基于时间槽的自相似流量随机早检测算法——SFRED

Time slot-based RED algorithm on self-similar flows:SFRED

分析研究了网络流量的自相似和长相关性,并基于分形布朗运动模型导出了自相似流量环境RED算法分组丢失概率的一种计算方法,从而提出了基于时间槽的自相似流量随机早检测队列管理算法SFRED。该算法在每个时间槽内计算一次分组丢失概率,大大降低系统负担。NS2仿真实验表明SFRED算法性能明显优于RED,能够很好地在自适应流背景下控制队列长度,并具有良好的吞吐量性能。

Based on fractional Brownian motion（FBM）,one calculation of the packet drop probability in the RED algorithm was derived under self-similar flows.Based on the self-similarity and the long-range dependence characteristics of Internet network traffics,a time slot-based RED algorithm on self-similar flows（SFRED） was proposed to the router queue management.The packet drop probability is calculated in every time-slot so that the burden is greatly reduced.It is simulated by NS2 and the experimental results show that the algorithm SFRED outperforms RED.SFRED can control the queue length under adaptive flows with a good throughput.