DocumentCode :
3424081
Title :
Iaas Cloud Selection using MCDM Methods
Author :
ur Rehman, Zia ; Hussain, Omar K. ; Hussain, Farookh Khadeer
Author_Institution :
Sch. of Inf. Syst., Curtin Univ. of Technol., Perth, WA, Australia
fYear :
2012
fDate :
9-11 Sept. 2012
Firstpage :
246
Lastpage :
251
Abstract :
The popularity of cloud computing and IaaS has spawned numerous cloud service providers which offer various cloud services, including IaaS, to cloud users. These services vary considerably in terms of their performance and cost and the selection of a suitable cloud service becomes a complex decision making issue for a cloud service user. Furthermore, the cloud services have several attributes all of which are the criteria that have to be taken into account when making a service selection decision. In the presence of these multiple criteria, a compromise has to be made because in most real-world situations, no single service exceeds all other services in all criteria but one service may be better in terms of some of the criteria while other services may outperform it if judged on the basis of the remaining criteria. Multi-criteria decision-making is a sub-field in operations research that deals with the techniques to solve such multi-criteria problems. There are several methods of multicriteria decision-making. In this paper, we use key multi-criteria decision-making methods for IaaS cloud service selection in a case study which contains five basic performance measurements of thirteen cloud services by a third party monitoring service. We demonstrate the use of these multi-criteria methods for cloud service selection and compare the results obtained by using each method to find out how the choice of a particular MCDM method affects the outcome of the decision-making process for IaaS cloud service selection.
Keywords :
cloud computing; decision making; operations research; performance evaluation; IaaS cloud selection; MCDM method; cloud computing; cloud service providers; cloud service user; multicriteria decision making; operations research; performance measurements; service selection decision making; third party monitoring service; Cloud computing; Decision making; Educational institutions; Monitoring; Operations research; Programming; Vectors; IaaS; MCDM; Service Selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
e-Business Engineering (ICEBE), 2012 IEEE Ninth International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2601-8
Type :
conf
DOI :
10.1109/ICEBE.2012.47
Filename :
6468246
Link To Document :
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