TY - GEN
T1 - Three-dimensional deployment optimization of sensor network based on an improved Particle Swarm Optimization algorithm
AU - Lian, Xiao Yan
AU - Zhang, Juan
AU - Chen, Chen
AU - Deng, Fang
PY - 2012
Y1 - 2012
N2 - Compared with the traditional two-dimensional (2D) deployment form, three-dimensional (3D) deployment of sensor network has greater research significance and practical potential to satisfy the detecting needs of targets with complex properties. In this paper, a method for 3D deployment optimization of sensor network based on an improved Particle Swarm Optimization (PSO) algorithm is proposed. Many factors such as coverage scale, detection probability and resource utilization are synthetically considered to optimize the sensor network's overall detection performance. To evaluate the network's performance, four indexes are presented and the 3D deployment space is divided into different height levels. Accordingly, the mathematical model is formulated by weighting the performance indexes and height levels due to their importance degrees. In order to solve the optimization problem, an algorithm called WCPSO is carried out, which has a dynamic inertia weight and adaptable acceleration constants. Verified by the simulation results, the presented 3D deployment optimization method effectively improves the sensor network's detection performance. The method in this paper can provide guidance and technical reference in future application of relevant research.
AB - Compared with the traditional two-dimensional (2D) deployment form, three-dimensional (3D) deployment of sensor network has greater research significance and practical potential to satisfy the detecting needs of targets with complex properties. In this paper, a method for 3D deployment optimization of sensor network based on an improved Particle Swarm Optimization (PSO) algorithm is proposed. Many factors such as coverage scale, detection probability and resource utilization are synthetically considered to optimize the sensor network's overall detection performance. To evaluate the network's performance, four indexes are presented and the 3D deployment space is divided into different height levels. Accordingly, the mathematical model is formulated by weighting the performance indexes and height levels due to their importance degrees. In order to solve the optimization problem, an algorithm called WCPSO is carried out, which has a dynamic inertia weight and adaptable acceleration constants. Verified by the simulation results, the presented 3D deployment optimization method effectively improves the sensor network's detection performance. The method in this paper can provide guidance and technical reference in future application of relevant research.
KW - 3D deployment optimization
KW - WCPSO
KW - sensor network
UR - http://www.scopus.com/inward/record.url?scp=84872323786&partnerID=8YFLogxK
U2 - 10.1109/WCICA.2012.6359220
DO - 10.1109/WCICA.2012.6359220
M3 - Conference contribution
AN - SCOPUS:84872323786
SN - 9781467313988
T3 - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
SP - 4395
EP - 4400
BT - WCICA 2012 - Proceedings of the 10th World Congress on Intelligent Control and Automation
T2 - 10th World Congress on Intelligent Control and Automation, WCICA 2012
Y2 - 6 July 2012 through 8 July 2012
ER -