Adaptive wavelet neural network controller for AQM router in TCP network

Jae Man Kim, Jin Bae Park, Yoon Ho Choi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper presents a wavelet neural network (WNN) controller based on adaptive learning rates (ALRs) method, for active queue management(AQM) in end-to-end TCP network. The AQM is important to regulate the queue length and short round trip time in TCP network. The WNN controller using ALRs adaptively controls the dropping probability of the TCP network. Also the proposed controller is intelligently trained by GD algorithm. The parameters of WNN are tuned by ALRs method. We apply Lyapunov theorem to verify the stability of WNN controller using ALRs. The simulation results show that the performance of WNN controller using ALRs is superior to that of WNN controller using fixed learning rates.

Original languageEnglish
Title of host publicationProceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006
Pages388-397
Number of pages10
DOIs
Publication statusPublished - 2006 Dec 1
Event5th Mexican International Conference on Artificial Intelligence, MICAI 2006 - Apizaco, Mexico
Duration: 2006 Nov 132006 Nov 17

Publication series

NameProceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006

Other

Other5th Mexican International Conference on Artificial Intelligence, MICAI 2006
CountryMexico
CityApizaco
Period06/11/1306/11/17

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software

Cite this

Kim, J. M., Park, J. B., & Choi, Y. H. (2006). Adaptive wavelet neural network controller for AQM router in TCP network. In Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006 (pp. 388-397). [4022173] (Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006). https://doi.org/10.1109/MICAI.2006.6