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| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.04432 |
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| _version_ | 1866914942651727872 |
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| author | Soto, Paola Camelo, Miguel Garcia-Aviles, Gines Municio, Esteban Gramaglia, Marco Kosmatos, Evangelos Slamnik-Kriještorac, Nina De Vleeschauwer, Danny Bazco-Nogueras, Antonio Fuentes, Lidia Ballesteros, Joaquin Lutu, Andra Cominardi, Luca Paez, Ivan Alcalá-Marín, Sergi Chatzieleftheriou, Livia Elena Garcia-Saavedra, Andres Fiore, Marco |
| author_facet | Soto, Paola Camelo, Miguel Garcia-Aviles, Gines Municio, Esteban Gramaglia, Marco Kosmatos, Evangelos Slamnik-Kriještorac, Nina De Vleeschauwer, Danny Bazco-Nogueras, Antonio Fuentes, Lidia Ballesteros, Joaquin Lutu, Andra Cominardi, Luca Paez, Ivan Alcalá-Marín, Sergi Chatzieleftheriou, Livia Elena Garcia-Saavedra, Andres Fiore, Marco |
| contents | As network complexity escalates, there is an increasing need for more sophisticated methods to manage and operate these networks, focusing on enhancing efficiency, reliability, and security. A wide range of Artificial Intelligence (AI)/Machine Learning (ML) models are being developed in response. These models are pivotal in automating decision-making, conducting predictive analyses, managing networks proactively, enhancing security, and optimizing network performance. They are foundational in shaping the future of networks, collectively forming what is known as Network Intelligence (NI). Prominent Standard-Defining Organizations (SDOs) are integrating NI into future network architectures, particularly emphasizing the closed-loop approach. However, existing methods for seamlessly integrating NI into network architectures are not yet fully effective. This paper introduces an in-depth architectural design for a Network Intelligence Stratum (NI Stratum). This stratum is supported by a novel end-to-end NI orchestrator that supports closed-loop NI operations across various network domains. The primary goal of this design is to streamline the deployment and coordination of NI throughout the entire network infrastructure, tackling issues related to scalability, conflict resolution, and effective data management. We detail exhaustive workflows for managing the NI lifecycle and demonstrate a reference implementation of the NI Stratum, focusing on its compatibility and integration with current network systems and open-source platforms such as Kubernetes and Kubeflow, as well as on its validation on real-world environments. The paper also outlines major challenges and open issues in deploying and managing NI. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_04432 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Designing the Network Intelligence Stratum for 6G Networks Soto, Paola Camelo, Miguel Garcia-Aviles, Gines Municio, Esteban Gramaglia, Marco Kosmatos, Evangelos Slamnik-Kriještorac, Nina De Vleeschauwer, Danny Bazco-Nogueras, Antonio Fuentes, Lidia Ballesteros, Joaquin Lutu, Andra Cominardi, Luca Paez, Ivan Alcalá-Marín, Sergi Chatzieleftheriou, Livia Elena Garcia-Saavedra, Andres Fiore, Marco Networking and Internet Architecture As network complexity escalates, there is an increasing need for more sophisticated methods to manage and operate these networks, focusing on enhancing efficiency, reliability, and security. A wide range of Artificial Intelligence (AI)/Machine Learning (ML) models are being developed in response. These models are pivotal in automating decision-making, conducting predictive analyses, managing networks proactively, enhancing security, and optimizing network performance. They are foundational in shaping the future of networks, collectively forming what is known as Network Intelligence (NI). Prominent Standard-Defining Organizations (SDOs) are integrating NI into future network architectures, particularly emphasizing the closed-loop approach. However, existing methods for seamlessly integrating NI into network architectures are not yet fully effective. This paper introduces an in-depth architectural design for a Network Intelligence Stratum (NI Stratum). This stratum is supported by a novel end-to-end NI orchestrator that supports closed-loop NI operations across various network domains. The primary goal of this design is to streamline the deployment and coordination of NI throughout the entire network infrastructure, tackling issues related to scalability, conflict resolution, and effective data management. We detail exhaustive workflows for managing the NI lifecycle and demonstrate a reference implementation of the NI Stratum, focusing on its compatibility and integration with current network systems and open-source platforms such as Kubernetes and Kubeflow, as well as on its validation on real-world environments. The paper also outlines major challenges and open issues in deploying and managing NI. |
| title | Designing the Network Intelligence Stratum for 6G Networks |
| topic | Networking and Internet Architecture |
| url | https://arxiv.org/abs/2405.04432 |