Solving coverage problem in wireless camera-based sensor networks by using a distributed evolutionary algorithm
Wireless camera-based sensor networks have developed as a main group of distributed intelligent systems. These systems involve huge number of low-power camera nodes to display an environment such as museums, military regions, airports, traffic control etc. One of the more important problems in smart networks is camera coverage control. It is necessary to allow automatic tracking of targets and monitoring the environment without human intervention, allowing these systems to scale. Since this problem is NP-hard, even for static targets, so Meta heuristic method such as genetic algorithm, Particle swarm optimization have been proposed to achieve near-optimal solution, which are with high time complexity. To overcome problem the distributed particle swarm optimization is examined in this paper. Simulation results show that the distributed particle swarm optimization results near-optimal solution faster.