Weighted DV-Hop Localization Algorithm for Wireless Sensor Network based on Differential Evolution Algorithm

2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT) Pub Date : 2019-03-14 DOI:10.1109/INFOCT.2019.8710981

Ya-ping Huang, Linghua Zhang

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引用次数: 9

Abstract

In wireless sensor networks, DV-Hop localization algorithm which uses average hop distance to represent the actual distance is a commonly used range-free localization technology. But this algorithm has great error and node energy consumption in practical applications. Evolutionary algorithm has a branch which is differential evolution algorithm. DE algorithm has been widely used in a large number of fields, as a result of DE algorithm has simple structure and can combine with other methods easily. To solve the disadvantages of DV-Hop algorithm, an advanced DV-Hop localization algorithm on basic of differential evolution in this paper has been proposed. To reduce the hop distance error, the improved algorithm advances weighted process in the second step of DV-hop algorithm by leading the average hop distance error correction value. The differential evolution algorithm is used to optimize the positioning result of the unknown node in the third step of DV-hop algorithm. From the advanced localization algorithm’s simulation, the positioning accuracy has improved.

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基于差分进化算法的无线传感器网络加权DV-Hop定位算法

在无线传感器网络中，用平均跳距表示实际距离的DV-Hop定位算法是一种常用的无距离定位技术。但该算法在实际应用中存在较大的误差和节点能耗。进化算法的一个分支是差分进化算法。由于DE算法结构简单，易于与其他方法结合，因此在许多领域得到了广泛的应用。针对DV-Hop算法的不足，本文提出了一种基于差分进化的改进的DV-Hop定位算法。为了减小跳距离误差，改进算法在DV-hop算法的第二步中进行加权处理，引入平均跳距离误差修正值。在DV-hop算法的第三步中，采用差分进化算法对未知节点的定位结果进行优化。通过对先进定位算法的仿真，提高了定位精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)

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