An improved K-dominance method for QoS based service recommendation in cloud

In the cloud computing environment, more and more functional-equivalent services are provided with different QoS levels by competitive provider, resulting to increasing importance of QoS-based service selection or recommendation. To cope with this multi-objective optimization problem, we first propose a novel improved k-dominance operator, i.e. the partial dominance score. By combining the partial dominance score and skyline computation, we redefine the optimization objective for the QoS based service recommendation. Then, we present an algorithm that can efficiently search and return top-k QoS optimal services in term of their partial dominance score. Finally, we evaluate the efficiency as well as the effectiveness of proposed algorithm through a set of experimental studies.