A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization

Shuo Zhang; Fanchao Meng; Zhongyi Zhang

doi:10.1109/CyberC.2018.00049

A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization

Shuo Zhang
, Fanchao Meng
, Zhongyi Zhang

School of Computer Science and Technology (School of Software), Harbin Institute of Technology Weihai

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

In an Infrastructure as a Service (IaaS) environment, a key requirement is the rational placement of virtual machines that consumers apply for. In order to reduce the energy consumption of servers and switches in the data center, reduce the operating cost of data center, this paper proposes a virtual machine placement scheme based on energy optimization. Aiming at the shortcomings of genetic algorithm in intelligent algorithm which is easy to fall into local optimum, the immune algorithm is combined to generate an optimized immune genetic algorithm and a placement scheme is generated. In this paper, the data center structure is constructed, the energy consumption model of data center is constructed, and the simulation experiment is carried out. Through the experiment comparison, the proposed virtual machine placement scheme can effectively reduce data center energy consumption, and achieve effective results.

Original language	English
Title of host publication	Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	215-221
Number of pages	7
ISBN (Electronic)	9781728109749
DOIs	https://doi.org/10.1109/CyberC.2018.00049
State	Published - 2 Jul 2018
Externally published	Yes
Event	10th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018 - Zhengzhou, China Duration: 18 Oct 2018 → 20 Oct 2018

Publication series

Name	Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018

Conference

Conference	10th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018
Country/Territory	China
City	Zhengzhou
Period	18/10/18 → 20/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Cloud data center
Energy optimization
Optimized immune genetic algorithm
Virtual machine placement

Access to Document

10.1109/CyberC.2018.00049

Cite this

Zhang, S., Meng, F., & Zhang, Z. (2018). A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization. In Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018 (pp. 215-221). Article 8644591 (Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CyberC.2018.00049

Zhang, Shuo ; Meng, Fanchao ; Zhang, Zhongyi. / A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization. Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 215-221 (Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018).

@inproceedings{783afe9061c74e448a1bca2fd42452b0,

title = "A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization",

abstract = "In an Infrastructure as a Service (IaaS) environment, a key requirement is the rational placement of virtual machines that consumers apply for. In order to reduce the energy consumption of servers and switches in the data center, reduce the operating cost of data center, this paper proposes a virtual machine placement scheme based on energy optimization. Aiming at the shortcomings of genetic algorithm in intelligent algorithm which is easy to fall into local optimum, the immune algorithm is combined to generate an optimized immune genetic algorithm and a placement scheme is generated. In this paper, the data center structure is constructed, the energy consumption model of data center is constructed, and the simulation experiment is carried out. Through the experiment comparison, the proposed virtual machine placement scheme can effectively reduce data center energy consumption, and achieve effective results.",

keywords = "Cloud data center, Energy optimization, Optimized immune genetic algorithm, Virtual machine placement",

author = "Shuo Zhang and Fanchao Meng and Zhongyi Zhang",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 10th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018 ; Conference date: 18-10-2018 Through 20-10-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/CyberC.2018.00049",

language = "英语",

series = "Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "215--221",

booktitle = "Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018",

address = "美国",

}

Zhang, S, Meng, F & Zhang, Z 2018, A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization. in Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018., 8644591, Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 215-221, 10th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018, Zhengzhou, China, 18/10/18. https://doi.org/10.1109/CyberC.2018.00049

A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization. / Zhang, Shuo; Meng, Fanchao; Zhang, Zhongyi.
Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 215-221 8644591 (Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization

AU - Zhang, Shuo

AU - Meng, Fanchao

AU - Zhang, Zhongyi

PY - 2018/7/2

Y1 - 2018/7/2

N2 - In an Infrastructure as a Service (IaaS) environment, a key requirement is the rational placement of virtual machines that consumers apply for. In order to reduce the energy consumption of servers and switches in the data center, reduce the operating cost of data center, this paper proposes a virtual machine placement scheme based on energy optimization. Aiming at the shortcomings of genetic algorithm in intelligent algorithm which is easy to fall into local optimum, the immune algorithm is combined to generate an optimized immune genetic algorithm and a placement scheme is generated. In this paper, the data center structure is constructed, the energy consumption model of data center is constructed, and the simulation experiment is carried out. Through the experiment comparison, the proposed virtual machine placement scheme can effectively reduce data center energy consumption, and achieve effective results.

AB - In an Infrastructure as a Service (IaaS) environment, a key requirement is the rational placement of virtual machines that consumers apply for. In order to reduce the energy consumption of servers and switches in the data center, reduce the operating cost of data center, this paper proposes a virtual machine placement scheme based on energy optimization. Aiming at the shortcomings of genetic algorithm in intelligent algorithm which is easy to fall into local optimum, the immune algorithm is combined to generate an optimized immune genetic algorithm and a placement scheme is generated. In this paper, the data center structure is constructed, the energy consumption model of data center is constructed, and the simulation experiment is carried out. Through the experiment comparison, the proposed virtual machine placement scheme can effectively reduce data center energy consumption, and achieve effective results.

KW - Cloud data center

KW - Energy optimization

KW - Optimized immune genetic algorithm

KW - Virtual machine placement

UR - https://www.scopus.com/pages/publications/85063126601

U2 - 10.1109/CyberC.2018.00049

DO - 10.1109/CyberC.2018.00049

M3 - 会议稿件

AN - SCOPUS:85063126601

T3 - Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018

SP - 215

EP - 221

BT - Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018

Y2 - 18 October 2018 through 20 October 2018

ER -

Zhang S, Meng F, Zhang Z. A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization. In Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 215-221. 8644591. (Proceedings - 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2018). doi: 10.1109/CyberC.2018.00049

A Cloud Data Center Virtual Machine Placement Scheme Based on Energy Optimization

Abstract

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UN SDGs

Keywords

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