NetKG: Synthesizing Interpretable Network Router Configurations With Knowledge Graph

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. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">In this paper, we present NetKG, an interpretable configuration synthesis tool.(<i>i</i>) NetKG leverages a knowledge graph as the intermediate representation for configurations, reformulating the configuration synthesis problem as a configuration knowledge completion task; (<i>ii</i>) NetKG regards network intents as query tasks that need to be satisfied in the current configuration space, achieving this through knowledge reasoning and completion; (<i>iii</i>) NetKG explains the synthesis process and the consistency between configuration and intent through the configuration knowledge involved in reasoning and completion. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">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.

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Publication Details

Journal
IEEE Transactions on Computers
Published
2025-09-01
DOI
https://doi.org/10.1109/tc.2025.3603712
Citations
1
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
1.49
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article

NetKG: Synthesizing Interpretable Network Router Configurations With Knowledge Graph

Zhenbei Guo, Fuliang Li, Xingwei Wang, Jiannong Cao et al.
1 citations
IEEE Transactions on Computers
Software System Performance and Reliability
1.49
article

NetKG: Synthesizing Interpretable Network Router Configurations With Knowledge Graph

Zhenbei Guo, Fuliang Li, Xingwei Wang, Jiannong Cao, Peng Zhang
article en
1 citations

Abstract

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. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">In this paper, we present NetKG, an interpretable configuration synthesis tool.(<i>i</i>) NetKG leverages a knowledge graph as the intermediate representation for configurations, reformulating the configuration synthesis problem as a configuration knowledge completion task; (<i>ii</i>) NetKG regards network intents as query tasks that need to be satisfied in the current configuration space, achieving this through knowledge reasoning and completion; (<i>iii</i>) NetKG explains the synthesis process and the consistency between configuration and intent through the configuration knowledge involved in reasoning and completion. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">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.

IEEE Transactions on ComputersVol. 74(11)
Hong Kong Polytechnic University (HK), Xi'an Jiaotong University (CN), Northeastern University (CN)
Openalex Percentile: Top 13%
Software System Performance and Reliability
1.49
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