A Novel Incentive Mechanism for Truthful Performance Assessments of Cloud Services (Extended Abstract)

Lie Qu (Macquarie University), Yan Wang (Macquarie University), Mehmet Orgun (Macquarie University)

Abstract

The performance evaluation of cloud services usually relies on continual assessments from cloud users. In order to elicit continual and truthful assessments, an effective incentive mechanism should allow users to provide uncertain assessments when they are not sure about the real performance of cloud services, rather than providing untruthful or arbitrary assessments. This paper a novel uncertain-assessment-aware incentive mechanism. Under this mechanism, a rational 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.