Managing context data for diverse operating spaces

Abstract

Context-aware computing is an exciting paradigm in which applications perceive and react to changing environments in an unattended manner. To enable behavioral adaptation, a context-aware application must dynamically acquire context data from different operating spaces in the real world, such as homes, shops and persons. Motivated by the sheer number and diversity of operating spaces, we propose a scalable context data management system in this paper to facilitate data acquisition from these spaces. In our system, we design a gateway framework for all operating spaces and develop matching algorithms to integrate the local context schemas of operating spaces into a global set of domain schemas upon which SQL-based context queries can be issued from applications. The system organizes the operating space gateways as peers in semantic overlay networks and employs distributed query processing techniques over these overlays. Evaluation results on a prototype implementation demonstrate the effectiveness of our system design.