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

作　　者：王晖[1] 季振洲[1] 孙彦东[1] 王远征[1] 

机构地区：[1]哈尔滨工业大学计算机科学与技术学院,黑龙江哈尔滨150001

出　　处：《通信学报》2010年第10期115-120,共6页Journal on Communications

摘　　要：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.

关 键 词：自相似 随机早期检测 主动队列管理 拥塞控制 网络流量模型 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]