OSDI '06 Abstract
Pp. 381–396 of the Proceedings
Fidelity and Yield in a Volcano Monitoring Sensor Network
Geoff Werner-Allen and Konrad Lorincz, Harvard University;
Jeff Johnson, University of New Hampshire; Jonathan Lees, University of North Carolina; Matt Welsh, Harvard University
Abstract
We present a science-centric evaluation of a 19-day sensor
network deployment at Reventador, an active volcano in Ecuador.
Each of the 16 sensors continuously sampled seismic and acoustic
data at 100 Hz. Nodes used an event-detection algorithm to trigger
on interesting volcanic activity and initiate reliable data transfer
to the base station. During the deployment, the network recorded
229 earthquakes, eruptions, and other seismoacoustic events.
The science requirements of reliable data
collection, accurate event detection, and high timing precision
drive sensor networks in new directions for geophysical monitoring.
The main contribution of this paper is an evaluation of the sensor
network as a scientific instrument, holding it to the standards
of existing instrumentation in terms of data fidelity (the
quality and accuracy of the recorded signals) and yield (the quantity
of the captured data).
We describe an approach to time rectification of the acquired
signals that can recover accurate timing despite failures of the
underlying time synchronization protocol. In addition, we perform a
detailed study of the sensor network's data using a direct comparison
to a standalone data logger, as well as an investigation of seismic
and acoustic wave arrival times across the network.
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