一种基于预测与动态调整负载因子的SDN流表优化算法  

SDN Optimization Algorithm Based on Prediction and Dynamic Load Factor

作　　者：史少平 庄雷[1] 杨思锦[1] SHI Shao-ping ZHUANG Lei YANG Si-jin(School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China)

机构地区：[1]郑州大学信息工程学院,郑州450001

出　　处：《计算机科学》2017年第1期123-127,共5页Computer Science

基　　金：国家重点基础研究发展计划("973"计划)基金资助项目(2012CB315901);国家自然科学基金资助项目(61379079);河南省国际合作项目(152102410021)资助

摘　　要：通过对SDN流表更新的研究,发现了网络流量高峰期流表更新不及时的问题。提出了一种基于预测与动态调整负载因子的SDN流表优化算法。算法首先收集每个单位时间内的新增流条目,然后用二次移动平均算法对收集的历史数据进行分析,并估计下一个单位时间内新增的流条目,最终根据负载因子动态调整交换机流表中流条目的停滞超时时间。实验结果表明,该算法提高了流表匹配率和数据成功转发率,增加了活动流表项的数量。This paper studied the adjustment of flow table in the software defined networking （SDN）. A SDN optimiza- tion of the flow table algorithm （SOOTFTA） based on prediction and dynamic load factor was proposed to address the problem that switch do not have enough space in the flow table for newly arrived flows. Firstly, the SOOTFTA collects the various newly arrived flows during per unit of time Based on the information, the SOOTFTA estimates the number of newly arrived flows in the next time unit by using the second moving average method （SMA）. Finally, the SOOT- FTA dynamically adjust the idle timeout of the flows in the table based on the dynamic load factor. Experimental result show that the flow table matching rate and data forwarding rate are improved by using the proposed SOOTFTA, in- creasing the number of activities in the flow table.

关 键 词：软件定义网络 二次移动平均 负载因子 停滞超时时间 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]