Journal
IEEE COMMUNICATIONS MAGAZINE
Volume 59, Issue 10, Pages 106-112Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MCOM.101.2100141
Keywords
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Funding
- AEI IBON project [PID2020-114135RB-I00]
- ICREA Institution
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The article proposes an end-to-end and ubiquitous secure machine learning (ML)-powered intent-based networking (IBN) framework for autonomously taking proactive actions for service assurance.
To reap its full benefits, 5G must evolve into a scalable decentralized architecture by exploiting intelligence ubiquitously and securely across different technologies, network layers, and segments. In this article, we propose end-to-end and ubiquitous secure machine learning (ML)-powered intent-based networking (IBN). The IBN framework is aware of its state and context to autonomously take proactive actions for service assurance. It is integrated in a zero-touch control and orchestration framework featuring an ML function orchestrator to manage ML pipelines. The objective is to create an elastic and dynamic infrastructure supporting per-domain and end-to-end network and services operation. The solution is supported by a radio access network and forwarding plane, and a cloud/edge virtualization infrastructure with ML acceleration. The resulting framework supports application-level resilience and intelligence through replication and elasticity. An illustrative intelligent application use case is presented.
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