Automated anomaly detection of IPTV user experience
Architecture of IPTV system is complex, involving a large number of terminals, network elements and connections. Therefore, a relatively complete monitoring system, which collected massive EPG experience data and formed multi-dimensional monitoring indicators, had been established to monitor user ex...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2019-07-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2019051/ |
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| _version_ | 1841530557553442816 |
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| author | Xiaomin TAN Ai FANG Duo JIN Changjiang LI |
| author_facet | Xiaomin TAN Ai FANG Duo JIN Changjiang LI |
| author_sort | Xiaomin TAN |
| collection | DOAJ |
| description | Architecture of IPTV system is complex, involving a large number of terminals, network elements and connections. Therefore, a relatively complete monitoring system, which collected massive EPG experience data and formed multi-dimensional monitoring indicators, had been established to monitor user experience. Due to a large number of indicators, manual monitoring was time consuming and laborious. It was hard to detect anomalies in time and it was impossible to determine the cause of abnormality. To solve the pain points of the operation, an intelligent algorithm was implied and improved to analyze massive experience data. The practice indicates that the algorithm with low calculation cost adapts to abnormal changes in the network and detect anomalies accurately and quickly, which reduces labor costs, improves operation efficiency and promotes intelligent operation. |
| format | Article |
| id | doaj-art-ea10b38cd8fc4f8e9c343dc7539266ae |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2019-07-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-ea10b38cd8fc4f8e9c343dc7539266ae2025-01-15T03:02:41ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012019-07-013515916459589155Automated anomaly detection of IPTV user experienceXiaomin TANAi FANGDuo JINChangjiang LIArchitecture of IPTV system is complex, involving a large number of terminals, network elements and connections. Therefore, a relatively complete monitoring system, which collected massive EPG experience data and formed multi-dimensional monitoring indicators, had been established to monitor user experience. Due to a large number of indicators, manual monitoring was time consuming and laborious. It was hard to detect anomalies in time and it was impossible to determine the cause of abnormality. To solve the pain points of the operation, an intelligent algorithm was implied and improved to analyze massive experience data. The practice indicates that the algorithm with low calculation cost adapts to abnormal changes in the network and detect anomalies accurately and quickly, which reduces labor costs, improves operation efficiency and promotes intelligent operation.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2019051/IPTVEPGautomated anomaly detectionintelligent operation |
| spellingShingle | Xiaomin TAN Ai FANG Duo JIN Changjiang LI Automated anomaly detection of IPTV user experience Dianxin kexue IPTV EPG automated anomaly detection intelligent operation |
| title | Automated anomaly detection of IPTV user experience |
| title_full | Automated anomaly detection of IPTV user experience |
| title_fullStr | Automated anomaly detection of IPTV user experience |
| title_full_unstemmed | Automated anomaly detection of IPTV user experience |
| title_short | Automated anomaly detection of IPTV user experience |
| title_sort | automated anomaly detection of iptv user experience |
| topic | IPTV EPG automated anomaly detection intelligent operation |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2019051/ |
| work_keys_str_mv | AT xiaomintan automatedanomalydetectionofiptvuserexperience AT aifang automatedanomalydetectionofiptvuserexperience AT duojin automatedanomalydetectionofiptvuserexperience AT changjiangli automatedanomalydetectionofiptvuserexperience |