Cloud server aging prediction method based on hybrid model of auto-regressive integrated moving average and recurrent neural network
In view of the nonlinear, stochastic and sudden characteristics of operating environment of cloud server system, a software aging prediction method based on hybrid auto-regressive integrated moving average and recurrent neural network model (ARIMA-RNN) was proposed.Firstly, the ARIMA model performs...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2021-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021015/ |
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| author | Haining MENG Xinyu TONG Yuekai SHI Lei ZHU Kai FENG Xinhong HEI |
| author_facet | Haining MENG Xinyu TONG Yuekai SHI Lei ZHU Kai FENG Xinhong HEI |
| author_sort | Haining MENG |
| collection | DOAJ |
| description | In view of the nonlinear, stochastic and sudden characteristics of operating environment of cloud server system, a software aging prediction method based on hybrid auto-regressive integrated moving average and recurrent neural network model (ARIMA-RNN) was proposed.Firstly, the ARIMA model performs software aging prediction of time series data in cloud server.Then the grey relation analysis method was used to calculate the correlation of the time series data to determine the input dimension of RNN model.Finally, the predicted value of ARIMA model and historical data were used as the input of RNN model for secondary aging prediction, which overcomes the limitation that ARIMA model has low prediction accuracy for time series data with large fluctuation.The experimental results show that the proposed ARIMA-RNN model has higher prediction accuracy than ARIMA model and RNN model, and has faster prediction convergence speed than RNN model. |
| format | Article |
| id | doaj-art-fa6c784256514f9eb656c5a4f68a1dfd |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-fa6c784256514f9eb656c5a4f68a1dfd2025-01-14T07:21:33ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-01-014216317159739936Cloud server aging prediction method based on hybrid model of auto-regressive integrated moving average and recurrent neural networkHaining MENGXinyu TONGYuekai SHILei ZHUKai FENGXinhong HEIIn view of the nonlinear, stochastic and sudden characteristics of operating environment of cloud server system, a software aging prediction method based on hybrid auto-regressive integrated moving average and recurrent neural network model (ARIMA-RNN) was proposed.Firstly, the ARIMA model performs software aging prediction of time series data in cloud server.Then the grey relation analysis method was used to calculate the correlation of the time series data to determine the input dimension of RNN model.Finally, the predicted value of ARIMA model and historical data were used as the input of RNN model for secondary aging prediction, which overcomes the limitation that ARIMA model has low prediction accuracy for time series data with large fluctuation.The experimental results show that the proposed ARIMA-RNN model has higher prediction accuracy than ARIMA model and RNN model, and has faster prediction convergence speed than RNN model.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021015/software agingcloud serverprediction methodauto-regressive integrated moving average modelrecurrent neural network model |
| spellingShingle | Haining MENG Xinyu TONG Yuekai SHI Lei ZHU Kai FENG Xinhong HEI Cloud server aging prediction method based on hybrid model of auto-regressive integrated moving average and recurrent neural network Tongxin xuebao software aging cloud server prediction method auto-regressive integrated moving average model recurrent neural network model |
| title | Cloud server aging prediction method based on hybrid model of auto-regressive integrated moving average and recurrent neural network |
| title_full | Cloud server aging prediction method based on hybrid model of auto-regressive integrated moving average and recurrent neural network |
| title_fullStr | Cloud server aging prediction method based on hybrid model of auto-regressive integrated moving average and recurrent neural network |
| title_full_unstemmed | Cloud server aging prediction method based on hybrid model of auto-regressive integrated moving average and recurrent neural network |
| title_short | Cloud server aging prediction method based on hybrid model of auto-regressive integrated moving average and recurrent neural network |
| title_sort | cloud server aging prediction method based on hybrid model of auto regressive integrated moving average and recurrent neural network |
| topic | software aging cloud server prediction method auto-regressive integrated moving average model recurrent neural network model |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021015/ |
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