Telegraph, TinyDB and PIER:
Three Takes on Adaptive Dataflow

Joseph M. Hellerstein
UC Berkeley

Friday, Oct. 11, 2002, 4:00 PM
Volen 101, Brandeis University

(preceded by a wine and cheese reception at 3:00 pm)

Abstract:

A key contribution of the database community has been data independence: the decoupling of applications from physical properties of the computing environment. This has been critical in database systems, where applications can live on for decades, while the rate of change of the environment tracks Moore's Law and the whims of database administrators. In networked systems, the rate of change of the environment can be extremely rapid, and the dataflows of interest can be unbounded. As networked applications become more distributed and sophisticated, it would seem that database expertise in delivering data independence should be relevant in the construction of dataflow applications over networks. In this talk, I will present three examples of work we're doing at Berkeley on adaptive dataflow over networked environments. I will begin by describing the building blocks of the Telegraph system in some detail. Telegraph is a centralized query processor for networked data sources and streams, which has been under development for over two years. I will also provide quick overviews of two more recent projects: TinyDB, a query processing system for wireless sensors, and PIER, a peer-to-peer overlay system for querying the Internet. In presenting these systems, I will try to illustrate why the networking community has been receptive to the work, and why it's timely for the database community to play with those folks more.

Speaker Bio:

Joseph M. Hellerstein is an Associate Professor of Computer Science at the University of California, Berkeley. He is an Alfred P. Sloan Research Fellow, and a recipient of the NSF CAREER, NASA New Investigator, and Okawa Foundation Fellowship awards. In 1999, MIT's Technology Review named him one of the top 100 young technology innovators (TR100). Hellerstein received his Ph.D. at the University of Wisconsin, Madison, a masters degree from UC Berkeley, and a bachelor's degree from Harvard College. He spent a pre-doctoral internship at IBM Almaden Research Center, and a post-doctoral internship at the Hebrew University in Jerusalem. Hellerstein's research focuses on data management and movement, including database systems, sensor networks, peer-to-peer and federated systems.

Maintained by Dina Goldin dqg AT cse.uconn.edu
Last updated on 10/02/02