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VISUALIZATION
2005
IEEE

Distributed Data Management for Large Volume Visualization

4 years 4 months ago
Distributed Data Management for Large Volume Visualization
We propose a distributed data management scheme for large data visualization that emphasizes efficient data sharing and access. To minimize data access time and support users with a variety of local computing capabilities, we introduce an adaptive data selection method based on an “Enhanced Time-Space Partitioning” (ETSP) tree that assists with effective visibility culling, as well as multiresolution data selection. By traversing the tree, our data management algorithm can quickly identify the visible regions of data, and, for each region, adaptively choose the lowest resolution satisfying userspecified error tolerances. Only necessary data elements are accessed and sent to the visualization pipeline. To further address the issue of sharing large-scale data among geographically distributed collaborative teams, we have designed an infrastructure for integrating our data management technique with a distributed data storage system provided by Logistical Networking (LoN). Data sets ...
Jinzhu Gao, Jian Huang, C. Ryan Johnson, Scott Atc
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where VISUALIZATION
Authors Jinzhu Gao, Jian Huang, C. Ryan Johnson, Scott Atchley, James Arthur Kohl
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