Long Saiqin, Huang Jinna, Li Zhetao, Pei Tingrui, Xia Yuanqing. Energy Efficiency Evaluation Method of Data Centers for Cloud-Network Integration[J]. Journal of Computer Research and Development, 2021, 58(6): 1248-1260. DOI: 10.7544/issn1000-1239.2021.20201069
Citation:
Long Saiqin, Huang Jinna, Li Zhetao, Pei Tingrui, Xia Yuanqing. Energy Efficiency Evaluation Method of Data Centers for Cloud-Network Integration[J]. Journal of Computer Research and Development, 2021, 58(6): 1248-1260. DOI: 10.7544/issn1000-1239.2021.20201069
Long Saiqin, Huang Jinna, Li Zhetao, Pei Tingrui, Xia Yuanqing. Energy Efficiency Evaluation Method of Data Centers for Cloud-Network Integration[J]. Journal of Computer Research and Development, 2021, 58(6): 1248-1260. DOI: 10.7544/issn1000-1239.2021.20201069
Citation:
Long Saiqin, Huang Jinna, Li Zhetao, Pei Tingrui, Xia Yuanqing. Energy Efficiency Evaluation Method of Data Centers for Cloud-Network Integration[J]. Journal of Computer Research and Development, 2021, 58(6): 1248-1260. DOI: 10.7544/issn1000-1239.2021.20201069
1(School of Computer Science, Xiangtan University, Xiangtan, Hunan 411105)
2(Key Laboratory of Hunan Province for Internet of Things and Information Security (Xiangtan University), Xiangtan, Hunan 411105)
3(Hunan International Scientific and Technological Cooperation Base of Intelligent Network (Xiangtan University), Xiangtan, Hunan 411105)
4(School of Automation, Beijing Institute of Technology, Beijing 100081)
Funds: This work was supported by the National Key Research and Development Program of China (2018YFB1003702), the National Natural Science Foundation of China (62032020, 61502407, 62076214), the Hunan Provincial Natural Science Foundation of China for Distinguished Young Scholars (2018JJ1025), the Hunan Science and Technology Planning Project (2019RS3019, 2018TP1036), the Natural Science Foundation of Hunan Province of China (2019JJ50592), and the Science Research Foundation of Hunan Provincial Educational Department(18C0107).
Cloud-network integration is developing at an accelerated pace, which not only promotes the rapid growth of data center scale, but also brings huge energy consumption. How to formulate reasonable data center energy efficiency evaluation standards has become a key issue that needs to be solved urgently to guide the improvement of data center energy efficiency. It is difficult to evaluate the energy efficiency of data centers comprehensively based on a single metric, and different data center energy efficiency metrics have their own focuses, and even contradict each other. It is proposed to integrate multiple metrics to evaluate the energy efficiency of data centers comprehensively. The model adopts a combination of subjective and objective weighting methods to set weights for different energy efficiency metrics. A multi-metric fusion evaluation strategy is designed based on the cloud model to obtain a more scientific and comprehensive data center energy efficiency evaluation result. Finally, the gray correlation method is proposed to analyze the relationship between the evaluation results and various energy efficiency metrics. The analysis results have important guiding significance for the improvement of data center energy efficiency.