Transcript Wireless Sensor Networks: Instrumenting the Physical World

Wireless Sensor Networks:
Instrumenting the Physical World
Deborah Estrin
UCLA Computer Science Department
and
USC/ISI
http://lecs.cs.ucla.edu/estrin
[email protected]
Collaborative work with SCADDS researchers Heidemann,
Govindan, Bulusu, Cerpa, Elson, Ganesan, Girod,
Intanagowat, Yu, and Zhao (USC/ISI and UCLA);
and Shenker (ACIRI)
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The long term goal
Embed numerous distributed
devices to monitor and interact
with physical world: in workspaces, hospitals, homes, vehicles,
and “the environment” (water,
soil, air…)
Circulatory Net
Disaster Response
Network these devices so that
they can coordinate to perform
higher-level tasks.
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Requires robust distributed
systems of hundreds or
thousands of devices.
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Vision
• Embed large numbers of small, low-power,
computationally powerful, communicating
devices...
• Communicate to correlate and coordinate
• Design, deploy, and control robust distributed
systems composed of hundreds or thousands of
physically-embedded devices
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Super Sensing
• Supercomputing and computational science
qualitatively altered science and engineering
by making it practical to analyze what was not
previously practical
• Distributed micro-sensing now makes it
practical to measure and monitor what was
not previously practical--radically increases
the spatial and temporal density of in situ
monitoring
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In the laboratory
– Marine Biology
• e.g., correlate samples with
temperature, salinity, etc.
– Contaminant flows
• Measure flows
without disrupting
process
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Bio-Tank
-scaled
Tethered
Robot
Algae
2 meters
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In the Field
– Habitat studies
Sensors
– Environmental
monitoring
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Inner wall of storm drain
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Model Development and Validation
– Seismic activity in urban centers
– Atmospheric monitoring in heterogeneous
regions
– Oceanographic current monitoring
– Coastal ocean networks
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www.argo.ucsd.edu
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Topex-www.jpl.nasa.gov
Complex Structures
– Seismic response in buildings
– Bridges
– Aircraft
– Photocopiers
– Transportation
Sensors
– “Computational
Fabric”
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New Constraints
• Tight coupling to the physical world
– Need better physical models
– More experimentation
• Designing for energy constraints
• Coping with “apparent” loss of layering
– Radio…to MAC…to routing…to application
– More experimentation
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New Design Goals
• Designing for long-lived (and often energyconstrained) systems
– Low-duty cycle operation
– Exploiting redundancy
– Tiered architectures
• Self configuring systems
– Measure and adapt to unpredictable RF and sensing
environment
– Exploit spatial diversity of sensor/actuator nodes
– Localization and Time synchronization are key building
blocks
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Technical challenges
• Ad hoc, self organizing, adaptive systems with
predictable behaviors
• Collaborative processing, data fusion, multiple
sensory modalities
• Data analysis/mining to identify collaborative
sensing, triggering thresholds, etc
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Enormous Potential Impact
Earth Science
Exploration
Medical monitoring
Disaster Recovery
and Urban Rescue
Networked Embedded
Systems
Smart spaces
Condition Based
Maintenance
Wearable computing
Transportation
Environmental
Monitoring
Biological
Monitoring
Active Structures
Bio-Tank
-scaled
Tethered
Robot
Strand
Stand
Algae
Sensors
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2 meters