Chaotic neural network method to control ATM traffic

Author

Yu, Zhang ; Junli, Zheng ; Wenxia, Chen

Author_Institution

Dept. of Electron. Eng., Tsinghua Univ., Beijing, China

fYear

1998

fDate

22-24 Oct 1998

Firstpage

429

Abstract

A chaotic neural network method is set forth to model and predict videoconference VBR traffic. The chaotic theory is employed to analyze the data and a neural network is used to model and predict the traffic. Based on the prediction of the VBR traffic, we estimate the available bandwidth and feed back explicit rate (ER) to the ABR source to control ABR traffic with VBR traffic background. The simulation results showed that the performance of the network is greatly improved with ER estimation via the chaotic neural network method

Keywords

asynchronous transfer mode; chaos; neural nets; telecommunication computing; telecommunication congestion control; telecommunication traffic; teleconferencing; ATM traffic control; available bandwidth estimation; chaotic neural network method; chaotic theory; data analysis; explicit rate estimation; network performance; simulation results; variable bit rate; videoconference VBR traffic; Bandwidth; Chaos; Communication system traffic control; Data analysis; Erbium; Feeds; Neural networks; Predictive models; Traffic control; Videoconference;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Technology Proceedings, 1998. ICCT '98. 1998 International Conference on

Conference_Location

Beijing

Print_ISBN

7-80090-827-5

Type

conf

DOI

10.1109/ICCT.1998.743279

Filename

743279