A Multi Criteria-Based Approach for Virtual Machines Consolidation to Save Electrical Power in Cloud Data Centers

被引：5

作者：

Amoon, Mohammed ^{[1
,2
]}

机构：

[1] King Saud Univ, Dept Comp Sci, Community Coll, Riyadh 2809511437, Saudi Arabia

[2] Menoufia Univ, Fac Elect Engn, Comp Sci & Engn Dept, Menoufia 32952, Egypt

来源：

IEEE ACCESS | 2018年 / 6卷

关键词：

Consolidation; throughtput; virtual machines; data center; power consumption; SERVER CONSOLIDATION; RESOURCE-MANAGEMENT; ENERGY; HEURISTICS; PERFORMANCE; ALGORITHM; AWARE;

D O I：

10.1109/ACCESS.2018.2830183

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Consolidation of virtual machines is used to reduce the power consumed in cloud computing systems. In consolidation, some virtual machines are migrated from some source servers to other destination servers and source servers are turned off. Most current consolidation approaches depend on the utilization of servers to determine both source and destination servers. In this paper, a consolidation approach that depends on multiple criteria is proposed and evaluated. The approach has one algorithm for determining source servers and another algorithm for determining destination servers. Simulations experiments show relevant improvements over utilization-based approach in terms of throughput, power consumption, monetary cost, and scalability by 21%, 12%, 24%, and 37%, respectively.

引用

页码：24110 / 24117

页数：8

共 23 条

[11] A virtual machine scheduler based on CPU and I/O-bound features for energy-aware in high performance computing clouds [J].

Fernandes, Felipe ;

Beserra, David ;

Moreno, Edward David ;

Schulze, Bruno ;

Gomes Pinto, Raquel Coelho .

COMPUTERS & ELECTRICAL ENGINEERING, 2016, 56 :854-870

[12] Scheduling highly available applications on cloud environments [J].

Frincu, Marc Eduard .

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2014, 32 :138-153

[13] Service level agreement based energy-efficient resource management in cloud data centers [J].

Gao, Yongqiang ;

Guan, Haibing ;

Qi, Zhengwei ;

Song, Tao ;

Huan, Fei ;

Liu, Liang .

COMPUTERS & ELECTRICAL ENGINEERING, 2014, 40 (05) :1621-1633

[14] Resource-utilization-aware energy efficient server consolidation algorithm for green computing in IIOT [J].

Han, Guangjie ;

Que, Wenhui ;

Jia, Gangyong ;

Zhang, Wenbo .

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2018, 103 :205-214

[15] Novel resource allocation algorithms to performance and energy efficiency in cloud computing [J].

Horri, Abbas ;

Mozafari, Mohammad Sadegh ;

Dastghaibyfard, Gholamhossein .

JOURNAL OF SUPERCOMPUTING, 2014, 69 (03) :1445-1461

[16] Energy efficient utilization of resources in cloud computing systems [J].

Lee, Young Choon ;

Zomaya, Albert Y. .

JOURNAL OF SUPERCOMPUTING, 2012, 60 (02) :268-280

[17] Energy optimization schemes in cluster with virtual machines [J].

Liao, Xiaofei ;

Hu, Liting ;

Jin, Hai .

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2010, 13 (02) :113-126

[18] Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey [J].

Manvi, Sunilkurnar S. ;

Shyam, Gopal Krishna .

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2014, 41 :424-440

[19] Sercon: Server Consolidation Algorithm using Live Migration of Virtual Machines for Green Computing [J].

Murtazaev, Aziz ;

Oh, Sangyoon .

IETE TECHNICAL REVIEW, 2011, 28 (03) :212-231

[20] Heuristics based server consolidation with residual resource defragmentation in cloud data centers [J].

Rao, K. Sunil ;

Thilagam, P. Santhi .

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2015, 50 :87-98

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