A balanced search tree with O(1) worst case update time
Acta Informatica
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
Journal of the ACM (JACM)
Multidimensional access methods
ACM Computing Surveys (CSUR)
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Comparison of access methods for time-evolving data
ACM Computing Surveys (CSUR)
Advanced database indexing
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
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Indexing Mobile Objects on the Plane
DEXA '02 Proceedings of the 13th International Workshop on Database and Expert Systems Applications
Dynamic Interpolation Search in o(log log n) Time
ICALP '93 Proceedings of the 20th International Colloquium on Automata, Languages and Programming
Indexing of Moving Objects for Location-Based Services
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
STRIPES: an efficient index for predicted trajectories
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
On past-time indexing of moving objects
Journal of Systems and Software
The TPR*-tree: an optimized spatio-temporal access method for predictive queries
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Indexing mobile objects on the plane revisited
ADBIS'07 Proceedings of the 11th East European conference on Advances in databases and information systems
ISB-tree: a new indexing scheme with efficient expected behaviour
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
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We present a time-efficient approach to index objects moving on the plane to efficiently answer range queries about their future positions. Each object is moving with non small velocity u, meaning that the velocity value distribution is skewed (Zipf) towards umin in some range [umin, umax], where umin is a positive lower threshold. Our algorithm enhances a previously described solution [18] by accommodating the ISB-tree access method as presented in [6]. Experimental evaluation shows the improved performance, scalability and efficiency of the new algorithm.