DocumentCode :
2201853
Title :
Optimal linear quadratic controller based on genetic algorithm for TCP/AQM router
Author :
Al-Faiz, Mohammed Zeki ; Sabry, Sana Sabah
Author_Institution :
Comput. Eng. Dept., Al-Nahrain Univ., Baghdad, Iraq
fYear :
2012
fDate :
2-5 April 2012
Firstpage :
78
Lastpage :
83
Abstract :
As an effective mechanism acting on the intermediate nodes to support end-to-end congestion control, Active Queue Management (AQM) takes a trade-off between link utilization and delay experienced by data packets. In this paper a linear quadratic optimal controller was designed based on linear control theory for TCP/AQM router. The design specifications, depends on choosing weighting matrices Q and R. One must carry out a trial- and- error process to choose the weighting matrices that can satisfy the design specifications. To overcome this difficulty we employ the Genetic Algorithm (GA) to find the proper weighting matrices. This idea gives a new alternative procedure in time varying feedback control to improve the stability performance. The controller simulation results show the efficiency of the proposed controller.
Keywords :
feedback; genetic algorithms; linear quadratic control; optimal control; telecommunication control; telecommunication network management; telecommunication network routing; time-varying systems; TCP/AQM router; active queue management; controller simulation; delay; end-to-end congestion control; genetic algorithm; link utilization; optimal linear quadratic controller; stability performance; time varying feedback control; trial-and-error process; Control theory; Equations; Genetic algorithms; Internet; Mathematical model; Optimal control; AQM router; Congestion Control; Genetic algorithm; linear quadratic optimal control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Future Communication Networks (ICFCN), 2012 International Conference on
Conference_Location :
Baghdad
Print_ISBN :
978-1-4673-0261-6
Electronic_ISBN :
978-1-4673-0259-3
Type :
conf
DOI :
10.1109/ICFCN.2012.6206877
Filename :
6206877
Link To Document :
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