Competitive Video on Demand Schedulers for Popular Movies

In this paper we investigate the online video on demand problem, namely having to accept or reject a request for a movie without knowing the future requests. We present online movie-scheduling schemes that implement the principles of refusal by choice and delayed notication. A novel way to schedule movies that exploits the knowledge of the distribution of the preference of requests for movies, is shown to have a competitive ratio that outperforms all the previously known schemes in practical situations. In fact, our scheduler has a competitive ratio bounded above by a constant, independent of the number of the users, channels, or movies, in the case that a large fraction of the requests tends to concentrate in a small number of movies. We extend our approach by presenting an \adaptive" randomized scheduler which initially is not aware of the movie popularities but it adapts to it, and achieves a similar asymptotic competitive ratio.