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Spatial air index with neighbor information for processing k-nearest neighbor searches in IoT mobile computing

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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.

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Acknowledgements

This research was supported by Grant MOST 106-2410-H-468-009 from the Ministry of Science and Technology, Taiwan.

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Authors and Affiliations

  1. Department of Information Communication, Asia University, Taichung, 41354, Taiwan

    Jun-Hong Shen, Ching-Ta Lu & Hong-Ray Chu

  2. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40447, Taiwan

    Jun-Hong Shen & Ching-Ta Lu

  3. Department of Industrial Education and Technology, National Changhua University of Education, Changhua, 50074, Taiwan

    Cheng-Jung Yu

  4. Department of Information Management, National Taichung University of Science and Technology, Taichung, 40401, Taiwan

    WenYen Lin & Tien-Chi Huang

  5. School of Computer Science and Engineering, University of Aizu, Aizuwakamatsu City, Fukushima, 9658580, Japan

    Neil Y. Yen

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  1. Jun-Hong Shen
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  2. Cheng-Jung Yu
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  3. Ching-Ta Lu
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  4. WenYen Lin
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Correspondence to Neil Y. Yen.

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Shen, JH., Yu, CJ., Lu, CT. et al. Spatial air index with neighbor information for processing k-nearest neighbor searches in IoT mobile computing. J Supercomput 76, 6177–6194 (2020). https://doi.org/10.1007/s11227-019-02753-5

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  • DOI: https://doi.org/10.1007/s11227-019-02753-5

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