Serving queries to multi-resolution datasets on disk-based storage clusters

Authors:
Xi Zhang;T. Pan;U. Catalyurek;T. Kurc;J. Saltz
Affiliations:
Dept. of Biomed. Informatics, Ohio State Univ., Columbus, OH, USA;Dept. of Biomed. Informatics, Ohio State Univ., Columbus, OH, USA;Dept. of Biomed. Informatics, Ohio State Univ., Columbus, OH, USA;Dept. of Biomed. Informatics, Ohio State Univ., Columbus, OH, USA;Dept. of Biomed. Informatics, Ohio State Univ., Columbus, OH, USA
Venue:
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
Year:
2004

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Abstract

This paper is concerned with efficient querying of very large multi-resolution datasets on storage and compute clusters. We present a suite of services that support storage, indexing, and data processing (data sampling and data aggregation) on datasets that consist of a collection of multi-resolution Grids. We empirically evaluate the performance impact of different data declustering, indexing, and query processing strategies. The experimental evaluation is carried out using a data server implemented to serve multi-terabyte multi-resolution volumetric datasets to remote visualization clients and a one-terabyte multi-resolution volumetric dataset on a PC cluster with distributed disk space.