Paper Presented By: Sean A. Williams Mobile Computing

1. Ecolocation: A Sequence Based Technique for RFLocalization in Wireless Sensor NetworksAuthors: Kiran Yedavalli, Bhaskar Krishnamachari, Sharmila Ravula, Bhaskar Srinivasan Paper Presented By: Sean A. Williams Mobile Computing

2. Overview • Background on Localization • Introduction to Ecolocation • Novelty and Contribution • Paper Details • Results • Conclusions

3. Background • Localization is process of determining an entity’s spatial coordinates. • Advantages of localization for WSNs? • Locating disasters and fires • Locating enemies on battlefields • Other services for rescue and relief • Range-based vs. Range-free • Estimating distance btw unknown & reference to determine location • Estimating distance of unknown node w/o reference to determine location

4. Background • Some Localization Techniques • Proximity • Closest reference node = location of unknown node • Centroid • Center of all reference nodes in range • Approximate point in Triangle • Creates triangle of each 3 anchor combination, location is the intersection of the triangles • Maximum Likelihood Estimation • Statistical estimation technique APIT

5. Introduction • Error COntrolling LOCAlizaTION • AKA: ECOLOCATION • Motivation • To provide a localization technique • Outperforms various other localization methods • Robust (fluctuation of Received Signal Strength –RSS)

6. Introduction • Novelty of Ecolocation • Distance-based ordering of reference nodes creates a unique fingerprint in a region

7. Evaluation Scenarios • Ideal vs. Real World Scenarios • Ideal: • Without multi-path fading and shadowing • Received Signal Strength (RSS) represents distance • Low RSS = Farther away • Real: • With multi-path fading and shadowing • Low RSS ~ Farther away

8. Ecolocation (Ideal) • Location based on unknown nodes constraints and grid-point location constraints • Unknown Node constraints determined by: • (RSS) of reference nodes and rank sequentially. • Based on the number of reference nodes and there RSS from the unknown node

9. Ecolocation (Ideal) • Location Grid points constraints • based on the Euclidean Distance to the reference nodes and not the RSS • Overall location of unknown node is: • Compare unknown constraints with all location grid point constraints • Grid point that has most matches is LE Given Points: P=(p1…pn) & Q=(q1…qn)

10. Ecolocation (Real) • LE is effected by shadowing and fading • Ecolocation is robust to multi-path effects • Evident in display of various erroneous constraints on an unknown node

11. Algorithm • Generate constraint matrix A • Based on Euclidean Distance btw grid points and reference nodes • Generate constraint matrix B • Based on RSS btw unknown node & reference node • If A’s element matches B’s -> increment maxConstraint count • Find all grid points where maximum number of constraints are matched • LE = centroid of those matching gridpoints

12. No Errors

13. 13.9% Erroneous Constraints

14. 12 11 10 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 22.2 % Erroneous Constraints Location estimate for 124739586 A6 A3 A9 Y-AXIS (length units) A8 A7 A2 P E A5 A1 A4 X-AXIS (length units)

15. 47.2% Erroneous Constraints

16. Evaluation • Simulation model equation • Simulation parameters and characteristics • 100 Random Trials • 10 seeds, 48bit RNG

17. SIMULATION RESULTS

18. Location Error

19. Location Precision • Standard Deviation in Location Error

20. EXPERIMENTAL RESULTS

21. Real World Experiments • Parking Lot • 11 reference MICA 2 Motes within 1 hop • No NLOS • Motes record RSS of each other that broadcast • Location Estimated and compared to actual • Office Building • 12 reference MICA 2 Motes within 1 hop • NLOS • Included power attenuation based on walls

22. True vs. Ecolocation

23. Parking Lot Location Error

24. True vs. Ecolocation

25. Indoor Location Error

26. Summary • Localization Techniques are more accurate in: • more open outdoor environments • NLOS • Possible to create a hybrid of localization techniques. • Taking advantage of different methods based on RF Techniques • TDOA/AOA, TOA/RSS, TDOA/RSS, RSS/Proximity, etc.

27. Critique • Strengths • The idea is logical and novel • Evaluation is thorough (Simulation, Indoor, Outdoor) • Weakness • Some details are left out, making it unclear • How are % calculated? • Why decrement 1 if not a match? Why not do nothing? • Flow of paper • Related work usually in beginning or end

28. Relativity • Course Relativity • We have discussed many location techniques • Both Range-based and Range-free • Range estimations based on RSS information • Project Relativity • We are performing a site survey tool which utilizes the RSS information

29. References • Kiran Yedavalli, et al. “Ecolocation: a sequence based technique for RF localization in wireless sensor networks”. Fourth Internation Symposium on Information Processing Sensor Networks, 2005. Pages 285-292. • Thoedore S. Rappaport, Wireless Communication, Principles & Practice, Prentice hall, 1999. • ceng.usc.edu/~bkrishna/research/talks/Krishnamachari_AROWorkshop05_Localization.ppt