PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Indexing moving points (extended abstract)
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Indexing the positions of continuously moving objects
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Q+Rtree: Efficient Indexing for Moving Object Databases
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Indexing of Moving Objects for Location-Based Services
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
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Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Introduction to multimedia and mobile agents
Efficient indexing of the historical, present, and future positions of moving objects
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An adaptive hashing technique for indexing moving objects
Data & Knowledge Engineering
Information Sciences: an International Journal
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Multimedia Tools and Applications
Efficient mutual nearest neighbor query processing for moving object trajectories
Information Sciences: an International Journal
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Information Sciences: an International Journal
Processing generalized k-nearest neighbor queries on a wireless broadcast stream
Information Sciences: an International Journal
Spatial indexing for massively update intensive applications
Information Sciences: an International Journal
Dynamic point-region quadtrees for particle simulations
Information Sciences: an International Journal
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In this paper, we develop a Q-hash index structure to efficiently store the position of moving objects. An environment of moving objects contains continuously changing locations which are hard to index using traditional index structures such as R-trees, QuadTrees and their variants. In order to answer the queries accurately, one of the problems faced in storing these positions is the number of updates that have to be made to the database whenever locations change. The high maintenance overhead on updates leads to performance degradation of these index structures; additionally, it makes the database very bulky which results in very poor performance in terms of query execution time. One of the main objectives of the structure we propose is to minimize the number of updates to the database to an optimal number so that the accuracy and response time of the query result are not compromised and at the same time the number of wireless communications can be reduced. The indexing is done using a hashing technique where the hashing function makes use of a region based QuadTree structure. To improve the efficiency of the query processing our index structure helps us define constraints over speed, direction and location of the moving object at the device level which controls the number of updates. In addition, in order to answer different query types efficiently at all levels we propose a three-tier (moving object, regional server, central repository) architecture. Our extensive performance evaluation and comparison of the proposed technique concludes that our scheme outperforms existing Q+R-tree and QuadTree in terms of range query execution time by a high order of magnitude.