High-bandwidth and real-time constraints for supporting concurrent video accesses make generic software architecture design for high-performance on-demand video servers challenging. This challenging task can be even more complicated when we consider that a generic software architecture should be applied to different hardware platforms. In this paper, we introduce the design, implementation, and evaluation of a generic software architecture for on-demand video servers. We describe different key components on controlling the storage and network devices within the server. The interactive collaborations between these software components are also illustrated. The experimental results indicate a very promising direction on exploring the right combinations of these software components. The server is, thus, able to increase the number of concurrent video accesses with the same hardware configuration. For instance, with the right combinations, the system achieved about 80 percent of the storage system bandwidth of four disks, about 70 percent of the storage system bandwidth of six disks, and generally reached the maximal achieved SCSI bandwidth when eight disks are used over two SCSI buses (i.e., four disks on each SCSI bus). Our research and experimental results are based on video servers currently under construction across a variety of hardware platforms, including SMP, DMP, and clusters of PC or workstations. The most-advanced prototype server is based on an SGI shared-memory multiprocessor with a mass storage system consisting of RAID-3 disk arrays. With all the enabling/management schemes, we were able to further investigate interesting research issues by considering the user's access profiles for taking advantage of popular video titles. The results were significant, with a range of 60 percent improvement given a 512 Kbyte block size. In addition to the experimental results, theoretical performance models were also developed that closely match to our collected experimental results.
|Original language||English (US)|
|Number of pages||19|
|Journal||IEEE Transactions on Knowledge and Data Engineering|
|State||Published - 1999|
Bibliographical noteFunding Information:
This work is supported, in part, by the Advanced Research Projects Agency (ARPA) through AFB Contract No. F19628-94-C-0044; by the National Science Foundation under Grants No. CDA-9502979, No. CDA-9414015, and No. CDA-9422044; and by a gift from IBM. The Distributed Multimedia Research Center (DMRC) is sponsored by U.S. West, Honeywell, IVI Publishing, Computing Devices International, and the Network Systems Corporation of Minnesota.