Title :
Using Neural Network Classifier of Packet Loss Causes to Improve TCP Congestion Control over Ad Hoc Networks
Author :
Changqing, Gong ; Linna, Zhao ; Xiaoyan, Wang
Author_Institution :
Coll.of Comput., Shenyang
Abstract :
A backpropagation neural network cIassifier is used for distinguishing network congestion and link error over ad hoc networks. TCP considers a 11 packet losses as network congestion, and reacts to such congestion by reducing its data rate. In ad hoc networks, there are many packet losses are due to Iink errors, but not due to network congestion; and then TCP often reduces its data rate mistakenly, cannot keep a reasonable data rate. Then we introduce an improvement TCP with a packet loss classifier, TCP-BP algorithm. The result of our simulation shows that the TCP-BP algorithm is superior to Vegas and TCP Westwood algorithm in TCP throughput.
Keywords :
ad hoc networks; backpropagation; neural nets; telecommunication congestion control; transport protocols; Iink errors; TCP congestion control; ad hoc networks; backpropagation neural network classifier; packet losses; transport control protocol; Ad hoc networks; Antennas and propagation; Communications technology; Electromagnetic compatibility; Microwave antennas; Microwave propagation; Microwave technology; Neural networks; Propagation losses; Wireless communication; ad hoc networks; congestion; neural network;
Conference_Titel :
Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2007 International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-1045-3
Electronic_ISBN :
978-1-4244-1045-3
DOI :
10.1109/MAPE.2007.4393599
