The authors describe StarWorks, a video applications server
software designed to support a wide range of digital video applications.
The StarWorks system will allow existing network applications, such as
databases and groupware applications, to add video support. These
applications can take advantage of the video application services to
support the real-time demands of streaming data. Attention is given to
the StarWorks operating environment, client software, and server
"Consequently, they may fail to deliver data on time, which will result in unacceptable playback quality. Real-time file servers, on the other hand, address the problem of real-time delivery over local area networks by carefully scheduling I/O operations to meet the consumption constraints of their clients      . "
[Show abstract][Hide abstract] ABSTRACT: The design of a distributed video-on-demand system that is suitable for large video libraries is described. The system is designed to store 1000s of hours of video material on tertiary storage devices. A video that a user wants to view is loaded onto a video file server close to the users desktop from where it can be played. The system manages the distributed cache of videos on the file servers and schedules load requests to the tertiary storage devices. The system also includes a metadata database, described in a companion paper, that the user can query to locate video material of interest. This paper describes the software architecture, storage organization, application protocols for locating and loading videos, and distributed cache management algorithm used by the system.
Proceedings of SPIE - The International Society for Optical Engineering 04/2001; DOI:10.1117/12.171775 · 0.20 Impact Factor
"NE common architecture shared by most existing videoon-demand (VoD) systems is that they are based on a single server. The video server can range from a standard PC for small-scale systems ,  to massively parallel supercomputers with thousands of processors for large-scale systems , . However, the price/performance ratio escalates quickly for high-end hardware, and ultimately the capacity of a single server is still limited. "
[Show abstract][Hide abstract] ABSTRACT: Most existing commercial video servers are designed for a single
server. Consequently, the capacity of the system in terms of maximum
sustainable concurrent sessions is limited by the performance of the
video server hardware. This paper proposes and analyzes the performance
of a novel parallel video server architecture where video data are
striped across an array of autonomous servers. The architecture allows
one to build incrementally scalable video servers without video data
replication. The proposed concurrent-push scheduling algorithm allows
the system to integrate with quality of service guarantees provided by
today's switching networks. In this paper, the striping policy, the
service model, and the concurrent-push scheduling algorithm are
presented. A system model is constructed to quantify three performance
metrics, namely, server buffer requirement, client buffer requirement,
and system response time. Results show that a simple extension of the
server-push service model does not perform well under the parallel video
server architecture. To improve system performance, a novel extension of
the grouped sweeping scheme called the asynchronous grouped sweeping
scheme (AGSS) is introduced. To further increase the scalability of the
architecture, a new subschedule striping scheme (SSS) is introduced.
With the proposed AGSS and SSS, our parallel video server architecture
can be scaled up to more than 10000 concurrent users
IEEE Transactions on Circuits and Systems for Video Technology 05/1999; 9(3-9):467 - 477. DOI:10.1109/76.754776 · 2.62 Impact Factor
"The available video-on-demand (VoD) system uses single-server as a video-server . T he video server can range from a simple PC to highly-parallel supercomputers system    . The price/performance ratio tends to i ncrease swiftly for high-end video-servers, due to lack of economy of scale. "
[Show abstract][Hide abstract] ABSTRACT: This Video data is stored in a video server for delivery to multiple receivers over a communications network in a traditional video-on-demand system. The hardware in this video server has the following limitations: 1) the maximum storage capacity, and 2) the maximum number of video sessions that can simultaneously be de livered. We prop ose a novel Adaptive-Multiple-VIdeo-Server -Architecture (AMVISA) that manipulates parallelism to achieve incremental scalability. This AMVISA architecture 1) exploits data striping in stead of data partition and replication, at the server level to achieve fine-grain load sharing across multiple servers, 2) employs a client-pull service model to eliminate the need for inter -server synchronization, 3) an admission-scheduling algorithm is proposed to further control the dynamic load at each server so that linear scalability can be accomplished. The results in our proposed AMVISA architecture show that the architecture can be linearly scaled up to more concurrent users simply by adding more video-servers and sharing the video data among the servers. The results also support that our new architecture for VoD system is more reliable than single-server VoD system.
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