Concepedia

Abstract

With rapidly increasing number of cloud computing resources deployed over the Internet as on-demand services, more and more service-oriented solutions are available for selection to meet personalized requirements of consumers. However, how to choice a desired cloud service from the pools of candidate services is becoming an increasingly important research issue. The reason is that a group of functionally equivalent or overlapped alternatives are difficult to quantify in service decision making. A multi-criteria decision-making (MCMD) method based on AHP (Analytic Hierarchy Process) is proposed in the paper to transform consumer's qualitative and semi-quantitative personalized preference into quantitative numeric weights. The case study in medical cloud environment is used to validate the feasibility and effectively of our method.

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