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author:

Lin, X. (Lin, X..) [1] | Liu, Z. (Liu, Z..) [2] | Guo, W. (Guo, W..) [3]

Indexed by:

Scopus

Abstract:

Cloud is the computing paradigm which provides computing resource as a service through network. The client can use computing resource in a convenient and on-demand way, just like the water and the electricity we use daily. The mapping between virtual machine and physical machine is the key of the VM scheduling problem. Nowadays we advocate low-carbon life. It calls for the green cloud computing solutions whether protecting the environment or saving the cost of cloud suppliers. The proposed VM placement algorithm is energy-efficient, and considers the multi-dimentional resource constrains, such as CPU, memory, network bandwidth, and so on. The experimental results show that the proposed algorithms not only contribute a lot to energy saving, but also try best to meet the quality of service (QoS). Therefore, we make significant savings in operating cost and make full use of various resources in the cloud data center. The algorithm has promising prospect in application. © Springer International Publishing Switzerland 2015.

Keyword:

Cloud data center; Cloud resource scheduling; Energy-efficient; VM live migration; VM placement

Community:

  • [ 1 ] [Lin, X.]Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing, College of Mathematics and Computer Science, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Liu, Z.]Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing, College of Mathematics and Computer Science, Fuzhou University, Fuzhou, 350116, China
  • [ 3 ] [Guo, W.]Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing, College of Mathematics and Computer Science, Fuzhou University, Fuzhou, 350116, China

Reprint 's Address:

  • [Guo, W.]Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing, College of Mathematics and Computer Science, Fuzhou UniversityChina

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Source :

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISSN: 0302-9743

Year: 2015

Volume: 9106

Page: 42-54

Language: English

0 . 4 0 2

JCR@2005

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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