Transcript Autonomous Localization in Wireless Sensor Networks

Autonomous Localization
in
Wireless Sensor Networks
Michael Allen
Cogent Applied Research Centre
Coventry University
Wireless Sensor
Network Applications
Industry
•Process control
•Automation
•Predictive maintenance
Scientific Research
•High spatial and temporal density sampling
•Habitat monitoring
•Event detection
Health Care
•Location aware patient monitoring
•Patient vital signals
Disaster Management
•Event detection (natural disasters – fire, earthquake)
•Location awareness (fire fighters looking for survivors)
•Emergency response
Military
•Battlefield surveillance
•Target tracking
Data context, localization
• In many of these applications, sensor nodes will
be reporting data, but this data needs context in
space and time – when and where it came from
• Localization addresses this context problem by
Estimating the physical position of an unknown target
based on information which is known about it
(Based on Savvides et al [1])
• With respect to wireless sensor networks and the
nodes that comprise them, we ask:
“Where is each of the nodes located?”
Examples of different
levels of localization
Global level
Node a is at +34° 0’
0.00”, -118 ° 0’ 0.00”
Room level
Node is in building A, floor
B, room C
Domain Specific
Node is on part A, machine
B, room C
High accuracy
Node is at (x,y,z) with 95% confidence of 10cm accuracy
The level of localization required is
informed by the application of the
Wireless Sensor Network (WSN)
How can we perform
localization?
• Need to assign positions to sensor nodes, e.g.
• Could be done manually, when nodes are
deployed
• Could be done by giving each node GPS
(consider power, accuracy and availability)
• Could get the network to do it for us:
– Gather ‘known information’: Get sensor nodes to estimate
distances between one another
– Calculate and refine relative positions based on this information
I am interested in real-life localization and how
(and when) it can be applied to real-life problems
My research goals
• In applying localization to given applications, I want to
produce a system which has these features:
• Autonomous – Sensor nodes perform the localization
without any external control
• Distributed – Localization computation is shared out
between all sensors in the network (no ‘special’ sensors)
• Scalable – Deployments may be augmented at a later
date, these must be integrated automatically
• Use in real-life application – Having an application as a
‘driver’ for WSN brings in a whole new set of issues
which need to be addressed
Application ‘drivers’
• Geographic Network Discovery (GND):
– Given a dense enough network,
localized accurately enough over
a terrain, build a map of it
• Soil Monitoring [2][3]:
– densely populated monitoring area
– metre order node separation
– augmentation likely
(Pictures taken from real-life deployment @ UCLA this summer)
The end…
Thank you!
Any questions?
References/Links
• [1] Savvides, A.; Srivastava, M.; Girod, L. & Estrin, D. Raghavendra,
C.; Sivalingam, K. & Znati, T. (ed.) Wireless Sensor Networks
Localization in Sensor Networks Springer, 2005
• [2] Cerpa, A., Elson, J., Estrin, D., Girod, L., Hamilton, M., and Zhao,
J. 2001. Habitat monitoring: application driver for wireless
communications technology. SIGCOMM Comput. Commun. Rev. 31,
2 supplement (Apr. 2001)
• [3] Energy Budget and AMARSS project http://egraham.bol.ucla.edu/SubPages/Energy.html
• James Reserve, CA www.jamesreserve.edu (deployment location)
• TinyOS, Wireless Sensor Nodes www.tinyos.net (key site for WSNs)
• Dust Networks www.dustnetworks.com (Example of industrial WSN
provider)
(Backup) Problems with
localization
• Not every method can be applied in every
situation
• Lots of theory, little practice
• Deployments can be small, sparse, easily
recorded by hand
• Real-life conditions bring a whole host of
new problems which simulation doesn’t
answer adequately
(Backup) Real-life
• Real-life deployment of sensor networks require
careful consideration
• Systems issues
– Actually making the network ‘work’ – data sampling,
data transport, time stamping, localization
• Physical issues
– Damaging the phenomena you’re studying, harsh
terrain, environment affecting communication
• Application issues
– We know where the data’s coming from, but is it
reliable – can we trust it? Can we use it?
(Backup) Localization –
service for WSN
• Localization is important
• Other applications/components within a
WSN may need to refer to the positions of
nodes
• If this is provided as a service, then the
localization takes care of itself, and the
components can rely that the most recent
data the get is the most accurate