DocumentCode :
2682366
Title :
Model Predictive Neural Control of TCP Flow in AQM Network
Author :
Rahnamai, Kourosh ; Gorman, Kevin ; Gray, Andrew
Author_Institution :
Dept. of Electr. Eng., Western New England Coll., Springfield, MA
fYear :
2006
fDate :
3-6 June 2006
Firstpage :
493
Lastpage :
498
Abstract :
Many research papers have been published on RED (random early detection) and variants of RED. Recently many articles have been presented on modeling a transmission control protocol (TCP) flow in an active queue management (AQM) of a bottlenecked network link (Dong Lin and R. Morris, 1997), (V. Misra, et al., 2000), (C. Hollot, et al., 2001). Classical control theories have also been applied to achieve or improve stability of the network flow (C. Hollot, et al., 2001). In this paper we present a neural network (NN) model predictive control (MPC) of TCP flows. We show the robust adaptive behavior of the MPC optimal controller under modeling errors and system dynamic changes. We also show the superior transient and steady state behavior as well as general stability of MPC as compared to the classical PI controller
Keywords :
computer networks; neurocontrollers; predictive control; stability; telecommunication congestion control; transport protocols; AQM network; TCP flow; active queue management; neural network model predictive control; random early detection; stability; transmission control protocol; Adaptive control; Control theory; Neural networks; Optimal control; Predictive control; Predictive models; Programmable control; Protocols; Robust control; Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society, 2006. NAFIPS 2006. Annual meeting of the North American
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0363-4
Electronic_ISBN :
1-4244-0363-4
Type :
conf
DOI :
10.1109/NAFIPS.2006.365459
Filename :
4216852
Link To Document :
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