A hybrid multi criteria decision method for cloud service selection from Smart data

Abdullah Al-Faifi, Biao Song, Mohammad Mehedi Hassan, Atif Alamri, Abdu Gumaei

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

Cloud computing refers to providing computing services and resources over the Internet. The cloud provider is an organization or company which offers the services to the consumer at different levels of features and characteristics. However, as the growth of cloud services as well as cloud service providers are increasing rapidly, it is becoming a challenge for consumers to choose the best service provider based on their requirements. In this paper, we propose a method to help the consumer to answer this question. A hybrid multi criteria decision method (MCDM) is developed to evaluate and rank cloud service providers from Smart data. Furthermore, this method considers the interdependencies and relations between the performance measurements. The hybrid method consists of two components: (i) clustering the providers using k-means algorithm to consolidate cloud service providers with similar features and (ii) applying MCDM methods using DEMATEL-ANP to rank clusters and make a final decision. The proposed method also considers the existing workloads of the organization as well as assigns different importance and weights for a set of criteria by clustering the cloud service providers using k-means algorithm. A simulation on the MATLAB was performed to evaluate the proposed method, and the results indicate how the proposed hybrid approach can provide an accurate and efficient way to select the best providers.

Original languageEnglish
Pages (from-to)43-57
Number of pages15
JournalFuture Generation Computer Systems
Volume93
DOIs
StatePublished - Apr 2019
Externally publishedYes

Keywords

  • Analytical network process
  • Cloud service selection
  • DEMATEL
  • K-means
  • Multi criteria decision method
  • Smart data

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