Mobile devices can better manage user privacy if they continuously model a user's context, but doing so can result in high energy consumption. The energy costs can be reduced by reasoning about what context information is known, what additional information is needed, how accurate it must be and how to efficiently acquire it. We model the sensors and their data properties, accuracy levels and energy costs in an RDF knowledge base supported by an OWL ontology. We describe a method to manage privacy on smartphones in an energy efficient manner by selecting the best choice sensor for maintaining the user's context information. Sensor selection is done by COntext MANager miDDleware (COMANDD), which maintains a context model and answers queries about it. Context requests are served by capability matching, accuracy level matching and selection of lowest energy cost sensor for reporting context data. A context change detection function is used to decide when the context should be updated.
['Prajit Kumar Das', 'Anupam Joshi', 'Tim Finin']
Energy efficient sensing for managing context and privacy on smartphones