DocumentCode :
809093
Title :
A genetic algorithm for the design of a fuzzy controller for active queue management
Author :
Di Fatta, Giuseppe ; Hoffmann, Frank ; Re, Giuseppe Lo ; Urso, Alfonso
Author_Institution :
Ist. di Calcolo e Reti ad Alte Prestazioni, Consiglio Nazionale delle Ricerche, Palermo, Italy
Volume :
33
Issue :
3
fYear :
2003
Firstpage :
313
Lastpage :
324
Abstract :
Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design methodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented.
Keywords :
Internet; control system synthesis; fuzzy control; genetic algorithms; telecommunication congestion control; telecommunication network routing; two-term control; FPI controller design methodology; Internet routers; PI controller; active queue management; fuzzy controller; fuzzy proportional integral controller; genetic algorithm; network congestion; optimal disturbance rejection; random early detection; router queue management; tail drop; tuning; Algorithm design and analysis; Control systems; Delay; Fuzzy control; Genetic algorithms; Internet; Pi control; Propagation losses; Proportional control; Tail;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Publisher :
ieee
ISSN :
1094-6977
Type :
jour
DOI :
10.1109/TSMCC.2003.818946
Filename :
1238673
Link To Document :
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