TCP - IP White Papers
A Machine Learning Approach to Improve Congestion Control Over Wireless Computer Networks
Overview This paper presents the application of machine learning techniques to the improvement of the congestion control of TCP in wired/wireless networks. TCP is suboptimal in hybrid wired/wireless networks because it reacts in the same way to losses due to congestion and losses due to link errors. The paper thus proposes to use machine learning techniques to build automatically a loss classifier from a database obtained by simulations of random network topologies. For this classifier to be useful in this application, it should satisfy both a computational constraint and a time varying constraint on its misclassification rate on congestion losses. Several machine learning algorithms are compared with these two constraints in mind. The best method for this application appears to be decision tree boosting.
| Publisher | University of Liege | File Format | |
|---|---|---|---|
| Date Published | January 2007 | ||
| Format | White Papers | ||
| Topics | |||
-
Did you find this white paper useful? 1 out of 1 users found this white paper useful
White Paper RSS
Download
Register
