Wireless coverage optimization for robotic swarm in emergency scenario

2015 ◽  
Author(s):  
F. Viani ◽  
E. Giarola ◽  
P. Rocca ◽  
G. Oliveri ◽  
A. Massa
Keyword(s):  
Coverage Optimization ◽  
Emergency Scenario ◽  
Robotic Swarm ◽  
Wireless Coverage

Wireless Coverage Optimization Scheme based on Wi-Fi

2021 ◽  
Author(s):  
Bin Sun ◽  
Hongjian Liao ◽  
Kaixi Liu ◽  
Jianwen Ding ◽  
Wei Wang ◽  
...  
Keyword(s):  
Optimization Scheme ◽  
Coverage Optimization ◽  
Wireless Coverage

Automated Wireless Coverage Optimization With Controlled Overlap

2008 ◽  
Vol 57 (4) ◽  
pp. 2395-2403 ◽  
Author(s):  
D. Fagen ◽  
P.A. Vicharelli ◽  
J. Weitzen
Keyword(s):  
Coverage Optimization ◽  
Wireless Coverage

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 Enhanced Computational Intelligence Algorithm for Coverage Optimization of 6G Non-Terrestrial Networks in 3D Space

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 70419-70429
Author(s):  
Mohamed Abdel-Basset ◽  
Laila Abdel-Fatah ◽  
Khalid A. Eldrandaly ◽  
Nabil M. Abdel-Aziz
Keyword(s):  
Computational Intelligence ◽  
Coverage Optimization ◽  
3D Space ◽  
Intelligence Algorithm ◽  
Terrestrial Networks

Coverage optimization of VLC in smart homes based on improved cuckoo search algorithm

2017 ◽  
Vol 116 ◽  
pp. 63-78 ◽  
Author(s):  
Geng Sun ◽  
Yanheng Liu ◽  
Ming Yang ◽  
Aimin Wang ◽  
Shuang Liang ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Smart Homes ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Coverage Optimization ◽  
Improved Cuckoo Search Algorithm
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