Towards Optimal Utilization of Main Memory for Moving Object Indexing

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.