Resource Allocation and Control in Communication and Cyberphysical Networks with Renewable Energy

Renewable energy sources, such as solar and wind power, have been widely used in various forms of networks, which include both communication networks and the smart power grid. Since the renewable energy is usually highly fluctuating, the temporal and spatial dynamics of such sources are often difficult to model and predict. This makes it extremely challenging to incorporate and operate such energy sources while maintaining adequate utilization of them. In this thesis, we study the control and optimization strategies of renewable energy in several network scenarios, including wireless sensor networks, WiFi networks, and the smart grid. We first investigate the problem of maximizing the throughput or utility performance for a wireless sensor network with renewable energy. The two solutions that we developed here are based on a finite time horizon and an infinite time horizon respectively. In the finite-horizon problem, we propose a simple heuristic distributed scheme in a rechargeable sensor network with optimal performance under some specific conditions and with provable performance guarantee. Regarding the infinite-horizon problem, after characterizing the optimal network utility with an upper bound, we develop a low-complexity online scheme that is asymptotically optimal as network operation period of time tends to infinite. It shows that by focusing on long-term system performance, we can greatly simplify computational complexity while maintaining high performance. We then study the problem of efficient channel access in WiFi networks, where