In this study, we present a framework based on a prediction model that facilitates user access to a number of services in a smart living environment. Users must be able to access all available services continuously equipped with mobile devices or smart objects without being impacted by technical constraints such as performance or memory issues, regardless of their physical location and mobility. To achieve this goal, we propose the use of cloudlet-based architecture that serves as distributed cloud resources with specific ranges of influence and a real-time processing framework that tracks events and preferences of the end consumers, predicts their requirements, and recommends services to optimize resource utilization and service response time.
This work was supported by the National Institute of Standards and Technologies (NIST), and conducted within a collaboration under Information Technology Laboratory, Advanced Network Technologies Division (ANTD) and the Universities of Grenoble and CNAM. Our special thanks go to Dr. Abdella Battou, ANTD division chief for his support and advises.