As computing devices and their users become increasingly mobile, the demand for information about the application's environment, or context, becomes significantly important to the efficient and robust operation of mobile and pervasive computing systems. Applications must be able to adapt themselves to changing conditions to satisfy users' demands and expectations and to ensure that the application's resource usage matches the environment's capabilities. Sensing context using traditional means incurs network communication, which competes with the applications using the network and expends valuable network resources, especially communication bandwidth and battery power. In this project, we are exploring passively sensing context metrics. This results in measurements that are basically approximations of actual context, but can be collected with zero cost in terms of network communication. This project develops a model of passive context sensing and a general framework for building and deploying passively sensed context metrics.

People

Dr. Christine Julien (Assistant Professor, Department of Electrical and Computer Engineering, The University of Texas at Austin)

Dr. Nirmalya Roy (Postdoctoral Researcher, Department of Electrical and Computer Engineering, The University of Texas at Austin)

Taesoo Jun (Ph.D. Candidate, Department of Electrical and Computer Engineering, The University of Texas at Austin)

Dr. Angela Dalton (Johns Hopkins Applied Physics Laboratory)

Papers

Passive Network Awareness for Adaptive Mobile Applications, in Proceedings of the 3rd International Workshop on Managing Ubiquitous Communications and Services, 2006. (This initial paper put forth the idea of passively sensing context in mobile computing scenarios and introduced a network context measure and a mechanism for passively sensing it.)