1. Range-Free Localization Schemes in Large Scale Sensor Networks
Tian He
Chengdu Huang
Brian. M. Blum
John A. Stankovic
Tarek F. Abdelzaher
Department of Computer Science, University of Virginia
September 16,2003
MobiCom' University of Virginia

2. APIT @ MobiCom'03 University of Virginia
Outline
Problem Statement
State of the Art
Motivation & Contribution
A.P.I.T. Algorithm Details
Evaluation
Conclusion
September 16,2003
MobiCom' University of Virginia

3. APIT @ MobiCom'03 University of Virginia
Problem Statement
Localization Problem:
How nodes discover their geographic positions in 2D or 3D space?
Target Systems:
Static large scale sensor networks or one with a low mobility
Goal:
An affordable solution suitable for large-scale deployment with a precision sufficient for many sensor applications.
September 16,2003
MobiCom' University of Virginia

4. APIT @ MobiCom'03 University of Virginia
State of the Art (1)
Range-based Fine-grained localizations
TOA (Time of Arrival ): GPS
TDOA (Time Difference of Arrival): MIT Cricket & UCLA AHLos
AOA (Angle of Arrive ): Aviation System and Rutgers APS
RSSI (Receive Signal Strength Indicator) : Microsoft RADAR and UW SpotOn
Required Expensive hardware
Limited working range ( Dense anchor requirement)
Log-normal model doesn’t hold well in practice [D. Ganesan]
Multilateration based on the distance estimation between nodes
September 16,2003
MobiCom' University of Virginia

5. APIT @ MobiCom'03 University of Virginia
State of the Art (2)
Range-Free Coarse-grained localization
USC/ISI Centroid localization
Rutgers DV-Hop Localization
MIT Amorphous Localization
AT&T Active Badge
Simple hardware/ Less accuracy
September 16,2003
MobiCom' University of Virginia

6. Under different localization Error ( % Radio Range)
Motivation
High precision in sensor network localization is overkill for a lot of applications.
Large scale deployment require cost-effective solutions.
Routing Delivery Ratio Entity Tracking Time
Under different localization Error ( % Radio Range)
September 16,2003
MobiCom' University of Virginia

7. APIT @ MobiCom'03 University of Virginia
Contributions
A novel range-free algorithm with enhanced performance under irregular radio patterns and random node placement with a much smaller overhead than flooding based solutions
The first to provide a realistic and detailed quantitative comparison of existing range-free algorithms.
First investigation into the effect of localization accuracy on application performance
September 16,2003
MobiCom' University of Virginia

8. Overview of APIT Algorithm
APIT employs a novel area-based approach. Anchors divide terrain into triangular regions
A node’s presence inside or outside of these triangular regions allows a node to narrow the area in which it can potentially reside.
The method to do so is called Approximate Point In Triangle Test (APIT). IN IN
Out
September 16,2003
MobiCom' University of Virginia

9. APIT @ MobiCom'03 University of Virginia
APIT Main Algorithm
For each node
Anchor Beaconing
Individual APIT Test
Triangle Aggregation
Center of Gravity Estim.
Pseudo Code:
Receive beacons (Xi,Yi) from N anchors
N anchors form triangles.
For ( each triangle Ti Є ){
InsideSet  Point-In-Triangle-Test (Ti) }
Position = COG ( ∩Ti  InsideSet);
September 16,2003
MobiCom' University of Virginia

10. Point-In-Triangle-Test
For three anchors with known positions: A(ax,ay), B(bx,by), C(cx,cy), determine whether a point M with an unknown position is inside triangle ∆ABC or not.
A(ax,ay) M
B(bx,by)
C(cx,cy),
September 16,2003
MobiCom' University of Virginia

11. APIT @ MobiCom'03 University of Virginia
Perfect P.I.T Theory
If there exists a direction in which M is departure from points A, B, and C simultaneously, then M is outside of ∆ABC. Otherwise, M is inside ∆ABC.
Require approximation for practical use
Nodes can’t move, how to recognize direction of departure
Exhaustive test on all directions is impractical
September 16,2003
MobiCom' University of Virginia

12. APIT @ MobiCom'03 University of Virginia
Departure Test
Recognize directions of departure via neighbor exchange
Receiving Power Comparison ( the solution we adopt)
Smoothed Hop Distance Comparison ( Nagpal 1999 MIT)
Experimental Result from Berkeley Experiment Result from UVA
September 16,2003
MobiCom' University of Virginia

13. APIT @ MobiCom'03 University of Virginia
A.P.I.T. Test
Approximation: Test only directions towards neighbors
Error in individual test exists , however is relatively small and can be masked by APIT aggregation.
APIT(A,B,C,M) = IN APIT(A,B,C,M) = OUT
September 16,2003
MobiCom' University of Virginia

