A factor framework for experimental design for performance evaluation of commercial cloud services

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Abstract
Given the diversity of commercial Cloud services, performance evaluations of candidate services would be crucial and beneficial for both service customers (e.g. cost-benefit analysis) and providers (e.g. direction of service improvement). Before an evaluation implementation, the selection of suitable factors (also called parameters or variables) plays a prerequisite role in designing evaluation experiments. However, there seems a lack of systematic approaches to factor selection for Cloud services performance evaluation. In other words, evaluators randomly and intuitively concerned experimental factors in most of the existing evaluation studies. Based on our previous taxonomy and modeling work, this paper proposes a factor framework for experimental design for performance evaluation of commercial Cloud services. This framework capsules the state-of-the-practice of performance evaluation factors that people currently take into account in the Cloud Computing domain, and in turn can help facilitate designing new experiments for evaluating Cloud services.
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