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A Distributed Range-free Localization Algorithm Based on Optimum Distance Derivation in Wireless Sensor Networks

机译:一种基于无线传感器网络中最佳距离推导的分布式无距离定位算法

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In this paper a distributed range-free localization algorithm based on optimum distance derivation is proposed for three-dimensional wireless sensor networks (WSNs). The algorithm presented in this paper is specified for WSNs in which anchor deployment is very sparse and communication range of each sensor is highly limited. A localization model is designed and evaluated in this paper. Based on this model, the shared relay nodes are formulated in the intersected space for any two sensor nodes within one or two hops. A distance calculation mechanism using the number of shared relay nodes is introduced by the geometrical relationships and probability distributions, which solves the error accumulation and low coverage problem in WSNs. With this mechanism the corresponding distance between any two sensor nodes can be determined using the number of shared relay nodes with minimum errors and high efficiency. Combining with the multi-hop characteristic of the network, unknown nodes establish distance connections with all anchors by hop distances and hop counts, whose final coordinates are then obtained with the least-square approximation. The proposed algorithm only depends on the connection information, which is quite suitable for self-organized Ad-hoc network. Another two different types of anchor node deployment are taken into account in the experiments. Comparisons are made with classic DV-Hop, Centroid and MDS-MAP algorithms. Experimental results prove the proposed algorithm is better in localization accuracy with high efficiency and 100% of localization rate in all parameter settings, as well as low localization cost. The average accuracy improvements in all kinds of circumstances are 74.76%, 79.32%, and 54.47% better compared with the classic DV-Hop, Centroid and MDS-MAP.
机译:在本文中,提出了一种基于最佳距离推导的分布式无距离定位算法,用于三维无线传感器网络(WSN)。本文呈现的算法针对WSN指定了其中锚部署是非常稀疏,并且每个传感器的通信范围非常有限。本文设计和评估了本地化模型。基于该模型,共享中继节点在一个或两个跳线内的任何两个传感器节点的相交空间中配制。通过几何关系和概率分布引入了使用共享中继节点数量的距离计算机制,其解决了WSN中的误差累积和低覆盖问题。利用该机制,可以使用具有最小误差和高效率的共享中继节点的数量来确定任意两个传感器节点之间的相应距离。结合网络的多跳特性,未知节点通过跳距和跳数建立与所有锚点的距离连接,然后通过最小二乘近似获得其最终坐标。所提出的算法仅取决于连接信息,这非常适合自组织的ad-hoc网络。在实验中考虑另外两种不同类型的锚点部署。使用经典DV-Hop,质心和MDS-MAP算法进行比较。实验结果证明了所提出的算法以高效率和100%的定位率在所有参数设置中的算法以及低位定位成本低100%。与经典的DV-Hop,Centroid和MDS-Map相比,各种情况下,各种情况的平均准确性提高为74.76%,79.32%和54.47%。

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