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A clustering method for wireless sensors networks

机译:无线传感器网络的聚类方法

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Clustering algorithms have been widely used in many domains so as to partition a set of elements into several subsets, each subset (or “cluster”) grouping elements which share some similarities. These algorithms are particularly useful in wireless sensor networks (WSNs), where they allow data aggregation and energy cuts. By forming clusters and electing cluster heads responsible for forwarding their packets, the small devices that compose WSNs have not to reach directly the base station (BS) of the network. They spare energy and they can lead further in time their measuring task, so as to detect forest fires or water pollution for example. In this paper, we will apply a new and general clustering algorithm, based on classificability and ultrametric properties, to a WSN. Our goal is to get clusters with a low computational complexity, but with an optimal structure regarding energy consumption.
机译:聚类算法已在许多领域中广泛使用,以便将一组元素划分为几个子集,每个子​​集(或“集群”)对具有相似性的元素进行分组。这些算法在无线传感器网络(WSN)中特别有用,在无线传感器网络中,它们允许数据聚合和能量削减。通过组建集群并选举负责转发其数据包的集群头,组成WSN的小型设备不必直接到达网络的基站(BS)。他们节省了能源,可以及时完成其测量任务,例如检测森林大火或水污染。在本文中,我们将基于分类性和超度量属性将一种新的通用聚类算法应用于WSN。我们的目标是使集群具有较低的计算复杂度,但具有关于能耗的最佳结构。

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