Title of article :
Parallel indexing technique for spatio-temporal data
Author/Authors :
He، نويسنده , , Zhenwen and Kraak، نويسنده , , Menno-Jan and Huisman، نويسنده , , Otto and Ma، نويسنده , , Xiaogang and Xiao، نويسنده , , Jing، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Pages :
13
From page :
116
To page :
128
Abstract :
The requirements for efficient access and management of massive multi-dimensional spatio-temporal data in geographical information system and its applications are well recognized and researched. The most popular spatio-temporal access method is the R-Tree and its variants. However, it is difficult to use them for parallel access to multi-dimensional spatio-temporal data because R-Trees, and variants thereof, are in hierarchical structures which have severe overlapping problems in high dimensional space. We extended a two-dimensional interval space representation of intervals to a multi-dimensional parallel space, and present a set of formulae to transform spatio-temporal queries into parallel interval set operations. This transformation reduces problems of multi-dimensional object relationships to simpler two-dimensional spatial intersection problems. Experimental results show that the new parallel approach presented in this paper has superior range query performance than R*-trees for handling multi-dimensional spatio-temporal data and multi-dimensional interval data. When the number of CPU cores is larger than that of the space dimensions, the insertion performance of this new approach is also superior to R*-trees. The proposed approach provides a potential parallel indexing solution for fast data retrieval of massive four-dimensional or higher dimensional spatio-temporal data.
Keywords :
Parallel index , R-tree , Interval , Spatio-temporal index
Journal title :
ISPRS Journal of Photogrammetry and Remote Sensing
Serial Year :
2013
Journal title :
ISPRS Journal of Photogrammetry and Remote Sensing
Record number :
2229193
Link To Document :
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