Energy Efficient Sink Placement in Wireless Sensor Networks by Brain Storm Optimization Algorithm

Wireless sensor networks represent one of the most promising technologies whose use has significantly increased in the past years. They are used in various applications such as health care monitoring, surveillance and monitoring in agriculture, industrial monitoring, habitat and underwater monitoring, etc. Deployment of the wireless sensor networks introduces number of hard optimization problems. Placement of the elements such as sensors, gateways, sinks and base stations, depend on different conditions and constraints such as signal propagation, distance, energy preservation, reliability. In this paper, we propose a method based on brain storm optimization algorithm for placing multiple sinks in a network consisting of regular sensors and gateways with higher battery capacity. Regular sensor nodes are statically organized in clusters around gateways considering not only distance but also energy efficiency. Gateways communicate with sinks for which optimal positions need to be determined. Location problems are in general difficult and in this case requirement of minimizing the energy additionally complicates the problem. The simulation results report estimation of the network life time. Obtained results have shown that our proposed method outperformed particle swarm optimization based method from literature in terms of mentioned metrics.