An Optimal Deployment Wireless Sensor Network Based on Compact Differential Evolution

This paper proposes a compact Differential Evolution (namely cED) for optimizing the deployment Wireless Sensor Network (WSN). The optimal scheme for deploying WSN should be a light and efficient algorithm because WSN limitations of size, memory, battery power, and computation. The proposed cDE uses a probabilistic model to generate candidate solutions for locating the promising area in search space. The solution of the population-based algorithm is expressed its distributed probability and is responding the order-one behavior for DE. So that cDE is a light and efficient tool that is suitable for deploying WSN. Simulation results are compared with the original and the other methods in the literature e.g. LEACH, LEACH-C, and HEED shows that the proposed method is the better performance regarding residual energy, nodes alive, and received items to save the energy of nodes.