We propose a fuzzy logic-based control scheme for real-time motion picture expert group (MPEG) video to avoid long delay or excessive loss at the user-network interface (UNI) in an asynchronous transfer mode (ATM) network. The system consists of a shaper whose role is to smooth the MPEG output traffic to reduce the burstiness of the video stream. The input and output rates of the shaper buffer are controlled by two fuzzy logic-based controllers. To avoid a long delay at the shaper, the first controller aims to tune the output rate of the shaper in the video frame time scale based on the number of available transmission credits at the UNI and the occupancy of the shaper's buffer. Based on the average occupancy of the shaper's buffer and its variance, the second controller tunes the input rate to the shaper over a much larger time scale by applying a closed-loop MPEG encoding scheme. With this approach, the traffic enters the network at an almost constant bit rate (with a very small variation) allowing simple network management functions such as admission control and bandwidth allocation, while guaranteeing a relatively constant video quality since the encoding rate is changed only in critical periods when the shaper buffer "threatens" to overflow. The performance of the proposed scheme is evaluated through numerical tests on real video sequences.

An important parameter in asynchronous transfer model (ATM)-based network design and management is the cell loss ratio (CLR) in ATM multiplexers. It is a key parameter to many vital functions in the network such as call admission control (CAC), bandwidth allocation, etc. However, the CLR depends usually on many unknown and unpredictable traffic parameters such as input traffic correlations. In this paper, we propose a simple and robust fuzzy-based algorithm to predict the CLR in large-sized systems based on both a small amount of information from small-sized systems, and the asymptotic behavior for very large systems. Unlike the model-based approaches, our approximation avoids the problem of assuming any traffic parameters or arrival process. This algorithm is used with real-time traffic measurement to propose an effective measurement-based call admission control framework for ATM networks.