1. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory MAL(Mobile-Assisted Localization) in Wireless Sensor Networks Choi Chang-hee MMC lab. Proceedings of IEEE INFOCOM, March 2005. Nissanka B. Priyantha(MIT)

2. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Index 1.Introduction 2.Rigidity Theory 3.MAL – Distance Measurement 4.MAL – Movement Strategy 5.Performance Evaluation 6.Conclusion 1

3. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory 2 Introduction

4. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Introduction 3 What is the Localization Problem? Determine an assignment of coordinates Node 1 Node 2Node 3 Input Node 1 Node 2Node 3 (0,0) (4,0) (0,3) Output

5. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Introduction 4 Steps of Localization Distance Measurement Localization Using MAL Using MAL & AFL( Another paper ) In this paper,

6. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Introduction Manually ( ex : Ruler, laser, etc… ) Ultrasonic on sensor node 5 Previous Methods – Distance Measurement

7. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Introduction Physical obstacles ( in especially indoors ) Non-omni-directional hardware Few distance information 6 Problem with Previous Methods in Practice Response curves of the sensor SU-D2000-M30N-C1-POS Very many obstacles in my lifeFew data

8. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Introduction Use mobility to estimate location!! – Roving human, robot, etc… 7 Proposed Method Node 2Node 3Node 1 Node 4 Ob sta cle

9. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory 8 Rigidity Theory

10. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Rigidity Theory Suppose C is a collection of mathematical objects, C is rigid if every c Є C is uniquely determined by less information c about than one would expect. Not locally rigid : local graph is not rigid Locally rigid : locally rigid, but local graphs is not rigid Globally rigid : global graph is rigid 9 Definition

11. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Rigidity Theory A graph is globally rigid if it is formed by starting from a clique of four non-coplanar nodes and repeatedly adding a node connected to at least four non-coplanar existing nodes 10 Thorem1 – In 3D InsufficientSufficient

12. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory 11 MAL - Distance Measurement

13. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory MAL - Distance Measurement In simultaneous equations – Necessary Condition : unknowns – equations ≤ 0 – The more we add m n, the more we have (unknowns-equations) 12 Calculating Distance between Two Nodes - Proposition 2 12 n 1 (a 1,b 1,c 1 )Noden 2 (a 2,b 2,c 2 ) 1 m 1 (x 1,y 1,z 1 ) Mobile Node 2 m 2 (x 2,y 2,z 2 ) 3 m 3 (x 3,y 3,z 3 ) Unknowns : 3 X 5 = 15 Equations : 2 X 3 = 6 15 – 6 = 9 ≥ 0 How can we solve this problem!! obstacle

14. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory obstacle MAL - Distance Measurement We need restriction! – Fixed Height ( c 1 = c 2 (known), z 1 = z 2 = z 3 = 0 ) – Parallel Line ( b 1 = b 2 = y 1 = y 2 = y 3 = 0) 13 Calculating Distance between Two Nodes – Proposition 2 12 n 1 (a 1,b 1,c 1 )Noden 2 (a 2,b 2,c 2 ) 1 m 1 (x 1,y 1,z 1 ) Mobile Node 2 m 2 (x 2,y 2,z 2 ) 3 m 3 (x 3,y 3,z 3 ) Unknowns : 3 X 5 = 15 – 10 = 5 Equations : 2 X 3 = 6 5 – 6 = -1 ≤ 0 We can solve this problem!!

15. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory MAL - Distance Measurement We need restriction! – Fixed Height ( c1=c2=c3(known), z1=z2=z3=z4=z5=z6=0 ) 14 Calculating Distance between Three Nodes – Proposition 3 12 n 1 (a 1,b 1,c 1 )Noden 2 (a 2,b 2,c 2 ) 1 m 1 (x 1,y 1,z 1 ) Mobile Node 2 m 2 (x 2,y 2,z 2 ) 3 m 3 (x 3,y 3,z 3 ) Unknowns : 3 X 9 = 27 – 9 = 18 Equations : 3 X 6 = 18 18 – 18 = 0 ≤ 0 We can solve this problem!! 3 n 3 (a 3,b 3,c 3 ) 4 m 4 (x 4,y 4,z 4 ) 5 m 5 (x 5,y 5,z 5 ) 6 m 6 (x 6,y 6,z 6 )

16. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory MAL - Distance Measurement There is no restriction – j nodes, k mobile positions – Unknowns : 3j-5 3D ( 3 X j ), 3 degrees of translational motion, 2 degrees of rotational motion – Equations : k(j-3) – Required mobile positions : k = ┌ (3j-5)/(j-3) ┐ – J = 4 then k = 7 15 Calculating Distance between Four Nodes – Proposition 4 1 3 Node 1 Mobile Node 3 2 4 5 6 7 2 4 Unknowns : 3 X 11-5 = 28 Equations : 4 X 7 = 28 28 – 28 = 0 ≤ 0 We can solve this problem!!

17. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory 16 MAL – Movement Strategy

18. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory MAL – Movement Strategy A) Find 4 stationary nodes that can be measured from mobile B) Move the mobile to at least 7 spots and measure distances C) Compute pair-wise distances between the four stationary nodes D) Localize the resulting tetrahedron according to Theorem 1 17 Initialize

19. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory MAL – Movement Strategy A) Pick a stationary node that has been localized but has not yet been examined by this loop B) Move the mobile around the stationary node, and search not-yet-localized nodes (1~3) C) If not-yet-localized nodes are – One, then measure distance with Proposition 2 – Two, then measure distance with Proposition 3 – Three, then measure distance with Proposition 4 D) Localize it according to Theorem 1(globally rigid) 18 Loop

20. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory 19 Performance Evaluation

21. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Performance Evaluation Localization : AFL(Anchor Free Localization) Simulation environment: Cricket No of nodes : 24 20 Environment Real distance : Manual

22. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Performance Evaluation 21 Graph Graph obtained by MAL Graph after applying AFL

23. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Performance Evaluation 22 Performance – Error CDF CDF of % error between original location and estimated location

24. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Performance Evaluation Estimated Location after applying AFL – AFL : avoid folding problem 23 Performance – Estimated Locations This spots can be localized by AFL

25. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory 24 Conclusion

26. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Conclusion Strong point – Very practical in indoor environment – Very accurate localization conjunction with AFL Weak point – Need for ultrasonic device – Need for human resource 25 Critique

27. 차세대 무선 네트워크 및 보안 2008 Fall CS710 Class in KAIST m ulti m edia c omputing laboratory Q&A 26