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    Volume 47, Issue 6 (February 2019)

    Special Issue Paper

    Spatial Data Indexing and Query Processing in GeoCloud

    (Received 15 July 2018; accepted 12 November 2018)

    Published Online: 26 February 2019

    CODEN: JTEVAB

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    Abstract

    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.

    Author Information:

    Shankar, Karthi
    School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu

    Sevugan, Prabu
    School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu


    Stock #: JTE20180502

    ISSN:0090-3973

    DOI: 10.1520/JTE20180502

    Author
    Title Spatial Data Indexing and Query Processing in GeoCloud
    Symposium ,
    Committee E12