Sensor Networks

Principal Investigators:
S. Madden

Summary:
One component of this project focuses on the issues surrounding the efficient processing of declarative queries within sensor networks, looking in particular at the ways in which traditional, relational query optimizers must change to support the lossy, streaming data from sensornets. Query optimization has the potential to dramatically reduce the energy costs associated with sensor network data collection, offering dramatic increases in network lifetime bandwidth usage.

The second component of the project focusses on data integration issues. For sensor networks to become truly ubiquitous, it is important that such networks be able to integrate with data sources and share query processing with databases outside of the network, including traditional relational databases, flat files, and even other, remote sensor networks. To enable such integration, systems must be enhanced to allow them to understand each other's capabilities and offload query processing tasks when there are significant energy or computational savings to be had. This project seeks to seamlessly integrate sensor network query processing systems with other database systems, be they conventional relational DBMSes or other sensornets. To do this, we introduce a proxy to eliminate the need to make invasive changes to pre-existing software and propose techniques based upon an optimization framework that chooses to push down computation when it will decrease the power consumption of the sensor network.

Sponsor: