A lower bound on range-free node localization algorithms

S. MacLean, S. Datta
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引用次数: 10

Abstract

Wireless sensor networks have been used in proposed solutions to many important practical problems. A very important problem in many wireless sensor networks is localization, or the determination of geographical locations of the sensor nodes. In this work, we study the problem of range-free localization-or computing locations based only on the neighborhood information of nodes. These algorithms typically assume that a fraction of the sensor nodes (called seeds) know their location at all times, by using GPS or other means. Other nodes compute their locations by exchanging information with their neighbors. A lower bound on the expected maximum achievable accuracy of range-free localization algorithms was presented in Nagpal et al., 2003. This bound has been widely quoted in the literature and has been extended by Hu and Evans, 2004. In this paper, we show that the previous argument used is incorrect and prove a correct lower bound. We compare our analytical results with measurements from simulation experiments. Finally, we discuss why bounds obtained using this argument may not be tight and how better bounds may be proved.
无距离节点定位算法的下界
无线传感器网络已被用于解决许多重要的实际问题。在许多无线传感器网络中,一个非常重要的问题是定位,或确定传感器节点的地理位置。在这项工作中,我们研究了无距离定位问题-或仅基于节点的邻域信息计算位置。这些算法通常假设一小部分传感器节点(称为种子)通过使用GPS或其他手段随时知道它们的位置。其他节点通过与邻居交换信息来计算它们的位置。Nagpal et al., 2003提出了无距离定位算法期望最大可实现精度的下界。这一界限在文献中被广泛引用,并由Hu和Evans(2004)扩展。在本文中,我们证明了先前使用的论点是不正确的,并证明了一个正确的下界。我们将分析结果与模拟实验的测量结果进行了比较。最后,我们讨论了为什么用这个论证得到的界可能不是紧的,以及如何证明更好的界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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