Synthetic traffic generation for streaming video to model IPTV

With the rapid development of access networks, Internet Protocol Television (IPTV) has become a popular streaming video delivery technology. However, streaming IPTV over a network is challenging as the data rate of a video streaming varies with scene, time, frame-rate, and encoding. As a result, it is important to evaluate the performance of an access network for IPTV traffic to ensure better experience for users. Using video traces for such evaluation requires different videos traces to represent different scenarios and needs slower I/O-based operations, such as file reading. To overcome these limitations, in this paper, we explore several aspects of modeling IPTV streaming and present a synthetic video trace generator that represents the IPTV streaming. Our analysis shows that our synthetic video trace follows the statistical properties of empirical videos and its resultant data rate is representative of the IPTV video streaming.