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Requirements and Specifications for the Orchestration of Network Intelligence in 6G

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  • Additional Information
    • Contributors:
      European Commission
    • Publication Information:
      IEEE
    • Publication Date:
      2022
    • Collection:
      Universidad Carlos III de Madrid: e-Archivo
    • Abstract:
      Next-generation mobile networks are expected to flaunt highly (if not fully) automated management. Network Intelligence (NI) will be the key enabler for such a vision, empowering myriad of orchestrators and controllers across network domains. In this paper, we elaborate on the DAEMON architectural model, which proposes introducing a NI Orchestration layer for the effective end-to-end coordination of NI instances deployed across the whole mobile network infrastructure. Specifically, we first outline requirements and specifications for NI design that stem from data management, control timescales, and network technology characteristics. Then, we build on such analysis to derive initial principles for the design of the NI Orchestration layer, focusing on (i) proposals for the interaction loop between NI instances and the NI Orchestrator, and (ii) a unified representation of NI algorithms based on an extended MAPE-K model. Our work contributes to the definition of the interfaces and operation of a NI Orchestration layer that foster a native integration of NI in mobile network architectures. ; This project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement no.101017109 DAEMON.
    • Relation:
      info:eu-repo/grantAgreement/EC/101017109; 2022-01-08; Online; 1ST INTERNATIONAL WORKSHOP ON 6G: VISIONS, USE CASES AND TECHNOLOGIES (6G'22); M. Camelo et al., "Requirements and Specifications for the Orchestration of Network Intelligence in 6G," 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), 2022, pp. 1-9; http://hdl.handle.net/10016/35798; 1st International Workshop on 6G: Visions, use cases and technologies; CC/0000033063
    • Accession Number:
      10.1109/CCNC49033.2022.9700729
    • Online Access:
      http://hdl.handle.net/10016/35798
      https://doi.org/10.1109/CCNC49033.2022.9700729
    • Rights:
      © Copyright 2022 IEEE ; open access
    • Accession Number:
      edsbas.F33F4458