Distributed energy-efficient wireless sensing and information fusion via event-driven and state-rank activation

The dynamic management of sensor nodes and advanced information fusion are necessary technologies to enhance the comprehensive performance of sensor networks. This paper presents a cascaded sensor dynamic activation and information fusion algorithm to simultaneously optimize the energy and sensing performance of wireless sensing networks. The proposed algorithm dynamically activates nodes that are most suitable for the current sensing task through a joint event-driven and state ranking activation algorithm that achieves a better sensing performance with lower energy costs. In addition, it further utilizes the sensing information of all the activated nodes with maximum efficiency, through an improved distributed Kalman information fusion, which achieves an extra improvement in sensing accuracy as measured by the minimum variance. Finally, the superiority of the proposed cascaded algorithm is verified by a simulation comparison, achieving almost zero dead nodes in terms of energy, and a 62.1% decrease in average error in terms of sensing.