Algorithm for ABR traffic control and formation feedback information

  • Authors:
  • Malrey Lee;Dong-Ju Im;Young Keun Lee;Jae-deuk Lee;Suwon Lee;Keun Kwang Lee;HeeJo Kang

  • Affiliations:
  • School of Electronics & Information Engineering, Chonbuk National University, ChonBuk, Korea;Department of Multimedia, Yosu National University;Department of Orthopedic Surgery, Chonbuk National University Hospital;Chosun College of Science & Technology, Korea;Kunsan National University;Dept of Skin Beauty Art, Naju Collage;Division of Computer & Multimedia Contents Engineering, Mokwon University

  • Venue:
  • ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part II
  • Year:
  • 2005

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Abstract

The feedback control method proposed in this paper predicts the queue length in the switch using the slope of queue length prediction function and queue length changes in time-series. The predicted congestion information is backward to the node. NLMS and neural network are used as the predictive control functions, and they are compared from performance on the queue length prediction. Simulation results show the efficiency of the proposed method compared to the feedback control method without the prediction. Therefore, we conclude that the efficient congestion and stability of the queue length controls are possible using the prediction scheme that can resolve the problems caused from the longer delays of the feedback information.