基于IFIT的网络业务质量智能评估与故障定位方法

Yanqin Wu, Tiantian Lv, Le Zhang
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引用次数: 1

摘要

在互联网和通信领域,现有的业务故障定位技术都是基于带外测量,无法真实再现问题点。提出了一种基于IFIT的网络业务质量智能评估与故障定位方法。根据IFIT上报的性能数据和设备数据,采用基于AI技术的端到端质量智能评估模型,对端到端服务质量进行评估,检测服务状态。当端到端业务质量状态为差或中断时,将检测方式调整为逐跳模式,确定具体质量差或中断的链路和端口,然后确定故障发生的区域。评价结果表明,本文方法的评价值均在85%以上,高于传统方法,综合比较结果表明,本文方法的评价值比传统方法高10%,证明了本文方法的有效性和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A network business quality intelligent assessment and fault location method based on IFIT
In the field of Internet and communication, the existing service fault location technology is based on out-of-band measurement, cannot really reproduce the problem points. This paper presents a network business quality intelligent assessment and fault location method based on IFIT. According to the performance data and device data reported by the IFIT, the end-to-end quality intelligent evaluation model based on AI technology is used to evaluate the end-to-end service quality and detect the service status. If the end-to-end service quality status is poor or interrupted, adjust the detection mode to hop-by-hop mode, determine the link and port where the specific quality is poor or interrupted, and then determine the area where the fault occurs. The evaluation results show that, and values of the methods in this paper are all over 85%, higher than the traditional methods, and the comprehensive comparison results show the method of this paper are 10% higher than traditional method, which prove the validity and reliability of the method presented in this paper.
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