Policing function in ATM network using multi-layer neural network

Artificial neural networks provide an attractive alternative in performing the policing function at the user network interface (UNI) of an asynchronous transfer mode (ATM) network. In order to guarantee quality of service (QOS) for the established connections in ATM networks, one of the policing functions at the UNI is to ensure that all data streams entering the ATM network conform to the allocated bandwidth, or otherwise the cell loss priority (CLP) bit in the ATM cell header must be set to reflect the situation that the output of the UNI has exceeded the permissible bandwidth. Feed-forward neural networks with back-propagation learning algorithms are chosen to perform the policing function at the UNI. Numerical results are presented to illustrate that the neural network is capable of performing the policing function