A Methodology for Eliciting and Ranking Control Points for Adaptive Systems
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Designing an adaptive system to meet its quality constraints in the face of environmental uncertainties, such as variable demands, can be a challenging task. In cloud environment, a designer has to also consider and evaluate different control points, i.e., those variables that affect the quality of the software system. This thesis presents a method for eliciting, evaluating and ranking control points for web applications deployed in cloud environments. The proposed method consists of several phases that take a high-level stakeholders' adaptation goal and transform it into lower level MAPE-K loop control points. The MAPE-K loop is then activated at runtime using an adaptation algorithm. We conducted several experiments to evaluate the different phases of the methodology and we report the results and the lesson learnt.