Video traffic modeling based on RBF networks

Author

Simin, Xiong ; Jinsong, Liang ; Zhimin, Yang ; Zhengming, Lei

Author_Institution

Dept. of Telecom. Eng., Chongqing Univ. of Posts & Telecom., China

fYear

1998

fDate

22-24 Oct 1998

Abstract

The basis of traffic and congestion control in the ATM network lies in the traffic modeling. Due to the variety of services and high transmitting speed, the traditional analytical methods become intractable. As an alternative, a radial basis function (RBF) neural network has been adopted for video traffic modeling. In this paper, an LBG algorithm based and Hestenes singular value decomposition (SVD) method has been proposed to select the centers of the hidden layer neuron and to calculate the weights of the output layer synapse in the RBF network. To evaluate the proposed approach, movie data have been utilized in several experiments

Keywords

asynchronous transfer mode; radial basis function networks; telecommunication congestion control; telecommunication networks; telecommunication traffic; visual communication; ATM network; LBG algorithm; RBF networks; RBF neural networks; SVD; congestion control; experiments; hidden layer neuron; output layer synapse weight; radial basis function; singular value decomposition; transmitting speed; video traffic modeling; Asynchronous transfer mode; B-ISDN; Communication system traffic control; Neural networks; Neurons; Predictive models; Quality of service; Radial basis function networks; Telecommunication traffic; Traffic control;

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.1998.741067

Filename

741067