An LLM-Based Framework for Intent-Driven Network Topology Design
Designing deployable and resilient network topologies from natural language requirements remains a challenging problem in network automation. This work investigates the ability of Large Language Models (LLMs) to generate structurally valid and constraint-compliant network topologies through a constraint-driven pipeline combining hierarchical modeling and systematic validation. The framework is evaluated via a multimodel comparison of proprietary and open-weight LLMs across four realistic network scenarios released as a public dataset. We assess structural correctness using node and edge F1-scores against reference topologies, and evaluate resilience through server and content connectivity...
| Authors | Kholoud El-Habbouli, Fen Zhou, Stephane Huet |
|---|---|
| Primary category | cs.NI |
| Published | 1 July 2026 |
| Last updated at source | 27 August 2026 |
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