A Resource Management Framework Based on the Many Sources Asymptotic for Video-on-Demand Servers

This paper proposes a framework for admission control of pre-stored video streams, which provide deterministic guarantees on the maximum delay of video traffic and increase the network resource utilization. The framework take advantage of the fact that video streams can be processed off-line to calculate the space and time parameters in order to estimate its effective bandwidth under the many sources asymptotic regime. To bypass the traffic prediction problem, since the off-line estimation does not capture the exact dynamics of the video stream in the time domain, the link is divided into several virtual links, where only streams with same content are multiplexed (group multiplexing approach). The efficiency of the model is analyzed and compared with the deterministic approach. It achieves accuracy and high channel utilization.