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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Moon, B. Acharya, A. Saltz, J. |
| Copyright Year | 1996 |
| Description | Author affiliation: Dept. of Comput. Sci., Maryland Univ., College Park, MD, USA (Moon, B.; Acharya, A.; Saltz, J.) |
| Abstract | The 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) the analytic and experimental evaluation of existing index-based declustering techniques and their extensions for grid files; and (2) the development of a proximity-based declustering algorithm called 'minimax', which is experimentally shown to scale and to consistently achieve better response time compared to available algorithms while maintaining perfect disk distribution. |
| Starting Page | 434 |
| Ending Page | 440 |
| File Size | 799876 |
| Page Count | 7 |
| File Format | |
| ISBN | 0818672552 |
| DOI | 10.1109/IPPS.1996.508092 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1996-04-15 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Multidimensional systems Delay Information retrieval Large-scale systems Computational modeling Algorithm design and analysis Minimax techniques |
| Content Type | Text |
| Resource Type | Article |
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