Research on Fault Management System based on Artificial Intelligence in Data Network

Yunzhou Dong, Xinyu Wang, Fangyou Fu, Zhengdong Lin, Chaona Yin, Yingkun Liao, Peng Lin
{"title":"Research on Fault Management System based on Artificial Intelligence in Data Network","authors":"Yunzhou Dong, Xinyu Wang, Fangyou Fu, Zhengdong Lin, Chaona Yin, Yingkun Liao, Peng Lin","doi":"10.1109/BMSB58369.2023.10211345","DOIUrl":null,"url":null,"abstract":"SDN, NFV and other technologies increase the complexity of data network systems, resulting in an increase in the probability of network failures and the difficulty of maintenance. In order to design a more practical fault management framework and mechanism, the data network environment is analyzed first. Based on the characteristics of data network environment and network elements, a fault management architecture based on artificial intelligence is proposed. The architecture includes device layer, data acquisition layer, data analysis layer and data management layer. In order to improve the application value and convenience of the fault management architecture, the elastic strategy, self-healing strategy and work order distribution mechanism of the data management layer are designed in detail. In the performance analysis, from the implementation feasibility and performance aspects, it is verified that the fault management mechanism proposed in this paper has good application value.","PeriodicalId":13080,"journal":{"name":"IEEE international Symposium on Broadband Multimedia Systems and Broadcasting","volume":"6 5","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE international Symposium on Broadband Multimedia Systems and Broadcasting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMSB58369.2023.10211345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

SDN, NFV and other technologies increase the complexity of data network systems, resulting in an increase in the probability of network failures and the difficulty of maintenance. In order to design a more practical fault management framework and mechanism, the data network environment is analyzed first. Based on the characteristics of data network environment and network elements, a fault management architecture based on artificial intelligence is proposed. The architecture includes device layer, data acquisition layer, data analysis layer and data management layer. In order to improve the application value and convenience of the fault management architecture, the elastic strategy, self-healing strategy and work order distribution mechanism of the data management layer are designed in detail. In the performance analysis, from the implementation feasibility and performance aspects, it is verified that the fault management mechanism proposed in this paper has good application value.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于人工智能的数据网络故障管理系统研究
SDN、NFV等技术增加了数据网络系统的复杂性,导致网络故障的概率增加,维护难度加大。为了设计更实用的故障管理框架和机制,首先对数据网络环境进行了分析。根据数据网络环境和网元的特点,提出了一种基于人工智能的故障管理体系结构。该体系结构包括设备层、数据采集层、数据分析层和数据管理层。为了提高故障管理体系结构的应用价值和便捷性,详细设计了数据管理层的弹性策略、自愈策略和工单分发机制。在性能分析中,从实施可行性和性能方面验证了本文提出的故障管理机制具有良好的应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Collaborative Task Offloading Based on Scalable DAG in Cell-Free HetMEC Networks Resource Pre-caching Strategy of Digital Twin System Based on Hierarchical MEC Architecture Research on key technologies of audiovisual media microservices and industry applications A Closed-loop Operation and Maintenance Architecture based on Digital Twin for Electric Power Communication Networks Edge Fusion of Intelligent Industrial Park Based on MatrixOne and Pravega
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1