覆盖传感器网络中基于长度的无锚点分布式定位

B. Sau, K. Mukhopadhyaya
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引用次数: 6

摘要

集中式定位在汇集各个节点的接近度信息时消耗了大量的能量。相反,分布式算法通常只在每个节点上使用本地信息。文献中可用的大多数定位算法都是基于锚点的,或者它们以失去精度为代价来估计传感器的位置。本文提出了一种约束模型下基于无锚长度的分布式定位技术,解决了该问题的一个特殊情况。该模型假设传感器之间的所有已知距离都小于传感器之间的通信距离,而所有未知距离都大于传感器之间的通信距离。我们还假设通信距离至少是传感距离的两倍。假设感兴趣的领域中的每个点都被某个传感器覆盖。每个传感器用来自邻居的信息来定位它的一些邻居。每个节点只向相邻节点传递定位信息;从而减少网络上的流量。我们还表明,在该模型下,唯一定位所有传感器所需的时间与传感器数量呈线性关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Length-based anchor-free distributed localization in a covered sensor network
Centralized localization dissipates a lot of energy in pooling the proximity information of the individual nodes. In contrast a distributed algorithm usually uses only local information at each node. Most localization algorithms available in the literature are are anchor based or they estimate the position of the sensors at the cost of losing accuracy. In this paper, we propose an anchor-free length-based distributed localization technique under a restricted model which solves a specialized case of this problem. The model assumes that all known distances between the sensors are less than the communication range of the sensors and all unknown distances are greater. We also assume that communication range is at least twice as much as the sensing range. Every point in the field of interest is assumed to be covered by some sensor. Each sensor localizes some of its neighbours with information from its neighbours. Each node communicates information for localization to its neighbours only; thus reducing traffic over the network. We also show that, the time required to localize all sensors uniquely under this model is linear in the number of sensors.
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