LSTM network traffic prediction and link congestion warning scheme for single port and single link
To predict the traffic at single port and single link,two network traffic prediction models based on long short-term memory neural network were proposed.The first model is for the traffic which changes smoothly at large time granularity.The second model is for the nonstationary traffic which fluctua...
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2019-12-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019066 |
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| _version_ | 1841530068462993408 |
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| author | Wei HUANG Cuncai LIU Sibo QI |
| author_facet | Wei HUANG Cuncai LIU Sibo QI |
| author_sort | Wei HUANG |
| collection | DOAJ |
| description | To predict the traffic at single port and single link,two network traffic prediction models based on long short-term memory neural network were proposed.The first model is for the traffic which changes smoothly at large time granularity.The second model is for the nonstationary traffic which fluctuates violently at small time granularity.By selecting different methods of splitting data and training models,two traffic prediction models with different neural network structures were constructed.The experimental results show that the former can achieve a very high accuracy when predicting smoothly changed traffic,the latter has a significantly better prediction effect than the support vector regression model and the back propagation neural network model when dealing with nonstationary traffic.Based on the second model,a link congestion warning scheme with variable parameters was proposed.The scheme is proved to be practicable by experiments. |
| format | Article |
| id | doaj-art-8bd5d977070c469c96b438206253ab85 |
| institution | Kabale University |
| issn | 2096-109X |
| language | English |
| publishDate | 2019-12-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-8bd5d977070c469c96b438206253ab852025-01-15T03:13:49ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2019-12-015505759557011LSTM network traffic prediction and link congestion warning scheme for single port and single linkWei HUANGCuncai LIUSibo QITo predict the traffic at single port and single link,two network traffic prediction models based on long short-term memory neural network were proposed.The first model is for the traffic which changes smoothly at large time granularity.The second model is for the nonstationary traffic which fluctuates violently at small time granularity.By selecting different methods of splitting data and training models,two traffic prediction models with different neural network structures were constructed.The experimental results show that the former can achieve a very high accuracy when predicting smoothly changed traffic,the latter has a significantly better prediction effect than the support vector regression model and the back propagation neural network model when dealing with nonstationary traffic.Based on the second model,a link congestion warning scheme with variable parameters was proposed.The scheme is proved to be practicable by experiments.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019066long short-term memory (LSTM)machine learningnetwork traffic predictionnonstationary traffic predictiontime series prediction |
| spellingShingle | Wei HUANG Cuncai LIU Sibo QI LSTM network traffic prediction and link congestion warning scheme for single port and single link 网络与信息安全学报 long short-term memory (LSTM) machine learning network traffic prediction nonstationary traffic prediction time series prediction |
| title | LSTM network traffic prediction and link congestion warning scheme for single port and single link |
| title_full | LSTM network traffic prediction and link congestion warning scheme for single port and single link |
| title_fullStr | LSTM network traffic prediction and link congestion warning scheme for single port and single link |
| title_full_unstemmed | LSTM network traffic prediction and link congestion warning scheme for single port and single link |
| title_short | LSTM network traffic prediction and link congestion warning scheme for single port and single link |
| title_sort | lstm network traffic prediction and link congestion warning scheme for single port and single link |
| topic | long short-term memory (LSTM) machine learning network traffic prediction nonstationary traffic prediction time series prediction |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019066 |
| work_keys_str_mv | AT weihuang lstmnetworktrafficpredictionandlinkcongestionwarningschemeforsingleportandsinglelink AT cuncailiu lstmnetworktrafficpredictionandlinkcongestionwarningschemeforsingleportandsinglelink AT siboqi lstmnetworktrafficpredictionandlinkcongestionwarningschemeforsingleportandsinglelink |