Locating sensors in the wild: pursuit of ranging quality

Localization is a fundamental issue of wireless sensor networks that has been extensively studied in the literature. The real-world experience from GreenOrbs, a sensor network system in the forest, shows that localization in the wild remains very challenging due to various interfering factors. In this paper we propose CDL, a Combined and Differentiated Localization approach. The central idea is that ranging quality is the key that determines the overall localization accuracy. In its unremitting pursuit of better ranging quality, CDL incorporates virtual-hop localization, local filtration, and ranging-quality aware calibration. We have implemented CDL and evaluated it by extensive experiments and simulations. The results demonstrate that CDL outperforms current state-of-art approaches with better accuracy, efficiency and consistent performance.

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