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Enhancements of the Self-Detection Scheme for Boundary Recognition in Wireless Sensor Networks

We address the problem of boundary recognition in wireless sensor networks and propose a new self-detection algorithm that identifies the boundary of the network and available holes with high degree of accuracy and efficiency. It is a self-detection algorithm in which every node in the network determines its position, whether it resides on the boundary or inside the network. We show that our algorithm works accurately in networks with random and uniform distribution and consumes low energy. We explore sparse sensor networks with lower density, and examine the challenges towards the boundary recognition in sparse networks.