重庆科技学院学报（自然科学版）2023，Vol.25Issue(6)：41-46,6.
基于深度学习算法的SDN路由动态优化方法
Study on Dynamic Optimization Method of SDN Routing Based on Deep Learning Algorithm
摘要
Abstract
Traditional software defined network(SDN)routing dynamic optimization methods can′t dynamically group routing node data results in longer network delay jitter in high data forwarding scenarios.Therefore,a dynam-ic optimization method for SDN routing based on deep learning algorithms is proposed.Firstly,according to the SDN hierarchy,the shortest path of transmission is dynamically planned.Then,by calculating the link lifetime,the dynamic grouping of routing node data is achieved.Secondly,based on the grouping results and matching and forwarding characteristics of routing nodes,a multi-objective routing dynamic optimization model is constructed.Finally,deep learning algorithms are used to establish the mapping relationship between network channel parame-ters and dynamic optimization solutions,so as to achieve dynamic optimization of SDN routing.The simulation experimental results show that this method can suppress network delay jitter and reduce network delay.关键词
深度学习算法/SDN/路由动态/优化方法Key words
deep learning algorithm/SDN/routing dynamics/optimization method分类
信息技术与安全科学引用本文复制引用
何健..基于深度学习算法的SDN路由动态优化方法[J].重庆科技学院学报（自然科学版）,2023,25(6):41-46,6.基金项目
广东省教育厅科学研究项目"基于大数据分析的网络空间安全关键技术研究"(2019GKTSCX132) （2019GKTSCX132）
