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Proceedings Paper

Distributed large data-object management architecture
Author(s): William E. Johnston; Jin Guojun; Jason Lee; Mary R. Thompson; Brian Tierney
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Paper Abstract

We are exploring the use of highly distributed computing and storage architectures to provide all aspects of collecting, storing, analyzing, and accessing large data-objects. These data-objects can be anywhere from tens of MBytes to tens of GBytes in size. Examples are: single large images from electron microscopes, video images such as cardio- angiography, sets of related images such as MRI data and images and numerical data such as the output from a particle accelerator-experiment. The sources of such data objects are often remote from the users of the data and from available large-scale storage and computation systems. Our Large Data- object Management system provides network interface between the object sources, the data management system and the user of the data. As the data is being stored, a cataloguing system automatically creates and stores condensed versions of the data, textual metadata and pointers to the original data. The catalogue system provides a Web based graphical interface to the data. The user is able the view the low- resolution data with a standard internet connection and Web browser, or if high-resolution is required can use a high- speed connection and special application programs to view the high-resolution original data.

Paper Details

Date Published: 15 January 1997
PDF: 5 pages
Proc. SPIE 3022, Storage and Retrieval for Image and Video Databases V, (15 January 1997); doi: 10.1117/12.263437
Show Author Affiliations
William E. Johnston, Lawrence Berkeley National Lab. (United States)
Jin Guojun, Lawrence Berkeley National Lab. (United States)
Jason Lee, Lawrence Berkeley National Lab. (United States)
Mary R. Thompson, Lawrence Berkeley National Lab. (United States)
Brian Tierney, Lawrence Berkeley National Lab. (United States)

Published in SPIE Proceedings Vol. 3022:
Storage and Retrieval for Image and Video Databases V
Ishwar K. Sethi; Ramesh C. Jain, Editor(s)

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