Spatial Network RNN Queries in GIS
Geographical information systems (GIS) and applications assist us in commuting, traveling and locating our points of interests. The efficient implementation and support of spatial queries in those systems is of particular interest and importance. The use of a Voronoi diagram has traditionally been applied to computational geometry. In this paper, we will show how a Voronoi diagram can be applied to support spatial queries in GIS systems, and in particular to reverse nearest neighbor (RNN) queries. An RNN query retrieves the set of interest objects having the query object as the nearest neighbor among other objects. Two cases of RNN queries are: monochromatic (MRNN) and bichromatic (BRNN). In the MRNN, the interest objects and the query object are of the same type, whereas in the BRNN they are of two different types. Due to the shortcomings of solutions for BRNN in the literature, we develop a new approach and algorithm, named the '2Vor BRNN algorithm', for processing this query type in the context of the spatial network database (SNDB). Our novel approach extends the previous work and uses the 'order-2 network Voronoi diagram' to provide a more efficient solution for the BRNN. In addition, we experimentally confirm that the proposed algorithm outperforms the previous one in terms of memory used and response time.
gis reverse nearest neighbor network voronoi diagram monochromatic queries bichromatic queries