,' IEEE Trans. on Automatic Control, vol. 47, no. 6, pp. 945-959, 2002 https://doi.org/10.1109/TAC.2002.1008360
  12. J.-S. R. Jang, C.-T. Sun, and E. Mizutani, Neurofuzzy and Soft Computing, Prentice Hall, 1997
  13. D. Bertsekas and R. Gallager, Data Networks, Prentice Hall, 1992