An Analysis of the Largest National Ecosystem of Public Internet eXchange Points: The Case of Brazil

Samuel Henrique Bucke Brito, Mateus Augusto Silva Santos, Ramon dos Reis Fontes, Danny Alex Lachos Perez, Hirley Dayan Lourenço da Silva, Christian Rodolfo Esteve Rothenberg

Abstract


Internet eXchange Points~(IXP) IXPs have become an increasing research target when aiming at understanding the complex and evolving Internet ecosystem. IXPs are shared infrastructures where Autonomous Systems~(AS) implement peering agreements for their traffic exchange and thus represent an interesting microcosm of the Internet diversity and a strategic vantage point to deliver end-user services.
In this article, we provided an in-depth analysis of the largest set of public IXPs in a single country, namely the case of Brazil. The Brazilian public peering ecosystem counts with over 25 IXPs maintained by an overarching project called IX.br following a non-profit business model that facilitates multilateral agreements. The nation-wide peering initiative provides an appealing environment for innovation and fostering IP connectivity market practices. Without IX.br, access providers are limited in terms of coverage, performance, cost, and dependence on transit providers. The open and incentive-rich IXP approach can be regarded as an interesting development that may inspire other development countries as well as more established regional markets.
Based on BGP data from all looking glass servers in IX.br, we provide insights into the peering ecosystem per IXP and from a nation-wide perspective by inspecting properties of the connectivity graphs and the IPv4 and IPv6 prefix distribution. We propose peering affinity as a metric well-suited to measure the connectivity between different types of ASes and overall found lower peering density in IX.br when compared to more mature ecosystems, such as AMS-IX, DE-CIX, LINX, and MSK-IX. When dissecting AS-level graphs we also observe the formation of IXP-enabled k-clique communities. Our final contribution is sharing the 11 GB dataset and supporting code to enable new research studies by the community.

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DOI: http://dx.doi.org/10.14209/jcis.2016.23

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