HTTP-based video streaming techniques have now been widely deployed to deliver video streams over communication networks. With these techniques, a video player can dynamically select a video stream from a set of pre-encoded representations of the video source based on its available bandwidth and viewport size. The bitrates of the encoded representations thus determine the video quality presented to viewers and also the averaged streaming bitrate which is highly related to streaming cost for massive video streaming platforms. Our work minimizes the average streaming bitrate on a per-chunk basis by modeling the probability that a player observes a particular representation. Since popularity of videos is regional, this paper exploits a further optimization that uses regional statistics of client bandwidth and viewport instead of the global statistics. Simulation results demonstrate that using regional statistics reduces streaming cost for low-bandwidth regions while improving the delivered quality for high-bandwidth regions compared to a baseline configuration that uses global statistics.
Media authentication is important in content delivery via untrusted intermediaries, such as peer-to-peer (P2P) file sharing. Many differently encoded versions of a media file might exist. Our previous work applied distributed source coding not only to distinguish the legitimate diversity of encoded images from tampering but also localize the tampered regions in an image already deemed to be inauthentic. The authentication data supplied to the
decoder consisted of a Slepian-Wolf encoded image projection.
We extend our scheme to authenticate cropped and resized images using an Expectation Maximization algorithm. Experimental results demonstrate that the proposed algorithm can distinguish legitimate encodings of authentic cropped and resized images from illegitimately modified versions using authentication data of less than 250 bytes.