Abstract
In this paper we present a hybrid ICA-fuzzy adaptive algorithm for traffic flow separation and control in contemporary computer networks. Our approach is composed by an ICA Block corresponding to the gradient algorithm proposed by Bell and Sejnowski for the information maximization at the output of a neural network as well as a Fuzzy Control System Block. The ICA algorithm is used to separate the controllable to the non-controllable network traffic sources. Additionally, we developed a predictive fuzzy controller following the Takagi and Sugeno fuzzy modeling. The combination of blind separation and control algorithm is applied to real network traffic traces. Finally, we verify that the proposed ICA-fuzzy adaptive control algorithm yields prominent control performances for single buffer server network environments.
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Vieira, F.H.T., Sousa, L.M.C., Bozinis, G.E., de Miranda, W.F., Cavalcante, C.C. (2009). Network Traffic Flow Separation and Control Through a Hybrid ICA-Fuzzy Adaptive Algorithm. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00599-2_91
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DOI: https://doi.org/10.1007/978-3-642-00599-2_91
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00598-5
Online ISBN: 978-3-642-00599-2
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