Ranking Prediction of Cloud Services based on BPR

Cloud is an advancing technology where the the concept of service oriented architecture, distributed, autonomic, and utility computing is being utilized by various service providers. The current changing world is highly challengeable to build high-quality cloud application. Since QoS ranking that provide beneficial information for optimal cloud service selection is time consuming and expensive, this paper focuses on QoS ranking prediction framework for selecting optimal cloud services based on Bayesian Personalized Ranking. Our proposed framework is able to perform well with no additional invocations of cloud services while predicting appropriate services. QoS Ranking Prediction can be done by two approaches. The simulation results show that the approaches are outperforming other competing approaches