Research on Intelligent Perception Model of SDN Network Delay
Zebin Chen, Wei Yichi, Hao Tang, Chuanhuang Li · 2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) · 2021
Based on the software-defined network architecture, this paper classifies and uniformly describes the basic state of the network in the SDN network. And on the basis of analyzing the basic state of the network, combined with deep learning technology, we proposed an algorithm model based on deep learning to perceive the basic state of the network and accurately predict the network delay. Based on the analysis of related theories, this paper proposes an intelligent perception model GGAE for the SDN network delay based on the graph neural network by combining the autoencoder into a neural network RouteNet, which is based on the message passing neural network (MPNN).