A novel energy-efficient sensor networks' fault diagnosis

Abstract

Aiming at the problem that the cluster head node is easy to cause misdiagnosis in the LEACH-DFD algorithm and the uneven energy consumption of nodes is easy to occur in sensor networks, a novel fault diagnosis algorithm for sensor networks based on clustering and double neighborhood median (CDMFD) is proposed in this paper. The algorithm introduces an energy-efficient clustering algorithm for clustering nodes. This algorithm makes the nodes with more residual energy have higher probability to be elected cluster head nodes, so as to avoid the problem of the uneven energy consumption of nodes. In order to avoid the misdiagnosis caused by the faulty cluster head nodes, the algorithm adds the process of diagnosis for cluster head nodes, and determines its final state. According to the final state of the cluster head nodes, the double-neighborhood median algorithm and the cluster head unidirectional diagnosis method are used to diagnose the fault nodes. The simulation results show that the proposed algorithm not only saves a lot of energy for the whole network, but also has a good diagnostic accuracy, while the false alarm rate is greatly reduced.