Policy Implications of Third-Party Measurement of Interdomain Congestion on the Internet

22 Pages Posted: 16 Mar 2018 Last revised: 17 Aug 2018

See all articles by David D. Clark

David D. Clark


Amogh D. Dhamdhere


Matthew Luckie

University of Waikato; CAIDA

KC Claffy

University of California, San Diego (UCSD)

Date Written: August 15, 2018


Internet engineering, science, and public policy communities have significant interest in understanding the extent and scope of, as well as potential consumer harm induced by, persistent interdomain congestion on the Internet. In recent work, we developed and implemented a lightweight active measurement method and system to measure evidence of congestion on thousands of interconnection links between broadband access ISPs and major interconnecting parties, including directly connected content providers. This method provides empirical grounding for discussions of interconnection congestion, without requiring direct access to interconnection links. We first review the previous work to provide context. We then present new techniques for visualizing the data in ways we believe are conducive to policy analysis, e.g, of infrastructure resilience, performance metrics, and potential harm to consumers of persistently under-provisioned interconnection links. We presenting data in ways that allow us to compare different access providers, and show how congestion varies over time. We focus on seven large U.S. broadband access networks, but there is nothing U.S.-specific about the methods we use. Finally, we describe policy-relevant limitations and implications of the work.

Keywords: Internet congestion, Internet peering, direct interconnection, network neutrality, interconnection congestion

Suggested Citation

Clark, David D. and Dhamdhere, Amogh D. and Luckie, Matthew and Claffy, KC C., Policy Implications of Third-Party Measurement of Interdomain Congestion on the Internet (August 15, 2018). TPRC 46: The 46th Research Conference on Communication, Information and Internet Policy 2018, Available at SSRN: https://ssrn.com/abstract=3141671 or http://dx.doi.org/10.2139/ssrn.3141671

David D. Clark (Contact Author)

MIT CSAIL ( email )

Stata Center
Cambridge, MA 02142
United States
617-253-6003 (Phone)

Amogh D. Dhamdhere

CAIDA/UC ( email )

9500 Gilman Drive
Mail Stop 0505
La Jolla, CA 92093-0505
United States

Matthew Luckie

University of Waikato ( email )

Te Raupapa
Private Bag 3105
Hamilton, Waikato 3240
New Zealand

CAIDA ( email )

United States

KC C. Claffy

University of California, San Diego (UCSD) ( email )

9500 Gilman Drive
Mail Code 0502
La Jolla, CA 92093-0112
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
PlumX Metrics