CRII: NeTS: Denoising Internet Delay Measurements using Weak Supervision

Funding source: NSF CNS-1850297. Period of performance: 06/15/2019 -- 05/31/2022.

Project Overview

Understanding the delay characterisitcs of the Internet is one of the key goals of Internet measurement researchers, service providers, and content delivery networks. To this end, a myriad of measurement tools and techniques were proposed by the researchers in academia and industry, and datasets from such measurement tools are curated to facilitate analyses at a later time.

Despite the benefits of the proposed tools to measure the delay characterisitics of the Internet and the availability of datasets from measurement efforts, what is critically lacking is a systematic framework to interpret the results from the tools and datasets. The key hinderance to creating this framework is measurement noise, which we define as the presence of non-representative and erroneous values in the delay measurements. Noise confounds all types of end-to-end delay measurements and can lead to performance issues and unnecessary operational decisions. State-of-the-art denoising techniques are (1) time consuming and labor intensive: they are done manually due to the lack of ground truth data required to classify and discern noise from the actual delay behaviors of the network, and (2) ineffective: they are too naïve with simple heuristics and filters, which are impractical and which can lead to unnecessary operational decisions.

To tackle these challenges, this research will develop a systematic weak supervision-based framework and culminate in NoMoNoise for denoising Internet delay measurements in an automated and rapid fashion.


  • PI: Ram Durairajan
  • B.S. Students: Jared Knofcynzski, Juno Mayer, Nolan Rudolph, Nick Hendersen
  • Ph.D. Students: Chris Misa, Yukhe Lavinia
  • Collaborators: Daniel Lowd, Reza Rejaie, Sudarsun Kannan, Walter Willinger


  • ARISE: A Multi-Task Weak Supervision Framework for Network Measurements
    Jared Knofczynski, Ramakrishnan Durairajan and Walter Willinger
    In IEEE JSAC Series on Machine Learning in Communications and Networks, July 2022.
    [PAPER]     [CODE]    

  • Dynamic Scheduling of Approximate Telemetry Queries
    Chris Misa, Walt O'Connor, Ramakrishnan Durairajan, Reza Rejaie and Walter Willinger
    In Proceedings of USENIX NSDI'22, Renton, WA, April 2022.

  • Revisiting Network Telemetry in COIN: A Case for Runtime Programmability
    Chris Misa, Ramakrishnan Durairajan, Reza Rejaie and Walter Willinger
    In IEEE Network (In-Network Computing: Emerging Trends for the Edge-Cloud Continuum), September 2021.

  • ELF: High-Performance In-band Network Measurement
    Joel Sommers and Ramakrishnan Durairajan
    In Proceedings of TMA'21, Virtual, September 2021.
    [PAPER]     [CODE]

  • Challenges in Using ML for Networking Research: How to Label If You Must
    Yukhe Lavinia, Ramakrishnan Durairajan, Reza Rejaie and Walter Willinger
    In Proceedings of Workshop on Network Meets AI & ML (NetAI'20)
    co-located with ACM SIGCOMM'20, New York, USA, August 2020.

  • MicroMon: A Monitoring Framework for Tackling Distributed Heterogeneity
    Babar Khalid*, Nolan Rudolph*, Ramakrishnan Durairajan and Sudarsun Kannan
    In Proceedings of 12th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage'20)
    co-located with Usenix ATC'20, Massachusetts, USA, July 2020.
    [PAPER]     (* co-primary authors)

  • On the Practicality of Learning Models for Network Telemetry
    Soheil Jamshidi, Zayd Hammoudeh, Ramakrishnan Durairajan, Daniel Lowd, Reza Rejaie and Walter Willinger
    In Proceedings of TMA'20, Berlin, Germany, June 2020.

  • Denoising Internet Delay Measurements using Weak Supervision
    Anirudh Muthukumar and Ramakrishnan Durairajan
    In Proceedings of IEEE ICMLA'19, Florida, USA, December 2019.

  • Can We Containerize Internet Measurements?
    Christopher Misa, Sudarsun Kannan and Ramakrishnan Durairajan
    In Proceedings of ACM/IRTF/ISOC Applied Networking Research Workshop (ANRW'19)
    co-located with IETF 105, Montreal, Canada, July 2019.