Journal of Intelligent Information Systems
Grid Services for Fast Retrieval on Large Multidimensional Databases
HPCN Europe 2001 Proceedings of the 9th International Conference on High-Performance Computing and Networking
Designing a Compression Engine for Multidimensional Raster Data
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Query processing techniques for arrays
The VLDB Journal — The International Journal on Very Large Data Bases
Mooshka: a system for the management of multidimensional gene expression data in situ
Information Systems - Special issue: Data management in bioinformatics
Performance Evaluation of Multidimensional Array Storage Techniques in Databases
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Large-scale, standards-based earth observation imagery and web mapping services
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
The OGC web coverage processing service (WCPS) standard
Geoinformatica
A cost model for distributed coverage processing services
Proceedings of the ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems
ArrayStore: a storage manager for complex parallel array processing
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Large-Scale earth science services: a case for databases
CoMoGIS'06 Proceedings of the 2006 international conference on Advances in Conceptual Modeling: theory and practice
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Storage management of multidimensional arrays aims at supporting the array model needed by applications and insuring fast execution of access operations. Current approaches to store multidimensional arrays rely on partitioning data into chunks (equally sized subarrays). Regular partitioning, however, does not adapt to access patterns, leading to suboptimal access performance. In this paper, we propose a storage approach for multidimensional discrete data (MDD) based on multidimensional arbitrary tiling. Tiling is arbitrary in that any partitioning into disjoint multidimensional intervals as well as incomplete coverage of n-D space and gradual growth of MDDs are supported. The proposed approach allows the storage structure to be configured according to user access patterns through tunable tiling strategies. We describe four strategies and respective tiling algorithms and present performance measurements which show their effectiveness in reducing disk access and post-processing times for range queries.