Resource Aware Programming for Sensor Networks
Speaker: Matt Welsh , Harvard University
Date: November 18 2009
Time: 4:00PM to 5:00PM
Location: 34-401B (Grier B)
Host: Sam Madden, CSAIL
Contact: Sheila Marian, x3-1996, sheila@csail.mit.edu
Resource Aware Programming for Sensor Networks
Matt Welsh, Harvard University
Abstract: Sensor networks have taken off, though tuning them to achieve good
resource efficiency is difficult. Our group has deployed sensor
networks for volcano monitoring and rehabilitation medicine, and each
time we find that tuning parameters to achieve the right tradeoff in
terms of data quality, battery lifetime, and bandwidth usage is quite
painful. To make things worse, resource availability fluctuates over time,
as does the load that the application places on those resources. The
severely constrained and decentralized nature of sensor networks makes
this problem fairly challenging.
In this talk, I will argue that the software for sensor networks
should be designed around the fundamental abstraction of
resource-aware programming. In this model, the application has direct
visibility and control over resources as a first-class primitive.
This requires the application code to take responsibility for its
own resource management decisions, since it cannot expect a "bailout"
from the OS. This approach enables much more effective adaptations to
changing conditions, and supports a rich space of resource-management
policies.
In this talk, I will present three related systems that leverage this
approach: Pixie, a new sensor node operating system; Lance, a
network-wide resource management plane; and Mercury, a platform for
maximizing data quality in a wearable sensor network. I will present
examples and evaluations based on our real-world deployments.
Bio: Matt Welsh is an Associate Professor of Computer Science at Harvard
University, where he has been on the faculty since 2003. His research
interests span many aspects of distributed systems, operating systems,
and programming languages. His current focus is on wireless sensor
networks including new OS and language designs to enable efficient,
high-data-rate applications. Prior to joining Harvard, he spent one
year at Intel Research, Berkeley. He completed his Ph.D. at UC
Berkeley and his B.S. at Cornell University.
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