Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks.
Fiche publication
Date publication
février 2022
Journal
Sensors (Basel, Switzerland)
Auteurs
Membres identifiés du Cancéropôle Est :
Pr GOUTON Pierre
Tous les auteurs :
Tossa F, Abdou W, Ansari K, Ezin EC, Gouton P
Lien Pubmed
Résumé
Wireless sensor networks (WSNs) have several important applications, both in research and domestic use. Generally, their main role is to collect and transmit data from an ROI (region of interest) to a base station for processing and analysis. Therefore, it is vital to ensure maximum coverage of the chosen area and communication between the nodes forming the network. A major problem in network design is the deployment of sensors with the aim to ensure both maximum coverage and connectivity between sensor node. The maximum coverage problem addressed here focuses on calculating the area covered by the deployed sensor nodes. Thus, we seek to cover any type of area (regular or irregular shape) with a predefined number of homogeneous sensors using a genetic algorithm to find the best placement to ensure maximum network coverage under the constraint of connectivity between the sensors. Therefore, this paper tackles the dual problem of maximum coverage and connectivity between sensor nodes. We define the maximum coverage and connectivity problems and then propose a mathematical model and a complex objective function. The results show that the algorithm, called GAFACM (Genetic Algorithm For Area Coverage Maximization), covers all forms of the area for a given number of sensors and finds the best positions to maximize coverage within the area of interest while guaranteeing the connectivity between the sensors.
Mots clés
area coverage, connectivity, genetic algorithm, sensors deployment, wireless sensor networks
Référence
Sensors (Basel). 2022 Feb 22;22(5):