The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Time-parameterized queries in spatio-temporal databases
Proceedings of the 2002 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
Similarity Indexing with the SS-tree
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
K-Nearest Neighbor Search for Moving Query Point
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
An efficient and scalable approach to CNN queries in a road network
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Continuous monitoring of top-k queries over sliding windows
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Query processing in spatial network databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Voronoi-based K nearest neighbor search for spatial network databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Design and analysis of an MST-based topology control algorithm
IEEE Transactions on Wireless Communications
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With the integration of wireless communication and positioning technologies, Location Based Services (LBSs) contribute to the enhancement of spatial databases applications and the efficiency of pervasive systems. This is ensured by providing efficient responses for location dependent queries triggered by mobile users. In this paper, we propose a new approach based on Delaunay Triangulation (DT) and the determination of Nearest Neighbors (NNs), which constitutes an important class of problems in LBS. We show that our approach, applied on road networks, is able to establish the Continuous k-Nearest Neighbors (CkNNs) while taking into account the dynamic changes of locations from which the queries are issued.