Dynamic resource allocation via video content and short-term traffic statistics

The reliable and efficient transmission of high-quality variable bit rate (VBR) video through the Internet generally requires network resources be allocated in a dynamic fashion. This includes the determination of when to renegotiate for network resources, as well as how much to request at a given time. The accuracy of any resource request method depends critically on its prediction of future traffic patterns. Such a prediction can be performed using the content and traffic information of short video segments. This paper presents a systematic approach to select the best features for prediction, indicating that while content is important in predicting the bandwidth of a video hit stream, the use of both content and available short-term bandwidth statistics can yield significant improvements. A new framework for traffic prediction is proposed in this paper; experimental results show a smaller mean-square resource prediction error and higher overall link utilization.