MINT: Modeling GenAI Impact on Network Traffic

arXiv:2609.35742 · cs.NI, cs.SY, eess.SY · Submitted 2026-09-28 · Read on arXiv

cs.NI, cs.SY, eess.SY

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/wayslab/LLM-Network-Study3https:

Terminology

• Trace — 11× in this paper · explained in 2 episodes
• Modeling GenAI Impact on Network Traffic — 7× in this paper
• Wasserstein Distance — 6× in this paper · explained in 4 episodes
• Clustering — 4× in this paper · explained in 2 episodes
• Generative AI — 4× in this paper · explained in 2 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Agentic Evaluation — 1× in this paper · explained in 1 episode
• Akaike Information Criterion — 1× in this paper
• Bayesian Information Criterion — 1× in this paper
• Cognitive Load — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Fingerprinting — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Steering — 1× in this paper · explained in 2 episodes
• T2T with Berkeley Function Calling Leaderboard — 1× in this paper
• Transformer — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Introducing Large Language Models as the Next Challenging Internet Traffic Source
• A Comprehensive Survey on Network Traffic Synthesis: From Statistical Models to Deep Learning
• Revisiting Service Level Objectives and System Level Metrics in Large Language Model Serving
• Qwen3 Technical Report

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