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Towards intent-based management for Open Radio Access Networks: an agile framework for detecting service-level agreement conflicts

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Abstract

Radio Access Networks (RAN) management and orchestration are challenging due to the network’s complexity and dynamics. Management and orchestration rely on enforcing complex policies derived from mapping high-level intents, expressed as Service-Level Agreements (SLAs), into low-level actions to be deployed on the network. Such mapping is human-made and frequently leads to errors. This paper proposes the AGility in Intent-based management of service-level agreement Refinements (AGIR) system for implementing automated intent-based management in Open Radio Access Networks (Open RAN). The proposed system is modular and relies on Natural Language Processing (NLP) to allow operators to specify Service-Level Objectives (SLOs) for the RAN to fulfill without explicitly defining how to achieve these SLOs. It is possible because the AGIR system translates imprecise intents into configurable network instructions, detecting conflicts among the received intents. To develop the conflict detection module, we propose to use two deep neural network models, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The deep neural network model determines whether intents and policies are conflicting. Our results reveal that the proposed system reaches more than 80% recall in detecting conflicting intents when deploying an LSTM model with 256 neurons.

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Data Availability

No datasets were generated or analyzed during the current study.

Notes

  1. The first three contributions are derived from the previous work, while the fourth is a new addition stemming from this extended version.

  2. https://rasa.community/.

  3. https://keras.io/.

  4. https://www.nltk.org/.

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Funding

This work was supported in part by CNPq, CAPES, RNP, FAPERJ, FAPESP (2018/23062-5) and Niterói City Hall/FEC/UFF (Edital PDPA 2020).

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Authors and Affiliations

  1. MídiaCom/PPGEET/TET/IC, Universidade Federal Fluminense (UFF), Niterói, RJ, Brazil

    Nicollas R. de Oliveira, Dianne S. V. Medeiros, Igor M. Moraes & Diogo M. F. Mattos

  2. Technology Innovation Institute, P.O. Box 9639, Masdar City, Abu Dhabi, United Arab Emirates

    Martin Andreonni

Authors
  1. Nicollas R. de Oliveira
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  2. Dianne S. V. Medeiros
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  3. Igor M. Moraes
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  4. Martin Andreonni
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  5. Diogo M. F. Mattos
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Contributions

Conceptualization, D.M.F.M., D.S.V.M.; methodology, N.R.O., D.M.F.M. and D.S.V.M.; validation, N.R.O., D.M.F.M., D.S.V.M. and N.R.O.; investigation, N.R.O., D.M.F.M. and D.S.V.M.; resources, D.M.F.M. and D.S.V.M.; writing—original draft preparation, N.R.O.; writing—review and editing, N.R.O., D.S.V.M., I.M.M., M.A.L., and D.M.F.M.; figures and diagrams, N.R.O.; supervision, D.M.F.M. and D.S.V.M.; project administration, D.M.F.M., D.S.V.M. and I.M.M.; funding acquisition, D.M.F.M. and D.S.V.M. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Nicollas R. de Oliveira.

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de Oliveira, N.R., Medeiros, D.S.V., Moraes, I.M. et al. Towards intent-based management for Open Radio Access Networks: an agile framework for detecting service-level agreement conflicts. Ann. Telecommun. (2024). https://doi.org/10.1007/s12243-024-01035-3

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