Do you see me now? Sparsity in passive observations of address liveness

J. Mirkovic, G. Bartlett, J. Heidemann, Hao Shi, Xiyue Deng
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引用次数: 3

Abstract

Accurate information about address and block usage in the Internet has many applications in planning address allocation, topology studies, and simulations. Prior studies used active probing, sometimes augmented with passive observation, to study macroscopic phenomena, such as the overall usage of the IPv4 address space. This paper instead studies the completeness of passive sources: how well they can observe microscopic phenomena such as address usage within a given network. We define sparsity as the limitation of a given monitor to see a target, and we quantify the effects of interest, temporal, and coverage sparsity. To study sparsity, we introduce inverted analysis, a novel approach that uses complete passive observations of a few end networks (three campus networks in our case) to infer what of these networks would be seen by millions of virtual monitors near their traffic's destinations. Unsurprisingly, we find that monitors near popular content see many more targets and that visibility is strongly influenced by bipartite traffic between clients and servers. We are the first to quantify these effects and show their implications for the study of Internet liveness from passive observations. We find that visibility is heavy-tailed, with only 0.5% monitors seeing more than 10% of our targets' addresses, and is most affected by interest sparsity over temporal and coverage sparsity. Visibility is also strongly bipartite. Monitors of a different class than a target (e.g., a server monitor observing a client target) outperform monitors of the same class as a target in 82–99% of cases in our datasets. Finally, we find that adding active probing to passive observations greatly improves visibility of both server and client target addresses, but is not critical for visibility of target blocks. Our findings are valuable to understand limitations of existing measurement studies, and to develop methods to maximize microscopic completeness in future studies.
你现在看到我了吗?地址活动被动观察的稀疏性
因特网中有关地址和块使用情况的准确信息在规划地址分配、拓扑研究和仿真中有许多应用。先前的研究使用主动探测,有时辅以被动观察,来研究宏观现象,例如IPv4地址空间的总体使用情况。相反,本文研究的是被动源的完备性:它们如何很好地观察微观现象,如给定网络中的地址使用。我们将稀疏性定义为给定监视器看到目标的限制,并量化兴趣、时间和覆盖稀疏性的影响。为了研究稀疏性,我们引入了反向分析,这是一种新颖的方法,它使用对几个终端网络(在我们的案例中是三个校园网)的完全被动观察来推断这些网络中的哪些将被数百万个靠近其流量目的地的虚拟监视器所看到。不出所料,我们发现靠近流行内容的监视器可以看到更多目标,并且可见性受到客户端和服务器之间的双向流量的强烈影响。我们是第一个量化这些影响的人,并从被动观察中展示了它们对互联网活跃度研究的影响。我们发现可见性是重尾的,只有0.5%的监视器看到超过10%的目标地址,并且最受兴趣稀疏性的影响。可见性也有很强的两面性。在我们的数据集中,与目标不同类别的监视器(例如,观察客户端目标的服务器监视器)在82-99%的情况下优于与目标相同类别的监视器。最后,我们发现在被动观察中添加主动探测大大提高了服务器和客户端目标地址的可见性,但对目标块的可见性并不重要。我们的发现对于理解现有测量研究的局限性,并在未来的研究中开发出最大化微观完整性的方法是有价值的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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