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On the Double-Faced Nature of P2P Traffic

机译:关于P2P流量的双面性质

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摘要

Over the last few years, peer-to-peer (P2P) file sharing applications have evolved to become a major traffic source in the Internet. The ability to quantify their impact on the network, as a consequence of both signaling and download traffic, is fundamental to a number of network operations, including traffic engineering, capacity planning, quality of service, forecasting for long-term provisioning, etc. We present here a measurement study on the characteristics of the traffic associated with different P2P applications. Our aim is to offer useful insight into the nature of P2P traffic, which we consider a step toward building P2P traffic aggregates generators in simulative environments. We show that P2P traffic can be divided into two distinguished behavioral profiles, which, independently of the application protocol, present significant differences in the average and standard deviation of four measurements: arrival times, durations, volumes and average packet sizes of P2P conversations. These profiles well represent the typical behavior of signaling and download traffic. Based on our findings, we argue that, if such distinction is not taken into account, the statistical measurements needed to model P2P traffic aggregates would result biased, and potentially bring to misleading results.
机译:在过去的几年中,点对点(P2P)文件共享应用程序已经发展成为互联网中的主要交通源。由于信号和下载流量的结果,能够量化它们对网络的影响,这是许多网络运营的基础,包括交通工程,能力规划,服务质量,长期供应等预测等这里存在关于与不同P2P应用相关的流量特性的测量研究。我们的目标是对P2P流量的性质提供有用的洞察力,我们考虑在模拟环境中构建P2P流量聚集器发生器的一步。我们表明P2P流量可以分为两个可分别的行为配置文件,它独立于应用协议,在四次测量的平均和标准偏差中存在显着差异:到达时间,持续时间,卷和平均数据包大小的P2P对话。这些配置文件很好地代表了信令和下载流量的典型行为。基于我们的研究结果,我们认为,如果没有考虑这种区分,可以将P2P交通汇总的统计测量结果产生偏见,并可能引起误导性结果。

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