TY - JOUR
T1 - Spatial network RNN queries in GIS
AU - Taniar, David
AU - Safar, Maytham
AU - Tran, Quoc Thai
AU - Rahayu, Wenny
AU - Park, Jong Hyuk
PY - 2011/4
Y1 - 2011/4
N2 - 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.
AB - 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.
KW - bichromatic queries
KW - GIS
KW - monochromatic queries
KW - network Voronoi diagram
KW - reverse nearest neighbor
UR - http://www.scopus.com/inward/record.url?scp=79953834907&partnerID=8YFLogxK
U2 - 10.1093/comjnl/bxq068
DO - 10.1093/comjnl/bxq068
M3 - Article
AN - SCOPUS:79953834907
SN - 0010-4620
VL - 54
SP - 617
EP - 627
JO - Computer Journal
JF - Computer Journal
IS - 4
ER -