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CMUR-Tree: Main Memory-based R-Tree for Supporting Frequent Updates
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- Authors
- Soon Young Park, Sang Hun Eo, Gyung Bae Kim, Hae Young Bae
- Issue Date
- 2006-05
- Citation
- International Conference on Computational Science and Its Applications (ICCSA) 2006, pp.1-10
- Language
- English
- Type
- Conference Paper
- Abstract
- Data streams from sensors have usually characterized continuous, very frequent updating. Queries over those data streams need to be processed in near real-time. So it is needed to design the index structure for supporting the frequent updates and fast retrieval of data efficiently. In this paper, CMURTree (Cache-conscious Modification Update R-Tree) is proposed, which is a spatial index for efficient processing of frequent updates of data streams in locality preserving monitoring applications. CMUR-Tree has two characteristics. First, it excludes index reconstruction overhead by permitting to modify only the index node of sensor which moves out of the corresponding MBR (Minimum Bound Rectangle). Second, it reduces the key spaces by applying new compression method for MBR used as key in R-Tree and by considering cache to prevent bottleneck which is a different result in speed between main memory and CPU. The experimental results indicate that the proposed CMUR-Tree enhances update performance and gives a good retrieval performance simultaneously.
- KSP Keywords
- Compression method, Data stream, Fast Retrieval, Index Structure, Index node, Locality preserving, Memory-based, Monitoring applications, Near real time, R-Tree, Retrieval performance