Programming embedded networked sensor systems

This talk describes a state-centric abstraction for application users to interact with sensor networks. Just as in data-centric routing and storage where physical nodes are less important than the data itself, state-centric abstraction introduces "states" as a natural vocabulary to describe spatio-temporal physical phenomena that the sensor networks are typically designed for. Application programmers specify the computation as creation, sharing, and transformation of states, which naturally map to descriptions in signal processing and control applications. We argue that due to the dynamic nature of sensor networks, programs written in state-centric abstractions are more invariant to constant changes in data stream configurations and make the resulting software more portable across multiple sensor network platforms. With help of models of sensor collaboration, sensing, and estimation, the state-centric specifications are mapped into collaborative processing tasks at compile time, and further maintained at run time, leveraging the data-centric caching and routing services. We use a multi-target tracking system as an example to show how state-centric programming models can raise the abstraction level for users to interact with sensor networks and help modularize the design.