Particle Swarm Optimization Algorithms for Maximizing Area Coverage in Wireless Sensor Networks
Nowadays, Wireless Sensor Network (WSN) systems appear to be the solution to many industrial applications in a wide range of fields due to their flexibility and scalability. However, limited coverage remains as one major defect of such systems and multiple problems had been proposed investigating practical parameters such as sensing range and obstacles. This paper tackles the area coverage optimization problem with respect to a given number of sensors having different sensing ranges. In order to solve this NP hard problem, two algorithms named Particle Swarm Optimization (PSO) and Democratic Particle Swarm Optimization (DPSO) algorithms are proposed in this paper. Two proposed algorithms are experimented on 15 instances constructed for this problem and the results are compared to other methods. The experimental results showcase a considerable improvement compared to the existing genetic algorithm in term of execution time and quality of solution.