An artificial chemistry based framework for personal and social context aware smart spaces

Supporting context-aware services and applications that are delivered to a user as they move through a smart space is a challenge. The complexity of awareness and interaction requires an efficient interaction and adaptation model. Most research prototypes comprise of many models and extensive middleware which seems excessive for simple context-aware applications involving pervasive devices. Part of the problem is finding a conceptual abstraction which is compact and concise yet can exclusively model all the dynamism and expressivity required for such a system. In this paper we propose a context aware architecture based on a smart space context model and a middleware inspired by chemical reactions.