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首页> 外文期刊>Internet of Things Journal, IEEE >Fuzzy Weighted Centroid Localization With Virtual Node Approximation in Wireless Sensor Networks
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Fuzzy Weighted Centroid Localization With Virtual Node Approximation in Wireless Sensor Networks

机译：无线传感器网络中带有虚拟节点逼近的模糊加权质心定位

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摘要

Due to their low cost, various range-free localization techniques are widely applied to estimate device locations in wireless sensor networks (WSNs), especially where other communication signals, such as those from a global positioning system, are absent. Among range-free techniques, the centroid algorithm has gained popularity because of its simplicity and low computational cost, rendering it suitable for power-sensitive sensor nodes or nodes. WSN topologies are unpredictable because sensor nodes are often deployed at arbitrary locations, making it difficult for sufficient numbers of known (anchor) nodes to cover all unknown nodes. Consequently, both centroid algorithm and its enhanced versions [e.g., weighted centroid (WC) algorithms] yield relatively high localization inaccuracy. In this paper, to successfully form anchor-node triangles, we propose a low-cost technique to determine the number of virtual anchor nodes or virtual nodes together with their positions. Specifically, we develop and provide proof for accurate approximate unknown node sides. We also improve localization accuracy by adding virtual nodes that collaborate with physical anchor nodes to provide the necessary coverage of the unknown nodes. We address estimations of unknown node locations by applying a fuzzy-based centroid localization method to prioritize anchor nodes by assigning different fine-tuned weighted factors. The results show that the proposed algorithm outperforms state-of-the-art fuzzy-based localization techniques for WC algorithms.
机译：由于其低成本，各种无范围定位技术被广泛应用于估计无线传感器网络（WSN）中的设备位置，尤其是在缺少其他通信信号（例如来自全球定位系统的通信信号）的情况下。在无范围技术中，质心算法因其简单性和较低的计算成本而得到普及，使其适用于对功率敏感的传感器节点或节点。 WSN拓扑不可预测，因为传感器节点通常部署在任意位置，这使得足够数量的已知（锚定）节点难以覆盖所有未知节点。因此，质心算法及其增强版本[例如，加权质心（WC）算法]都产生相对较高的定位误差。在本文中，为了成功地形成锚节点三角形，我们提出了一种低成本的技术来确定虚拟锚节点或虚拟节点的数量及其位置。具体来说，我们开发并提供了精确的近似未知节点边的证明。我们还通过添加与物理锚节点协作以提供未知节点的必要覆盖范围的虚拟节点来提高定位精度。我们通过应用基于模糊的质心定位方法通过分配不同的微调加权因子来对锚节点进行优先级排序，从而解决了未知节点位置的估计问题。结果表明，所提出的算法优于WC算法的最新的基于模糊的定位技术。

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