Nets: Small: Freenet: Cognitive Wireless Networking Powered By Green Energy

The project aims to liberate wireless access networks currently constrained by spectral and energy scarcity via a new framework, referred to as FreeNet, by exploiting cognitive networking and green energy. FreeNet will be designed and optimized using a series of novel techniques such as dynamic network architecture optimization, network resource aware traffic scheduling, and spectrum sharing. The network architecture optimization framework will apply advanced probability theory to investigate inherent relationships between the optimal network architecture and the availability of spare spectrum and green energy, and adopt control theory to adapt the network architecture according to the dynamics of the spare spectrum and green energy. The network resource aware traffic scheduling and spectrum sharing algorithms will be designed based on optimization theory. Finally, theoretical analysis will be reduced to practice and translated into communications protocols in enabling and prototyping FreeNet. The theoretical analysis will elicit a series of theorems to direct the utilization of green energy in communication networks.

The communication protocols design and FreeNet prototyping will provide guidelines for designing resource aware communication systems. The research activities will advance the understanding of inherent relationships among the network architecture, traffic scheduling, spectrum utilization, and energy consumption. FreeNet will be deployed for offloading mobile traffic in urban areas, delivering content in rural areas, and enhancing emergency communication capacity during natural disasters. FreeNet will improve the availability and capacity of wireless networks, broaden the benefits of wireless networking, and enhance the living environment, the earth, by reducing the release of carbon footprints. Research outcomes from this project will be disseminated via Publications and a website with frequent updates. Other broader impacts include integration of research and education through participation of both undergraduate and graduate students in the project, incorporation of research outcomes into course work, interactions and exchanges with invited speakers, and seeking involvement of REU students and under-represented groups.