AI

Reducing Web Latency: the Virtue of Gentle Aggression

Abstract

To serve users quickly, Web service providers build infrastructure closer to clients and use multi-stage transport connections. Although these changes reduce client-perceived round-trip times, TCP's current mechanisms fundamentally limit latency improvements. We performed a measurement study of a large Web service provider and found that, while connections with no loss complete close to the ideal latency of one round-trip time, TCP's timeout-driven recovery causes transfers with loss to take five times longer on average.

In this paper, we present the design of novel loss recovery mechanisms for TCP that judiciously use redundant transmissions to minimize timeout-driven recovery. Proactive, Reactive, and Corrective are three qualitatively different, easily-deployable mechanisms that (1) proactively recover from losses, (2) recover from them as quickly as possible, and (3) reconstruct packets to mask loss. Crucially, the mechanisms are compatible both with middleboxes and with TCP's existing congestion control and loss recovery. Our large-scale experiments on Google's production network that serves billions of flows demonstrate a 23% decrease in the mean and 47% in 99th percentile latency over today's TCP.