Research

Self-Driving Networks

The long-term research goal for Systems and Networking Lab (SNL) is to develop self-driving networks, i.e., build networks that can run themselves with minimal intervention. Specifically, our goal is to develop self-driving last-mile networks (e.g., cable, mobile, satellite, etc.) that can provide highly available, reliable, performant and secure network connectivity to under-served communities.

To this end, our group explores (1) how we can leverage the flexibility of programmable data-plane targets and the intelligibility of ML algorithms to solve different learning problems in networking; and (2) how we can establish trust in ML-based artifacts for networking, such that network operators feel confident relinquishing control to these artifacts in production settings.

Related Publications

Some of the recent works that best represent some of the ongoing projects at SNL:

• AI/ML for Network Security: The Emperor has no Clothes, ACM CCS, 2022.
• The Importance of Contextualization of Crowdsourced Active Speed Test Measurements, ACM IMC, 2022.
• Detecting Ephemeral Optical Events with OpTel, USENIX NSDI, 2022.
• Internet Inequity in Chicago: Adoption, Affordability, and Availability, TPRC, 2022.
• DynamiQ: Planning for Dynamics in Network Streaming Analytics Systems, arXiv: Report 2106.05420, 2021.
• An Effort to Democratize Networking Research in the Era of AI/ML, ACM HotNets 2019.

Funding

The research in my group is funded by National Science Foundation (NSF) and different network service providers (Verizon Innovations, ViaSat) and vendors (Intel).

You can find more details about some of the funded projects here:

• IMR: RI-P: Programmable Closed-loop Measurement Platform for Last-Mile Networks (NSF)
• IMR: MM-1A: ADDRESS: Augment, Denoise and Debias Crowdsourced Measurements for Statistical Synthesis of Internet Access Characterization (NSF)
• CC* Integration-Large: Democratizing Networking Research in the Era of AI/ML (NSF)
• CC* Integration-Large: Bringing Code to Data: A Collaborative Approach to Democratizing Internet Data Science (NSF)
• The Estimation and Monitoring of Quality of Experience Delivered over Internet Services (ViaSat)
• MLWiNS: RL-based Self-driving Wireless Network Management System for QoE Optimization (NSF and Intel)
• Scaling Cybersecurity Infrastructure using Programmable Data Planes (Verizon)