Distributed localization in wireless sensor networks

1
Distributed localization in wireless sensor
networks

• Koen Langendoen
• Niels Reijers
• Delft University of Technology
• The Netherlands

2
Technology trend

• Small integrated devices
• Smaller, cheaper, more powerful
• PDAs, mobile phones
• Many opportunities, and research areas
• Power management
• Distributed algorithms

3
Wireless sensor networks

• Wireless sensor node
• power supply
• sensors
• embedded processor
• wireless link
• Many, cheap sensors
• wireless ? easy to install
• intelligent ? collaboration
• low-power ? long lifetime

4
Possible applications

• Fire rescue
• breadcrumbs
• exit path
• hazard detection
• Environmental monitoring
• detecting forest fires
• Monitoring bulk goods (potatoes)
• mix sensors with goods
• temperature, humidity

5
Required technologies

• Efficient data routing
• ad-hoc network
• one or more datasinks
• In-network data processing
• large amounts of raw data
• limited power and bandwidth
• Node localization

6
Ad-hoc localization

• Many nodes (gt 100)
• NO infrastructure
• NO central processing
• Sparse anchor nodes
• known position
• Other nodes determine position using this data
• Distance measurement

7
Ad-hoc localization

• 2D, static node positions
• Several different algorithms
• have been proposed
• 3 will be compared
• Simulations on
• DAS2 supercomputer

8
Main result

• no one size fits all
• Best algorithm depends on
• error in range measurement (range variance)
• connectivity (number of neighbours)
• network topology
• node capabilities
• application requirements

9
Three-phase approach

• Determine distance to anchor nodes
• (communication)
• Establish position estimates
• (computation)
• Iteratively refine positions using additional
  range measurements
• (both)

10
Phase 1 Distance to anchor

• Three algorithms
• Sum-dist Savvides et al.
• DV-Hop Niculescu et al., Savarese et al.
• Euclidean Niculescu et al.
• anchors flood network
• with their known position

11
Phase 1Sum-dist

• Anchors
• flood network with known position
• Nodes
• add hop distances
• require range measurement

B
C
A
12
Phase 1 DV-hop

• Anchors
• flood network with known position
• flood network with avg hop distance
• Nodes
• count hops to anchors
• multiply with avg hop distance

3 hops
B
avg hop 4
C
A
13
Phase 1Euclidean

• Anchors
• flood network with known position
• Nodes
• determine distance by
• range measurement
• geometric calculation
• require range measurement

B
C
A
14
Phase 1Euclidean (2)

• Wanted
• Distance A-G

D
G
E
Using AEGF A-G 8
...or 3
F
Using AEGD A-G 8
...or 0.5
A
15
Phase 1Euclidean (3)

• Needs high connectivity
• Error prone (selecting wrong distance)
• Perfect accuracy possible

B
D
G
E
C
F
A
16
Phase 1Comparison

• Range
• measurement
• Very accurate Euclidean
• Reasonable Sum-dist
• None / very bad DV-hop

17
Phase 2Determining position

• Two algorithms
• Lateration
• very common
• local triangulation
• solve Axb
• Min-max Savvides et al.

B
C
A
18
Phase 2Min-max

• Using range to anchors to determine a bounding
  box
• Use center of box as
• position estimate

B
C
A
19
Comparison distance error
20
Comparison distance bias
21
A problem with Min-max

• Very sensitive to anchor placement

22
Phase 1 2 combined
23
Phase 1 2 combined
Euclidean very sensitive to both range variance
and connectivity
24
Error and coverage
25
Matrix
26
Phases 1 and 2

• Position error usually 30 of the radio range or
  higher
• Range measurements between nodes only used to
  determine anchor distance
• Can we do better?

27
Phase 3 Iterative refinement

• obtain initial position (phases 1 and 2)
• broadcast my position
• iteratively refine position using
• ranges to direct neighbours
• their initial positions

28
Phase 3Iterative refinement

• Initial estimate

• Receive neighbour positions

• Local lateration

A
29
Phase 3 Position error
30
Phase 3 Coverage
31
Conclusion

• No one size fits all
• Refinement needs better coverage to be useful
• Lots of room for improvement in all phases
• Details in Tech Report PDS-2002-03
• (http//pds.twi.tudelft.nl/reports/2002/PDS-2002-0
  03)

32
What is wrong?

• Bad topology
• identical hop-TERRAIN positions
• twins
• Error propagation
• rapid infection of complete network
• hop triangulate hop triangulate

33
Confidence weights

• Weight input for triangulation (wAx wb)
• Initialization
• anchors 1.0
• twins, identical hops 0
• others 0.1
• Triangulation
• large residue 0
• small residue avg of input confidences