In this project, referred to as the Compact System-level Models (CSM) Project, we are developing new techniques to help advanced computing systems for signal processing better adapt to the environments in which they operate. This project is important because signal processing is everywhere (cell phones, computer networks, manufacturing systems, agriculture, etc.). Adapting to the environment helps these systems to operate more reliably by, for example, adapting to changing radio interference or the challenging radio environments presented by clusters of tall buildings. Many of these communication systems are also battery-operated or must run on limited energy; adapting to their operating environments helps to reduce their energy consumption and improve battery life. These techniques are particularly useful for cognitive radio, an emerging technology that allows devices for wireless communication (such as cell phones) to more efficiently use radio spectrum.
This project is developing new methods for creating software that can be reconfigured at run time. Typical software is created to operate in a particular mode; changing the software's operating conditions requires redesigning the software itself. New mathematical models and algorithms will allow system designers to create software that is designed to adapt itself dynamically to its environment. The project is addressing both models specifying the behavior of the software and for translating that specification into an efficient implementation.
The project is a collaboration among researchers at Georgia Institute of Technology, USA; Institut National des Sciences Appliquées (INSA) de Rennes, France; National Chiao Tung University, Taiwan; and University of Maryland at College Park, USA. The collaborators in Georgia, France, Taiwan, and Maryland provide complementary expertise in areas that include cyber-physical systems, cognitive radio algorithms, model-based design, and embedded signal processing. The collaboration also provides valuable international research experience for the Ph.D. student researchers involved in the project.
The project has produced a number of educational resources, including the following.
A list of publications from the CSM project can be found on the CSM Project Publications Page.
This research is supported in part by the Computer and Network Systems Program of the U.S. National Science Foundation under Grant No. CNS1514425 (University of Maryland), and CNS1513404 (Georgia Institute of Technology).
This webpage was last updated on August 22, 2018.