A Multi-Recommenders System for Service Provisioning in Multi-Cloud Environment

Cloud service recommendation has become an important technique that helps users decide whether a service satisfies their requirements or not. However, the few existing recommendation systems are not suitable for real world environments and only deal with services hosted in a single cloud, which is simply unrealistic. In addition, a same service may be hosted on more than one cloud and, hence, may have different user ratings that depend on specific conditions of their cloud availability zones. This uncertainty regarding the real quality of the cloud service and users' satisfaction levels raises a question about how to trust the different users' ratings in order to recommend the adequate cloud service. Unlike existing solutions, the goal of this work is to propose a cooperative recommender system that aims to resolve two major issues: recommendation of cloud services in multiple clouds and recommendation under uncertainty of users' ratings. The proposed system will take advantage from a set of powerful techniques and paradigms in order to offer an overlay of cloud recommender entities that cooperate to deliver top-rated services to the user.