A Fault Detection Method Based On Dirichlet Reputation For Wirelsee Sensor Networks

Wireless sensor networks often consist of a large number of low-cost sensor nodes, which are deployed in extreme environment to collect data and monitor some interest things. Due to limitations in available resources, such as power, memory and computing capability, sensor nodes, operating in an unattended mode, have higher fault rates than traditional network nodes. Therefore, the fault detection for wireless sensor networks has a very important theoretical and practical significance.Fault detection in wireless sensor network means to monitor the working condition of the sensor nodes and get some information of the failed nodes. The research content and results are as follows.1) With the limited energy in wireless sensor network, considering the physical makeup of the sensor nodes and distribution of energy consumption, we propose the neighbor nodes selection algorithm. The algorithm, starting from the point of view of energy savings, under the premise of a tolerable fault detection performance, only select some key nodes as the neighbor nodes to participate the comparison in the fault detection algorithm. The neighbor nodes selection algorithm not only ensures the accuracy of fault detection, but also avoids the excessive consumption of energy, which extend the life of the network effectively.2) In order to make full use of the historical data, the paper, based on the Dirichlet distribution function, establishes a reputation function for each sensor node and proposes the fault detection algorithm for wireless sensor networks. Besides, the fault detection algorithm only selects some key nodes to participate the comparison, which help to save energy greatly. The algorithm consists of measurement module, reputation updating module and fault judgement module. The health level of sensor node was calculated in measurement module. The reputation updating module is responsible for maintaining and updating the reputation of the sensor node. Fault judgment module determines whether a node is faulty or not, and whether the sensitive event happens or not.