Resource scheduling algorithm of cloud computing for energy optimization base on virtual machine migration

Liang Hao; Gang Cui; Ming Cheng Qu; Wen De Ke

doi:10.4028/www.scientific.net/AMR.926-930.3232

Resource scheduling algorithm of cloud computing for energy optimization base on virtual machine migration

Liang Hao^*
, Gang Cui
, Ming Cheng Qu
, Wen De Ke

^*Corresponding author for this work

Faculty of Computing

Harbin Institute of Technology

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

Abstract

As the growing demand for cloud computing, the scale of cloud data centers increased gradually, so that the energy issues of cloud environments have become increasingly prominent. For the situation of energy consumption serious in cloud computing data center, the resource scheduling algorithm of cloud computing for energy optimization was designed base on the technology of virtual machine migration. The energy consumption of cloud data center was saved effectively through effective use of resources, rational allocation of resources scheduling. Simulation results showed that compared to sequence execution algorithm, utilization of CPU, the average energy consumption, the average time was reduced by 16.63%, 27.26% and 23.72%, respectively.

Original language	English
Title of host publication	Progress in Applied Sciences, Engineering and Technology
Publisher	Trans Tech Publications
Pages	3232-3235
Number of pages	4
ISBN (Print)	9783038350996
DOIs	https://doi.org/10.4028/www.scientific.net/AMR.926-930.3232
State	Published - 2014
Event	2014 International Conference on Materials Science and Computational Engineering, ICMSCE 2014 - Qingdao, China Duration: 20 May 2014 → 21 May 2014

Publication series

Name	Advanced Materials Research
Volume	926-930
ISSN (Print)	1022-6680

Conference

Conference	2014 International Conference on Materials Science and Computational Engineering, ICMSCE 2014
Country/Territory	China
City	Qingdao
Period	20/05/14 → 21/05/14

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Cloud computing
Energy consumption
Resource scheduling
Virtual machine migration

Access to Document

10.4028/www.scientific.net/AMR.926-930.3232

Cite this

@inproceedings{b7e4c61e2d6b447fa4f7f58b96cd2ada,

title = "Resource scheduling algorithm of cloud computing for energy optimization base on virtual machine migration",

abstract = "As the growing demand for cloud computing, the scale of cloud data centers increased gradually, so that the energy issues of cloud environments have become increasingly prominent. For the situation of energy consumption serious in cloud computing data center, the resource scheduling algorithm of cloud computing for energy optimization was designed base on the technology of virtual machine migration. The energy consumption of cloud data center was saved effectively through effective use of resources, rational allocation of resources scheduling. Simulation results showed that compared to sequence execution algorithm, utilization of CPU, the average energy consumption, the average time was reduced by 16.63\%, 27.26\% and 23.72\%, respectively.",

keywords = "Cloud computing, Energy consumption, Resource scheduling, Virtual machine migration",

author = "Liang Hao and Gang Cui and Qu, \{Ming Cheng\} and Ke, \{Wen De\}",

year = "2014",

doi = "10.4028/www.scientific.net/AMR.926-930.3232",

language = "英语",

isbn = "9783038350996",

series = "Advanced Materials Research",

publisher = "Trans Tech Publications",

pages = "3232--3235",

booktitle = "Progress in Applied Sciences, Engineering and Technology",

address = "德国",

note = "2014 International Conference on Materials Science and Computational Engineering, ICMSCE 2014 ; Conference date: 20-05-2014 Through 21-05-2014",

}

Hao, L, Cui, G, Qu, MC & Ke, WD 2014, Resource scheduling algorithm of cloud computing for energy optimization base on virtual machine migration. in Progress in Applied Sciences, Engineering and Technology. Advanced Materials Research, vol. 926-930, Trans Tech Publications, pp. 3232-3235, 2014 International Conference on Materials Science and Computational Engineering, ICMSCE 2014, Qingdao, China, 20/05/14. https://doi.org/10.4028/www.scientific.net/AMR.926-930.3232

Resource scheduling algorithm of cloud computing for energy optimization base on virtual machine migration. / Hao, Liang; Cui, Gang; Qu, Ming Cheng et al.
Progress in Applied Sciences, Engineering and Technology. Trans Tech Publications, 2014. p. 3232-3235 (Advanced Materials Research; Vol. 926-930).

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

TY - GEN

T1 - Resource scheduling algorithm of cloud computing for energy optimization base on virtual machine migration

AU - Hao, Liang

AU - Cui, Gang

AU - Qu, Ming Cheng

AU - Ke, Wen De

PY - 2014

Y1 - 2014

N2 - As the growing demand for cloud computing, the scale of cloud data centers increased gradually, so that the energy issues of cloud environments have become increasingly prominent. For the situation of energy consumption serious in cloud computing data center, the resource scheduling algorithm of cloud computing for energy optimization was designed base on the technology of virtual machine migration. The energy consumption of cloud data center was saved effectively through effective use of resources, rational allocation of resources scheduling. Simulation results showed that compared to sequence execution algorithm, utilization of CPU, the average energy consumption, the average time was reduced by 16.63%, 27.26% and 23.72%, respectively.

AB - As the growing demand for cloud computing, the scale of cloud data centers increased gradually, so that the energy issues of cloud environments have become increasingly prominent. For the situation of energy consumption serious in cloud computing data center, the resource scheduling algorithm of cloud computing for energy optimization was designed base on the technology of virtual machine migration. The energy consumption of cloud data center was saved effectively through effective use of resources, rational allocation of resources scheduling. Simulation results showed that compared to sequence execution algorithm, utilization of CPU, the average energy consumption, the average time was reduced by 16.63%, 27.26% and 23.72%, respectively.

KW - Cloud computing

KW - Energy consumption

KW - Resource scheduling

KW - Virtual machine migration

UR - https://www.scopus.com/pages/publications/84902272362

U2 - 10.4028/www.scientific.net/AMR.926-930.3232

DO - 10.4028/www.scientific.net/AMR.926-930.3232

M3 - 会议稿件

AN - SCOPUS:84902272362

SN - 9783038350996

T3 - Advanced Materials Research

SP - 3232

EP - 3235

BT - Progress in Applied Sciences, Engineering and Technology

PB - Trans Tech Publications

T2 - 2014 International Conference on Materials Science and Computational Engineering, ICMSCE 2014

Y2 - 20 May 2014 through 21 May 2014

ER -

Resource scheduling algorithm of cloud computing for energy optimization base on virtual machine migration

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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