Abstract
To effectively achieve various query requests oriented at mobile objects, this thesis proposes the DTDI index structure based on grid by extending GG TPR tree index structure. By adding corresponding spatial grid model to GG TPR leave node records, this structure realizes the correspondence between the mobile objects and their moving space, thus makes it possible to predict the current and future locations of mobile objects on the grid road. Meanwhile, as we improve the children node of leaves and information unit in GG TPR index, DTDI index structure is able to achieve the integrated maintenance, query and pruning of one-group mobile objects according to road curves and crossing points and thus to reduce the information updates of mobile objects, enhancing the efficiency of the index and maintenance of mass data within a limited range and the query performance of mobile objects, being available to respond to various types of query requests. Experimental results show that the performance of DTDI structure is better than the other indexing structure on indexing and querying a great capacity of moving objects within a limited area.
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Liang, Y. (2012). Double R-Tree and Double Indexing for Mobile Objects. In: Tan, H. (eds) Knowledge Discovery and Data Mining. Advances in Intelligent and Soft Computing, vol 135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27708-5_36
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DOI: https://doi.org/10.1007/978-3-642-27708-5_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27707-8
Online ISBN: 978-3-642-27708-5
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