The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Enhanced nearest neighbour search on the R-tree
ACM SIGMOD Record
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
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
Performance of Nearest Neighbor Queries in R-Trees
ICDT '97 Proceedings of the 6th International Conference on Database Theory
K-Nearest Neighbor Search for Moving Query Point
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Semantic Caching in Location-Dependent Query Processing
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Continuous nearest neighbor search
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Approximate continuous K-nearest neighbor queries for uncertain objects in road networks
WAIM'11 Proceedings of the 12th international conference on Web-age information management
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One of the most important kind of queries in spatial data-bases to support location-based services (LBS) is the continuous nearest neighbors (CNN) query. Given a spatial data set of points of interest and a moving query point q, the CNN query partitions q into a set of adjacent disjoint intervals associated with their nearest points of interest. Existing solutions to this problem are known to be sub-optimal in terms of disk accesses. In this paper, we present an algorithm to compute the CNN query that is I/O optimal. With an experimental evaluation, we show that not only the number of disk accesses is reduced with the optimal algorithm, but also the CPU performance is improved, in some cases.