基于图神经网络的网络性能智能预测

Intelligent prediction method of network performance based on graph neural network

传统网络性能预测技术存在网络状态获取不够全面及网络性能评估准确性欠佳等问题,利用图神经网络学习推理网络关系数据的特点,结合捕获的网络全局信息,提出了一种基于图神经网络的网络性能智能预测方法。通过网络系统抽象及网络性能建模,将复杂的网络信息转化为形式化的图数据进行描述,利用图空域卷积处理图网络节点的消息传递过程,实现网络信息之间的关系推理,研究了实现网络性能预测的图神经网络模型,提出了一种能处理流量矩阵、网络拓扑、路由策略、节点配置的图神经网络体系结构,最后通过实验论证了模型能更好地实现包括时延、抖动和丢包率的网络性能的准确预测。

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 perfor-mance 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.