Query Processing in Sensor Networks
Friday, March 28, 2003
Host: Richard Cole, email@example.com, 212-998-3119
Many of the emerging applications for sensor networks are focused on data collection and monitoring in remote environments. Unfortunately, existing tools for building such applications require users of these networks, who often aren't trained computer scientists, to write low-level, embedded C code. Such deployments frequently become mired in the difficulties of coding power-management, routing, and storage features in these volatile distributed environments.
In this talk, I will discuss how many of these difficulties can be overcome by providing users with a simple declarative interface where short, SQL-like queries are pushed into the network. Such queries concisely express a user's data needs, freeing him or her from the details of implementation and execution. In additional to dramatically simplifying the task of sensor-network programming, this approach enables the system to transparently optimize in-network query execution to minimize overall power consumption in ways that even sophisticated programmers may miss.
I will summarize the query processing features of TinyDB, a query processor for sensor networks we have developed at Berkeley, focusing on a framework for executing and optimizing aggregation queries. I will discuss current deployments that are underway at Berkeley, along with new features that are being incorporated to accommodate these deployments. I will include a brief demonstration of the system.
Biographic info: Sam Madden is a 4th year Ph.D. student in the Database Group in the Computer Science Department at the University of California, Berkeley. He received his M.Eng. and B.S. from MIT in 1999.