Using Natural Language Constructs and Concepts to Aid Network Management

The increasing complexity of networks together with technological trends that allow for fine-grained control and programmability have made network management a pressing challenge. In this work, we propose to harness the vast amounts of network management data that are available from different sources in an automated system that can infer context and semantics. We present an argument for a Network Processing Language that is based on the ideas of natural language processing. Our approach shows how concepts, such as collocations, can be applied to network management data. We demonstrate the effectiveness of our approach to detect route prefix and sub-prefix hijacks. This work presents one step toward effectively using automated tools for network management in complex, programmable networks.