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作 者:李为民[1] 刘晓楠[1] 缪晨[1] 陈陆颖[1] 雷振明[1]
机构地区:[1]北京邮电大学信息与通信工程学院,北京海淀区100876
出 处:《电子科技大学学报》2014年第2期247-251,256,共6页Journal of University of Electronic Science and Technology of China
基 金:国家自然科学基金(61072061)
摘 要:网络流量的识别和分类是网络管理、流量工程等应用的重要前提。该文针对占据主要互联网流量的bitTorrent、HTTP、PPStream、QQ和迅雷5种典型业务进行研究。对不同时间段采集数据的分析结果表明:各典型业务的包长分布均有独特的分布规律,且随时间不同仅存在微小变化。对数据集按不同比例进行采样分析结果表明:随样本总数的递减,各典型业务包长分布形态没有显著改变,且随着样本总数的递减,包长分布曲线虽有所变化,但整体形态和趋势并没有显著改变。该文对研究互联网各业务流量特点,分析和掌握网络流量规律等方面具有重要价值。Identification and classification of network traffic are an essential prerequisite of network traffic, network management, traffic engineering, and other applications. This paper mainly studies five typical Internet applications, including bitTorrent, HTTP, PPStream, QQ, and thunder, which occupy a majority of the Internet traffic. Analysis of data collected during different time periods shows that each application has a unique typical packet size distribution, and there are only minimal changes in packet size distribution among different durations. Moreover, the analysis on data of discrete sample proportions shows that with decreasing the number of samples, the packet size distribution patterns do not change significantly. With the decreasing of the total number of samples, the packet size distributions curve varies, but the overall shape and the trends have not changed substantially.
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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