A generic context model enhanced with self-configuring features

This paper addresses two fundamental research problems in the domain of context aware autonomic systems: the development of a generic context model that can be used to represent general purpose contexts in a system interpretable way and the autonomic context model management. The proposed context model uses two equivalent and synchronized ways of representing the context: a set based representation and an ontology based representation. The set based representation is used to evaluate the conditions under which the self-* processes should be executed in order to enforce the autonomic properties. The ontology representation is used by context aware applications for reasoning and learning purposes. The increasing complexity of execution environments of the context aware systems and the difficulties of their management have headed us towards the necessity of defining and integrating the self-configuring autonomic paradigm in the context model management process. The self-configuring property is enforced by monitoring the real world context in order to detect context variations or conditions for which the context artifacts must be updated.