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Communication Dans Un Congrès Année : 2014

Optimized Sink node Deployment in WSN Using Genetic Algorithms through Coverage and Cost Constraints

Résumé

Wireless Sensor Networks (WSN) is the main infrastructure of a smart building. An optimal installation of a WSN is needed to ensure the best operating of the smart building. WSN suffer from a multitude of constraints, the major ones are: (1) optimal coverage (to ensure best QoS), (2) deployment cost (installation cost), and (3) network lifetime (network energy consumption). In order to ensure a WSN deployment that meets these three goals, we must formulate our problem as a multi-objective one, which can be solved by different methods. Find the optimal sensors positions in a deployment space can be considered as NP-hard problem [1]. If we consider a (M) deployment space and a set of (N) sensors to be deployed, the possible combination is equal to M!/(M-N)! [2]. Until this day, there are no specific solutions to deal with such problems. To get approximation of an optimal solution, the use of meta-heuristic methods is needed. In this paper, we attempt to propose a proper modeling of the three principal WSN deployment objectives. The deployment space is considered as a building. To solve the problem and to get optimal sensors positions we use MultiObjective Genetic Algorithms (MOGA).
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Dates et versions

hal-04099556 , version 1 (16-05-2023)

Identifiants

  • HAL Id : hal-04099556 , version 1

Citer

Mohamed Amin Benatia, M'hammed Sahnoun, Anne Louis, David Baudry, Bélahcène Mazari, et al.. Optimized Sink node Deployment in WSN Using Genetic Algorithms through Coverage and Cost Constraints. Internation Conference on Metaheuristics and Nature Inspired Computing, Oct 2014, Marrakech (MA), Morocco. ⟨hal-04099556⟩
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