Optimistic Attack Detection Using Triangular Mutation based Particle Swarm Optimization in Wireless Multimedia Sensor Networks

2018 ◽  
Author(s):  
Sandeep Kaur ◽  
Tejinder Sharma
Keyword(s):  
Particle Swarm Optimization ◽  
Sensor Networks ◽  
Particle Swarm ◽  
Attack Detection ◽  
Wireless Multimedia Sensor Networks ◽  
Wireless Multimedia ◽  
Swarm Optimization ◽  
Multimedia Sensor Networks

IADF security: insider attack detection using fuzzy logic in wireless multimedia sensor networks

2020 ◽  
Vol 24 (18) ◽  
pp. 13893-13902
Author(s):  
Ashwinth Janarthanan ◽  
Dhananjay Kumar ◽  
R. Remo Antony ◽  
C. B. Divya Parvathe
Keyword(s):  
Fuzzy Logic ◽  
Sensor Networks ◽  
Attack Detection ◽  
Wireless Multimedia Sensor Networks ◽  
Wireless Multimedia ◽  
Multimedia Sensor Networks ◽  
Insider Attack

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.

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