Cheap and tiny processors, radios, sensors, and actuators resulting from progress in microelectronics are leading to a new class of embedded systems, often called Wireless Sensor Networks, that consist of a large number of individual nodes that are physically-coupled, energy-constrained, spatially-distributed (often in an ad hoc fashion), and wirelessly-networked. Such systems provide information about the physical environment at an unprecedented level of detail, and to manipulate the physical environment based on this information, in diverse applications such as security and surveillance, monitoring of wildlife habitats, smart sensor-instrumented environments, and condition-based maintenance of complex systems. This research involves the study of techniques to systematically design, optimize, and manage Wireless Sensor Networks so as to meet applications requirements such as how long the system should last, what space should it cover, and how accurately and how rapidly should it sense the environment.
Wireless Sensor Networks are autonomous, self-configuring, and adaptive distributed systems that perform collaborative computation among energy-constrained nodes to produce the desired information about the physical world. The study is developing design-time resource allocation and run-time resource management methods for such systems while exploiting the inter-play of energy, space, time, and accuracy dimensions that underlies the notion of quality of service in these systems. The focus is on trade-offs that manifest themselves at the level of the entire "sensor field' as opposed to the individual sensor nodes. This study is important both for understanding the fundamental performance limits of wireless sensor networks, as well as for developing practical methods to systematically deploy and operate sensor networks for specific applications.
