This thesis presents various studies on energy efficient design of wireless networks. It starts with a survey on recent shortest path based energy efficient routing algorithms developed for ad hoc and sensor networks, making a comprehensive classification for these algorithms. In addition to energy efficient design, sustainable and environmentally friendly deployment of wireless networks demands increased use of renewable energy. However, this calls for novel design principles to efficiently utilize the variation in the availability of the energy. The thesis continues with an investigation of state-of-the-art resource management and scheduling algorithms developed for energy harvesting wireless sensor networks. Building on the stateof- the-art, the main contribution of this thesis is to formulate and solve a utility maximizing scheduling problem in a multiuser broadcast channel with an energy harvesting transmitter. The goal is to determine the optimal power and time allocations to users between energy arrivals. The structural properties of the problem are analyzed, and its biconvexity is proved. A Block Coordinate Descent (BCD) based algorithm is developed to obtain the optimal solution. Two simple and computationally scalable heuristics, PTF and ProNTO, which mimic the characteristics of the optimal policy, are proposed. Finally, an online algorithm, PTF-On,that will bypass the need for offline knowledge about the energy harvesting statistics, is developed. PTF-On uses a Kalman filter based energy harvesting prediction algorithm, developed in this thesis, to predict the energy that will arrive in the future.