Monitoring k-Nearest Neighbor Queries over Moving Objects
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
A generic framework for monitoring continuous spatial queries over moving objects
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Proceedings of the 6th international conference on Mobile data management
Maintenance of K-nn and spatial join queries on continuously moving points
ACM Transactions on Database Systems (TODS)
Nearest and reverse nearest neighbor queries for moving objects
The VLDB Journal — The International Journal on Very Large Data Bases
Continuous Skyline Queries for Moving Objects
IEEE Transactions on Knowledge and Data Engineering
Towards optimal continuous nearest neighbor queries in spatial databases
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Maintenance of spatial semijoin queries on moving points
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficient KNN processing over moving objects with uncertain velocity
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
SSDBM '08 Proceedings of the 20th international conference on Scientific and Statistical Database Management
Continuous probabilistic nearest-neighbor queries for uncertain trajectories
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Continuous K-Nearest Neighbor Query over Moving Objects in Road Networks
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
Probabilistic threshold k nearest neighbor queries over moving objects in symbolic indoor space
Proceedings of the 13th International Conference on Extending Database Technology
Efficient mutual nearest neighbor query processing for moving object trajectories
Information Sciences: an International Journal
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Optimized algorithms for predictive range and KNN queries on moving objects
Information Systems
Direction-based spatial skylines
Proceedings of the Ninth ACM International Workshop on Data Engineering for Wireless and Mobile Access
Efficient k-nearest neighbor search on moving object trajectories
The VLDB Journal — The International Journal on Very Large Data Bases
Finding the least influenced set in uncertain databases
Information Systems
Scalable processing of continuous K-nearest neighbor queries with uncertain velocity
Expert Systems with Applications: An International Journal
Probabilistic time consistent queries over moving objects
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
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
Spatial skyline queries: exact and approximation algorithms
Geoinformatica
Ranking continuous nearest neighbors for uncertain trajectories
The VLDB Journal — The International Journal on Very Large Data Bases
Direction-based surrounder queries for mobile recommendations
The VLDB Journal — The International Journal on Very Large Data Bases
Panda: a predictive spatio-temporal query processor
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Predictive spatio-temporal queries: a comprehensive survey and future directions
Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems
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A desirable feature in spatio-temporal databases is the ability to answer future queries, based on the current data characteristics (reference position and velocity vector). Given a moving query and a set of moving objects, a future query asks for the set of objects that satisfy the query in a given time interval. The difficulty in such a case is that both the query and the data objects change positions continuously, and therefore we can not rely on a given fixed reference position to determine the answer. Existing techniques are either based on sampling, or on repetitive application of time-parameterized queries in order to provide the answer. In this paper we develop an efficient method in order to process nearest-neighbor queries in moving-object databases. The basic advantage of the proposed approach is that only one query is issued per time interval. The time-parameterized R-tree structure is used to index the moving objects. An extensive performance evaluation, based on CPU and I/O time, shows that significant improvements are achieved compared to existing techniques.