Generalized end-to-end performance estimation of ATM networks using combined simulation model and neural network

Without the practical design method that guarantees every users´ specified quality of service, ATM technology can not be the solution for building a public wide-area broadband integrated services network. In this paper, we propose a generalized and light-weight computational method to estimate the end-to-end performance of an ATM network. Degradation of quality of service at the terminating node is analyzed in view of the dynamics of the switching network and a neural network model for identifying the characteristics of outgoing traffic in a single switching node is suggested. The proposed ATM network design procedure to combine the simulation model and neural network model is easily adaptable and reusable