Virtual Machine Dynamic Deployment Scheme Based on Double-Cursor Mechanism

被引:3
作者
Liu, Shukun [1 ]
Li, Chaoliang [2 ]
Liu, Zhimin [3 ]
Zhang, Qiang [4 ]
机构
[1] Hunan Womens Univ, Coll Informat Sci & Engn, Changsha 410004, Hunan, Peoples R China
[2] Hunan Univ Technol & Business, Coll Comp & Informat Engn, Changsha 410205, Peoples R China
[3] Hunan First Normal Univ, Coll Math & Computat Sci, Changsha 410205, Peoples R China
[4] Hunan Univ Sci & Technol, Sch Comp Sci & Engn, Xiangtan 411201, Peoples R China
关键词
Virtual machining; Cloud computing; Resource management; Optimization; Energy consumption; Data centers; Dynamic scheduling; Double cursors; virtual machine; automatic deployment; virtual machine migration; SCHEDULING METHOD;
D O I
10.1109/ACCESS.2020.3040912
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In accordance with the dynamically changing characteristics of user application load demand, the optimization of energy consumption in the process of virtual machine automatic deployment on the basis of the effective integration of user personalized resource demand in cloud platforms and the dynamic migration technology of virtual machines is studied in this work. Aiming at the problem of energy consumption optimization, an energy-efficient virtual machine deployment framework, which can be dynamically adjusted in accordance with the user's actual resource needs, is designed. In the virtual machine deployment framework, this paper presents a virtual machine deployment selection algorithm based on a double-cursor control mechanism for the resource usage state of CPU and memory, which achieves a binocular optimization balance to a certain extent. Simulation experiment results show that when the virtual machine deployment framework proposed in this paper and the virtual machine deployment selection algorithm based on a double-cursor control mechanism are combined, the number of necessary active physical nodes in the cloud data center can be effectively controlled, and the frequency of virtual machine migration synchronization can be reduced. Consequently, the cloud data center can maintain low energy costs.
引用
收藏
页码:214481 / 214493
页数:13
相关论文
共 23 条
[1]   Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing [J].
Beloglazov, Anton ;
Abawajy, Jemal ;
Buyya, Rajkumar .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2012, 28 (05) :755-768
[2]  
Cai Mengjuan, 2018, Journal of Computer Applications, V38, P305, DOI 10.11772/j.issn.1001-9081.2017082167
[3]  
Dong H., 2020, Control Eng., V27, P335
[4]  
Jialei L., 2018, P 12 INT C UB INF MA, P54
[5]  
Jie L., 2016, COMPUT APPL RES, V33, P2963
[6]   A Virtual Machine Scheduling Strategy with a Speed Switch and a Multi-Sleep Mode in Cloud Data Centers [J].
Jin, Shunfu ;
Hao, Shanshan ;
Qie, Xiuchen ;
Yue, Wuyi .
JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING, 2019, 28 (02) :194-210
[7]   Multi-objective optimization for rebalancing virtual machine placement [J].
Li, Rui ;
Zheng, Qinghua ;
Li, Xiuqi ;
Yan, Zheng .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2020, 105 :824-842
[8]  
[李双俐 Li Shuangli], 2020, [重庆邮电大学学报. 自然科学版, Journal of Chongqing University of Posts and Telecommunications. Natural Science Edition], V32, P356
[9]  
Lijun X., 2018, LAB RES EXPLOR, V37, P120
[10]   An Energy Efficient Ant Colony System for Virtual Machine Placement in Cloud Computing [J].
Liu, Xiao-Fang ;
Zhan, Zhi-Hui ;
Deng, Jeremiah D. ;
Li, Yun ;
Gu, Tianlong ;
Zhang, Jun .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2018, 22 (01) :113-128