A major issue in today's wireless world is the dramatic increase in demand for new capacity and higher performance of wireless networks. The development of these capabilities is limited severely by the scarcity of two of the principal resources in wireless networks, namely energy and bandwidth. Consequently, the community has turned to a third principal resource, the addition of intelligence throughout the network, in order to exploit increases in processing power afforded by Moore's Law type improvements in microelectronics. This talk will consider a major aspect of this phenomenon - the role of signal processing in improving the energy efficiency of wireless networks. The talk will focus on two facets of this problem: the effects of advanced node-level signal processing on the energy efficiency of wireless communication networks, where quality-of-service is a primary concern; and the use of advanced signal processing principles, such as collaborative beam-forming, sensor scheduling, and distributed learning, to enhance the energy efficiency of wireless sensor networks, where inferential performance is paramount.