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Localization in sparse networks using sweeps

机译:使用扫描在稀疏网络中进行本地化

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摘要

Determining node positions is essential for many next-generation network functionalities. Previous localization algorithms lack correctness guarantees or require network density higher than required for unique localizability. In this paper, we describe a class of algorithms for fine-grained localization called Sweeps. Sweeps correctly finitely localizes all nodes in bilateration networks. Sweeps also handles angle measurements and noisy measurements. We demonstrate the practicality of our algorithm through extensive simulations on a large number of networks, upon which it consistently localizes one-thousand-node networks of average degree less than five in less than two minutes on a consumer PC.
机译:确定节点位置对于许多下一代网络功能至关重要。以前的定位算法缺乏正确性保证,或者需要的网络密度高于独特的定位能力。在本文中,我们描述了一类用于细粒度定位的算法,称为 Sweeps 。正确扫描 biliteration 网络中的所有节点有限地定位。扫描还处理角度测量和噪声测量。通过在大量网络上进行广泛的仿真,我们证明了该算法的实用性,在此基础上,该算法始终在不到两分钟的时间内将本地度小于5的一千个节点网络定位在消费类PC上。

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