Practice on fifth-generation core (5GC) network fault self-recovery based on a Digital Twin

Digital Twin Pub Date : 2022-12-06 DOI:10.12688/digitaltwin.17692.1

Yifeng Zheng, Huaming Kong, Na Wang, Mei Li, Xiaoyu Wang, Zhesheng Xia, Pei Wang, Chenhao Wang

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Abstract

Background: The development of cloud-based, service-focused and intelligent networks has increased the demand for highly reliable, error-tolerant and computationally efficient means of reducing the costs associated with network operation, maintenance, testing and innovations. Methods: We present a fault self-recovery method for fifth-generation core (5GC) networks. Data models are built according to the data governance approach to include the equipment, links and services of the physical network in the digital twin. Visual topology technology is used to extract knowledge-as-a-service (KaaS) capabilities such as call quality tests, fault-propagation chain reasoning and disaster recovery analysis. Results: The proposed method realises 5GC closed-loop self-recovery through four processes: perception, analysis, decision-making and execution. In tests, it achieved 5GC network fault detection in 1 min, delimitation in 20 min, and recovery in 5 min. Conclusions: Through the network digital twin technology, based on the model and state data, the twinning capabilities such as simulation and event topology can be used to realize the network anomaly perception, fault rapid confinement and service survival decision, thus effectively improving the fault processing efficiency and reducing the fault impact.

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基于数字孪生的第五代核心(5GC)网络故障自恢复实践

背景:基于云的、以服务为中心的智能网络的发展增加了对高可靠、容错和计算高效的手段的需求，以降低与网络运营、维护、测试和创新相关的成本。方法:提出了一种针对第五代核心(5GC)网络的故障自恢复方法。根据数据治理方法构建数据模型，将物理网络的设备、链路和服务包括在数字孪生中。可视化拓扑技术用于提取知识即服务(KaaS)功能，如呼叫质量测试、故障传播链推理和灾难恢复分析。结果:该方法通过感知、分析、决策、执行四个过程实现5GC闭环自恢复。在测试中，实现了5GC网络故障检测1分钟，划分20分钟，恢复5分钟。结论:通过网络数字孪生技术，基于模型和状态数据，利用仿真和事件拓扑等孪生能力，实现网络异常感知、故障快速约束和业务生存决策，有效提高了故障处理效率，降低了故障影响。

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Digital Twin digital twin technologies-

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期刊介绍： Digital Twin is a rapid multidisciplinary open access publishing platform for state-of-the-art, basic, scientific and applied research on digital twin technologies. Digital Twin covers all areas related digital twin technologies, including broad fields such as smart manufacturing, civil and industrial engineering, healthcare, agriculture, and many others. The platform is open to submissions from researchers, practitioners and experts, and all articles will benefit from open peer review.  The aim of Digital Twin is to advance the state-of-the-art in digital twin research and encourage innovation by highlighting efficient, robust and sustainable multidisciplinary applications across a variety of fields. Challenges can be addressed using theoretical, methodological, and technological approaches. The scope of Digital Twin includes, but is not limited to, the following areas:  ● Digital twin concepts, architecture, and frameworks ● Digital twin theory and method ● Digital twin key technologies and tools ● Digital twin applications and case studies ● Digital twin implementation ● Digital twin services ● Digital twin security ● Digital twin standards Digital twin also focuses on applications within and across broad sectors including: ● Smart manufacturing ● Aviation and aerospace ● Smart cities and construction ● Healthcare and medicine ● Robotics ● Shipping, vehicles and railways ● Industrial engineering and engineering management ● Agriculture ● Mining ● Power, energy and environment Digital Twin features a range of article types including research articles, case studies, method articles, study protocols, software tools, systematic reviews, data notes, brief reports, and opinion articles.