14. APIT @ MobiCom'03 University of Virginia
APIT Aggregation
Aggregation provides a good accuracy, even results by individual tests are coarse and error prone.
High Possibility area
Grid-Based Aggregation
With a density 10 nodes/circle, Average 92% A.P.I.T Test is correct
Average 8% A.P.I.T Test is wrong
Low possibility area
Localization Simulation example
September 16,2003
MobiCom' University of Virginia

15. APIT @ MobiCom'03 University of Virginia
Evaluation (1)
Comparison with state-of-the art solutions
USC/ISI Centroid localization by N.Bulusu and J. Heidemann 2000
Rutgers DV-Hop Localization by D.Niculescu and B. Nath 2003
MIT Amorphous Localization by R. Nagpal 2003
Centroid DV-Hop (online)/ Amorphous (offline)
September 16,2003
MobiCom' University of Virginia

16. APIT @ MobiCom'03 University of Virginia
Evaluation (2)
Radio Model: Continuous Radio Variation Model.
Degree of Irregularity (DOI ) is defined as maximum radio range variation per unit degree change in the direction of radio propagation α
DOI = DOI = DOI = 0.2
September 16,2003
MobiCom' University of Virginia

17. APIT @ MobiCom'03 University of Virginia
Simulation Setup
Setup
1000 by 1000m area
2000 ~ 4000 nodes ( random or uniform placement )
10 to 30 anchors ( random or uniform placement )
Node density: 6 ~ 20 node/ radio range
Anchor percentage 0.5~2%
90% confidence intervals are within in 5~10% of the mean
Metrics
Localization Estimation Error ( normalized to units of radio range)
Communication Overhead in terms of #message
September 16,2003
MobiCom' University of Virginia

18. Error Reduction by Increasing #Anchors
AH=10~28,ND = 8, ANR = 10, DOI = 0
Placement = Uniform
Placement = Random
September 16,2003
MobiCom' University of Virginia

19. Error Reduction by Increasing Node Density
AH=16, Uniform, AP = 0.6%~2%, ANR = 10
DOI=0.1
DOI=0.2
September 16,2003
MobiCom' University of Virginia

20. Error Under Varying DOI
ND = 8, AH=16, AP = 2%, ANR = 10
Placement = Uniform
Placement = Random
September 16,2003
MobiCom' University of Virginia

21. Communication Overhead
Centroid and APIT
Long beacons
DV-Hop and Amorphous
Short beacons
Assume: 1 long beacon = Range2  short beacons = 100 short beacons
APIT > Centroid
Neighborhood information exchange
DV-Hop > Amorphous
Online HopSize estimation
ANR=10, AH = 16, DOI = 0.1, Uniform
September 16,2003
MobiCom' University of Virginia

22. APIT @ MobiCom'03 University of Virginia
Performance Summary
Centroid
DV-Hop
Amorphous
APIT
Accuracy
Fair
Good
Node Density
>0
>8
>6
Anchor
>10
ANR
>3
DOI
GPSError
Overhead
Smallest
Largest
Large
Small
September 16,2003
MobiCom' University of Virginia

23. APIT @ MobiCom'03 University of Virginia
Hermes UVA
NEST Demo
EnviroTrack
Real-Time Routing
QoS Scheduling
Data Aggregation
Lazy Binding MAC
Sensing Coverage
APIT Localization
Mote Test Bed
September 16,2003
MobiCom' University of Virginia

24. APIT @ MobiCom'03 University of Virginia
Conclusions
Range-free schemes are cost-effective solutions for large scale sensor networks.
Through a robust aggregation, APIT performs best with irregular radio patterns and random node placements
APIT performs well with a low communication overhead( e.g instead of 25,000 msgs)
September 16,2003
MobiCom' University of Virginia

25. APIT @ MobiCom'03 University of Virginia
Questions?
Thanks
September 16,2003
MobiCom' University of Virginia

26. APIT @ MobiCom'03 University of Virginia
Error Case
Since the number of neighbors is limited, an exhaustive test on every direction is impossible.
InToOut Error can happen when M is near the edge of the triangle
OutToIn Error can happen with irregular placement of neighbors
PIT = IN while APIT = OUT PIT = OUT while APIT = IN
September 16,2003
MobiCom' University of Virginia

27. Empirical Study on APIT Approximation
Percentage of error due to APIT approximation is relatively small (e.g. 14% in the worst case, 8% when density is 10)
More important, Errors can be masked by APIT aggregation.
APIT Error under Varying Node Densities
September 16,2003
MobiCom' University of Virginia