Abstract
To ensure the function of wireless sensor networks (WSNs), nodes that fail to forward packets must be localized efficiently and then fixed or replaced promptly. The state-of-the-art work frames lossy node localization in WSNs as an optimal sequential testing problem guided by end-to-end data. It combines both the active and passive measurements to minimize the testing cost and the number of iterations. However, this hybrid approach has many limitations. Inspired by the success of coverage-based software debugging, and the similarity between software debugging and lossy node localization, we propose a coverage-based lossy node detection for WSNs. Supported by established statistic theories, this approach greatly boosts the performance. Experiments on randomly generated networks and deployed networks show that the proposed algorithm can significantly reduce testing cost and number of iterations, which are the two optimization goals of previous work. We expect to use this approach for other diagnostic problems in WSNs.
Published Version
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