Coping with Sensor Networks in the Real World: A Systems Approach

April 30, 2007
Time: 11:00am-12:00pm
Interschool Lab, Room 750 CEPSR
Speaker: Ben Greenstein, University of California, Los Angeles

Abstract

Someday soon, sensor networks will be all around us, helping to find survivors and assessing structural damage after a natural disaster, estimating the carbon budget of forests, tracking levels of arsenic in groundwater, and helping asthmatics avoid particulate matter block by block in polluted cities. The challenge to their ubiquity is that, at present, they're fragile, difficult to use, inaccessible, and designed for a single use by a single user. My work builds toward transforming these networks---collections of nodes with low-bandwidth radios and limited processors---into reusable infrastructure that we can share. Through Tenet, I provide a way for users to construct tasks for the sensing tier on capable PC-class devices, and a mote runtime that can support several tasks concurrently. The sensing tier thus becomes flexible and generic, supporting a wide range of application services. To lessen communication and power overhead, I created VanGo, which provides software filters to reduce high-rate data at its source. In this framework, PC-class devices, with their greater resources, calibrate and configure data reduction software running on constrained embedded sensing nodes. Finally, since planning for efficient sensing-tier operation requires evaluating the constraints relevant to sensor network applications, I designed SNACK. The Sensor Network Application Construction Kit provides a configuration language and compiler so top-tier devices can express and solve this constraint-satisfaction problem, merging individually specified tasks into efficient combinations to make the best use of sensor resources.

Speaker Biography

Ben Greenstein is postdoctoral researcher at Intel Research Seattle. He received a Ph.D. in Computer Science in 2006 from the University of California, Los Angeles, where he studied wireless networks and embedded sensing software systems under the direction of Deborah Estrin and Eddie Kohler. He received an M.S. in Computer Science from Temple University and a B.A. in History from the University of Pennsylvania. He has worked at Intel Research Berkeley, the International Computer Sciences Institute, and AT&T.


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