Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
GHOST: Fine Granularity Buffering of Indexes
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Index Access with a Finite Buffer
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
MDM '01 Proceedings of the Second International Conference on Mobile Data Management
Indexing the Current Positions of Moving Objects Using the Lazy Update R-tree
MDM '02 Proceedings of the Third International Conference on Mobile Data Management
Query Processing for Moving Objects with Space-Time Grid Storage Model
MDM '02 Proceedings of the Third International Conference on Mobile Data Management
Q+Rtree: Efficient Indexing for Moving Object Databases
DASFAA '03 Proceedings of the Eighth International Conference on Database Systems for Advanced Applications
STRIPES: an efficient index for predicted trajectories
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Supporting frequent updates in R-trees: a bottom-up approach
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
The TPR*-tree: an optimized spatio-temporal access method for predictive queries
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Query and update efficient B+-tree based indexing of moving objects
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
IMPACT: a twin-index framework for efficient moving object query processing
Data & Knowledge Engineering
Relaxed space bounding for moving objects: a case for the buddy tree
ACM SIGMOD Record
Indexing Moving Objects Using Short-Lived Throwaway Indexes
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
MOVIES: indexing moving objects by shooting index images
Geoinformatica
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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.