Estimating the Resource Demand in Power-Aware Clusters by Regressing a Linearly Dependent Relation

doi:10.1109/TSUSC.2019.2894708

	Estimating the Resource Demand in Power-Aware Clusters by Regressing a Linearly Dependent Relation
	Hu, Cheng 1,2; Deng, Yuhui 1,3; Yang, Laurence T.4; Zhao, Yufan 1
	2021-07-01
发表期刊	IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING
ISSN	2377-3782
卷号	6 期号:3 页码:385-397
摘要	Large-scale clusters are often built with over-provisioned service resources, so as to satisfy the huge demand raised by enormous users in cloud environments. By estimating the resource demand of workloads, an on-demand resource provisioning method can be realized in these clusters, thus improving the energy efficiency. However, to guarantee Quality of Service (QoS), the resource demand of workload should be accurately estimated so as to provide suitable resources. Many statistical approaches estimate actual resource demand based on some workload features. But the relations between actual resource demand and workload features are generally obscure, and it's a big challenge to gain an accurate estimation under an obscure relation. In this paper, by considering a cluster as a queueing system, we construct a linearly dependent relation between resource demand and multiple feature combinations. The linearly dependent relation is inconstant due to its variable coefficients. Then, to ascertain specific relations which match actual situations, we design a Basic Linear regression (BL) algorithm. BL can obtain the optimal values for these coefficients, thus determining the inconstant relation to specific ones. Finally, we propose a Constructed Linear regression (CL) approach to estimate actual resource demands. CL forms a two-layer neural network by using several processes of BL as the neurons. To evaluate CL, we realize an On-Demand Resource Provisioning (ODRP) method in a typical power-aware cluster. Several evaluation metrics are proposed for conducting extensive experiments. The experimental results show that CL is effective to make accurate estimations.
关键词	Estimation Servers Linear regression Quality of service Computational modeling Analytical models Task analysis Resource demand estimation linear regression power-aware cluster QoS SLA
DOI	10.1109/TSUSC.2019.2894708
收录类别	SCI
语种	英语
资助项目	NSFC[61572232] ; Science and Technology Planning Project of Guangzhou[201802010028] ; Science and Technology Planning Project of Guangzhou[201802010060] ; Science and Technology Planning Project of Nansha[2017CX006] ; Open Research Fund of Key Laboratory of Computer System and Architecture, Institute of Computing Technology, Chinese Academy of Sciences[CARCH201705]
WOS研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Information Systems ; Telecommunications
WOS记录号	WOS:000695943900003
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/17182
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Deng, Yuhui
作者单位	1.Jinan Univ, Dept Comp Sci, Guangzhou 510632, Peoples R China 2.Guangdong Univ Foreign Studies, Sch Informat Sci & Technol, Guangzhou 510006, Peoples R China 3.Chinese Acad Sci, Inst Comp, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 4.Sci St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS B2G 2W5, Canada
推荐引用方式 GB/T 7714	Hu, Cheng,Deng, Yuhui,Yang, Laurence T.,et al. Estimating the Resource Demand in Power-Aware Clusters by Regressing a Linearly Dependent Relation[J]. IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING,2021,6(3):385-397.
APA	Hu, Cheng,Deng, Yuhui,Yang, Laurence T.,&Zhao, Yufan.(2021).Estimating the Resource Demand in Power-Aware Clusters by Regressing a Linearly Dependent Relation.IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING,6(3),385-397.
MLA	Hu, Cheng,et al."Estimating the Resource Demand in Power-Aware Clusters by Regressing a Linearly Dependent Relation".IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING 6.3(2021):385-397.