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Parallel Cloud Service Selection and Ranking Based on QoS History

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Abstract

The growing number of cloud services has made service selection a challenging decision-making problem by offering wide ranging choices for cloud service consumers. This necessitates the use of formal decision making methodologies to assist a decision maker in selecting the service that best fulfills the user’s requirements. In this paper, we present a cloud service selection methodology that utilizes quality of service history of cloud services over different time periods and performs parallel multi-criteria decision analysis to rank all cloud services in each time period in accordance with user preferences before aggregating the results to determine the overall rank of all the available options for cloud service selection. This methodology assists the cloud service user to select the best possible available service according to the requirements. The multi-criteria decision making processes used for each time period are independent of the other time periods and are executed in parallel.

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Authors and Affiliations

  1. School of Information Systems, Curtin University, Perth, WA, Australia

    Zia ur Rehman & Omar Khadeer Hussain

  2. Decision Support and e-Service Intelligence Lab (DeSI Lab), Quantum Computation and Intelligent Systems, School of Software, University of Technology, Sydney, NSW, Australia

    Farookh Khadeer Hussain

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  1. Zia ur Rehman
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  2. Omar Khadeer Hussain
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  3. Farookh Khadeer Hussain
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Correspondence to Farookh Khadeer Hussain.

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Rehman, Z.u., Hussain, O.K. & Hussain, F.K. Parallel Cloud Service Selection and Ranking Based on QoS History. Int J Parallel Prog 42, 820–852 (2014). https://doi.org/10.1007/s10766-013-0276-3

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  • DOI: https://doi.org/10.1007/s10766-013-0276-3

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