Dianxin kexue (Mar 2022)

Intelligent prediction method of network performance based on graph neural network

  • Yijiang LI,
  • Huibiao YE,
  • Renhua XIE,
  • Jiali LOU,
  • Danna ZHUANG,
  • Chuanhuang LI

Journal volume & issue
Vol. 38
pp. 143 – 157

Abstract

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There are some problems in the traditional network performance prediction technology, such as incomplete network state acquisition and poor accuracy of network performance evaluation.Combined with the characteristics of graph neural network learning and reasoning network relational data and the captured global information of the network, on the basis of the current network performance prediction methods, an intelligent prediction method of network performance based on graph neural network was proposed.Aiming at the complex network information, through the research of network system abstraction and network performance modeling, the network information can be transformed into the graph space convolution was used to process the message passing process of graph network nodes to realize the relationship reasoning between network information.The graph neural network model for network performance prediction was studied, and a graph neural network architecture which could deal with traffic matrix, network topology, routing strategy and node configuration was proposed.Finally, the experiments show that the model can better achieve accurate prediction of the network performance including delay, jitter and packet loss rate.

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