Adaptive wavelet neural network controller for AQM router in TCP network

Jae Man Kim; Jin Bae Park; Yoon Ho Choi

doi:10.1109/MICAI.2006.6

Adaptive wavelet neural network controller for AQM router in TCP network

Jae Man Kim, Jin Bae Park, Yoon Ho Choi

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006
Pages	388-397
Number of pages	10
DOIs	https://doi.org/10.1109/MICAI.2006.6
Publication status	Published - 2006
Event	5th Mexican International Conference on Artificial Intelligence, MICAI 2006 - Apizaco, Mexico Duration: 2006 Nov 13 → 2006 Nov 17

Publication series

Name	Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006

Other

Other	5th Mexican International Conference on Artificial Intelligence, MICAI 2006
Country	Mexico
City	Apizaco
Period	06/11/13 → 06/11/17

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Software

Access to Document

10.1109/MICAI.2006.6

Fingerprint Dive into the research topics of 'Adaptive wavelet neural network controller for AQM router in TCP network'. Together they form a unique fingerprint.

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

@inproceedings{7784d3d76361408d8135321228ea1531,

title = "Adaptive wavelet neural network controller for AQM router in TCP network",

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.",

author = "Kim, {Jae Man} and Park, {Jin Bae} and Choi, {Yoon Ho}",

year = "2006",

doi = "10.1109/MICAI.2006.6",

language = "English",

isbn = "0769527221",

series = "Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006",

pages = "388--397",

booktitle = "Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006",

note = "5th Mexican International Conference on Artificial Intelligence, MICAI 2006 ; Conference date: 13-11-2006 Through 17-11-2006",

}

Kim, JM, Park, JB & Choi, YH 2006, Adaptive wavelet neural network controller for AQM router in TCP network. in Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006., 4022173, Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006, pp. 388-397, 5th Mexican International Conference on Artificial Intelligence, MICAI 2006, Apizaco, Mexico, 06/11/13. https://doi.org/10.1109/MICAI.2006.6

Adaptive wavelet neural network controller for AQM router in TCP network. / Kim, Jae Man; Park, Jin Bae; Choi, Yoon Ho.

Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006. 2006. p. 388-397 4022173 (Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Adaptive wavelet neural network controller for AQM router in TCP network

AU - Kim, Jae Man

AU - Park, Jin Bae

AU - Choi, Yoon Ho

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=34547691157&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34547691157&partnerID=8YFLogxK

U2 - 10.1109/MICAI.2006.6

DO - 10.1109/MICAI.2006.6

M3 - Conference contribution

AN - SCOPUS:34547691157

SN - 0769527221

SN - 9780769527222

T3 - Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006

SP - 388

EP - 397

BT - Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006

T2 - 5th Mexican International Conference on Artificial Intelligence, MICAI 2006

Y2 - 13 November 2006 through 17 November 2006

ER -

Adaptive wavelet neural network controller for AQM router in TCP network

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Cite this