CCCloud: Context-aware and credible cloud service selection based on subjective assessment and objective assessment

Qu, L, Wang, Y, Orgun, M, Liu, L, Liu, H and Bouguettaya, A 2015, 'CCCloud: Context-aware and credible cloud service selection based on subjective assessment and objective assessment', IEEE Transactions on Services Computing, vol. 8, no. 3, pp. 369-383.


Document type: Journal Article
Collection: Journal Articles

Title CCCloud: Context-aware and credible cloud service selection based on subjective assessment and objective assessment
Author(s) Qu, L
Wang, Y
Orgun, M
Liu, L
Liu, H
Bouguettaya, A
Year 2015
Journal name IEEE Transactions on Services Computing
Volume number 8
Issue number 3
Start page 369
End page 383
Total pages 15
Publisher IEEE
Abstract Due to the diversity and dynamic nature of cloud services, it is usually hard for potential cloud consumers to select the most suitable cloud service. This paper proposes CCCloud: a context-aware and credible cloud service selection model based on the comparison and aggregation of subjective assessments extracted from ordinary cloud consumers and objective assessments from quantitative performance testing parties. We propose a novel approach to evaluate cloud users' credibility, which not only can accurately evaluate how truthfully they assess cloud services, but also resist user collusion. In addition, in our model, objective assessments are used as benchmarks to filter out potentially biased subjective assessments, and then objective assessments and subjective assessments are aggregated to evaluate the overall performance of a cloud service. Furthermore, our model takes the contexts of objective assessments and subjective assessments into account. By calculating the similarity between different contexts, the benchmark level of objective assessments is dynamically adjusted according to context similarity, and the aggregated final scores of alternative cloud services are weighted by the similarity between the contexts of a potential cloud consumer and every testing party. This makes our cloud service selection model reflect potential cloud consumers' customized requirements more effectively. Finally, our proposed model is evaluated through the experiments conducted under different conditions. The experimental results demonstrate that our model significantly outperforms the existing work, especially in the resistance of user collusion.
Subject Computer Software not elsewhere classified
Distributed Computing not elsewhere classified
Information Systems not elsewhere classified
Keyword(s) cloud service selection
context similarity
credibility of cloud users
subjective or objective assessments
DOI - identifier 10.1109/TSC.2015.2413111
Copyright notice © 2015 IEEE
ISSN 1939-1374
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