面向5G智慧医疗的切片分组网络告警识别

Alarm Recognition of Sliced Packet Network for 5G Wisdom Medical Treatment

为提升5G智慧医疗专网的场景化运行和承载能力,快速识别和排除日常运维中遇到的故障告警,文章从构建SPN智慧医疗专用切片网络入手,在分析切片专网的组成结构和业务模型特征的基础上,提出基于告警三级智能处置模型的切片专网告警处置流程,并通过故障模拟进行效果验证。通过仿真发现三级告警有效压降率分别为35%、41%、22%,总体告警压降率达98%,可有效完成智慧医疗切片网络的告警识别和排障指导,保障智慧医疗专网业务的安全运行。

In order to improve the scene operation and carrying capacity of 5G wisdom medical private network,and quickly identify and eliminate the fault alarms encountered in daily operation and maintenance,this paper starts with the construction of SPN wisdom medical dedicated sliced network,analyzes the composition structure and business model characteristics of sliced private network,and puts forward the alarm disposal process of sliced private network based on alarm three-level intelligent disposal model.The effect is verified by fault simulation.The simulation results show that the effective voltage drop rates of three-level alarms are 35%,41%and 22%respectively,and the overall alarm voltage drop rate reaches 98%,which can effectively complete the alarm identification and troubleshooting guidance of wisdom medical sliced network,and ensure the safe operation of wisdom medical private network services.