Scalable On-Demand Streaming of Nonlinear Media

A conventional video file contains a single temporally-ordered sequence of video frames. Clients requesting on-demand streaming of such a file receive (all or intervals of) the same content. For popular files that receive many requests during a file playback time, scalable streaming protocols based on multicast or broadcast have been devised. Such protocols require server and network bandwidth that grow much slower than linearly with the file request rate. This paper considers ldquononlinearrdquo video content in which there are parallel sequences of frames. Clients dynamically select which branch of the video they wish to follow, sufficiently ahead of each branch point so as to allow the video to be delivered without jitter. An example might be ldquochoose-your-own-endingrdquo movies. With traditional scalable delivery architectures such as movie theaters or TV broadcasting, such personalization of the delivered video content is very difficult or impossible. It becomes feasible, in principle at least, when the video is streamed to individual clients over a network. For on-demand streaming of nonlinear media, this paper analyzes the minimal server bandwidth requirements, and proposes and evaluates practical scalable delivery protocols.