DocumentCode :
265494
Title :
Performance analysis of evolutionary multi-objective based approach for deployment of wireless sensor network with the presence of fixed obstacles
Author :
Syarif, Abdusy ; Abouaissa, Abdelhafid ; Idoumghar, Lhassane ; Sari, Riri Fitri ; Lorenz, Pascal
Author_Institution :
Univ. of Haute Alsace, Mulhouse, France
fYear :
2014
fDate :
8-12 Dec. 2014
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, a study about wireless sensor network (WSN) deployment strategy is demonstrated and made workable for the use of multi-objective approach. The development of sensor nodes by considering multiple objectives and existence of fixed obstacles is an important optimization problem. There are two objectives in this study, connectivity and coverage as two fundamental issues in wireless sensor networks deployment. In this work a multi-objective evolutionary algorithms based on elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed to address this problem. Two proposed functions, ranking function and fitness function, are used to determine the best optimal solution from Pareto optimal fronts. Further we presented simulation and analysis to verify and validate the deployment of wireless sensor network in area with the presence of permanent obstacles.
Keywords :
Pareto optimisation; genetic algorithms; sensor placement; wireless sensor networks; NSGA-II; Pareto optimal fronts; WSN deployment strategy; fitness function; multiobjective evolutionary algorithms; nondominated sorting genetic algorithm; ranking function; sensor nodes; wireless sensor network deployment; Algorithm design and analysis; Genetic algorithms; Robot sensing systems; Sociology; Statistics; Throughput; Wireless sensor networks; Deployment; Genetic Algorithm; Multi-objective optimization; Obstacle; Wireless Sensor Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Communications Conference (GLOBECOM), 2014 IEEE
Conference_Location :
Austin, TX
Type :
conf
DOI :
10.1109/GLOCOM.2014.7036775
Filename :
7036775
Link To Document :
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