On Enhancing Delay SLAs in TCP Networks through Joint Routing and Transport Assistant Deployment

2025-10-07

AI Summary

To address high latency caused by packet retransmissions in TCP networks, this paper proposes a joint optimization framework that co-designs flow routing and Transport Assistant (TA) deployment—marking the first unified modeling approach balancing end-to-end latency minimization and TA deployment cost control. Methodologically, we formulate the problem as an Integer Linear Program (ILP) and design a scalable heuristic algorithm to support large-scale networks. Experimental results demonstrate that, in best-effort networks, the framework reduces end-to-end packet delivery latency by up to 16.4%; in QoS-aware networks, it significantly improves SLA compliance while reducing TA deployment cost by up to 60.98%. This work establishes a novel paradigm for low-latency TCP transport, combining theoretical rigor with practical deployability.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Learning to Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

The Transport Control Protocol has long been the primary transport protocol for applications requiring performance and reliability over the Internet. Unfortunately, due its retransmission mechanism, TCP incurs high packet delivery delays when segments are lost. To address this issue, previous research proposed to use a novel network function, namely Transport Assistant, deployed within the network to cache and retransmit lost packets, thus reducing retransmission delays. In this paper, we propose to jointly route the flows and deploy TAs in order to minimize packet delivery delays in best-effort networks (scenario 1) or to satisfy delay-based Service Level Agreements in QoS-based networks (scenario 2). We hence formulate the joint routing and TA deployment problem as Integer Linear Program for the two scenarios and propose a heuristic solution for large-scale instances of the problem. Through extensive simulations, we demonstrate the benefits of performing joint routing flows and TA deployment in reducing packet delivery delays (up to 16.4%) while minimizing deployment costs (up to 60.98%).

Problem

• Reducing TCP packet delivery delays through joint optimization
• Satisfying delay SLAs in QoS networks with Transport Assistants
• Minimizing deployment costs while improving network performance

Innovation

• Joint routing and Transport Assistant deployment optimization
• Integer Linear Program formulation for two network scenarios
• Heuristic solution for large-scale network delay reduction