Title :
Neural networks for adaptive traffic control in ATM networks
Author :
Nordström, Ernst ; Carlström, Jakob ; Gällmo, Olle ; Asplund, Lars
Author_Institution :
Uppsala Univ., Sweden
fDate :
10/1/1995 12:00:00 AM
Abstract :
Neural networks (NNs) have several valuable properties for implementing ATM traffic control. The authors present NN-based solutions for two problems arising in connection admission control, affecting the grade of service (GOS) at both the cell and call levels, and propose that neural networks may increase the network throughput and revenue
Keywords :
adaptive control; asynchronous transfer mode; channel capacity; neural nets; telecommunication computing; telecommunication congestion control; telecommunication network routing; telecommunication traffic; ATM networks; GOS; adaptive traffic control; connection admission control; learning; link allocation; network throughput; neural networks; revenue; routing; Adaptive control; Adaptive systems; Asynchronous transfer mode; Communication switching; Communication system traffic control; Intelligent networks; Neural networks; Programmable control; Switches; Traffic control;
Journal_Title :
Communications Magazine, IEEE
