An efficient interval many-objective evolutionary algorithm for cloud task scheduling problem under uncertainty

doi:10.1016/j.ins.2021.11.027

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 人工智能与机器学习（杨雪冰）-技术团队

	An efficient interval many-objective evolutionary algorithm for cloud task scheduling problem under uncertainty
	Zhang, Zhixia 1; Zhao, Mengkai 2; Wang, Hui 3; Cui, Zhihua 2; Zhang, Wensheng4
发表期刊	INFORMATION SCIENCES
ISSN	0020-0255
	2022
卷号	583 页码:56-72
通讯作者	Cui, Zhihua(cuizhihua@gmail.com)
摘要	Task scheduling is an important research direction in cloud computing. The current research on task scheduling considers mainly the design of scheduling strategies and algorithms and rarely gives attention to the influences of uncertain factors, such as the network bandwidth and millions of instructions per second (MIPS), on the scheduling process. The network bandwidth and MIPS directly affect the performance of a virtual machine (VM), which further influences the scheduling performance. In this paper, uncertain factors are transformed into interval parameters. The make-span, scheduling cost, load balance, and task completion rate are simultaneously considered in the scheduling process. Then, an interval many-objective cloud task scheduling optimization (I-MCTSO) model is designed to simulate real cloud computing task scheduling. To implement this model, an interval many-objective evolutionary algorithm (InMaOEA) is proposed. An interval credibility strategy is employed to improve the convergence performance. The hyper-volume and degree of overlap based on the interval congestion distance strategy are used to increase the population diversity. Simulation results demonstrate the effectiveness and superior performance of InMaOEA in comparision with other algorithms. The proposed approaches can provide decision-makers with an efficient allocation plan for cloud task scheduling. (c) 2021 Elsevier Inc. All rights reserved.
关键词	Interval optimization Interval many-objective optimization Many-objective evolutionary algorithm Cloud task scheduling
DOI	10.1016/j.ins.2021.11.027
关键词[WOS]	OPTIMIZATION ALGORITHM
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018YFC1604000] ; National Natural Science Foundation of China[61806138] ; National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[61961160707] ; National Natural Science Foundation of China[61976212] ; National Natural Science Foundation of China[61772478] ; National Natural Science Foundation of China[62166027] ; Key R&D program of Shanxi Province (International Cooperation)[201903D421048] ; Key R&D program of Shanxi Province (High Technology)[201903D121119] ; Natural Science Foundation of Jiangxi Province[20212ACB212004]
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Key R&D program of Shanxi Province (International Cooperation) ; Key R&D program of Shanxi Province (High Technology) ; Natural Science Foundation of Jiangxi Province
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems
WOS记录号	WOS:000727727800002
出版者	ELSEVIER SCIENCE INC
引用统计	被引频次：47[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/46792
专题	多模态人工智能系统全国重点实验室_人工智能与机器学习（杨雪冰）-技术团队
通讯作者	Cui, Zhihua
作者单位	1.Taiyuan Univ Sci & Technol, Sch Elect Informat Engn, Taiyuan, Peoples R China 2.Taiyuan Univ Sci & Technol, Sch Comp Sci & Technol, Taiyuan, Peoples R China 3.Nanchang Inst Technol, Sch Informat Engn, Nanchang 330099, Jiangxi, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Intelligent Control & Management Co, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Zhixia,Zhao, Mengkai,Wang, Hui,et al. An efficient interval many-objective evolutionary algorithm for cloud task scheduling problem under uncertainty[J]. INFORMATION SCIENCES,2022,583:56-72.
APA	Zhang, Zhixia,Zhao, Mengkai,Wang, Hui,Cui, Zhihua,&Zhang, Wensheng.(2022).An efficient interval many-objective evolutionary algorithm for cloud task scheduling problem under uncertainty.INFORMATION SCIENCES,583,56-72.
MLA	Zhang, Zhixia,et al."An efficient interval many-objective evolutionary algorithm for cloud task scheduling problem under uncertainty".INFORMATION SCIENCES 583(2022):56-72.