An adaptive fuzzy model using orthonormal basis functions based on multifractal characteristics applied to network traffic control

被引:8
作者
Vieira, F. H. T. [1 ]
Rocha, F. G. C. [1 ]
机构
[1] Univ Fed Goias, Sch Elect & Comp Engn EEEC, BR-74605010 Goiania, Go, Brazil
关键词
Fuzzy model; Orthonormal basis functions; Adaptive learning; Congestion control; Multifractal traffic; TIME VBR VIDEO; CONGESTION CONTROL; SERVICE; IDENTIFICATION; PERFORMANCE; PREDICTION; ALGORITHM; SYSTEMS; LOGIC;
D O I
10.1016/j.neucom.2010.07.038
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
In this paper, we present an adaptive predictive orthonormal basis functions (OBF)-fuzzy model that considers the multifractal behavior of network traffic flows. To this end, we model the traffic flows using orthonormal basis functions obtained through multifractal analysis. We insert the orthonormal basis functions into a fuzzy model trained with an adaptive clustering algorithm. Further, we propose a predictive flow control scheme for broadband networks. Also, using the fuzzy model parameters, we derive an expression for the optimal traffic source rate. Comparisons to other predictive control schemes prove the efficiency of the proposed adaptive OBF-fuzzy based control and training algorithm. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:1894 / 1907
页数:14
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