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    ASIA unversity > 資訊學院 > 資訊傳播學系 > 期刊論文 >  Item 310904400/112047


    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/112047


    Title: Spatial Air Index with Neighbor Information for Processing k Nearest Neighbor Searches in IoT Mobile Computing
    Authors: 沈俊宏;SHEN, JUN-HONG;俞錚蓉;Yu, Cheng-Jung;陸清達;Lu, Ching-Ta;林文彥;Lin, WenYen;Yen, Neil Y.;Yen, Neil Y.;黃天麒;Huang, Tien-Chi;朱鋐瑞;Chu, Hong-Ray
    Contributors: 資訊傳播學系
    Date: 2019-01
    Issue Date: 2019-09-18 10:39:12 (UTC+8)
    Abstract: In the Internet of thing (IoT), with the geographic location of geospatial sensor data and the global positioning systems, location-based services (LBSs) can provide powerful location-aware IoT applications for mobile clients according to their current locations. For LBSs, a k-nearest neighbor (kNN) search can provide a mobile client with geospatial sensor data of k-nearest spatial points of interest (POIs) according to its current location. In this paper, we propose a spatial air index with neighbor information to organize IoT geospatial sensor data for processing kNN searches in the wireless broadcast systems. Since the answered POIs may be neighbors of each other, we add neighbor information to the index structure, which is interleaved with geospatial sensor data, to speed up the query processing. To avoid unnecessary examination of geospatial sensor data from the wireless channel, the proposed method provides the centroid of geospatial data and the corresponding longest distance between the centroid and geospatial data in the region. With this information, the query processing of a kNN search can quickly determine whether to skip examining this region, saving energy consumption of the mobile device. Performance evaluations have verified that the proposed method outperforms the distributed spatial index.
    Relation: JOURNAL OF SUPERCOMPUTING
    Appears in Collections:[資訊傳播學系] 期刊論文

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