Complexities in Internet peering: Understanding the “Black” in the “Black Art”
Complexities in Internet peering: Understanding the “Black” in the “Black Art”
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互联网对等互连的复杂性：理解“黑艺术”中的“黑”
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
C. Dovrolis
中科院分区：
文献类型：
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作者：
Aemen Lodhi;Nikolaos Laoutaris;A. Dhamdhere;C. Dovrolis
互联网域间网络中的对等一直被认为是一种“黑艺术”，只有少数对等专家才能深入了解，而大多数网络运营商社区只采用传统的经验法则来通过自组织个人交互形成对等链接。为什么窥视被认为是一种黑魔法？在识别潜在对等点、协商稳定对等关系以及通过对等进行效用优化时，复杂性的主要来源是什么？当代业务实践如何处理这些问题？在这项工作中，我们解决这些问题的第2级网络服务提供商。我们确定并探讨了三个主要来源的复杂性对等：（a）无法预测交通流量之前，链路形成（B）无法预测经济效用，由于一个复杂的过境和对等定价结构（c）计算不可行性确定的最佳设置的同行，因为网络结构。我们表明，框架最佳的同行选择作为一个正式的优化问题，并解决它是不可行的这些问题的性质。我们的流量复杂性的结果表明，15%的NSP失去了一些客户流量后，对等。此外，我们的经济复杂性结果显示，15%的NSP在对等连接后失去效用，大约50%的NSP最终使用对等连接的累计成本高于仅使用中转的成本，只有10%的NSP获得付费对等连接客户。
Peering in the Internet interdomain network has long been considered a “black art”, understood in-depth only by a select few peering experts while the majority of the network operator community only scratches the surface employing conventional rules-of-thumb to form peering links through ad hoc personal interactions. Why is peering considered a black art? What are the main sources of complexity in identifying potential peers, negotiating a stable peering relationship, and utility optimization through peering? How do contemporary operational practices approach these problems? In this work we address these questions for Tier-2 Network Service Providers. We identify and explore three major sources of complexity in peering: (a) inability to predict traffic flows prior to link formation (b) inability to predict economic utility owing to a complex transit and peering pricing structure (c) computational infeasibility of identifying the optimal set of peers because of the network structure. We show that framing optimal peer selection as a formal optimization problem and solving it is rendered infeasible by the nature of these problems. Our results for traffic complexity show that 15% NSPs lose some fraction of customer traffic after peering. Additionally, our results for economic complexity show that 15% NSPs lose utility after peering, approximately, 50% NSPs end up with higher cumulative costs with peering than transit only, and only 10% NSPs get paid-peering customers.