Wireless Sensor Network deployment using a variable-length genetic algorithm

The Sensor Deployment Problem (SDP) is one of the most studied problems in the field of Wireless Sensor Networks (WSNs). It can generally be defined as selecting the sensors locations in a specified Region of Interest (RoI) to achieve one or more design objectives of the WSN. Two of the commonly required design objectives are maximizing coverage and minimizing the deployment cost of the WSN. In this paper, we address the SDP of covering a finite set of target locations in a specified RoI using non-homogenous, non-isotropic sensors with minimum sensor deployment cost. We propose a novel approach for solving the SDP using a Variable-Length Genetic Algorithm (VLGA). We apply our proposed algorithm on a WSN surveillance case-study to evaluate its performance. Based on the experimental results, we show that our proposed algorithm outperforms an existing approach which uses a Fixed-Length GA (FLGA) in terms of the quality of obtained solutions, speed of convergence and scalability.