Fault detection algorithm for sensor network based on tendency-similarity

被引：0
作者：
Fu X. [1 ]
Yang Y. [1 ]
Yao H. [1 ]
机构：
[1] Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2018年 / 46卷 / 10期
关键词：
Fault detection; Median value; Tendency similarity; Trigger mechanism; Wireless sensor network;
D O I：
10.13245/j.hust.181017
中图分类号：
学科分类号：
摘要：
A fault detection algorithm based on tendency-similarity (FDTS) was proposed. This algorithm could detect the faults in wireless sensor networks via the comparison of the nodes to be detected with its neighbours in terms of tendency-similarity and median-value. On this basis, aiming to avoid the excessive energy consumption caused by over-frequent fault detection, a trigger mechanism based on cubic exponential smoothing method was presented. The simulation results indicate that the tendency-correlation threshold is positively related to the detection rate and false positive rate while the centre-consistency threshold is negatively related to the detection rate and false positive rate. The excellent detection accuracy of FDTS was proved when facing four common fault types. When the proportion of the fault nodes achieves 25%, at least 75% of fault nodes can be recognized when facing the four fault types and the false positive rate is below 20%. © 2018, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
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页码：98 / 104
页数：6
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