AnyOpt: Predicting and Optimizing IP Anycast Performance
AnyOpt: Predicting and Optimizing IP Anycast Performance
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AnyOpt：预测和优化 IP 任播性能
DOI：
10.1145/3452296.3472935
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Yang, Xiaowei
中科院分区：
文献类型：
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作者：
Zhang, Xiao;Sen, Tanmoy;Zhang, Zheyuan;April, Tim;Chandrasekaran, Balakrishnan;Choffnes, David;Maggs, Bruce M;Shen, Haiying;Sitaraman, Ramesh K;Yang, Xiaowei
优化基于anycast的系统（例如根DNS或CDN）性能的关键是选择正确的站点集来宣布anycast前缀。这里的一个挑战是预测集水区。naïve方法是从所有可用站点的子集中发布前缀，并选择性能最好的子集，但这种方法的可伸缩性不太好。我们证明，通过在与第1层网络对等的站点之间进行两两实验，我们可以预测如果我们向站点的任何子集宣布将导致的集水区。我们在简化的BGP模型中证明了该方法的有效性，并与常见的BGP路由策略保持一致，并在实际的测试平台中对其进行了评估。然后我们介绍了AnyOpt，一个预测anycast集水区的系统。使用AnyOpt，网络运营商可以在不使用naïve方法的情况下找到最小化客户端延迟的任意播站点子集。在一项使用15个站点的实验中，每个站点与6个传输提供商中的一个进行对等连接，AnyOpt预测站点集水15300个客户端，准确率为94.7%，客户端rtt平均误差为4.6%。AnyOpt确定了一个由12个站点组成的子集，并宣布与贪婪方法相比，该方法使到客户端的平均RTT降低了33ms，而贪婪方法使相同数量的站点具有最低的平均单播延迟。
The key to optimizing the performance of an anycast-based system (e.g., the root DNS or a CDN) is choosing the right set of sites to announce the anycast prefix. One challenge here is predicting catchments. A naïve approach is to advertise the prefix from all subsets of available sites and choose the best-performing subset, but this does not scale well. We demonstrate that by conducting pairwise experiments between sites peering with tier-1 networks, we can predict the catchments that would result if we announce to any subset of the sites. We prove that our method is effective in a simplified model of BGP, consistent with common BGP routing policies, and evaluate it in a real-world testbed. We then present AnyOpt, a system that predicts anycast catchments. Using AnyOpt, a network operator can find a subset of anycast sites that minimizes client latency without using the naïve approach. In an experiment using 15 sites, each peering with one of six transit providers, AnyOpt predicted site catchments of 15,300 clients with 94.7% accuracy and client RTTs with a mean error of 4.6%. AnyOpt identified a subset of 12 sites, announcing to which lowers the mean RTT to clients by 33ms compared to a greedy approach that enables the same number of sites with the lowest average unicast latency.