Title :
Kohonen neural network based admission control in ATM telecommunication network
Author :
YiMing, Pi ; Zemin, Liu
Author_Institution :
Beijing Univ. of Posts & Telecommun., China
Abstract :
In this paper, based on the Kohonen neural network, we propose a new method for call admission control in an ATM network. It avoids the contradiction between accurate training and a large number of training data in a BP neural network. It not only has a fast learning convergence rate, but also provides a high utilization rate of the channel and assures the quality of service in the simulation
Keywords :
asynchronous transfer mode; backpropagation; self-organising feature maps; telecommunication channels; telecommunication congestion control; ATM telecommunication network; BP neural network; Kohonen neural network based admission control; call admission control; channel utilization rate; fast learning convergence rate; quality of services; simulation; training; Admission control; Asynchronous transfer mode; Bit rate; Call admission control; Communication system traffic control; Convergence; Intelligent networks; Neural networks; Quality of service; Traffic control; Training data;
Conference_Titel :
Communication Technology Proceedings, 1996. ICCT'96., 1996 International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-2916-3
DOI :
10.1109/ICCT.1996.545027
