Energy-Aware Scheduling Based on Marginal Cost and Task Classification in Heterogeneous Data Centers

doi:10.3390/en14092382

	Energy-Aware Scheduling Based on Marginal Cost and Task Classification in Heterogeneous Data Centers
	Ji, Kaixuan 5,6; Chi, Ce 5,6; Zhang, Fa 6; Anta, Antonio Fernandez 4; Song, Penglei 3; Marahatta, Avinab 2; Wang, Youshi 1; Liu, Zhiyong 6
刊名	ENERGIES
	2021-05-01
卷号	14 期号:9 页码:26
关键词	data center energy-aware marginal cost task scheduling cooling system task classification
DOI	10.3390/en14092382
英文摘要	The energy consumption problem has become a bottleneck hindering further development of data centers. However, the heterogeneity of servers, hybrid cooling modes, and extra energy caused by system state transitions increases the complexity of the energy optimization problem. To deal with such challenges, in this paper, an Energy Aware Task Scheduling strategy (EATS) utilizing marginal cost and task classification method is proposed that cooperatively improves the energy efficiency of servers and cooling systems. An energy consumption model for servers, cooling systems, and state transition is developed, and the energy optimization problem in data centers is formulated. The concept of marginal cost is introduced to guide the task scheduling process. The task classification method is incorporated with the idea of marginal cost to further improve resource utilization and reduce the total energy consumption of data centers. Experiments are conducted using real-world traces, and energy reduction results are compared. Results show that EATS achieves more energy-savings of servers, cooling systems, state transition in comparison to the other two techniques under a various number of servers, cooling modules and task arrival intensities. It is validated that EATS is effective at reducing total energy consumption and improving the resource utilization of data centers.
资助项目	National Key Research and Development Program of China[2017YFB1010001] ; National Natural Science Foundation of China[61520106005] ; National Natural Science Foundation of China[61761136014]
WOS研究方向	Energy & Fuels
语种	英语
出版者	MDPI
WOS记录号	WOS:000650184100001
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/17698]
专题	中国科学院计算技术研究所
通讯作者	Liu, Zhiyong
作者单位	1.Meituan Dianping Grp, Beijing 100102, Peoples R China 2.Chinese Acad Sci, Inst Informat Engn, Beijing 100093, Peoples R China 3.Capital Normal Univ, Informat Engn Coll, Beijing 100048, Peoples R China 4.IMDEA Networks Inst, Avda Mar Mediterraneo 22, Leganes 28918, Spain 5.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 101408, Peoples R China 6.Chinese Acad Sci, Inst Comp Technol, High Performance Comp Res Ctr, Beijing 100095, Peoples R China
推荐引用方式 GB/T 7714	Ji, Kaixuan,Chi, Ce,Zhang, Fa,et al. Energy-Aware Scheduling Based on Marginal Cost and Task Classification in Heterogeneous Data Centers[J]. ENERGIES,2021,14(9):26.
APA	Ji, Kaixuan.,Chi, Ce.,Zhang, Fa.,Anta, Antonio Fernandez.,Song, Penglei.,...&Liu, Zhiyong.(2021).Energy-Aware Scheduling Based on Marginal Cost and Task Classification in Heterogeneous Data Centers.ENERGIES,14(9),26.
MLA	Ji, Kaixuan,et al."Energy-Aware Scheduling Based on Marginal Cost and Task Classification in Heterogeneous Data Centers".ENERGIES 14.9(2021):26.