Brain Storm Optimization for Sensors’ Duty Cycle in Wireless Sensor Network

Abstract

Wireless Sensor Networks (WSNs) became one of the emergent networks that are used in many real life applications. They are also used in many of the critical applications such as battle field monitoring and health care. Therefore, sensor nodes are required to survive for long time. However, such nodes suffer from low memory, limited storage, limiting sensing and communication ranges, limited energy sources, and limited processing capabilities. One of the effective methods to save the nodes' energy is the duty cycling where some of the nodes can go to sleep while others can perform the required monitored field tasks. In this paper, we propose a new algorithm that utilizes the concept of the people thinking which the Brain Storming Optimization (BSO) for sensor nodes duty cycle management. Through extensive set of experiments using homogenous and heterogeneous WSNs, BSO seems to outperform the Non-duty cycle algorithm.