Dynamic resource allocation based on online traffic prediction for video streams

In this paper, we propose a new dynamic resource allocation (DRA) scheme to support the constantly increasing online video stream traffic, especially high definition (HD) video streams. Our DRA scheme is based on online traffic prediction using seasonal time analysis. Our scheme seeks to provide accurate traffic prediction, to minimize the resource negotiation frequency, and to increase the utilization of the network resources while meeting maximum delay requirements. We validate our approach using various video traces, including our video collection of more than 50 HD video traces. We show through our results that our proposed scheme achieve up to 19.8% improvement in allocating bandwidth for short-length video traces, and up to 25% for long traces compared to the variable step-size adaptive (VSA) algorithm.