Network Traffic Flow Separation and Control Through a Hybrid ICA-Fuzzy Adaptive Algorithm
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Modeling a multi-queue network node with a fuzzy predictor
Fuzzy Sets and Systems
Fuzzy qualitative trigonometry
International Journal of Approximate Reasoning
Information Sciences: an International Journal
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In order to exploit the nonlinear time-varying property of network traffic, the traffic flow from controlled sources is described by a fuzzy autoregressive moving-average model with auxiliary input (fuzzy ARMAX process), with the traffic flow from uncontrolled sources (i.e., cross traffic) being described as external disturbances. In order to overcome the difficulty of the transmission delay in the design of congestion control, the fuzzy traffic model is translated to an equivalent fuzzy predictive traffic model. A fuzzy adaptive flow control scheme is proposed to avoid congestion at high utilization while maintaining good quality of service. By use of fuzzy adaptive prediction technique, the difficulties in congestion control design due to nonlinearity, time-varying characteristics, and large propagation delay can be overcome by the proposed adaptive traffic control method. A comparative evaluation is also given to show the superiority of the proposed method.