Department of Computer Science
Korea Advanced Institute of Science and Technology (KAIST)
SeeMon: a Scalable and Energy-efficient Context Processing Framework for Sensor-rich Mobile Environments
Proactively providing services to mobile users is essential for many emerging pervasive computing applications. Such services require different types of contexts with different degrees of context-awareness. Individuals have different service requirements and preferences, personalized to their own needs. Personal sensor networks will grow much in scale, diversity, and complexity and provide much broader coverage and higher accuracy in recognized contexts. As a full-fledged, integrated personal service agent, a personal mobile system should provide an efficient context processing framework, incorporating personal sensor networks and running multiple applications simultaneously. It should continuously process a large volume of sensor data while supporting a number of applications. We present SeeMon, a scalable and energy-efficient context processing framework for sensor-rich, resource-limited mobile environments. Running on a personal mobile device, SeeMon effectively performs context monitoring involving numerous sensors and applications. On top of SeeMon, multiple applications on the mobile device can proactively understand users’ contexts and react appropriately. We present a novel context monitoring approach that provides efficient processing and sensor control mechanisms. We implemented and tested a prototype system on several mobile devices: a smart-phone (Nokia N96), a UMPC, and a wearable device with a diverse set of sensors. Example applications are also developed based on the implemented system. Experimental results show that SeeMon achieves a high level of scalability and energy efficiency.Bio:
Junehwa Song is an associate professor, Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea. Before joining KAIST, he worked at IBM T.J. Watson Research Center, Yorktown Heights, NY from 1994 to 2000. He received his Ph.D. in Computer Science from University of Maryland at College Park in 1997. His research interest includes Mobile and Pervasive Computing Systems, Internet Systems Technologies, High Performance Web Serving Infrastructure, System Support for E-Commerce and Multimedia Service on the Internet.