A case study of traffic demand response to broadband service-plan upgrades

Sarthak Grover, Roya Ensafi, Nick Feamster

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Internet service providers are facing mounting pressure from regulatory agencies to increase the speed of their service offerings to consumers; some are beginning to deploy gigabit-per-second speeds in certain markets, as well. The race to deploy increasingly faster speeds begs the question of whether users are exhausting the capacity that is already available. Previous work has shown that users who are already maximizing their usage on a given access link will continue to do so when they are migrated to a higher service tier. In a unique controlled experiment involving thousands of Comcast subscribers in the same city, we analyzed usage patterns of two groups: a control group (105 Mbps) and a randomly selected treatment group that was upgraded to 250 Mbps without their knowledge. We study how users who are already on service plans with high downstream throughput respond when they are upgraded to a higher service tier without their knowledge, as compared to a similar control group. To our surprise, the difference between traffic demands between both groups is higher for subscribers with moderate traffic demands, as compared to high-volume subscribers. We speculate that even though these users may not take advantage of the full available capacity, the service-tier increase generally improves performance, which causes them to use the Internet more than they otherwise would have.

Original languageEnglish (US)
Title of host publicationPassive and Active Measurement - 17th International Conference, PAM 2016, Proceedings
EditorsThomas Karagiannis, Xenofontas Dimitropoulos
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319305042
StatePublished - 2016
Event17th International Conference on Passive and Active Measurement, PAM 2016 - Heraklion, Greece
Duration: Mar 31 2016Apr 1 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other17th International Conference on Passive and Active Measurement, PAM 2016

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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