Method for evaluation on energy consumption of cloud computing data center based on deep reinforcement learning

Ma Haizhou; Ding Aiping

首页> 外文期刊>Electric Power Systems Research >Method for evaluation on energy consumption of cloud computing data center based on deep reinforcement learning

【24h】

Method for evaluation on energy consumption of cloud computing data center based on deep reinforcement learning

机译：Method for evaluation on energy consumption of cloud computing data center based on deep reinforcement learning

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相关主题

摘要

In view of the problem that the current method for evaluation on energy consumption of cloud computing data center has larger fluctuations of relative error and deviation value for evaluated power variation and greater evaluation training losses, this paper proposes an energy consumption evaluation method for cloud computing data center. Firstly, we build an energy consumption evaluation model, analyze the correlation between inde-pendent variables and dependent variables through multiple linear regression model and multiple nonlinear regression model, and then measure the accuracy of the evaluation results by using average relative deviation and relative deviation; The depth learning mechanism is introduced, and the depth residual network is used for iterative training of regression parameters to complete the mapping of regression parameters; Comprehensively obtain the regression parameters in the energy consumption model, put them into the memory playback pool, solve the energy consumption evaluation function according to the sub strategy parameters, and reconstruct the energy consumption model of cloud computing data center. The comprehensive evaluation of energy con-sumption of cloud computing data center is realized. The experimental results show that the energy consumption deviation of this method is small and stable. It can effectively reduce the relative error of evaluation power change and reduce the evaluation training loss.

著录项

来源
《Electric Power Systems Research》 |2022年第7期|107899.1-107899.7|共7页
作者
Ma Haizhou; Ding Aiping;
展开▼
作者单位

Yellow River Conservancy Tech Inst, Sch Informat Engn, Kaifeng 475004, Henan, Peoples R China;

展开▼
收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类
关键词
Deep reinforcement learning; Cloud computing; Data center; Evaluation on energy consumption; Deviation value; Deep Residual network;

Method for evaluation on energy consumption of cloud computing data center based on deep reinforcement learning

摘要

著录项

相关主题

期刊订阅