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Note: Some of the projects listed here may have multiple associated publications, others may have none; we attempt to provide a link to at least one published paper or presentation/other reference, per project, if available, but the set of references provided on this page does not aim to be exhaustive. Where possible we also provide a link to the associated data.

2020-2021

1. Technical Working group on Test Methods for MBA throughput evaluations at Gigabit ranges

To evaluate alternate approaches to testing at Gigabit -range services, and address questions from the MBA Collaborative as to the best test methods at service tiers of that order, a technical working group was set up to discuss the problem space and prospective solutions. Presentations offered by TWG participants and the FCC can be found at the links below.

  1. University of Chicago/Comcast
  2. Al Morton, AT&T (re Contributions to IETF/BBF/ITU/Other Standards Bodies)
  3. CableLabs
  4. FCC MBA Team 9/30/20
  5. FCC MBA Team 03/21

2019-2020

1. Study on the performance of encrypted DNS:

With the increased focus on privacy in the presence of pervasive monitoring, and the resulting emergence of specifications aimed at increasing DNS lookup confidentiality, this effort is aimed at evaluating the performance implications of two alternatives, viz. DNS over HTTPS and DNS over TLS.

A team consisting of Austin Hounsel, PhD. Student, Princeton University (https://www.cs.princeton.edu/~ahounsel/) , advised by Dr. Nick Feamster, University of Chicago, and other research colleagues at Princeton and elsewhere conducted this study.

Hounsel A., Schmitt P., Borgolte K., Feamster N. (2021) Can Encrypted DNS Be Fast?. In: Hohlfeld O., Lutu A., Levin D. (eds) Passive and Active Measurement. PAM 2021. Lecture Notes in Computer Science, vol 12671. Springer, Cham. https://doi.org/10.1007/978-3-030-72582-2_26. Link to PDF: https://link.springer.com/content/pdf/10.1007%2F978-3-030-72582-2_26.pdf

2018

1. An Updated Data Consumption Metric:

A ‘data consumption’ or ‘data usage’ metric has been in operation as part of the fixed MBA test suite since the start of the MBA program in 2011.

The measurement device in use in the fixed MBA program (referred to elsewhere in MBA documentation as the ‘Whitebox’) is based on a hardware platform positioned within the home network so as to be able to perform the required measurement functions. Over the years since the program’s inception, both the ongoing evolution in consumer Internet services, and the associated modifications to connection methods and on-premise equipment offered by ISPs to their customer base, have necessitated accompanying changes to the relative positions and functions of the ‘Whitebox’ within MBA panel participants’ home networks.

As a result, the initial version of the data usage metric remained viable on a progressively smaller fraction of the MBA test panel, in which the ‘Whiteboxes’ (in addition to their measurement function) were also configured to provide the operative in-home Wi-fi Access points. The proportion of whitebox installations where this configuration was instantiated had dwindled considerably since 2011.

In response to recurring requests from multiple quarters, in mid-2018, the data consumption metric was updated so it could operate uniformly across the entire MBA measurement panel regardless of the specifics of Whitebox configuration. The metric was further enhanced so it can distinguish the relative proportions of Internet-related WI-Fi and wired traffic. The existing capability to measure the volume of test-generated traffic was retained and all constituent measurements within the metric (see data dictionary link below) were designed to correlate in terms of measurement interval and protocol layer.

The data dictionary for the updated usage metric is available here: 2018 usage data dictionary

A detailed technical description can be found here: Technical Methodology for measuring data usage (Live document)

The initial datasets collected (accrued per month from deploying this metric are at the following:

July 2018: https://files.samknows.com/~fcc_public/datausage_july2018.zip
August 2018: https://files.samknows.com/~fcc_public/datausage_august2018.zip
September 2018: https://files.samknows.com/~fcc_public/datausage_september2018.zip

As of December 2018 the data for this metric is now released along with that from the other MBA measurements, at regular quarterly intervals.

2013-2017

1. Locating Last Mile Performance Bottlenecks

  • Dr. Sri Sundaresan and Professor Nick Feamster, Georgia Institute of Technology/Princeton University
  • 2013: https://ecfsapi.fcc.gov/file/7022416629.pdf
  • 2016: “Home Network or Access Link? Locating Last-mile Downstream Throughput Bottlenecks”, Drs. Srikanth Sundaresan/Nick Feamster/Renata Teixeira (Georgia Institute of Technology/ICSI Berkeley/Princeton University/INRIA, France)

2. CAIDA Geolocation algorithm calibration for use in the Time Series Latency Probe (TSLP) and other CAIDA projects,
Drs. kc Claffy/Brad Huffaker, Cooperative for Applied Internet Data Analysis(CAIDA), UCSD.
https://ecfsapi.fcc.gov/file/60001012191.pdf

3. Highly Granular Packet Loss Data collection.

This is packet loss data aggregated by the minute instead of the hour as normally done in the Fixed Broadband Measurements. This was undertaken at the request of a team consisting of researchers from MIT CSAIL (Drs. David Clark, Steve Bauer) and CAIDA/UCSD (Drs. KC Claffy, Amogh Dhamdhere)

4 . NAT Revelio: Detecting NAT 444 in the ISP

This is a project led by Drs. Amogh Dhamdhere and kc. Claffy at the Cooperative for Applied Internet Data Analysis(CAIDA), University of California, San Diego (UCSD), partnering with Simula Research, Norway and the University of Carlos III, Madrid, Spain. As indicated in the title, it investigates one of the means of stretching now exhausted IPv4 address space in the evolving Internet. These experiments were done in two phases. The publication links are below.
https://www.caida.org/publications/papers/2016/nat_revelio/nat_revelio.pdf
https://www.caida.org/publications/papers/2017/tracking_big_nat_across/

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