Title :
Applying Neural Network to Improve TCP Performance over Distributed Spaceflight TT&C Networks
Author :
Gong, Changqing ; Meng, Qingjie ; Zhao, Linna ; Bi, Xiaoxia
Author_Institution :
Shenyang Inst. of Aeronaut. Eng., Shenyang
Abstract :
A backpropagation neural network classifier is presented, which can classify packet loss cause over TT&C (tracking, telemetry, and command) networks. In TT&C networks, there are many packet losses are due to link errors, but not due to network congestions; and then TCP often reduces its data rate mistakenly, cannot keep a reasonable data rate. Based on the packet loss classifier, TCP-BP algorithm is proposed. The result of our simulation shows that the TCP-BP algorithm is superior to Vegas and Reno algorithm.
Keywords :
backpropagation; neural nets; packet radio networks; space communication links; telemetry; transport protocols; TCP performance; TT&C networks; backpropagation neural network classifier; command networks; distributed spaceflight; link errors; packet loss classifier; telemetry networks; tracking networks; Aerospace engineering; Backpropagation algorithms; Computer networks; Distributed computing; Educational institutions; Input variables; Neural networks; Protocols; Satellites; Vibration measurement;
Conference_Titel :
Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-0737-8
Electronic_ISBN :
978-1-4244-0737-8
DOI :
10.1109/ICIEA.2007.4318553
