Design optimization of wireless sensor networks in precision agriculture using improved BQIGSA

Using Wireless Sensor Networks (WSNs) is a new direction of research in agricultural and farming applications. Recently, WSNs are widely used in precision agriculture. One of the most important issues in WSNs is improving the energy consumption of the network while the special properties and the connectivity requirements are considered. In this study, a modified binary version of quantum-inspired gravitational search algorithm is developed to optimize the performance of the WSN used in precision agriculture. The proposed approach is applied to a WSN composed of sensor deployed in a farm to monitor the environmental conditions for a precision agriculture. The aim is to determine the operational mode of each sensor to improve the energy consumption and extend the life span of the network, taking into consideration the communication and application-specific requirements. To demonstrate the benefit of our proposed approach, which is called improved BQIGSA, a comparison between this approach and the existing methods including Binary Genetic Algorithm (BGA), Binary Particle Swarm Optimization (BPSO), the Quadrivalent Quantum-Inspired Gravitational Search Algorithm (QQIGSA) and the Binary Quantum-Inspired Gravitational Search Algorithm (BQIGSA) is given. The results of the performed experiments indicate the effectiveness of the WSN designed by the proposed modified BQIGSA in improving the energy consumption and subsequently prolonging the life span of the network.