A Parallelizing Method for Generation of Voronoi Diagram Using Contact Zone

Due to the recent popularization of the Geographic Information System (GIS), spatial network environments that can display the changes of spatial axes on mobile devices are receiving great attention. In spatial network environments, since a query object that seeks location information selects severa...

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Bibliographic Details
Published inJournal of data intelligence Vol. 1; no. 2; pp. 159 - 175
Main Authors Okahana, Yuuhi, Gotoh, Yusuke
Format Journal Article
LanguageEnglish
Published 01.06.2020
Online AccessGet full text
ISSN2577-610X
2577-610X
DOI10.26421/JDI1.2-4

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Summary:Due to the recent popularization of the Geographic Information System (GIS), spatial network environments that can display the changes of spatial axes on mobile devices are receiving great attention. In spatial network environments, since a query object that seeks location information selects several candidate target objects based on the search conditions, we often use a k-nearest neighbor (kNN) search, which seeks several target objects near the query object. However, since a kNN search needs to find the kNN by calculating the distance from the query to all the objects, the computational complexity might become too large based on the number of objects. To reduce this computation time in a kNN search, many researchers have proposed a search method that divides regions using a Voronoi diagram. However, since conventional methods generate Voronoi diagrams for objects in order, the processing time for generating Voronoi diagrams might become too large when the number of objects is increased. In this paper, we propose a generation method of the Voronoi diagram by parallelizing the generation of Voronoi regions using a contact zone. Our proposed method can reduce the processing time of generating the Voronoi diagram by generating Voronoi regions in parallel based on the number of targets. Our evaluation confirmed that the processing time under the proposed method was reduced about 15.9\% more than conventional methods that are not parallelized.
ISSN:2577-610X
2577-610X
DOI:10.26421/JDI1.2-4