01479nas a2200145   4500008004100000245006200041210006200103300001600165520096300181100002101144700002301165700001901188700001601207856011001223       2003                        eng d00aCompetitive Video on Demand Schedulers for Popular Movies0 aCompetitive Video on Demand Schedulers for Popular Movies  aPP. 49 - 613 a<p>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 noti- 4cation. 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 knownschemes inpractical situations. Infact, 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 the same asymptotic competitive ratio.</p>
1 aBouras, Christos1 aKapoulas, Vaggelis1 aSpirakis, Paul1 aPantziou, G  uhttp://telematics.upatras.gr/telematics/publications/competitive-video-demand-schedulers-popular-movies-001476nas a2200145   4500008004100000245006200041210006200103260001700165520096100182100002101143700002301164700001901187700001601206856010801222       1997                        eng d00aCompetitive Video on Demand Schedulers for Popular Movies0 aCompetitive Video on Demand Schedulers for Popular Movies  c11 - 12 July3 a<p>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 notication. 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.</p>
1 aBouras, Christos1 aKapoulas, Vaggelis1 aSpirakis, Paul1 aPantziou, G  uhttp://telematics.upatras.gr/telematics/publications/competitive-video-demand-schedulers-popular-movies00432nas a2200133   4500008004100000245004000041210004000081300000800121100002100129700002300150700001900173700001600192856009000208       1996                        eng d00aRandomized adaptive video on demand0 aRandomized adaptive video on demand  a1791 aBouras, Christos1 aKapoulas, Vaggelis1 aSpirakis, Paul1 aPantziou, G  uhttp://telematics.upatras.gr/telematics/publications/randomized-adaptive-video-demand