For future smart environment scenarios to exhibit autonomic behavior, both networks and application components and services need to be aware of their computational and environmental context, and must tune their activities accordingly. This position paper proposes an abstract architecture for knowledge networks that addresses the key issues of how both physical contextual knowledge and more importantly social knowledge from the users of communication networks can be used to form a knowledge space to support autonomous agents for smart environments. We discuss that the availability of raw contextual data is not enough to achieve meaningful autonomic behaviors. Rather, contextual information should be properly organized into ’networks of knowledge’, to be exploited by both network and application components as the basic ’nervous system’ in which situational stimuli reify into digital knowledge to be used by smart devices within and across smart environments.
|Title of host publication||Proceedings of the IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications (DIS'06)|
|Publication status||Published (in print/issue) - 2006|