Abstract
Index is a key technique in improving the query processing performance of moving objects databases. However, current index methods for moving object trajectories take trajectory units as the basic index records and frequent index updates are needed when location updates occur, which greatly affects the overall performance of moving objects databases. To solve this problem, we propose a new index method, network-constrained Moving Object Sketched-Trajectory R-Tree (MOSTR-Tree) in this paper, which outperforms previously proposed methods under frequent location updates.
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Ding, Z. (2011). Indexing Frequently Updated Trajectories of Network-Constrained Moving Objects. In: Hameurlain, A., Liddle, S.W., Schewe, KD., Zhou, X. (eds) Database and Expert Systems Applications. DEXA 2011. Lecture Notes in Computer Science, vol 6861. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23091-2_40
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DOI: https://doi.org/10.1007/978-3-642-23091-2_40
Publisher Name: Springer, Berlin, Heidelberg
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