CloudRec:A Mobile Cloud Service Recommender System Based On Adaptive QoS Management

The rapid development and growth of mobile Internet and cloud computing have made the usage of mobile cloud services widespread. More and more people know mobile cloud service and use mobile cloud service in daily life. However, many similar functionalized cloud services available on global markets cause difficulties for mobile users to select proper services to consume. Unlike the normal cloud service, the context of mobile cloud service changes no matter when and where. Obviously the quality of a mobile cloud service is affected by its usage context. Users expect qualified services that can cope with their usage situations and are optimized for satisfying their expectations.In this thesis, we introduce a mobile cloud service recommender system named CloudRec based on adaptive Quality of Service (QoS) management. In the analysis of domestic and foreign scholars’ research on mobile cloud service, we propose to design a recommender system to solve the problem of mobile cloud service selection. CloudRec makes recommendation of best mobile cloud service based on QoS evaluation. The system can adaptively recommend the most appropriate mobile cloud service to a user according to the user’s usage context on the basis of service performance monitoring and service quality evaluation. CloudRec will monitor the mobile cloud service when it’s running, and change its service model to keep QoS to satisfy the user by adaptive QoS management. We designed CloudRec prototype system on Android platform and made system evaluation on mobile searching cloud service. System evaluation based on a prototype implementation and user studies shows the effectiveness of CloudRec. And user investigation also showed that CloudRec is a popular mobile cloud service recommendation software.