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Towards optimal utilization of main memory for moving object indexing

By Bin Cui, Dan Lin and Kian-lee Tan


Abstract. In moving object databases, existing disk-based indexes are unable to keep up with the high update rate while providing speedy retrieval at the same time. However, efficient management of moving-object database can be achieved through aggressive use of main memory. In this paper, we propose an Integrated Memory Partitioning and Activity Conscious Twin-index (IMPACT) framework where the moving object database is indexed by a pair of indexes based on the properties of the objects ’ movement- a main-memory structure manages active objects while a disk-based index handles inactive objects. As objects become active (or inactive), they dynamically migrate from one structure to the other. Moreover, the main memory is also organized into two partitions- one for the main memory index, and the other as buffers for the frequently accessed nodes of the disk-based index. Our experimental study shows that the IMPACT framework provides superior performance.

Year: 2005
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