A high performance system for processing queries on distributed geospatial data sets

Authors:
Mahdi Abdelguerfi;Venkata Mahadevan;Nicolas Challier;Maik Flanagin;Kevin Shaw;Jay Ratcliff
Affiliations:
Department of Computer Science, University of New Orleans, New Orleans, Louisiana;Department of Computer Science, University of New Orleans, New Orleans, Louisiana;Department of Computer Science, University of New Orleans, New Orleans, Louisiana;Department of Computer Science, University of New Orleans, New Orleans, Louisiana;Naval Research Laboratory, Stennis Space Center, Mississippi;U.S. Army Corps of Engineers, New Orleans, Louisiana
Venue:
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
Year:
2004

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Abstract

The size of many geospatial databases has grown exponentially in recent years. This increase in size brings with it an increased requirement for additional CPU and I/O resources to handle the querying and retrieval of this data. A number of proprietary systems could be ideally suited for such tasks, but are impractical in many situations because of their high cost. On the other hand, Beowulf clusters have gained popularity for providing such resources in a cost-effective manner. In this paper, we present a system that uses the compute nodes of a Beowulf cluster to store fragments of a large geospatial database and allows for the seamless viewing, querying, and retrieval of desired geospatial data in a parallel fashion i.e. utilizing the compute and I/O resources of multiple nodes in the cluster. Experimental results are provided to quantify the performance of the system and ascertain its feasibility versus traditional GIS architectures.