Dynamic Resource Allocation Via Video Content and Short-term Traffic Statistics

The reliable and efficient transmission of high quality VBR video through the Internet generally requires network resources be allocated in a dynamic fashion. This includes the determination of when to re-negotiate 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 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 bitstream, the use of both content and available short-term bandwidth statistics can yield significant improvements. A new framework for tra#c prediction is proposed in this paper; experimental results show a smaller mean-square resource prediction error and higher overall link utilization