Waiting for QUIC: Passive Measurements to Understand QUIC Deployments

TL;DR

This paper presents a passive measurement approach to analyze QUIC deployment and configuration variations among major hypergiants over five years, revealing differences in settings, deployment strategies, and load balancing insights.

Contribution

It introduces a novel passive measurement method to study QUIC deployments and configurations, providing insights into hypergiant strategies over time.

Findings

Meta, Google, and Cloudflare have different QUIC retransmission and timeout settings.

Identifies off-net hypergiant deployments using packet features.

Deployment configurations of hypergiants change over time.

Abstract

QUIC experiences a rapid adoption since its standardization in 2021, and hypergiants configure their infrastructure to optimize for QUIC performance. In this paper, we introduce a passive measurement method to study both the progressive rollout and individual hypergiant configurations during the last five years. By analyzing backscatter traffic of the UCSD network telescope, we are able to make the following observations. First, Meta, Google, and Cloudflare configure significantly different maximal retransmission numbers and timeouts. Second, we can identify different off-net deployments of hypergiants, using packet features, such as QUIC connection IDs, packet coalescence, and packet lengths. Third, we observe changing hypergiant deployment configurations during our different measurement periods. Fourth, connection IDs can allow further insights into load balancer deployments, such as the number of servers. We bolster our results using two orthogonal measurements: passive recording of QUIC flows and active probing.