Context-aware Cloud Service Selection based on Comparison and Aggregation of User Subjective Assessment and Objective Performance Assessment

Abstract—Due to the diversity and dynamics of cloud services, it is usually hard for potential cloud consumers to select the most suitable cloud service. In prior studies, cloud service selection is usually based on either objective performance assessment or cloud users ’ subjective assessment (e.g., subjective ratings). However, either assessment way has its limitation in reflecting the quality of cloud services. This causes a problem that some vital performance aspects which concern potential cloud consumers are not taken into account in cloud service selection. This paper proposes a novel context-aware cloud service selection model based on the comparison and aggregation of subjective assessment extracted from cloud user feedback and objective assessment from quantitative performance testing. In this model, objective assessment provided by some professional testing parties is used as a benchmark to filter out potentially biased subjective assessment from cloud users, then objective assessment and subjective assessment are aggregated to eval-uate the overall performance of cloud services according to potential cloud users ’ personalized requests. Moreover, our model takes the contexts of objective assessment and subjective assessment into account. By calculating the similarity between different contexts, the benchmark level of objective assessment is dynamically adjusted according to context similarity, which makes the following comparison and aggregation process more accurate and effective. After aggregation, the final results can quantitatively reflect the overall quality of cloud services. Fi-nally, our proposed model is evaluated through the experiments executed in different conditions. Keywords-Cloud service selection; Subjective or objective assessment; Context similarity; I