Abstract: Sensor networks are usually envisioned as wireless networks of embedded computers that are equipped with several environmental sensors. Such sensors include, but are not limited to: thermistors, photometers, humidity sensors, accelerometers, and GPS. Using these devices, researchers have imagined (and in some cases implemented) applications that perform environmental monitoring, disaster response, and social monitoring. Some day, we may even be immersed in a sensor rich world where users are able to interact and query the physical world much like today's internet. In this presentation, I will give a basic overview of this field including some technological highlights and recent research trends. Afterwards, I'll focus on programming models for sensor networks. I'll discuss why programming sensor networks is challenging, and how these challenges can be resolved using an appropriate programming model. Specifically, I'll introduce the Hierarchical Programming model, a programming model that uses event-based groups of sensor nodes to task and program the sensor network. I'll then briefly discuss a straightforward implementation of this model. Afterwards, I'll introduce a very different implementation of this model that uses spreadsheet-inspired interfaces to program the sensor network. Finally, I'll discuss some future work with respect to alternative implementations of the model and discuss how this research may be applied to other pervasive-computing fields.

Short Bio: TBA