计算机应用与软件2025，Vol.42Issue(6)：141-148,217,9.DOI:10.3969/j.issn.1000-386x.2025.06.019
基于时空注意力的软件定义网络流量分类方法
SOFTWARE-DEFINED NETWORK TRAFFIC CLASSIFICATION METHOD BASED ON SPATIO-TEMPORAL ATTENTION
摘要
Abstract
It is necessary that emerging technologies such as 5G and B6G promote the continuous increase of network scale and increase the difficulty of traffic control.SDN can realize centralized control of network traffic.However,the existing methods are difficult to accurately describe the temporal and spatial characteristics of network traffic,and the algorithm convergence speed is low.In response to the above problems,this paper proposes a software-defined network traffic classification method based on spatio-temporal attention.The model was composed of two components,spatial and temporal feature extraction.The spatial component included a channel and a spatial attention module,and the temporal component was composed of a temporal attention module.It was composed of multi-layer two-way GRU stacks,and an innovative reconstruction mechanism integrated time and space characteristics.The simulation results show that this method is significantly better than the existing baseline method in classification performance,the algorithm converges fast,and has better classification performance under different types of traffic.关键词
网络流量分类/空间特征/时间特征/重构Key words
Network traffic classification/Spatial characteristics/Temporal characteristics/Reconstruction分类
计算机与自动化引用本文复制引用
吴海银,潘成胜,孔志翔..基于时空注意力的软件定义网络流量分类方法[J].计算机应用与软件,2025,42(6):141-148,217,9.基金项目
国家自然科学基金重点项目(61931004). （61931004）
