Sensor networking is an emerging technology that promises an unprecedented ability to monitor the physical world via a spatially distributed network of small and inexpensive wireless sensor nodes. The nodes can sense the physical environment in a variety of modalities, including acoustic, seismic, thermal, and infrared. A wide range of applications of sensor networks have been envisioned, including environmental monitoring, homeland security, and medical diagnostics. While the practically unlimited range of applications of sensor networks is quite evident, our current understanding of their design and management is far from complete. Because sensor networks collect data in a spatially distributed fashion, statistical inference problems in sensor networks present a distinct new challenge. In addition to common issues such as measurement noise and sample size limitations, limited energy resources place a very high cost on the sharing of data via wireless communications. Consequently, energy efficient methods for processing and communicating information play a central role in the theory and practice of sensor networks.
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