{"title":"基于人工智能的数据网络故障管理系统研究","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":"{\"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}","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}
Research on Fault Management System based on Artificial Intelligence in Data Network
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.