Classification-Based and Energy-Efficient Dynamic Task Scheduling Scheme for Virtualized Cloud Data Center
文献类型：期刊论文
| 作者 | Marahatta, Avinab4,5; Pirbhulal, Sandeep3; Zhang, Fa4; Parizi, Reza M.2; Choo, Kim-Kwang Raymond1; Liu, Zhiyong4 |
| 刊名 | IEEE TRANSACTIONS ON CLOUD COMPUTING
 |
| 出版日期 | 2021-10-01 |
| 卷号 | 9期号:4页码:1376-1390 |
| 关键词 | Cloud data center virtualization energy efficiency task scheduling task merging virtual machine |
| ISSN号 | 2168-7161 |
| DOI | 10.1109/TCC.2019.2918226 |
| 英文摘要 | The size and number of cloud data centers (CDCs) have grown rapidly with the increasing popularity of cloud computing and high-performance computing. This has the unintended consequences of creating new challenges due to inefficient use of resources and high energy consumption. Hence, this necessitates the need to maximize resource utilization and ensure energy efficiency in CDCs. One viable approach to achieve energy efficiency and resource utilization in CDC is task scheduling. While several task scheduling approaches have been proposed in the literature, there appears to be a lack of classification-based merging concept for real-time tasks in these existing approaches. Thus, an energy-efficient dynamic scheduling scheme (EDS) of real-time tasks for virtualized CDC is presented in this paper. In the scheduling scheme, the heterogeneous tasks and virtual machines are first classified based on a historical scheduling record. Then, similar type of tasks are merged and scheduled to maximally utilize an operational state of the host. In addition, energy efficiencies and optimal operating frequencies of heterogeneous physical hosts are employed to attain energy preservation while creating and deleting the virtual machines. Experimental results show that, in comparison with existing techniques, EDS significantly improves overall scheduling performance, achieves a higher CDC resource utilization, increases task guarantee ratio, minimizes the mean response time, and reduces energy consumption. |
| 资助项目 | National Natural Science Foundation of China[61520106005] ; National Natural Science Foundation of China[61761136014] ; National Key Research and Development Program of China[2017YFB1010001] ; CAS-TWAS President's Fellowship at Chinese Academy of Sciences, Beijing, China ; Cloud Technology Endowed Professorship ; NSF CREST Grant[HRD-1736209] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000725800700008 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/18163]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Choo, Kim-Kwang Raymond; Liu, Zhiyong |
| 作者单位 | 1.Univ Texas San Antonio, Dept Informat Syst & Cyber Secur, San Antonio, TX 78249 USA 2.Kennesaw State Univ, Dept Software Engn & Game Dev, Marietta, GA 30060 USA 3.Chinese Acad Sci, Shenzhen Inst Adv Technol, CAS Key Lab Human Machine Intelligence Synergy Sy, Shenzhen 518058, Peoples R China 4.Chinese Acad Sci, High Performance Comp Res Ctr, Inst Comp Technol, Beijing 100091, Peoples R China 5.Univ Chinese Acad Sci, Huairou 101408, Peoples R China |
| 推荐引用方式 GB/T 7714 | Marahatta, Avinab,Pirbhulal, Sandeep,Zhang, Fa,et al. Classification-Based and Energy-Efficient Dynamic Task Scheduling Scheme for Virtualized Cloud Data Center[J]. IEEE TRANSACTIONS ON CLOUD COMPUTING,2021,9(4):1376-1390. |
| APA | Marahatta, Avinab,Pirbhulal, Sandeep,Zhang, Fa,Parizi, Reza M.,Choo, Kim-Kwang Raymond,&Liu, Zhiyong.(2021).Classification-Based and Energy-Efficient Dynamic Task Scheduling Scheme for Virtualized Cloud Data Center.IEEE TRANSACTIONS ON CLOUD COMPUTING,9(4),1376-1390. |
| MLA | Marahatta, Avinab,et al."Classification-Based and Energy-Efficient Dynamic Task Scheduling Scheme for Virtualized Cloud Data Center".IEEE TRANSACTIONS ON CLOUD COMPUTING 9.4(2021):1376-1390. |
入库方式： OAI收割
来源：计算技术研究所
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