Issues in location-based indexing for co-operating mobile information systems
OTM'07 Proceedings of the 2007 OTM confederated international conference on On the move to meaningful internet systems - Volume Part I
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A new hierarchical spatial access method called the nDR-tree is proposed that preserves all spatial relationships between all objects in n-dimensional space. The nDR-tree fits the existing data by using nodes that are the same dimensionality. The two-dimensional version, the 2DR-tree, is presented. The 2DR-tree uses two-dimensional nodes to index two-dimensional data. The minimum bounding rectangles in each node are organized according to a “validity rule” that preserves spatial relationships. This provides support for both binary searching that takes advantage of spatial relationships, and greedy searching that reduces the number of minimum bounding rectangles within a node that must be tested. The insertion and deletion strategies both use a binary partition of a node to insert an object or update a non-leaf minimum bounding rectangle. A validity test ensures that each node involved in an insertion or deletion preserves the spatial relationships among its objects. Any node invalidity is handled by employing different splitting strategies. The binary search strategy performs a recursive binary partition of a node to find minimum bounding rectangles that overlap a search region. Both an analysis and a performance evaluation are presented. The analysis shows a polynomial worst-case or better running time for all algorithms. Experimental results for insertion show that the 2DR-tree is ideal for larger objects sets with respect to tree height. The average number of disk accesses and splits per insert are reasonable. In addition, it is ideal for a dynamic skewed data set, which achieves lower coverage, overcoverage, and overlap than a dynamic, uniformly distributed data set. Experimental results for binary search show that the 2DR-tree is ideal for executing region queries where the search region is between 5–10% of the search space. In addition, region search performance improves with the number of objects in the tree.