The wireless networks of the next 10 years are expected to consist of a plethora of microprocessor-sensor devices embedded in clothes, shoes, cars, buses, as well as the traditional portable handhelds, and laptops. Since information is expected to flow through thousands to millions of wireless devices themselves in these networks (rather than a few gateways), it is essential that an aggregate view of the essential qualities of the mobile network be built and made available. Quality-of-Service (QoS) decisions (regarding energy consumption, delay and throughput) will play a prominent role in making intelligent decisions in these large-scale networks.
The major research contribution of this project is the development of methodologies for tracking and disseminating QoS metrics in mobile, wireless networks of microprocessor-sensor devices by building QoS maps in the joint memories of the nodes over relevant time scales. QoS potential functions are constructed over space by the nodes via path integration methods, and distributed via information exchange during node encounters. Novel concepts, such as the coherence time of QoS metrics, enable the application of signal processing methods to the refinement of QoS maps.
This project opens the way to building the first-generation large-scale networks of small, mobile, microprocessor-sensor devices in civilian settings, which will transform the way our society operates, utilizing a plethora of sensors and supporting semantic devices that translate this information to useful actions. This project integrates the traditionally separate signal processing and networking techniques in graduate coursework, and develops an early career focus program for minority undergraduate students.
