Situation-based and self-adaptive applications for the smart environment

Situation-based and self-adaptive applications are the key enablers of smart environments and ecosystems. In those environments, developers and users focus on innovating and making added-value applications, instead of solving the problems of interoperability and complexity of heterogeneous systems. This paper contributes by introducing an innovative adaptation framework for the situation-based and self-adaptive applications of smart environments. The framework embodies a novel architecture, generic ontologies for context, security, and performance management, and dynamic models for performing runtime reasoning and adaptation. The framework is intended for an application developer who is i) creating application scenarios, and ii) transforming the scenarios into annotated sequence diagrams with the help of the static models of the framework, the ontologies, and the rules defined in them. Thereafter, the application developer iii) transforms the annotated application behavior description into the selected rule language, SPARQL. The approach is exemplified through the creation of the GuideMe application, which exploits context, security, and performance information to adapt the service according to the quality requirements and the context of the user, as well as the smart environment, without bothering the end-user.