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Center for Applied Internet Data Analysis > publications : papers : 2018 : inferring_persistent_interdomain_congestion
Inferring Persistent Interdomain Congestion
A. Dhamdhere, D. Clark, A. Gamero-Garrido, M. Luckie, R. Mok, G. Akiwate, K. Gogia, V. Bajpai, A. Snoeren, and k. claffy, "Inferring Persistent Interdomain Congestion", in ACM SIGCOMM, Aug 2018.

This paper was awarded Best Paper at SIGCOMM 2018.

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Inferring Persistent Interdomain Congestion

Amogh Dhamdhere1
David Clark2
Alexander Gamero-Garrido1
Matthew Luckie4
Ricky K. P. Mok1
Gautam Akiwate1
Kabir Gogia1
Vaibhav Bajpai3
Alex Snoeren1
kc claffy1

CAIDA, San Diego Supercomputer Center, University of California San Diego


Massachusetts Institute of Technology's Computer Science & Artificial Intelligence Laboratory (MIT/CSAIL)


TU Munich


University of Waikato

There is significant interest in the technical and policy communities regarding the extent,scope, and consumer harm of persistent interdomain congestion. We provide empirical grounding for discussions of interdomain congestion by developing a system and method to measure congestion on thousands of interdomain links without direct access to them. We implement a system based on the Time Series Latency Probes (TSLP) technique that identifies links with evidence of recurring congestion suggestive of an under-provisioned link. We deploy our system at 86 vantage points worldwide and show that congestion inferred using our lightweight TSLP method correlates with other metrics of interconnection performance impairment. We use our method to study interdomain links of eight large U.S. broadband access providers from March 2016 to December 2017, and validate our inferences against ground-truth traffic statistics from two of the providers. For the period of time over which we gathered measurements, we did not find evidence of widespread endemic congestion on interdomain links between access ISPs and directly connected transit and content providers, although some such links exhibited recurring congestion patterns. We describe limitations, open challenges, and a path toward the use of this method for large-scale third-party monitoring of the Internet interconnection ecosystem.

Keywords: congestion, measurement methodology, passive data analysis, topology
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