Abstract—Geo-spatial data becomes more and more large amount of data on the Web. On the other hand, managing massive spatial data is one of challenges for supporting spatial queries and high performance computational is also needed to support spatial queries. Thus there is needed to solve this criteria is to create a better spatial indexing method. The proposed method is to create Grid-based R-tree index structure for k nearest neighbour query and range query. R-tree is constructed with Minimum Bounding Rectangle (MBR) that contains a group of objects. The proposed system is combined R-tree with grid index that is reduced overlapping and covering area. The proposed system is to support spatial queries efficiently and also supports speed up computational performance
Index Terms—K nearest neighbor search, R-tree, grid-index, LBS.
Aung Zaw Myint is with Faculty of Computing, University of Computer Studies, Yangon (UCSY), Myanmar (e-mail: aungzawmyint@ucsy.edu.mm).
Khin Mo Mo Tun is with the Faculty of Computing, University of Information Technology, Myanmar (e-mail: khinmomotun@uit.edu.mm).
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Cite: Aung Zaw Myint and Khin Mo Mo Tun, "Grid-Based Spatial Index Method for Location-Based Nearest Neighbour Search," International Journal of Future Computer and Communication vol. 9, no. 2, pp. 40-45, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
(CC BY 4.0).
