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Study of Scalable Declustering Algorithms for Parallel Grid Files (1996)
| Content Provider | CiteSeerX |
|---|---|
| Author | Saltz, Joel Moon, Bongki Acharya, Anurag |
| Description | In Proceedings of the Tenth International Parallel Processing Symposium |
| Abstract | Efficient storage and retrieval of large multidimensional datasets is an important concern for large-scale scientific computations such as long-running time-dependent simulations which periodically generate snapshots of the state. The main challenge for efficiently handling such datasets is to minimize response time for multidimensional range queries. The grid file is one of the well known access methods for multidimensional and spatial data. We investigate effective and scalable declustering techniques for grid files with the primary goal of minimizing response time and the secondary goal of maximizing the fairness of data distribution. The main contributions of this paper are (1) analytic and experimental evaluation of existing index-based declustering techniques and their extensions for grid files, and (2) development of a proximity-based declustering algorithm called minimax which is experimentally shown to scale and to consistently achieve better response time compared to availabl... |
| File Format | |
| Publisher Date | 1996-01-01 |
| Access Restriction | Open |
| Subject Keyword | Multidimensional Range Query Well Known Access Method Long-running Time-dependent Simulation Primary Goal Spatial Data Parallel Grid File Response Time Secondary Goal Large-scale Scientific Computation Main Challenge Proximity-based Declustering Algorithm Grid File Experimental Evaluation Large Multidimensional Datasets Scalable Declustering Algorithm Important Concern Efficient Storage Data Distribution Index-based Declustering Technique Scalable Declustering Technique |
| Content Type | Text |
| Resource Type | Proceeding Conference Proceedings Article |
