Coverage-based lossy node localization in wireless sensor networks using Chi-square test

Locating lossy nodes in wireless sensor networks (WSNs) is difficult due to the large amount of sensor nodes, and their limited resources. 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 active and passive measurements to minimize testing cost and number of iterations. However, this hybrid approach has many limitations. Inspired by the success of statistic methods in coverage-based software testing, and the similarity between software testing and lossy node localization, we develop an improved approach by employing Chi-square test in WSN lossy node localization. Supported by well-established statistic theories, our elegant approach delivers great performance. Experiments on randomly generated networks and deployed networks show significant performance improvement using the proposed algorithm. We expect to use this approach for other diagnostic problems in WSNs.