2D wireless sensor network deployment based on Centroidal Voronoi Tessellation

In recent years, Wireless Sensor Networks (WSNs) have rapidly evolved and now comprise a powerful tool in monitoring and observation of the natural environment, among other fields. The use of WSNs is critical in early warning systems, which are of high importance today. In fact, WSNs are adopted more and more in various applications, e.g. for fire or deformation detection. The optimum deployment of sensors is a multi-dimensional problem, which has two main components; network and positioning approach. Although lots of work has dealt with the issue, most of it emphasizes on mere network approach (communication, energy consumption) and not on the topography (positioning) of the sensors in achieving ideal geometry. In some cases, it is hard or even impossible to achieve perfect geometry in nodes’ deployment. The ideal and desirable scenario of nodes arranged in square or hexagonal grid would raise extremely the cost of the network, especially in unfriendly or hostile environments. In such environments the positions of the sensors have to be chosen among a list of possible points, which in most cases are randomly distributed. This constraint has to be taken under consideration during the WSN planning. Full geographical coverage is in some applications of the same, if not of greater, importance than the network coverage. Cost is a crucial factor at network planning and given that resources are often limited, what matters, is to cover the whole area with the minimum number of sensors. This paper suggests a deployment method for nodes, in large scale and high density WSNs, based on Centroidal Voronoi Tessellation (CVT). It approximates the solution through the geometry of the random points and proposes a deployment plan, for the given characteristics of the study area, in order to achieve a deployment as near as possible to the ideal one.