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
Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity)
16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1)
Range variance 0 Eucl Lat Eucl Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.025 Sum-d Lat Sum-d MM Sum-d MM Sum-d MM DV-hop MM
Range variance 0.05 Sum-d Lat Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.1 Sum-d MM Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.25 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Range variance 0.5 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity)
16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1)
Range variance 0 Eucl Lat Eucl Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.025 Sum-d Lat Sum-d MM Sum-d MM Sum-d MM DV-hop MM
Range variance 0.05 Sum-d Lat Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.1 Sum-d MM Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.25 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Range variance 0.5 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity)
16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1)
Range variance 0 Eucl Lat Eucl Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.025 Sum-d Lat Sum-d MM Sum-d MM Sum-d MM DV-hop MM
Range variance 0.05 Sum-d Lat Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.1 Sum-d MM Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.25 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Range variance 0.5 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity)
16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1)
Range variance 0 Eucl Lat Eucl Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.025 Sum-d Lat Sum-d MM Sum-d MM Sum-d MM DV-hop MM
Range variance 0.05 Sum-d Lat Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.1 Sum-d MM Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.25 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Range variance 0.5 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity)
16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1)
Range variance 0 Eucl Lat Eucl Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.025 Sum-d Lat Sum-d MM Sum-d MM Sum-d MM DV-hop MM
Range variance 0.05 Sum-d Lat Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.1 Sum-d MM Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.25 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Range variance 0.5 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity) Radio range (connectivity)
16 (15.3) 14 (12.0) 12 (8.8) 10 (6.4) 8 (4.1)
Range variance 0 Eucl Lat Eucl Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.025 Sum-d Lat Sum-d MM Sum-d MM Sum-d MM DV-hop MM
Range variance 0.05 Sum-d Lat Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.1 Sum-d MM Sum-d Lat Sum-d MM Sum-d MM DV-hop MM
Range variance 0.25 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
Range variance 0.5 DV-hop Lat DV-hop MM DV-hop MM DV-hop MM DV-hop MM
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

1. Initial estimate

1. Receive neighbour positions

1. 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