Storage and Retrieval of Moving Objects
MDM '01 Proceedings of the Second International Conference on Mobile Data Management
Indexing the Trajectories of Moving Objects in Networks*
Geoinformatica
Techniques for Efficient Road-Network-Based Tracking of Moving Objects
IEEE Transactions on Knowledge and Data Engineering
ANTS: Efficient Vehicle Locating Based on Ant Search in ShanghaiGrid
ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
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
Spatio-Temporal Indexing for Large Multimedia Applications
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Optimizing predictive queries on moving objects under road-network constraints
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
Predictive line queries for traffic prediction
Transactions on Large-Scale Data- and Knowledge-Centered Systems VI
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In the past composite structures for managing road network-constrained moving objects, the road network is usually broken up into road segments. This scheme will cause high concentrated update operations, and some needless queries while tracking the moving objects. In this paper, we propose a new unit called cross region(CR) to break up the road network, and use CR to build a new structure called CR-tree to be the static part of the composite structure. By indexing the moving objects with our composite structure, experiments show that the update density could be evened, the update frequency and the update cost could be decreased compare with the past ones.