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2014 IEEE International Conference on Web Services (ICWS) (2014)
Anchorage, AK, USA
June 27, 2014 to July 2, 2014
ISBN: 978-1-4799-5053-9
pp: 81-88
ABSTRACT
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 evaluate 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. Finally, our proposed model is evaluated through the experiments executed in different conditions.
INDEX TERMS
Context, Benchmark testing, Monitoring, Context modeling, Quality of service, Time factors
CITATION

L. Qu, Y. Wang, M. A. Orgun, L. Liu and A. Bouguettaya, "Context-Aware Cloud Service Selection Based on Comparison and Aggregation of User Subjective Assessment and Objective Performance Assessment," 2014 IEEE International Conference on Web Services (ICWS), Anchorage, AK, USA, 2014, pp. 81-88.
doi:10.1109/ICWS.2014.24
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