The widespread distribution and availability of small-scale sensors, actuators, and embedded processors is transforming the physical world into a computing platform. Sensor networks that consist of a large number of sensor nodes combining physical sensing capabilities such as temperature, light, or seismic sensors with networking and computation capabilities will become ubiquitous. Applications range from environmental control, warehouse inventory, health care to scientific and military scenarios. Sensor networks are heavily resource-constraint, and thus careful resource management is an important task.
This research will investigate cross-layer optimizations for the preservation of resources in sensor networks using a data-centric approach of programming the sensor network through queries. Due to the regularity of query processing patterns, query-layer specific routing algorithms that are optimized for the more regular types of communication patterns that are generated by a query layer. Anticipated results include techniques for processing continuous queries and ad-hoc queries over wireless sensor networks, techniques for in-network data storage including approaches for deciding when, what, and for how long data should be stored, algorithms for periodic sensor data archival, and novel techniques for gossip-style query processing in highly volatile environments. This research will also result in a prototype that integrates the research into a working system for use in research and education.