An uncertain assessment compatible incentive mechanism for eliciting continual and truthful assessments of cloud services

Abstract

The evaluation of dynamic performance of cloud services relies on continual assessments from cloud users, e.g., ordinary consumers and testing parties. In order to elicit continual and truthful assessments, an effective incentive mechanism in cloud environments should allow users to provide uncertain assessments when they are not sure about the real performance of cloud services, e.g., when users do not access cloud services on time, rather than providing untruthful or arbitrary assessments. Different from all prior works, we propose a novel uncertain assessment compatible incentive mechanism. Under this mechanism, a user not only has sufficient incentives to continually provide truthful assessments, but also would prefer providing uncertain assessments over untruthful or arbitrary assessments since uncertain assessments can bring more benefits than untruthful or arbitrary assessments. We theoretically analyze the proposed incentive mechanism and evaluate it through simulations under different circumstances. The theoretical analysis demonstrates the effectiveness of our approach. Moreover, the experimental results based on simulations strongly support the results from the theoretical analysis.