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
Modern database systems: the object model, interoperability, and beyond
Modern database systems: the object model, interoperability, and beyond
The pyramid-technique: towards breaking the curse of dimensionality
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
PODS '99 Proceedings of the eighteenth 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
A foundation for representing and querying moving objects
ACM Transactions on Database Systems (TODS)
ACM Computing Surveys (CSUR)
Data Structures for Range Searching
ACM Computing Surveys (CSUR)
A class of data structures for associative searching
PODS '84 Proceedings of the 3rd ACM SIGACT-SIGMOD symposium on Principles of database systems
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Locating Objects in Mobile Computing
IEEE Transactions on Knowledge and 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
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Hilbert R-tree: An Improved R-tree using Fractals
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
On the Generation of Spatiotemporal Datasets
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Indexing Spatio-Temporal Data Warehouses
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Indexing the Trajectories of Moving Objects in Networks*
Geoinformatica
R-Trees: Theory and Applications (Advanced Information and Knowledge Processing)
R-Trees: Theory and Applications (Advanced Information and Knowledge Processing)
Spatio-Temporal Indexing for Large Multimedia Applications
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Accelerating spatial join operations using bit-indices
ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115
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A trajectory is defined as the record of time-varying spatial phenomenon. The trajectory database is an important research area that has received a lot of interest in the last decade, with the objective of trajectory databases being to extend existing database technology to support the representation and querying of moving objects and their trajectories. Querying in trajectory databases can be very expensive due to the nature of the data and the complexity of the query processing algorithms. Given also that location-aware devices, like the GPS, are present everywhere these days, trajectory databases will soon face an enormous amount of data. Consequently the performance in the presence of a vast amount of data will be a significant problem and efficient indexing schemes are required to support both updates and searches efficiently. This paper provides the methodology for using the recursive partitioning technique for indexing trajectories in the unrestricted space, which is called the Recursively Partitioned Trajectory Index (RPTI). RPTI uses the two-level indexing structure, as does the state of art indexing scheme, SETI, and maintains separate indices for the space and time dimensions. We present the algorithms for constructing the RPTI and the algorithms for updates that include insertion and deletion. We also provide the results of the experimental study on the RPTI and have demonstrated that RPTI is better than SETI in handling trajectory-based queries and is competitive with SETI in handling coordinate-based queries. The structure of RPTI can be easily implemented by using any of the existing spatial indexing structures. The only design parameters required are the standard disk page size and maximum level of recursive partitioning.