A machine learning approach to improve congestion control over wireless computer networks
Geurts, P.; El Khayat, I.; Leduc, G.
Data Mining, 2004. ICDM apos;04. Fourth IEEE International Conference on
Volume , Issue , 1-4 Nov. 2004 Page(s): 383 - 386
Digital Object Identifier   10.1109/ICDM.2004.10063
Summary: In this paper, we present the application of machine learning techniques to the improvement of the congestion control of TCP in wired/wireless networks. TCP is sub-optimal in hybrid wired/wireless networks because it reacts in the same way to losses due to congestion and losses due to link errors. We thus propose to use machine learning techniques to build automatically a loss classifier from a database obtained by simulations of random network topologies. Several machine learning algorithms are compared for this task and the best method for this application turns out to be decision tree boosting. It outperforms ad hoc classifiers proposed in the networking literature.

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