The design and analysis of spatial data structures
The design and analysis of spatial data structures
Proceedings of the sixteenth international conference on Very large databases
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
Two algorithms for nearest-neighbor search in high dimensions
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
A cost model for nearest neighbor search in high-dimensional data space
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Multidimensional access methods
ACM Computing Surveys (CSUR)
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ACM Computing Surveys (CSUR)
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Modeling and Querying Moving Objects
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Cost and Imprecision in Modeling the Position of Moving Objects
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
The hBP-tree: A Modified hB-tree Supporting Concurrency, Recovery and Node Consolidation
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Moving Objects Databases: Issues and Solutions
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
A Geometric Framework for Specifying Spatiotemporal Objects
TIME '99 Proceedings of the Sixth International Workshop on Temporal Representation and Reasoning
The Geometry of Uncertainty in Moving Objects Databases
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Semantic Caching in Location-Dependent Query Processing
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Efficient Querying of Periodic Spatiotemporal Objects
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Group Nearest Neighbor Queries
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Monitoring k-Nearest Neighbor Queries over Moving Objects
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Ranking continuous nearest neighbors for uncertain trajectories
The VLDB Journal — The International Journal on Very Large Data Bases
A new continuous nearest neighbor technique for query processing on mobile environments
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part II
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Nearest neighbor queries have received much interest in recent years due to their increased importance in advanced database applications. However, past work has addressed such queries in a static setting. In this paper we consider instead a dynamic setting where data objects move continuously. Such a mobile spatiotemporal environment is motivated by real life applications in traffic management, intelligent navigation and cellular communication systems. We consider two versions of nearest neighbor queries depending on whether the temporal predicate is a single time instant or an interval. For example: "find the closest object to a given object o after 10 minutes from now", or, "find the object that will be the closest to object o between 10 and 15 minutes from now". Since data objects move continuously it is inefficient to update the database about their position at each time instant. Instead our approach is to employ methods that store the motion function of each object and answer nearest neighbor queries by efficiently searching through these methods.