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Web of Proceedings - Francis Academic Press
Web of Proceedings - Francis Academic Press

Data Mining-based Traffic Anomaly Detection Method of Communication Network

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DOI: 10.25236/iccem.2021.036

Author(s)

Wang Rui, Wang Henan

Corresponding Author

Wang Rui

Abstract

In the full-duplex heterogeneous optical communication network, the traffic anomaly detection algorithm of the full-duplex heterogeneous optical communication network in S-band and X-band is constructed to improve the traffic output stability of the communication network, and the stability control method of traffic anomaly detection of the communication network based on data mining is proposed. The identification model of flow state parameters of full-duplex heterogeneous optical communication network in different frequency bands is constructed, the channel equalization control of full-duplex heterogeneous optical communication network is carried out by means of nonlinear system control, the flow monitoring model of full-duplex heterogeneous optical communication network with single-channel tracking in S and X frequency bands is established in combination with steady-state error compensation design, the fuzzy compensation method is adopted in combination with nonlinear stability analysis method, full-duplex heterogeneous optical communication network control and analysis of uncertain disturbance characteristics, Realize the channel balance control in the process of communication network traffic anomaly detection. According to the full-duplex heterogeneous optical communication network traffic state parameters, combined with the performance of input and output state parameters, realize the full-duplex heterogeneous optical communication network traffic anomaly detection and analysis. The test shows that the output stability of full-duplex heterogeneous optical communication network traffic detection with this method is good, and the error compensation ability is strong, which improves the output balance of communication network.

Keywords

Data mining, Optical communication network, Flow, Abnormal detection, Channel equalization