CloudRank: A QoS-Driven Component Ranking Framework for Cloud Computing

Abstract

The rising popularity of cloud computing makes building high quality cloud applications a critical and urgently required research problem. Component quality ranking approaches are crucial for making optimal component selection from a set of functionally equivalent component candidates. Moreover, quality ranking of cloud components helps the application designers detect the poor performing components in the complex cloud applications, which usually include huge number of distributed components. To provide personalized cloud component ranking for different designers of cloud applications, this paper proposes a QoS-driven component ranking framework for cloud applications by taking advantage of the past component usage experiences of different component users. Our approach requires no additional invocations of the cloud components on behalf of the application designers. The extensive experimental results show that our approach outperforms the competing approaches.