The goal of this project is to collect anonymized traces from the Columbia network in order to analyze video traffic characteristics during the work/study-from home period. This information will be used for developing various ML-based tools for Quality of Experience (QoE) measurement. We will perform the feature extraction at the collection time itself and use anonymization techniques (e.g., IP address anonymization), to preserve user privacy. Students will analyze/measure encrypted network traffic to provide ground truth for potential RL/ML algorithms for estimating video QoE and identifying device/application (e.g., the start of a video streaming session). These algorithms can serve as a basis for new video adaptation techniques (see for example - https://wimnet.ee.columbia.edu/wimnet-team-wins-3rd-place-in-the-acm-mmsys20-twitch-grand-challenge/)

For the summer term, selected candidate(s) may receive a stipend directly from the faculty advisor. This is not a guarantee of payment, and the total amount is subject to available funding.

Faculty Advisor

  • Professor: Gil Zussman
  • Department/School: Electrical Engineering
  • Location: CEPSR 8th floor
  • The lab focuses on the design and performance evaluation of protocols and applications for future wireless and wired networks (e.g., beyond-5G, VR/AR, etc.). Among other things, lab members collect data and conduct experiments on the COSMOS testbed (https://cosmos-lab.org) and apply various techniques including learning in networks and learning for network optimization.

Project Timeline

  • Earliest starting date: 3/1/2021
  • End date: 8/10/2021
  • Number of hours per week of research expected during Spring 2021: ~8
  • Number of hours per week of research expected during Summer 2021: ~35

Candidate requirements

  • Skill sets:
    • Understanding of networking (e.g.,cpdump, iperf, WireShark) and familiarity with Linux OS
    • Programming languages required include Python (or C/ C++)
    • Knowledge of ML algorithms and Deep Reinforcement Learning prefered
    • Experience with optical transceivers and switch configuration preferred
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes