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    Rights statement: © ACM, 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SIGCOMM '17 Proceedings of the Conference of the ACM Special Interest Group on Data Communication http://dx.doi.org/10.1145/3098822.3098855

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Detecting peering infrastructure outages in the wild

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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  • Vasileios Giotsas
  • Christoph Dietzel
  • Georgios Smaragdakis
  • Anja Feldmann
  • Arthur Berger
  • Emile Aben
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Publication date7/08/2017
Host publicationSIGCOMM 2017 - Proceedings of the 2017 Conference of the ACM Special Interest Group on Data Communication
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages446-459
Number of pages14
ISBN (electronic)9781450346535
<mark>Original language</mark>English
Event2017 Conference of the ACM Special Interest Group on Data Communication, SIGCOMM 2017 - Los Angeles, United States
Duration: 21/08/201725/08/2017

Conference

Conference2017 Conference of the ACM Special Interest Group on Data Communication, SIGCOMM 2017
Country/TerritoryUnited States
CityLos Angeles
Period21/08/1725/08/17

Conference

Conference2017 Conference of the ACM Special Interest Group on Data Communication, SIGCOMM 2017
Country/TerritoryUnited States
CityLos Angeles
Period21/08/1725/08/17

Abstract

Peering infrastructures, namely, colocation facilities and Internet exchange points, are located in every major city, have hundreds of network members, and support hundreds of thousands of interconnections around the globe. These infrastructures are well provisioned and managed, but outages have to be expected, e.g., due to power failures, human errors, attacks, and natural disasters. However, little is known about the frequency and impact of outages at these critical infrastructures with high peering concentration. In this paper, we develop a novel and lightweight methodology for detecting peering infrastructure outages. Our methodology relies on the observation that BGP communities, announced with routing updates, are an excellent and yet unexplored source of information allowing us to pinpoint outage locations with high accuracy. We build and operate a system that can locate the epicenter of infrastructure outages at the level of a building and track the reaction of networks in near real-time. Our analysis unveils four times as many outages as compared to those publicly reported over the past five years. Moreover, we show that such outages have significant impact on remote networks and peering infrastructures. Our study provides a unique view of the Internet's behavior under stress that often goes unreported.

Bibliographic note

© ACM, 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SIGCOMM '17 Proceedings of the Conference of the ACM Special Interest Group on Data Communication http://dx.doi.org/10.1145/3098822.3098855