scholarly journals An Energy Efficiency Node Scheduling Model for Spatial-Temporal Coverage Optimization in 3D Directional Sensor Networks

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 4408-4419 ◽  
Author(s):  
Chong Han ◽  
Lijuan Sun ◽  
Fu Xiao ◽  
Jian Guo
Keyword(s):  
Energy Efficiency ◽  
Sensor Networks ◽  
Directional Sensor Networks ◽  
Coverage Optimization ◽  
Node Scheduling ◽  
Scheduling Model ◽  
Temporal Coverage ◽  
Directional Sensor

scholarly journals Virtual Angle Boundary-Aware Particle Swarm Optimization to Maximize the Coverage of Directional Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2868
Author(s):  
Gong Cheng ◽  
Huangfu Wei
Keyword(s):  
Particle Swarm Optimization ◽  
Sensor Networks ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
The Internet ◽  
Directional Sensor Networks ◽  
Swarm Optimization ◽  
Coverage Optimization ◽  
Boundary Constraint ◽  
Directional Sensor

With the transition of the mobile communication networks, the network goal of the Internet of everything further promotes the development of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs). Since the directional sensor has the performance advantage of long-term regional monitoring, how to realize coverage optimization of Directional Sensor Networks (DSNs) becomes more important. The coverage optimization of DSNs is usually solved for one of the variables such as sensor azimuth, sensing radius, and time schedule. To reduce the computational complexity, we propose an optimization coverage scheme with a boundary constraint of eliminating redundancy for DSNs. Combined with Particle Swarm Optimization (PSO) algorithm, a Virtual Angle Boundary-aware Particle Swarm Optimization (VAB-PSO) is designed to reduce the computational burden of optimization problems effectively. The VAB-PSO algorithm generates the boundary constraint position between the sensors according to the relationship among the angles of different sensors, thus obtaining the boundary of particle search and restricting the search space of the algorithm. Meanwhile, different particles search in complementary space to improve the overall efficiency. Experimental results show that the proposed algorithm with a boundary constraint can effectively improve the coverage and convergence speed of the algorithm.

scholarly journals Local Coverage Optimization Strategy Based on Voronoi for Directional Sensor Networks

Sensors ◽  
2016 ◽  
Vol 16 (12) ◽  
pp. 2183 ◽  
Author(s):  
Guanglin Zhang ◽  
Shan You ◽  
Jiajie Ren ◽  
Demin Li ◽  
Lin Wang
Keyword(s):  
Sensor Networks ◽  
Optimization Strategy ◽  
Directional Sensor Networks ◽  
Coverage Optimization ◽  
Directional Sensor

scholarly journals Voronoi-Based Coverage Optimization for Directional Sensor Networks

2009 ◽  
Vol 01 (05) ◽  
pp. 417-424 ◽  
Author(s):  
Jing LI ◽  
Ruchuan WANG ◽  
Haiping HUANG ◽  
Lijuan SUN
Keyword(s):  
Sensor Networks ◽  
Directional Sensor Networks ◽  
Coverage Optimization ◽  
Directional Sensor
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