基于SDN的一体化信息网络业务流分类策略

Traffic classification strategy of integrated information network based on SDN

一体化信息网络有多种类型协议的网络接入,流量管理与调度困难,针对这种情况设计基于软件定义网络(SDN)架构的一体化信息网络业务流分类技术。根据SDN框架转控分离的特点,设计流量感知节点采集流量信息,针对一体化信息网络流量连续特征属性多、业务类别分布不平衡、存在大量噪声的特点,设计基于Fayyad边界点定理改进CART算法,与基于弱分类器系数和分类误差相似度改进的Adaboost算法相结合的分类模型。实验结果表明,该技术能够对采集到的业务流进行分类,与相关算法相比,分类精度和用时均有明显改进。

The integrated information network has network access of various types of protocols,and traffic management and scheduling are difficult.In view of this situation,a service flow classification technology of integrated information network based on software defined network(SDN)architecture was designed.According to the characteristics of transfer and control separation of SDN framework,a traffic sensing node was designed to collect traffic information.According to the characteristics of continuous traffic characteristic attributes,unbalanced service category distribution and large amount of noise in the integrated information network,an improved CART algorithm based on Fayyad boundary point theorem,and the classification model was combined with the improved AdaBoost algorithm based on weak classifier coefficient and classification error similarity was designed.Experimental results show that this technology can classify the collected traffic flow,and the classification accuracy and time are significantly improved compared with the relevant algorithms.