基于抽样流记录的RTT估计  

RTT Estimation Based on Sampled Flow Data

作　　者：苏琪[1,2] 龚俭[1,2] 苏艳珺 

机构地区：[1]东南大学计算机科学与工程学院,江苏南京210096 [2]江苏省计算机网络重点实验室,江苏南京210096

出　　处：《软件学报》2014年第10期2346-2361,共16页Journal of Software

基　　金：国家科技支撑计划(2008BAH37B04);国家基础研究发展计划(973)(2009CB320505);国家自然科学基金(60973123)

摘　　要：往返时延(RTT)是网络测量中的一个重要测度,是刻画网络性能的重要指标.传统的RTT测量都是基于报文的,需要专门的主动或被动测量平台的支持.提出一种新的RTT估计方法,仅使用现有路由器设备提供的流记录,不需要额外的网络测量设施.通过对TCP块状流传输特性的分析,分别建立了当套接字缓冲区长度与带宽延迟积BDP相对较小、较大和相近这3种情况下的RTT估计模型.实验结果表明,这些模型都能很好地完成RTT估计.同时,由于在估计当中只使用了流持续时间和总报文两个变量,因此,该方法同样适用于以抽样流记录为输入的环境,能够有效地应用于现有的大规模主干网环境的网络检测与管理.Round-Trip time （RTT） is an important metric for network measurement and an essential indicator for network performance monitoring. Traditional packet trace based RTT estimation usually depends on particular active or passive measurement platforms. This paper proposes a new RTT estimation method, which merely takes flow data from existed routers and hardly needs extra network measurement facility. Based on the analysis of transmission features of TCP bulk flow, RTT estimation models are established corresponding to the conditions where socket buffer size and bandwidth delay product （BDP） are relatively small, large and approximate. Experiments show RTT estimation can be well accomplished through those models. Moreover, considering only duration and total packet number of a TCP bulk flow are involved in estimation, this method is also adoptable to situation with sampling flow data as input, and thus is effective in monitoring and managing the large-scale backbone network performance.

关 键 词：RTT估计 抽样流记录 网络测量 网络管理 随机过程 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]