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A Distributed Localization Algorithm Based on Random Diffusion in WSN

机译:WSN中基于随机扩散的分布式定位算法

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摘要

In many applications of Wireless Sensor Networks, it is crucial to know the location of sensor nodes. The distribution of the sensor nodes in many scenes is not uniform. However, it is impossible to equip all nodes with GPS receivers or configure the location for each node manually. Thus many localization methods have been proposed, such as the classical multi-dimensional scaling(MDS) localization algorithm. However, it has a low accuracy in large scale of sensor network with a lot of nodes. Thus, a random diffusion distributed localization algorithm is proposed in this paper. Results of simulations show that all the nodes can find their positions in 15 rounds when the network has 200 nodes in a square network. The localization algorithm has less running time, and provides a lower complexity than the classical MDS algorithm. The precision of this localization technique is restricted by the number of anchor nodes, communication radius of sensor node and the connectivity of network.
机译:在无线传感器网络的许多应用中,了解传感器节点的位置至关重要。传感器节点在许多场景中的分布不均匀。但是,不可能为所有节点配备GPS接收器或手动配置每个节点的位置。因此,已经提出了许多定位方法,例如经典的多维缩放(MDS)定位算法。但是,它在具有大量节点的大规模传感器网络中具有较低的精度。因此,本文提出了一种随机扩散分布式定位算法。仿真结果表明,当一个正方形网络中有200个节点时,所有节点都可以在15轮内找到其位置。与经典的MDS算法相比,该定位算法具有更少的运行时间,并且提供了更低的复杂度。这种定位技术的精度受到锚节点数量,传感器节点通信半径和网络连通性的限制。

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