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Reliable anchor node based range-free localization algorithm in anisotropic wireless sensor networks

机译:基于可靠的锚点基于各向异性无线传感器网络的无距离定位算法

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In the wireless sensor networks, location based applications require an accurate localization algorithm. To estimate location, each normal node, which do not know its own location, uses estimated distances to anchor nodes which have their own location. Hence, the estimation of distance is a key issue in the wireless sensor networks localization. Most previous works assume isotropic networks where approximate the shortest path distances to the Euclidian distances. These approaches cannot obtain accurate distance estimations in anisotropic networks where the shortest path distances are not linearly proportion to the Euclidian distances. In the anisotropic networks, the shortest path between two nodes may be detoured and its length may be estimated much larger than the corresponding Euclidean distance. Because of the phenomenon, it is important to select reliable anchor nodes which offer the precisely estimated distance. In this paper, we propose a reliable anchor node selection algorithm in the anisotropic networks. Each normal node selects the three anchor nodes with Triangular rule to enhance localization accuracy in the proposed algorithm. We also show that our scheme is reasonable through mathematical observation.
机译:在无线传感器网络中,基于位置的应用需要准确的本地化算法。为了估算位置,不知道其自己位置的每个正常节点都使用估计的距离来具有自己位置的锚点节点。因此,距离的估计是无线传感器网络本地化中的关键问题。最先前的作品假设各向同性网络,其中近似于欧几里德距离的最短路径距离。这些方法无法在各向异性网络中获得准确的距离估计,其中最短路径距离与欧几里德距离的最短路径距离不是线性比例。在各向异性网络中,两个节点之间的最短路径可以剥离,并且其长度可以估计大于相应的欧几里德距离。由于现象,选择提供精确估计距离的可靠锚点节点非常重要。在本文中,我们在各向异性网络中提出了一种可靠的锚点选择算法。每个正常节点选择具有三角规则的三个锚点节点,以提高所提出的算法中的本地化精度。我们还表明,我们的计划通过数学观察合理。

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