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A Case for CATS: A Conductor-driven Asymmetric Transport Scheme for Semantic Prioritization

Syed Muhammad Aqdas Rizvi

Abstract

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.

A Case for CATS: A Conductor-driven Asymmetric Transport Scheme for Semantic Prioritization

Abstract

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.
Paper Structure (17 sections, 1 equation, 3 figures, 2 tables)

This paper contains 17 sections, 1 equation, 3 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Datacenters and Routers
  4. Datacenter Transport Scheduling
  5. Active Queue Management and Protocol Coexistence
  6. QUIC and HTTP/3
  7. The "Interceptor and Feeder" Architecture
  8. The CATS API and Signaling Ecosystem
  9. Priority Definition and Signaling
  10. End-to-End Signaling via TCP Option
  11. Network Efficiency Mechanisms
  12. The Cats Conductor and the Intra-Flow Fairness Mechanism
  13. Experimental Evaluation
  14. Experimental Setup
  15. Results: Priority Group Completion
  16. ...and 2 more sections

Figures (3)

  • Figure 1: The CATS Interceptor and Feeder architecture. The Conductor places all intercepted application data into priority queues and it is then fed to the underlying TCP base one prioritized, segment-sized chunk at a time.
  • Figure 2: Comparison of Priority Group Completion Times for Baseline TCP vs. CATS, demonstrating the priority inversion achieved by CATS.
  • Figure 3: Comparison of Effective Throughput. Baseline prioritizes throughput for the first object sent (P4), while CATS achieves higher throughput for the prioritized objects (P0-P3).