Name
Abstract | ||
|---|---|---|
Ideally, moving object databases should handle the past, current and future positions of moving objects efficiently. However, existing indexes such as SEB-Tree, SETI-Tree, 2+3R-Tree, 2- 3RT-Tree and etc. can only provide the capability for past and current query, and the others such as TPR-Tree, and 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 present the Past-Current-Future+-Index (PCFI+-Index) which indexes the past, current & future information of the moving objects. The PCFI+-Index builds upon the PCFI-Index which was based on SETI-tree and TPR*-tree. The PCFI+-Index consists of two parts, in memory part with the name frontline, and disk based part. The whole region is partitioned into none-overlapping cells, and a spatial access method is used to index these cells. A set of main-memory TPR*-tree is used to index the moving objects that belong to the cells (one cell, one TPR*-tree). Considering the large update operation triggered by moving objects, the current data file which contains 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 index the lifetimes of the pages. The performance analysis proves that the PCFI+-Index can handle most of the queries efficiently and provides a uniform solution for the trajectory, time-slice, internal and moving queries, and has a better performance than the SETI-Index, TPR*-Index, and PCFI- Index. |
Year | Venue | Keywords |
|---|---|---|
2005 | COMAD | indexation |
Field | DocType | Citations |
Data mining,Access method,Computer science,Search engine indexing,Indexed file,Hash function,Data file,Database,Trajectory | Conference | 4 |
PageRank | References | Authors |
0.45 | 21 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhao-hong Liu | 1 | 4 | 0.45 |
| Xiao-li Liu | 2 | 4 | 0.45 |
| Junwei Ge | 3 | 51 | 3.24 |
| Hae-Young Bae | 4 | 78 | 31.47 |