Performance of a mass storage system for video-on-demand

Hsieh, Jenwei; Lin, Mengjou; Liu, J.C.L.; Du, David Hung-Chang; Ruwart, Thomas M.

doi:10.1109/infcom.1995.515946

Cited by 12 publications

(8 citation statements)

References 9 publications

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“…Our admission policies are based on deterministic guarantee model. These policies include i) we have setup the practical limits of the supported video streams by precollecting experimental results [17], [26] in advance; ii) new requests are accepted only when the resulting new load in addition to the existing loads will not exceed these limits; and iii) mechanisms were imposed in NAPs and SAPs report to CCACS whenever the loads on the storage/network devices (i.e., NCP and SCP) are changed.…”

Section: ) Central Control and Admission Control Servermentioning

confidence: 99%

“…1. The interactions of the system hardware components (i.e., storage, processing, and networking) can be described as follows: In order to support a large number of concurrent video accesses, video files are usually archived in the storage subsystem according to data striping schemes [17], [26]. They are retrieved in a streaming style through the processing and routing component, and then transferred to the network subsystem.…”

Section: Introductionmentioning

confidence: 99%

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Design and evaluation of a generic software architecture for on-demand video servers

Liu

Shim

et al. 1999

IEEE Trans. Knowl. Data Eng.

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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.Index Terms-Experimental systems, system integration and management, distributed multimedia systems.

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Section: ) Central Control and Admission Control Servermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design and evaluation of a generic software architecture for on-demand video servers

Liu

Shim

et al. 1999

IEEE Trans. Knowl. Data Eng.

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“…Most of the existing research involves disk scheduling and allocation strategies [ORS94, ORS95, KSP+95, RV93, GC92, LD93, GVKR95, BPJ94,HLL+95]. Buffer management for prefetching and maximizing buffer utilization has also been investigated in the context of guaranteeing the continuity requirements of media streams.…”

Section: Introductionmentioning

confidence: 99%

Buffer model and management in distributed multimedia presentation systems

Gollapudi

Zhang

1998

Multimedia Systems

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The delivery of continuous and synchronous multimedia data from a database (or file) server to multiple destinations over a network presents new challenges in the area of buffer management. Many factors that were not considered in conventional buffer management must be examined. In this paper, we investigate the principles of buffer model and management for multimedia data presentations in distributed systems. The primary goal is to minimize the response time of multimedia presentations while ensuring that all continuity and synchronization requirements are satisfied. A framework for buffer model and management is introduced. Minimum buffering requirements at both client and server sides to guarantee the continuity and synchrony of the presentation of multimedia data are examined. A prefetching and replacement strategy which satisfies these requirements is then offered. These principles and techniques provide users with the full range of information required to develop a distributed system for multimedia presentations.

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“…Rowe [Fede94,Rowe92] is building a comprehensive system including a video file server, a continuous media player, and a large library of digitized videos. [Hsie94] studies the performance of an actual video server running on a Silicon Graphics Onyx computer system.…”

Section: Introductionmentioning

confidence: 99%

The SPIFFI scalable video-on-demand system

Freedman

DeWitt

1995

Proceedings of the 1995 ACM SIGMOD International Conference on Management of Data - SIGMOD '95

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This paper presents a simulation study of a video-on-demand system.We present video server algorithms for real-time disk scheduling, prefetching, and buffer pool management. The performance of these algorithms is compared against the performance of simpler algorithms such aselevator and round-robin disk scheduling and global LRU buffer pool management. Finally, we show that the SPIFFI video-on-demand system scales nearly linearly as the number of disks, videos, and terminals is increased.

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Performance of a mass storage system for video-on-demand

Cited by 12 publications

References 9 publications

Design and evaluation of a generic software architecture for on-demand video servers

Design and evaluation of a generic software architecture for on-demand video servers

Buffer model and management in distributed multimedia presentation systems

The SPIFFI scalable video-on-demand system

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