NetKG: Synthesizing Interpretable Network Router Configurations With Knowledge Graph

作者：Zhenbei Guo, Fuliang Li, Peng Zhang, Xingwei Wang, Jiannong Cao · 发表于：IEEE Transactions on Computers · 年份：2025 · DOI：10.1109/tc.2025.3603712 · 被引用次数：1 · 研究领域：Software System Performance and Reliability、Advanced Graph Neural Networks、Network Packet Processing and Optimization

Advanced router configuration synthesizers aim to prevent network outages by automatically synthesizing configurations that implement routing protocols. However, the lack of interpretability makes operators uncertain about how low-level configurations are synthesized and whether the automatically generated configurations correctly align with routing intents. This limitation restricts the practical deployment of synthesizers.In this paper, we present NetKG, an interpretable configuration synthesis tool.(i) NetKG leverages a knowledge graph as the intermediate representation for configurations, reformulating the configuration synthesis problem as a configuration knowledge completion task; (ii) NetKG regards network intents as query tasks that need to be satisfied in the current configuration space, achieving this through knowledge reasoning and completion; (iii) NetKG explains the synthesis process and the consistency between configuration and intent through the configuration knowledge involved in reasoning and completion.We show that NetKG can scale to realistic networks and automatically synthesize intent-compliant configurations for static routes, OSPF, and BGP. It can explain the consistency between configuration and intent at different granularities through a visual interface. Experimental results indicate that NetKG synthesizes configurations in 2 minutes for a network with up to 197 routers, which is 7.37x faster than the SMT-based synthesizer.