Abstract
<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;">In this paper, a reliability evaluation model based on fuzzy neural network is proposed to evaluate the reliability of wireless sensor networks without a unified standard. Firstly, the reliability is analyzed from the point of view of topology structure, protocol stack structure and reliability mechanism of wireless sensor network, and the performance indexes that affect the reliability are extracted. Secondly, some performance indexes are screened out, and the standard value matrix of reliability evaluation for index fuzzy quantization is established. The sample data is generated by interpolation, and the reliability evaluation model based on fuzzy neural network is established. The neural network model takes the selected index values as input, and outputs are the reliability of the wireless sensor network. The simulation results show that the evaluation model is basically consistent with the actual situation, and it can evaluate the wireless sensor network from the system level.</span>
Highlights
Wireless sensor network (WSN) has the advantages of convenient installation, automatic networking, wireless communication and low cost, so it has been widely used in logistics, industrial monitoring, smart grid [1], smart home [2] and other fields
We will extract the performance indexes of WSN from the system perspective and establish a wireless sensor network reliability model based on fuzzy neural network to achieve WSN reliability assessment
Assuming that WSN reliability evaluation is divided into q levels and there are m performance indexes, the q–level evaluation corresponding to these m evaluation factors constitutes the reliability evaluation standard value matrix: CC =J×L
Summary
Wireless sensor network (WSN) has the advantages of convenient installation, automatic networking, wireless communication and low cost, so it has been widely used in logistics, industrial monitoring, smart grid [1], smart home [2] and other fields. For a WSN to be constructed, the performance indexes such as network delay, network lifetime, fault tolerance and redundancy of the network, and environmental interference need to be considered in advance. Each performance index doesn’t exist in isolation, but affects each other and restricts each other. By establishing the relationship between each performance index and the reliability of the sensor network, it can be verified whether the constructed network can meet the actual needs. The research on reliability of WSN focuses on the impact of protocols or algorithms on network performance [3,4,5]. We will extract the performance indexes of WSN from the system perspective and establish a wireless sensor network reliability model based on fuzzy neural network to achieve WSN reliability assessment
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