Enhancement of TCP over wired/wireless networks with packet loss classifiers inferred by supervised learning

TCP is suboptimal in heterogeneous wired/wireless networks because it reacts in the same way to losses due to congestion and losses due to link errors. In this paper, we propose to improve TCP performance in wired/wireless networks by endowing it with a classifier that can distinguish packet loss causes. In contrast to other proposals we do not change TCP’s congestion control nor TCP’s error recovery. A packet loss whose cause is classified as link error will simply be ignored by TCP’s congestion control and recovered as usual, while a packet loss classified as congestion loss will trigger both mechanisms as usual. To build our classification algorithm, a database of pre-classified losses is gathered by simulating a large set of random network conditions, and classification models are automatically built from this database by using supervised learning methods. Several learning algorithms are compared for this task. Our simulations of different scenarios show that adding such a classifier to TCP can improve the throughput of TCP substantially in wired/wireless networks without compromizing TCP-friendliness in both wired and wireless environments.