A High-Performance, Scalable Infrastructure for Large-Scale Active DNS Measurements
A High-Performance, Scalable Infrastructure for Large-Scale Active DNS Measurements
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DOI：
10.1109/jsac.2016.2558918
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发表时间：
2016-04
影响因子：
16.4
通讯作者：
R. V. Rijswijk-Deij;M. Jonker;A. Sperotto;A. Pras
中科院分区：
文献类型：
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作者：
R. V. Rijswijk-Deij;M. Jonker;A. Sperotto;A. Pras
域名系统(域名系统)是互联网的核心组件。它执行将人类可读的名称映射到机器可读数据(例如IP地址、哪些主机处理电子邮件等)的重要任务。域名系统的内容揭示了许多关于域的技术操作。因此，研究大部分域名系统随时间变化的状态可以揭示有关互联网发展的有价值的信息。我们收集了一个独特的长期数据集，其中包含互联网上主要顶级域名(TLD)下所有域名(包括.com、.net和.org，占全球域名空间的50%)的每日域名测量数据。本文讨论了执行如此大规模的主动测量的挑战。这些挑战包括扩展每日测量以收集最大的TLD(.com，拥有1.23亿个名字)的数据，以及确保这种规模的测量不会给全球DNS基础设施带来不可接受的负担。本文讨论了我们为迎接这些挑战而做出的设计选择，并记录了基于这些选择我们实现的测量系统的设计。两个与云电子邮件服务相关的案例研究说明了以这种规模衡量域名系统的价值。该系统收集的数据对网络研究界具有很高的价值。因此，我们通过讨论如何使其他研究人员能够访问数据来结束这篇文章。
The domain name system (DNS) is a core component of the Internet. It performs the vital task of mapping human readable names into machine readable data (such as IP addresses, which hosts handle e-mail, and so on). The content of the DNS reveals a lot about the technical operations of a domain. Thus, studying the state of large parts of the DNS over time reveals valuable information about the evolution of the Internet. We collect a unique long-term data set with daily DNS measurements for all the domains under the main top-level domains (TLDs) on the Internet (including .com, .net, and .org, comprising 50% of the global DNS name space). This paper discusses the challenges of performing such a large-scale active measurement. These challenges include scaling the daily measurement to collect data for the largest TLD (.com, with 123M names) and ensuring that a measurement of this scale does not impose an unacceptable burden on the global DNS infrastructure. The paper discusses the design choices we have made to meet these challenges and documents the design of the measurement system we implemented based on these choices. Two case studies related to cloud e-mail services illustrate the value of measuring the DNS at this scale. The data this system collects is valuable to the network research community. Therefore, we end this paper by discussing how we make the data accessible to other researchers.