IEEE Access (Jan 2023)

NLP Powered Intent Based Network Management for Private 5G Networks

  • Joseph Mcnamara,
  • Daniel Camps-Mur,
  • Meysam Goodarzi,
  • Hilary Frank,
  • Lorena Chinchilla-Romero,
  • Ferran Canellas,
  • Adriana Fernandez-Fernandez,
  • Shuangyi Yan

DOI
https://doi.org/10.1109/ACCESS.2023.3265894
Journal volume & issue
Vol. 11
pp. 36642 – 36657

Abstract

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Intent driven networking holds the promise of simplifying network operations by allowing operators to use declarative, instead of imperative, interfaces. Adoption of this technology for 5G and beyond networks is however still in its infancy, where the required architectures, platforms, interfaces and algorithms are still being discussed. In this work, we present the design and implementation of a novel intent based platform for private 5G networks powered by a Natural Language Processing (NLP) interface. We demonstrate how our platform simplifies network operations in three relevant private network use cases, including: i) an intent based slice provisioning use case, ii) an intent based positioning use case, and iii) an intent based service deployment use case. Finally, all use cases are benchmarked in terms of intent provisioning time.

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