A TRIAL MULTILAYER PERCEPTRON NEURAL NETWORK FOR ATM CONNECTION ADMISSION CONTROL

Abstract

Future broadband ATM networks are expected to accommodate various kinds of multi-media services with different traffic characteristics and quality of service (QOS) requirements. However, it is very difficult to control traffic by conventional mechanisms in this complex traffic environment. As an alternative approach, a multilayer perceptron neural network model is proposed as an intelligent control mechanism like ''a traffic control policeman'' in order to perform ATM connection admission control. This proposed neural control model is analyzed by computer simulations in a homogeneous and heterogeneous traffic environment and the result shows the effectiveness of this intelligent control mechanism, compared with that of an analytical method.