Distributed parallel data storage systems
Author(s) -
Brian Tierney,
Jason Lee,
Ling Tony Chen,
Hanan Herzog,
Gary Hoo,
Guojun Jin,
William E. Johnston
Publication year - 1994
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
ISBN - 0-89791-686-7
DOI - 10.1145/192593.192709
Subject(s) - computer science , software portability , scalability , data stream mining , computer data storage , the internet , distributed computing , embedded system , computer network , operating system , machine learning
We have designed, built, and analyzed a distributed parallel storage system that will supply image streams fast enough to permit multi-user, “real-time”, video-like applications in a wide-area ATM network-based Internet environment. We have based the implementation on user-level code in order to secure portability; we have characterized the performance bottlenecks arising from operating system and hardware issues, and based on this have optimized our design to make the best use of the available performance. Although at this time we have only operated with a few classes of data, the approach appears to be capable of providing a scalable, high-performance, and economical mechanism to provide a data storage system for several classes of data (including mixed multimedia streams), and for applications (clients) that operate in a high-speed network environment.
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