Energy Optimization in Wireless Sensor Networks Using Grey Wolf Optimizer

Wireless Sensor Network (WSN) has some great advantages such as various communication and arrangement, low power consumption and low cost. These sensors are small in size and they can carry out the process of sensing events and communicate with each other. These networks are used to detect events or phenomena, collect and process data, and send sensory information to the user. In WSNs, due to the short battery life span of sensors, optimal energy consumption has always been a challenge. In this paper, an energy optimization method is proposed using Grey Wolf Optimization and Genetic algorithms for communications. The proposed method uses different energy model to optimize energy consumption with an arbitrary set of parameters. Simulation results show that the proposed method has a good performance in terms of energy consumption and network lifetime compared with the similar method.