Data structures for mobile data
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Indexing the positions of continuously moving objects
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Strip trees: a hierarchical representation for curves
Communications of the ACM
Journal of Computer and System Sciences - Special issue on PODS 2000
Indexing the Trajectories of Moving Objects in Networks*
Geoinformatica
Indexing spatiotemporal archives
The VLDB Journal — The International Journal on Very Large Data Bases
Indexing Spatio-Temporal Trajectories with Efficient Polynomial Approximations
IEEE Transactions on Knowledge and Data Engineering
Computational Geometry: Algorithms and Applications
Computational Geometry: Algorithms and Applications
A visual analytics system for metropolitan transportation
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Ordered polyline trees for efficient search of objects moving on a graph
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part I
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We present a dynamic spatio-temporal data structure called the Graph Strip Tree (GStree) for indexing objects constrained to move on a graph. The GStree is designed to efficiently answer range queries about the current or past positions of moving objects. To test the efficiency of our data structure, a road network of 66,437 roads was used. Average search times for random queries to find moving objects indexed by a GStree were compared to average search times for the same queries on moving objects indexed by a MON-tree. Results indicate that the GStree is up to 24 times faster than the MON-tree for internal memory searching, and visits between 3.6 and 38 times fewer nodes. Analysis indicates the GStree will be significantly faster for external memory search where the search time is dominated by the number of disk I/Os.