Covering a 3D flat surface with autonomous and mobile wireless sensor nodes

International audienceWireless Sensor Networks (WSNs) are used in a wide range of applications due to their monitoring and tracking abilities. Depending on the applications goals, sensor nodes are deployed either in a two dimensional (2D) area or in a three-dimensional (3D) area. In addition, WSN deployment can be either in a distributed or a centralized manner. In this paper, we are interested in a fully distributed deployment of WSN in several 3D-flat-surface configurations using autonomous and mobile nodes. Our goal is to ensure full 3D flat surfaces coverage and maintain network connectivity for these surfaces. To reach our goal we propose 3D-DVFA-FSC, a distributed deployment algorithm based on virtual forces strategy to move sensor nodes over different 3D-flat-surface shapes. Simulation results show that 3D-DVFA-FSC provides a full coverage rate regardless of the 3D-flat-surface configuration while maintaining network connectivity

Clusterización y triangulación de redes inalámbricas heterogéneas para la infraestructura de medición avanzada de energía eléctrica

This article is intended to comparing clustering algorithms, triangulation and minimal spanning tree on heterogeneous networks raises them to be applied for the deployment of the communications network of the advanced metering infrastructure, important for the development of smart grids as regards stage the exchange of information between the smart meter customer and electricity distribution companies, thus forming a neighborhood area network (NAN). Clustering algorithms compared here warn georeferenced scenarios to bind and form clusters of smart meters; Furthermore triangulation algorithms are employed to solve scenarios betwen regions to form segments of a neighborhood area network. On the other hand, they hope to know the best algorithm comparing the performance and the algorithm that minimizes the number of cluster to cover all meter population. Moreover, the algorithm helps to optimize the minimal spanning tree to connect the clusters obtaining the best coverage through the union of Vononi-Delaunay for triangulation.En este artículo se plantea la comparación de algoritmos de clusterización, triangulación y el árbol de mínima expansión sobre redes heterogéneas inalámbricas, los mismos que se aplicarán para el despliegue de la red de comunicaciones de la infraestructura de medición avanzada, etapa importante para el desarrollo de redes eléctricas inteligentes en lo que respecta al intercambio de información entre el medidor inteligente del cliente y las empresas de distribución eléctrica, formando así una red de área de vecindario. Los algoritmos de clusterización comparados con el trabajo advierten escenarios geo-referenciados para aglutinar y formar conglomerados de medidores inteligentes; por otro lado los algoritmos de triangulación se usan para escenarios entre regiones para formar los sectores de la red de área de barrio. En un segundo instante se espera conocer el algoritmo que tiene un mejor rendimiento, minimice la cantidad de clústeres necesarios para aglutinar la población de medidores y luego permita optimizar mejor el árbol de expansión para la conexión de clústeres obteniendo la mejor cobertura por medio de la dualidad Voronoi-Delaunay

Optimal surface deployment problem in wireless sensor networks

Abstract—Sensor deployment is a fundamental issue in a wireless sensor network, which often dictates the overall network performance. Previous studies on sensor deployment mainly focused on sensor networks on 2D plane or in 3D volume. In this paper, we tackle the problem of optimal sensor deployment on 3D surfaces, aiming to achieve the highest overall sensing quality. In general, the reading of a sensor node exhibits unreliability, which often depends on the distance between the sensor and the target to be sensed, as observed in a wide range of applications. Therefore, with a given set of sensors, a sensor network offers different accuracy in data acquisition when the sensors are deployed in different ways in the Field of Interest (FoI). We formulate this optimal surface deployment problem in terms of sensing quality by introducing a general function to measure the unreliability of monitored data in the entire sensor network. We present its optimal solution and propose a series of algorithms for practical implementation. Extensive simulations are conducted on various 3D mountain surface models to demonstrate the effectiveness of the proposed algorithms. I