Scheduling policies for an on-demand video server with batching
MULTIMEDIA '94 Proceedings of the second ACM international conference on Multimedia
Patching: a multicast technique for true video-on-demand services
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Optimal and efficient merging schedules for video-on-demand servers
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Competitive on-line stream merging algorithms for media-on-demand
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
An 5-competitive on-line scheduler for merging video streams
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
On Optimal Batching Policies for Video-on-Demand Storage Servers
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Supplying Instantaneous Video-on-Demand Services Using Controlled Multicast
ICMCS '99 Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02
| Hi-index | 0.00 |
Stream merging is a promising technique for reducing server bandwidth in video-on-demand systems. There are many heuristics for the problem proposed whose effectiveness has been confirmed empirically. However, it is desirable to prove their effectiveness mathematically. In the pioneering work [2], Bar-Noy and Ladner studied stream merging using competitive analysis. They designed an O(log n)-competitive online scheduler, where n is the totaln umber of stream requests. However, their result is applicable only to systems with large client bandwidth and buffer size. In this paper we design the first on-line scheduler for stream merging in the general setting, in which we lift the large resource requirements, and our scheduler achieves constant competitive ratio.