Convex Voronoi space-partitioning for coverage purposes in heterogeneous sensor networks

This article addresses the problem of space-partitioning in heterogeneous sensor networks, where the nodes have uniform symmetric sensing patterns, though their maximum sensing distance differs. Inappropriateness of classical spatial Voronoi tessellation for coverage purposes is denoted, compared to the proposed space-partitioning technique, which takes into account this heterogeneity. Unlike weighted-Voronoi techniques, the latter's definition is reflected in a way that the assigned regions are convex sets, their construction is computationally-efficient, while special properties of Voronoi diagrams, which hold for homogeneous networks, are kept active. Simulation results confirm the efficacy of the proposed region-assignment scheme when dealing with heterogeneous networks, in contrast with classical Voronoi tessellation.