CRII: NeTS: The Battle for Bandwidth: Heterogeneous Congestion Control on Today's Internet

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Internet congestion is more and more frequently a challenge in home networks, Internet service providers, enterprises, and cloud datacenters. Where congestion occurs, it introduces packet loss, increases network latency, and slows down throughput for individual connections - all of which contribute to poor performance for applications running over the Internet. A close look at congestion can reveal that there are winners and losers on the Internet: when bandwidth becomes a scarce resource, some senders crowd others out, dominating link capacity and harming the performance of other connections. Analyzing these winners and losers becomes challenging because every Internet service is free to independently determine its sending rate, speeding up to consume more bandwidth or slowing down to share the link, according to the parameters of its congestion control algorithm. Examples of common congestion control (CC) algorithms include NewReno, Cubic, Akamai's FastTCP, and Google's BBR.This proposal aims to understand the state of fair bandwidth allocation given the heterogenous congestion control algorithms in use today. Our project goal is twofold: (1) to measure what CC algorithms are in use 'in the wild' today; and (2) to evaluate each algorithm in controlled experiments in contention with other algorithms. To achieve (1), we will design and implement new techniques to identify and characterize the CC in use for arbitrary Internet services (even when we cannot control the service ourselves). To achieve (2), we propose new frameworks to conduct scientific evaluation of fairness and, where possible, combine our fairness measurements with mathematical models describing our results.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.