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5G-MoNArch Use Case for ETSI ENI: Elastic Resource Management and Orchestration

机译:5G-Monarch使用ETSI ENI的案例:Elastic Resource Management和Orchestration

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5G networks will grant spectacular improvements of the most relevant Key Performance Indicators (KPIs) while allowing resource multi-tenancy through network slicing. However, the other side of the coin is represented by the huge increase of the management complexity and the need for efficient algorithms for resource orchestration. Therefore, the management and orchestration of the network through Artificial Intelligence (AI) and Machine Learning (ML) algorithms is considered a promising solution, as it allows to reduce the human interaction (usually expensive and error-prone) and scale to large scenario composed by thousands of slices in heterogeneous environments. In this paper, we provide a review of the current standardization efforts in this field, mostly due to the work performed by the Experiential Network Intelligence (ENI) industry specification group (ISG) within the European Telecommunications Standards Institute (ETSI). Then, we thoroughly describe an exemplary use case on elastic network management and orchestration through learning solutions proposed by the 5GPPP project 5G-MoNArch and recently approved at ETSI ENI.
机译:5G网络将授予最相关的关键绩效指标(KPI)的壮观改进,同时通过网络切片允许资源多租赁。然而,硬币的另一边是由管理复杂性的巨大增加和资源编排的有效算法的巨大增加来表示。因此,通过人工智能(AI)和机器学习(ML)算法的网络管理和编排被认为是一个有希望的解决方案,因为它允许减少人类交互(通常昂贵且易于出错)和扩展到大型场景在异构环境中的数千片切片。在本文中,我们对本领域目前的标准化工作进行了审查,主要是由于欧洲电信标准研究所(ETSI)内的经验网络智能(ENI)行业规范组(ISG)执行的工作。然后,我们通过5GPPP项目5G-MONARCH提出的解决方案彻底描述了弹性网络管理和编排的示例性用例,并在ETSI eni批准。

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