Structure and Stability of Internet Top Lists
Structure and Stability of Internet Top Lists
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互联网排行榜的结构和稳定性
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
G. Carle
中科院分区：
文献类型：
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作者：
Quirin Scheitle;Jonas Jelten;O. Hohlfeld;L. Ciprian;G. Carle
积极的互联网测量研究依赖于要扫描的目标列表。虽然探测整个IPv4地址空间对于有限的复杂性扫描是可行的，但更复杂的扫描并不能扩展到完整的互联网。因此，通常以“顶级列表”的形式使用互联网样本。最广泛使用的列表是Alexa全局TOP1M列表。尽管有盛行，但很少质疑使用顶级列表。关于它们的创造，代表性，潜在偏见，稳定性或列表之间的重叠知之甚少。结果，在研究中应用最高列表的潜在后果尚不清楚。在这项研究中，我们旨在通过研究经验互联网扫描的常见最佳列表的适当性，包括稳定性，相关性和此类列表的潜在偏见。
Active Internet measurement studies rely on a list of targets to be scanned. While probing the entire IPv4 address space is feasible for scans of limited complexity, more complex scans do not scale to measuring the full Internet. Thus, a sample of the Internet can be used instead, often in form of a "top list". The most widely used list is the Alexa Global Top1M list. Despite their prevalence, use of top lists is seldomly questioned. Little is known about their creation, representativity, potential biases, stability, or overlap between lists. As a result, potential consequences of applying top lists in research are not known. In this study, we aim to open the discussion on top lists by investigating the aptness of frequently used top lists for empirical Internet scans, including stability, correlation, and potential biases of such lists.