Transcript Bio-inspired algorithms in a Wireless Sensor Network

Proactive monitoring in
natural environments
Ian Marshall, Computing Laboratory, University of Kent
[email protected]
Technical Director of the Envisense Research centre
http://envisense.org
Current research methods
• Single expensive
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package
In situ process studies
Low spatial resolution
Short lifetime
Small areas
Wireless Sensor networks
• Ad-hoc wireless communication
• Physical measurement
• No access to mains
• Large area (sq kms)
• Long life (months)
• Many measurement points
WSN management
• Low probability of manual
intervention
• Highly dynamic, unpredictable
environment
• Very unreliable nodes and comms
• Need to automate response to
events
• ‘model free’ adaptive control
Peak district Experiments
Floodnet
SECOAS
Scroby sands wind
farm and its impact
on sedimentation
processes
CEFAS Survey
April 2002
Mechanical General
Arrangement
Buoy (yellow)
Radio equipment
Chain
Data cable
Chain
Plough anchor
Warp
Warp
Real trial Oct-Nov 2004
Initial Deployment Areas
6 Sensors
150m apart
Shore station
1 NM
Seabed Package
• Measure Oceanographic variables (15
minute cycle)
• Temperature (1 sample/min)
• Pressure (1 sample/s for 5 mins)
• Turbidity (10 samples/min)
• Tilt (aka current) - (1 sample/s for 5 mins)
• Conductivity (1 sample/min)
• Adapt sampling rates
• Adaptively log data
• Transmit selected data to radio buoy
Adaptive sampling
• Measure, delete, combine, forward, sleep
• Use local variability, neighbour variability
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and internal state
Self configure using distributed
evolutionary “algorithm” (bacteria)
Can adjust priorities and frequency of
actions
Can form groups (quorum sensing)
Reward set by user using a diffusion
(gossip) protocol – changes drive autoreconfiguration of genome
QoS on a Sensor Network
Processing
Summary
• Autonomous adaptive control is needed in
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environmental sensor networks
Network protocols must support and respond
to application semantics (be app aware)
In simulation adaptation was almost as good
as optimal sliding window
In practice it dealt well with change from calm
to stormy
More research will be needed
• www.secoas.org
• www.envisense.org