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LACFA: an algorithm for localization aware cluster formation in wireless sensor networks

机译:LACFA:无线传感器网络中用于本地化感知群集形成的算法

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摘要

The ability of a sensor node to determine its position is a fundamental requirement for many applications in wireless sensor networks (WSNs). In this article, we address a scenario where a subset of sensors, called anchor nodes, knows its own position and helps other nodes determine theirs through range-based positioning techniques. Such techniques benefit from a high degree of connectivity, since range measurements from at least four anchor nodes are necessary (three-dimensional scenario). On the other hand, WSN topologies, most notably the cluster-tree topology, tend to limit connectivity between nodes to save energy. This results in very poor performance of the network in terms of localization. In this article, we propose LACFA, a network formation algorithm that increases the probability of localization of sensors in a cluster-tree topology. It does so by properly allocating anchor nodes to different clusters during the network formation phase. Our algorithm achieves very high localization probability when compared with existing cluster formation algorithms, at no additional cost. Moreover, a distributed cluster formation algorithm, with no need for any centralized information exchange mechanisms, is defined.
机译:传感器节点确定其位置的能力是无线传感器网络(WSN)中许多应用程序的基本要求。在本文中,我们解决了一个场景,其中一个传感器子集(称为锚节点)知道其自身位置,并通过基于范围的定位技术帮助其他节点确定它们的位置。这样的技术得益于高度的连通性,因为必须至少测量四个锚节点的距离(三维场景)。另一方面,WSN拓扑(最著名的是群集树拓扑)倾向于限制节点之间的连接以节省能源。在本地化方面,这导致网络的性能非常差。在本文中,我们提出了LACFA,这是一种网络形成算法,可增加簇树拓扑中传感器定位的可能性。它是通过在网络形成阶段将锚点节点适当地分配给不同的群集来实现的。与现有的簇形成算法相比,我们的算法实现了很高的定位概率,而无需任何额外费用。此外,定义了不需要任何集中式信息交换机制的分布式集群形成算法。

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