CCCloud: Context-Aware and Credible Cloud Service Selection Based on Subjective Assessment and Objective Assessment

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.

1 Introduction

Due to the diversity and dynamic nature of cloud services, selecting the most suitable cloud service has become a major issue for potential cloud consumers. Prior to cloud service selection, an evaluation of cloud services should be performed first. There are two types of approaches which can be used to conduct such an evaluation. The first type of approaches is based on objective performance assessment from ordinary QoS parameters (Quality-of-Service, e.g., service response time, availability and throughput) [1], [2], [3] and predesigned benchmark testing [4], [5], [6]. As cloud services are highly virtualized, some methods and tools for traditional IT computation measurements can be appropriately applied in cloud environments. By combining these methods and tools according to the characteristics of cloud services, many metrics can be quantitatively assessed (e.g., the speed of CPU and I/O). The second type of approaches is based on ordinary consumers’ (OCs) subjective assessments extracted from their subjective ratings for every concerned aspect of cloud services [7], [8]. In this type of approaches, cloud services are usually treated like traditional web services, thus some rating-based reputation systems [9], [10], [11] can be utilized for cloud service selection.