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Industrial IoT Technologies and Applications. Second EAI International Conference, Industrial IoT 2017, Wuhu, China, March 25–26, 2017, Proceedings

Research Article

An Improved DV-Hop Localization Algorithm via Inverse Distance Weighting Method in Wireless Sensor Networks

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  • @INPROCEEDINGS{10.1007/978-3-319-60753-5_17,
        author={Wenming Wang and Xiaowei Cao and Meng Qian and Liefu Ai},
        title={An Improved DV-Hop Localization Algorithm via Inverse Distance Weighting Method in Wireless Sensor Networks},
        proceedings={Industrial IoT Technologies and Applications. Second EAI International Conference, Industrial IoT 2017, Wuhu, China, March 25--26, 2017, Proceedings},
        proceedings_a={INDUSTRIALIOT},
        year={2017},
        month={9},
        keywords={Wireless sensor networks DV-Hop Mean-squared error (MSE) Inverse distance},
        doi={10.1007/978-3-319-60753-5_17}
    }
    
  • Wenming Wang
    Xiaowei Cao
    Meng Qian
    Liefu Ai
    Year: 2017
    An Improved DV-Hop Localization Algorithm via Inverse Distance Weighting Method in Wireless Sensor Networks
    INDUSTRIALIOT
    Springer
    DOI: 10.1007/978-3-319-60753-5_17
Wenming Wang,*, Xiaowei Cao, Meng Qian, Liefu Ai
    *Contact email: Wangwenming500@163.com

    Abstract

    The node localization is an important problem in wireless sensor network (WSN). An improved algorithm is proposed by analyzing the deficiencies of random distribution in DV-Hop. Different from the previous results, minimum mean-squared error (MSE) and inverse distance weighting method are adopted to deal with the average one-hop distance in improved algorithm. Improved algorithm and DV-Hop are simulated by MATLAB R2015b, and the results of these two algorithms are analyzed and compared. The results show that the positioning accuracy is improved on the condition of no increasing complexity and cost.

    Keywords
    Wireless sensor networks DV-Hop Mean-squared error (MSE) Inverse distance
    Published
    2017-09-19
    Appears in
    SpringerLink
    http://dx.doi.org/10.1007/978-3-319-60753-5_17
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