Traffic Engineering in Large-scale Networks with Generalizable Graph Neural Networks

arXiv:2503.24203 · cs.NI, cs.LG · Submitted 2025-03-31 · Read on arXiv

cs.NI, cs.LG

Submitted: 2025-03-31

Updated: 2026-09-17

Comments: Updated version to include link to new open-source repository. The previous repo was invalidated due to institutional Github license change. The code and detailed instructions for reproduction are now hosted in a public repo

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Generalizability — 22× in this paper · explained in 6 episodes
• Traffic Engineering — 22× in this paper
• Generalization — 14× in this paper · explained in 13 episodes
• GNNs — 9× in this paper · explained in 2 episodes
• Reinforcement Learning — 6× in this paper · explained in 4 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Loss Function — 4× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Low Earth Orbit — 3× in this paper
• Objective Function — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Aggregation Function — 2× in this paper · explained in 1 episode
• Combinatorial Optimization — 2× in this paper · explained in 2 episodes
• Steering — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Alternating Direction Method of Multipliers — 1× in this paper
• Alternating Direction Method of Multipliers (ADMM) — 1× in this paper · explained in 2 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Federated Learning — 1× in this paper · explained in 14 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Graph Neural Network (GNN) — 1× in this paper · explained in 2 episodes
• Online Adaptation — 1× in this paper · explained in 3 episodes
• Over-smoothing — 1× in this paper · explained in 4 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• State-ofthe-art Linear Program — 1× in this paper

Sources

• An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
• DeeperGCN: All You Need to Train Deeper GCNs
• What Can Neural Networks Reason About?
• Gemini: Practical Reconfigurable Datacenter Networks with Topology and Traffic Engineering

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