K-d trees for semidynamic point sets
SCG '90 Proceedings of the sixth annual symposium on Computational geometry
The K-D-B-tree: a search structure for large multidimensional dynamic indexes
SIGMOD '81 Proceedings of the 1981 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
IEEE Transactions on Knowledge and Data Engineering
A New Tree Type Data Structure with Homogeneous Nodes Suitable for a Very Large Spatial Database
Proceedings of the Sixth International Conference on Data Engineering
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Spatio-Temporal Data Management for Moving Objects Using the PMD-Tree
ER '98 Proceedings of the Workshops on Data Warehousing and Data Mining: Advances in Database Technologies
Prediction and indexing of moving objects with unknown motion patterns
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Moving Objects Databases (The Morgan Kaufmann Series in Data Management Systems) (The Morgan Kaufmann Series in Data Management Systems)
Main-memory operation buffering for efficient R-tree update
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
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Management systems for moving objects such as automobiles, airplanes, ships, and humans, must not only manage the moving objects efficiently but also quickly provide information about their surroundings on demand, because a moving object must know its environment to determine optimal solutions, e.g., the best path to a destination. In this paper, an efficient method for managing moving objects is proposed. This method is developed by extending the spatial data structure, MD-tree, through the introduction of two novel concepts, internal leaf and improvements in bottom-up search. The internal leaf that is managed by corresponding internal node in a tree has pointers to moving objects and helps reduce the update cost of the tree. The improved bottom-up search of the tree reduces the retrieval costs by managing the non-overlapped areas of split data space. Moreover, the usual spatial searches and updates of the tree can be executed as efficient as the MD-tree.