Improved area estimates for localization in wireless sensor networks

V. A. Pillai, W. Seah, Y. Chew
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引用次数: 1

Abstract

To accurately determine the location of every sensor in large wireless sensor networks is normally very computation intensive and hence, is not cost-effective. On the other hand, a coarse estimate of the sensors' location is usually sufficient for many applications. The Area Localization Scheme (ALS) has been proposed as a scheme that estimates the position of every sensor within a certain region rather than identifying its exact location. Experimental results have shown that ALS is a promising technique with an accuracy of over 80% of sensors successfully localized. However, the accuracy of the scheme is dependent of the location of the sensors, as the regions into which the sensors are localized are not of uniform sizes. If a sensor is predicted to lie in a small region, then there is a higher probability that the prediction is inaccurate, and vice versa. In this paper, we aim to correct such discrepancy in defining positioning error. We propose to aggregate smaller regions to form more uniform regions within which nodes are localized. This effort improves the overall scheme's accuracy according to some predefined threshold.
改进的无线传感器网络定位区域估计
在大型无线传感器网络中,要准确地确定每个传感器的位置通常需要大量的计算,因此成本效益不高。另一方面,对传感器位置的粗略估计通常对许多应用来说是足够的。区域定位方案(Area Localization Scheme, ALS)是一种估计每个传感器在特定区域内的位置而不是确定其确切位置的方案。实验结果表明,ALS是一种很有前途的技术,传感器的定位精度超过80%。然而,该方案的精度依赖于传感器的位置,因为传感器定位到的区域不是均匀的大小。如果一个传感器被预测位于一个小区域,那么预测不准确的概率就会更高,反之亦然。本文旨在纠正定位误差定义上的这种差异。我们建议将较小的区域聚集在一起,形成更均匀的区域,在这些区域内节点被定位。这项工作根据一些预定义的阈值提高了整体方案的准确性。
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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