Fault Diagnosis of Nodes in WSN Based on Particle Swarm Optimization
In the Wireless Sensor Network (WSN), the operation reliability is usually evaluated by processing the measured data of the network nodes. As the problems of the large energy consumption and complex calculation in traditional algorithms, a method for faul
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Fault Diagnosis of Nodes in WSN Based on Particle Swarm Optimization Chengbo Yu, Rui Li, Qiang He, Lei Yu and Jun Tan
Abstract In the Wireless Sensor Network (WSN), the operation reliability is usually evaluated by processing the measured data of the network nodes. As the problems of the large energy consumption and complex calculation in traditional algorithms, a method for fault diagnosis of nodes in WSN based on particle swarm optimization is proposed in the paper. The range of threshold value is obtained by optimizing the measured data of nodes according to the fast convergence rate and simple rules of characteristics of the PSO. The judgment of the nodes’ malfunction is determined by analyzing the relationship between the measured data and the range of threshold value. The experimental results show that the method of fault diagnosis can find the fault nodes promptly and effectively and improve the reliability of WSN greatly. Keywords Wireless sensor network (WSN) optimization (PSO)
Fault diagnosis Particle swarm
18.1 Introduction The research and innovate of WSN nodes’ hardware design, computing process, wireless communication, network protocol and energy efficient are put forward constantly in recent years and the demand of the network’s reliability and C. Yu (&) R. Li Q. He L. Yu J. Tan Research Institute of Remote Test and Control, Chongqing University of Technology, Chongqing 400054, People’s Republic China e-mail: [email protected] R. Li e-mail: [email protected]
W. Lu et al. (eds.), Proceedings of the 2012 International Conference on Information Technology and Software Engineering, Lecture Notes in Electrical Engineering 210, DOI: 10.1007/978-3-642-34528-9_18, Ó Springer-Verlag Berlin Heidelberg 2013
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sustainability is increasing, the fault diagnosis of nodes in WSN plays an important role in understanding the network’s state in real time [1]. But the probability of sensor nodes’ failure is much higher than other systems due to many inevitably factors and the complex and harsh environment. The fault nodes will reduce the service quality of the whole network and they will also produce or transmit wrong sensor data, these make the surveillance center can’t receive the correct detection information and then produce wrong decisions which may cause a heavy loss or even the whole network paralyzed. Therefore, the study for fault diagnosis of nodes in WSN is very necessary. Aiming at the merits and demerits of some typical algorithms for WSN nodes’ fault diagnosis (distributed Bayesian algorithms [2], weighted median fault detection [3] and distributed fault detection [4]), the worldwide scholars study a lot and put forward many other methods. Literature [5] puts forward a solution based on MANNA hierarchical structure topology, this method needs to do centralized diagnosis on nodes through external base stations and the communication cost is large. Literature [6] puts forward a method based on tree structure for WSN fault diagnosis, this method has a high diagnosis p
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