Boundary Reconstruction for Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) are critical for various applications ranging from environment monitoring to industrial monitoring. The varying and continuously growing interest in this field demands an understanding of the sensor node distribution to ensure robustness and to improve resource utilization for data processing and decision making. In this paper, we focus on reconstructing the boundaries of a wireless sensor network, which also has a lot of applications in IoT and Robotics. As these sensor node locations can be considered as a set of points in the 2D plane, boundary detection of a WSN can be related to classical shape reconstruction problem in Computational Geometry. In this paper, we extend a simple and generic strategy for hole detection to a geometric solution for boundary/shape reconstruction. Furthermore, we introduce a simple and controllable heuristic algorithm to patch the coverage holes identified by our boundary reconstruction algorithm. Not only does this study improve the reliability of WSNs, but it also provides a useful tool for the extensive domain of computational geometry and shape analysis. Our different experiments show that the proposed reconstruction algorithm outperforms the existing state-of-the-art methods, and hole patching gives a simple and controllable solution for mobile node placement.

Keywords

• Shape reconstruction
• Delaunay triangulation
• coverage hole detection
• dynamic node placement
• coverage optimization