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Indexing Large Moving Objects from Past to Future with PCFI+-Index

Zhao-Hong Liu, Xiao-Li Liu, Jun-Wei Ge, and Hae-Young Bae

Presented at 11th International Conference on Management of Data (COMAD 2005) (COMAD 2005), Goa, India, January 6-8, 2005


In moving object database, the moving objects’ current position must be kept in memory, also to the trajectory, in some case, as same as the future. But the current existing indexes such as SETI-Tree can only provide the capability for past and current query, and the TPR*-Tree can only provide the capability for current and future query. None of them can provide a strategy for indexing the past, current and also the future information of moving objects. In this paper, we prove the Past-Current-Future+-Index (PCFI+-Index) to index the past, current & future information of the moving objects. It is a new version of the PCFI-Index which oriented from SETI-tree and TPR*-tree. The PCFI+-Index is consisted of two parts, in memory part with the name frontline, and disk based part. The whole region is partitioned into none-overlapped cells, and a spatial access method is used to indexing these cells. A set of main-memory TPR*-tree are used to index the moving objects belong to the cells (one cell, one TPR*-tree). Considering the large update operation triggered by moving objects, the current data file which containing the moving objects’ current information is organized as a hash index file. By keeping the restriction in SETI-Index, one page only contains the segments from one cell. Another sparse R*-tree is used to indexing the life times of the pages. The performance analysis proves that the PCFI+-Index can handle most of the query efficiently and provides a uniform solution for the trajectory query, time-slice query, internal query and moving query, and has a better performance than the SETI-Index, TPR*-Index, and PCFI-Index.

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