Ranysha Ware

Battle for Bandwidth: On the Deployability of New Congestion Control Algorithms Degree Type: Ph.D. in Computer Science
Advisor(s): Justine Sherry, Srinivasan Seshan
Graduated: August 2024

Abstract:

The Internet has become the central source of information and communication in modern society. Congestion control algorithms (CCAs) are critical for the stability of the Internet: ensuring that users can fairly and eciently share the network. Over the past 30 years, researchers and Internet content providers have proposed and deployed dozens of new CCAs designed to keep up with the growing demands of faster networks, diverse applications, and mobile users. Without tools to understand this growing heterogeneity in CCAs deployed on the Internet, the fairness of the Internet is at stake.

Towards understanding this growing heterogeneity, we develop CCAnalyzer, a tool to determine what CCA a particular web service deploys, outperforming previous classiers in accuracy and eciency. With CCAnalyzer, we show that new CCAs, both known and unknown, have widespread deployment on the Internet today, including a recently proposed CCA by Google: BBRv1. Next, we develop the rst model of BBRv1, and prove BBRv1 can be very unfair to legacy loss-based CCAs, an alarming nding given the prolic deployment of BBRv1.

Consequently, we argue the need for a better methodology for determining if a new CCA is safe to deploy on the Internet today. We describe how the typical methodology testing for equal-rate fairness (every user gets the same bandwidth) is both an unachievable goal and ultimately, not the right threshold for determining if a new CCA is safe to deploy alongside others. Instead of equal-rate fairness, we propose a new metric we call, harm, and argue for a harm-based threshold. Lastly, we present RayGen, a novel framework for evaluating interactions between heterogeneous CCAs. RayGen uses a genetic algorithm to eciently explore the large state space of possible workloads and network settings when two CCAs compete. With a small budget of experiments, RayGen nds more harmful scenarios than a parameter sweep and random search.

Thesis Committee:
Justine Sherry (Co-Chair)
Srinivasan Seshan (Co-Chair)
Theophilus A. Benson
Jim Kurose (University of Massachusetts Amherst)

Srinivasan Seshan, Head, Computer Science Department
Martial Hebert, Dean, School of Computer Science

Keywords:
Computer Networks, Congestion Control, Internet Measurement