A Case for CATS: A Conductor-driven Asymmetric Transport Scheme for Semantic Prioritization
This addresses performance issues for latency-sensitive and interactive applications by providing a novel transport-layer solution, though it builds upon existing TCP BBR and is incremental in improving prioritization.
The paper tackled the problem of standard transport protocols lacking semantic awareness for latency-sensitive applications by introducing CATS, a framework that prioritizes critical content, resulting in a 78% reduction in First Contentful Paint in a worst-case scenario without penalizing total page load time.
Standard transport protocols like TCP operate as a blind, FIFO conveyor belt for data, a model that is increasingly suboptimal for latency-sensitive and interactive applications. This paper challenges this model by introducing CATS (Conductor-driven Asymmetric Transport Scheme), a framework that provides TCP with the semantic awareness necessary to prioritize critical content. By centralizing scheduling intelligence in a transport-native "Conductor", CATS significantly improves user-perceived performance by delivering essential data first. This architecture directly confronts a cascade of historical performance workarounds and their limitations, including the high overhead of parallel connections in HTTP/1.1, the transport-layer Head-of-Line blocking in HTTP/2, and the observed implementation heterogeneity of prioritization in HTTP/3 over QUIC. Built upon TCP BBR, our ns-3 implementation demonstrates this principle by reducing the First Contentful Paint by over 78% in a representative webpage download configured as a deliberate worst-case scenario, with no penalty to total page load time compared to the baseline.