Spatial Data Indexing and Query Processing in GeoCloud

被引:0
作者
Shankar, Karthi [1 ]
Sevugan, Prabu [1 ]
机构
[1] Vellore Inst Technol, Sch Comp Sci & Engn, Vellore 632014, Tamil Nadu, India
关键词
spatial data; indexing; query processing; GeoCloud; SpatialHadoop; FRAMEWORK;
D O I
10.1520/JTE20180502
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
GeoCloud is essential for spatial data management. This article depicts GeoCloud and SpatialHadoop, both of which are developed for spatial information, indexing, and query processing. It contains traditional spatial indexing that comprises R-tree, Hilbert R-tree, and improved Bloom filter tree. We enhance the query search by utilizing Spatial Join, Range Query, k-nearest neighbor (k-NN), and Max k-NN queries. By doing so, we implement the data structures and query evaluation performance of different spatial datasets in GeoCloud instances with SpatialHadoop. We show that our proposed system is more efficient in terms of data storage and retrieval in GeoCloud.
引用
收藏
页码:4039 / 4053
页数:15
相关论文
共 36 条
[1]  
Akdogan A., 2010, Proceedings of the 2010 IEEE 2nd International Conference on Cloud Computing Technology and Science (CloudCom 2010), P9, DOI 10.1109/CloudCom.2010.92
[2]   GISQF: An Efficient Spatial Query Processing System [J].
Al-Naami, Khaled Mohammed ;
Seker, Sadi ;
Khan, Latifur .
2014 IEEE 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD), 2014, :681-688
[3]  
Aly A.G., 2013, International Journal Of Computer Science, V1, P17
[4]  
[Anonymous], INT J ENG SCI RES TE
[5]  
[Anonymous], 2013, INT J ENG COMPUTER S
[6]  
[Anonymous], 2005, In Proc
[7]  
Bhat M.A., 2011, International Journal on Computer Science and Engineering (IJCSE), V3, P594
[8]  
Bhosale H.S., 2014, Int J Sci Res, V4, P1
[9]  
BILL R., 2011, Springer Handbook of Geographic Information, P461
[10]  
Byungyeon Hwang, 1994, Proceedings of the 20th EUROMICRO Conference. EUROMICRO 94. System Architecture and Integration, P53, DOI 10.1109/EURMIC.1994.390406