基于深度置信网络的云应用负载预测方法
为了准确预测云应用负载以便及时执行云应用自适应优化,从而保证云应用性能的稳定,根据云环境下应用负载预测问题的特点,提出了基于深度置信网络的云应用负载预测方法.首先给出能够有效描述负载数据的显式特征和隐式特征并定义了负载预测模型,进而给出基于深度置信网络的负载预测算法.对算法进行了分析并在真实数据集上与相关算法进行了比较,结果表明,本文提出的方法能够更加有效地解决云应用负载预测问题....
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| Published in | 东北大学学报（自然科学版） Vol. 38; no. 2; pp. 209 - 213 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
东北大学 计算机科学与工程学院,辽宁 沈阳,110169
2017
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| Subjects | |
| Online Access | Get full text |
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| Abstract | 为了准确预测云应用负载以便及时执行云应用自适应优化,从而保证云应用性能的稳定,根据云环境下应用负载预测问题的特点,提出了基于深度置信网络的云应用负载预测方法.首先给出能够有效描述负载数据的显式特征和隐式特征并定义了负载预测模型,进而给出基于深度置信网络的负载预测算法.对算法进行了分析并在真实数据集上与相关算法进行了比较,结果表明,本文提出的方法能够更加有效地解决云应用负载预测问题. |
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| AbstractList | 为了准确预测云应用负载以便及时执行云应用自适应优化,从而保证云应用性能的稳定,根据云环境下应用负载预测问题的特点,提出了基于深度置信网络的云应用负载预测方法.首先给出能够有效描述负载数据的显式特征和隐式特征并定义了负载预测模型,进而给出基于深度置信网络的负载预测算法.对算法进行了分析并在真实数据集上与相关算法进行了比较,结果表明,本文提出的方法能够更加有效地解决云应用负载预测问题. TP393; 为了准确预测云应用负载以便及时执行云应用自适应优化,从而保证云应用性能的稳定,根据云环境下应用负载预测问题的特点,提出了基于深度置信网络的云应用负载预测方法.首先给出能够有效描述负载数据的显式特征和隐式特征并定义了负载预测模型,进而给出基于深度置信网络的负载预测算法.对算法进行了分析并在真实数据集上与相关算法进行了比较,结果表明,本文提出的方法能够更加有效地解决云应用负载预测问题. |
| Abstract_FL | To implement the adaptive optimization to ensure the performance of cloud application, it is necessary to accurately predict the load for cloud application. According to the feature of load prediction in cloud application, an approach is proposed for load prediction based on deep belief networks. Explicit and implicit features for load data are given. Load prediction model is defined. Then, the algorithm of load prediction based on deep belief networks is designed and implemented. This approach is evaluated and compared with some related load prediction algorithms, which reveals very encouraging results in terms of the prediction quality. |
| Author | 马安香 张长胜 张斌 张晓红 |
| AuthorAffiliation | 东北大学计算机科学与工程学院,辽宁沈阳110169 |
| AuthorAffiliation_xml | – name: 东北大学 计算机科学与工程学院,辽宁 沈阳,110169 |
| Author_FL | MA An-xiang ZHANG Chang-sheng ZHANG Bin ZHANG Xiao-hong |
| Author_FL_xml | – sequence: 1 fullname: MA An-xiang – sequence: 2 fullname: ZHANG Chang-sheng – sequence: 3 fullname: ZHANG Bin – sequence: 4 fullname: ZHANG Xiao-hong |
| Author_xml | – sequence: 1 fullname: 马安香 张长胜 张斌 张晓红 |
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| ClassificationCodes | TP393 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DOI | 10.3969/j.issn.1005-3026.2017.02.012 |
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| DocumentTitleAlternate | Load Prediction Approach for Cloud Application Based on DeepBelief Networks |
| DocumentTitle_FL | Load Prediction Approach for Cloud Application Based on Deep Belief Networks |
| EndPage | 213 |
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| Keywords | cloud application 负载预测 自适应优化 云应用 deep belief network 深度置信网络 load prediction cloud computing 云计算 adaptive optimization |
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| Notes | 21-1344/T MA An-xiang,ZHANG Chang-sheng,ZHANG Bin,ZHANG Xiao-hong（School of Computer Science ＆ Engineering,Northeastern University,Shenyang 110169,China. ） To implement the adaptive optimization to ensure the performance of cloud application, it is necessary to accurately predict the load for cloud application. According to the feature of load prediction in cloud application,an approach is proposed for load prediction based on deep belief networks. Explicit and implicit features for load data are given. Load prediction model is defined. Then, the algorithm of load prediction based on deep belief networks is designed and implemented. This approach is evaluated and compared with some related load prediction algorithms,which reveals very encouraging results in terms of the prediction quality. cloud computing; cloud application; deep belief network; load prediction; adaptive optimization |
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| SubjectTerms | 云应用 云计算 深度置信网络 自适应优化 负载预测 |
| Title | 基于深度置信网络的云应用负载预测方法 |
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