Stability detection method of large-scale network information transmission based on digital twin technology
by Xiao Lin; Jian Du; Wenjun Gao; Aobo Zhou
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 16, No. 4, 2024

Abstract: In order to overcome the problems of low accuracy of transmission channel state estimation, low detection accuracy and long detection task completion time in traditional transmission stability detection methods, a large-scale network information transmission stability detection method based on digital twin technology is proposed. The data twin technology is used to build the network data acquisition architecture, extract the analysis results of large-scale network information transmission channel characteristics, and obtain the transmission channel state estimation results with the channel state correlation coefficient matrix. The output of the detection model is adjusted according to the fuzzy logic to obtain accurate detection results. The experimental results show that the average correct rate of channel state estimation of large-scale network information transmission is 96.9%, the detection accuracy of large stability is high, and the maximum detection task completion time is 2.0 s. The practical application effect is good.

Online publication date: Fri, 25-Oct-2024

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