Knowledge Graphs for Enhanced Cross-Operator Incident Management and Network Design
draft-tailhardat-nmop-incident-management-noria-02

Abstract

Operational efficiency in incident management on telecom and computer networks requires correlating and interpreting large volumes of heterogeneous technical information. Knowledge graphs can provide a unified view of complex systems through shared vocabularies. YANG data models enable describing network configurations and automating their deployment. However, both approaches face challenges in vocabulary alignment and adoption, hindering knowledge capitalization and sharing on network designs and best practices. To address this, the concept of a IT Service Management (ITSM) Knowledge Graph (KG) is introduced to leverage existing network infrastructure descriptions in YANG format and enable abstract reasoning on network behaviors. The key principle to achieve the construction of such ITSM-KG is to transform YANG representations of network infrastructures into an equivalent knowledge graph representation, and then embed it into a more extensive data model for Anomaly Detection (AD) and Risk Management applications. In addition to use case analysis and design pattern analysis, an experiment is proposed to assess the potential of the ITSM-KG in improving network quality and designs.

Authors

Lionel Tailhardat
Raphaël Troncy
Yoan Chabot
Fano Ramparany
Pauline Folz

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