Coverage Improvement Strategy Based on Voronoi for Directional Sensor Networks

Nowadays, directional sensor networks (DSNs) have drawn a lot of attentions, which are made up of a large number of tiny directional sensors that are different from traditional omnidirectional sensors. Directional sensor is characterized by working direction and angle of view (AOV). In this paper we study area coverage of DSNs. We exploit Voronoi theory to divide sensors into polygons, by optimizing the local coverage in each polygon to achieve the overall coverage. We take full use of Voronoi vertexes and edges to judge whether a sensor gets full coverage inside in current polygon, if not, then the sensor calls Move Inside Cell Algorithm (MIC) and Rotate Working Direction Algorithm (RWD) algorithms we have designed. Compared to the similar methods to solve this question our algorithms are relatively simple and moving distance is shorter. Simulation results reveal that our algorithms outperform some existing methods in term of the area coverage.