A robust boundary detection algorithm based on connectivity only for 3D wireless sensor networks

In this work we develop a distributed boundary detection algorithm, dubbed Coconut, for 3D wireless sensor networks. It first constructs a tetrahedral structure to delineate the approximate geometry of the 3D sensor network, producing a set of "sealed" triangular boundary surfaces for separating non-boundary nodes and boundary node candidates. The former are hollowed out immediately while the latter are further refined to yield the final boundary nodes and fine-grained boundary surfaces. The proposed Coconut algorithm offers several salient features. First, it requires connectivity information only, with no need for localization or distance measurement. Second, it does not rely on particular communication models, but only assumes a constant maximum transmission range, which is generally known in practical wireless sensor networks. Third, it is robust to sensor distribution, effectively identifying boundaries in both uniformly and non-uniformly distributed sensor networks. We prove the correctness of the algorithm and quantitatively demonstrate its effectiveness via simulations under various network models.