An AR model based on a fuzzy approach for traffic modeling

Broadband integrated digital networks (B-ISDN) using an asynchronous transfer mode (ATM) is the new generation of ISDNs for telecommunication networks. An ATM is designed to support various classes of multimedia traffic flow (voice, data, and video) with different bit rate and quality of service (QoS) requirements. However, in actual networks, congestion and deadlock may occur due to some problem. An AMT provides various traffic controls to reduce congestion and to keep high quality networking such as connection admission control (CAC), usage parameter control (UPC), priority control (PC). These controls are essentially reactive-type control. For proactive control, future cell rate flowing into the ATM has to be predicted on the basis of the past and current traffic and control signal then generated using the predicted cell rate. We propose a traffic model by an autoregressive (AR) model based on fuzzy approach in this paper. Computational experiments were carried out to show usefulness of the proposed model. As a result of experiments, the proposed model shows better performance than that by previous models