Title :
A Genetic Based Fuzzy Markov Game Flow Controller for High-speed Networks
Author :
Li, Xin ; Yu, Haibin
Author_Institution :
Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang, China
Abstract :
For the congestion problems in high-speed networks, a genetic based fuzzy Markov game flow controller (GFMC) is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for high-speed networks. In this case, the fuzzy Markov game, which is independent of mathematic model, and prior-knowledge, has good performance. It offers a promising platform for robust control in the presence of the bounded external disturbances. The genetic operators are used to obtain the consequent parts of fuzzy rules. Simulation results show that the proposed controller can learn to take the best action to regulate source flow with the features of high throughput and low packet loss ratio, and can avoid the occurrence of congestion effectively.
Keywords :
Markov processes; flow control; fuzzy control; robust control; time-varying systems; bounded external disturbances; genetic based fuzzy markov game flow controller; high-speed networks; robust control; Delay; Games; Genetics; High-speed networks; Loading; Markov processes; Throughput; Markov game; flow control; high-speed network;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2011 Third International Conference on
Conference_Location :
Shangshai
Print_ISBN :
978-1-4244-9010-3
DOI :
10.1109/ICMTMA.2011.21