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

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 multiresolution 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 multiterabyte multi-resolution volumetric datasets to remote visualization clients and a one-terabyte multi-resolution volumetric dataset on a PC cluster with distributed disk space.

• Type: Conference
• Year: 2004
• Where: CCGRID
• Authors: Xi Zhang, Tony Pan, Ümit V. Çatalyürek, Tahsin M. Kurç, Joel H. Saltz
• Keywords: CCGRID 2004, Data Aggregation, Distributed And Parallel Computing, Large Multi-resolution Datasets, Multi-resolution Volumetric Dataset