Neural network-based ATM QoS estimation
W. Sheng, Javier Martín Rueda, David C. Blight · 2002
A key technology for the B-ISDN is asynchronous transfer mode (ATM). ATM traffic management or congestion control is needed to guarantee the quality of service (QoS) parameters. A neural network-based QoS estimation is presented to enhance the performance in ATM management so that the service-providers can offer better services to their users. Several methods such as learning vector quantization (LVQ) and self-organizing map (SM) are used to estimate the QoS levels.