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Wireless Sensor Networks Localization

Wireless Sensor Networks Localization. Professor Jack Stankovic Department of Computer Science University of Virginia June 2009. Localization. One of the most fundamental problems One of the most difficult One of the most researched Function of many parameters and requirements

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Wireless Sensor Networks Localization

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  1. Wireless Sensor NetworksLocalization Professor Jack Stankovic Department of Computer Science University of Virginia June 2009

  2. Localization • One of the most fundamental problems • One of the most difficult • One of the most researched • Function of many parameters and requirements • Easy to solve under certain conditions

  3. Localization • Node Localization • Target Localization

  4. Target Localization 100m 10m

  5. Node Localization • A process by which a node determines where it is geographically • Ad hoc self-organizing wireless sensor networks • What if you carefully place every node?

  6. Localization via 3 Distance Measurements Ideal D2 D1 X X X = anchors or landmarks or beacons X D3 Non-collinear

  7. Localization via N Distance Measurements Realistic D2 D1 X X Use more than 3 anchors X = anchors or landmarks or beacons X D3

  8. Localization Taxonomy • Range-Based Localization – use absolute point to point distance/angle estimates • TDOA (Time Difference of Arrival): • MIT Cricket & UCLA AHLOS Radio (Speed of light) X Y Sound

  9. Time of Arrival - GPS • Use 3 satellites to obtain x, y position • 3-Dimensions – need 4 satellites • Accuracy within 2-10m most of the time • May not be accurate enough • Cost per node • Not indoors, under trees

  10. Localization - Spotlight • Sensor nodes randomly deployed from UAV/helicopter • Sensor nodes self-organize into a network, execute a time-sync protocol • The UAV (Spotlight device) flies over the network and generates (invisible) light events • Sensor nodes detect the events and report the timestamps • The Spotlight device computes the location of the sensor nodes • No extra hardware needed on motes!

  11. Low Cost – Highly Accurate Spotlight (X1, Y1, R1) at T1 (X2, Y2, R2) at T2 Line of Sight (X2, Y2, R2) (X1, Y1, R1)

  12. Performance Point Scan EDF μSpotlight

  13. Localization Taxonomy • Range Free • No need to determine distances directly, instead use hop count • Use average distances between hops • Then compute location using geometry

  14. The Problem Accurate Node Location in Complex CPS Environments

  15. Hierarchical Framework A node that has a location and receives a HELLO message, “Jumps” and executes as an Anchor. Weighted average of R-LP1 and R-LP2 Only execute if needed A node that reaches this point and does not have a location, broadcasts a HELLO message All nodes have a location at this point.

  16. Research Questions • Execute serially/parallel • When more than 1 executes in parallel, how to combine results • Execute subsequent protocols only for nodes not previously localized • What if under attack • What if mobility

  17. Implementation • Adopted/Modified TinyOS implementations for: • Spotlight • Centroid • DV-Hop • Walking GPS • All schemes statically linked Relatively large. Mica2 has 4KB RAM

  18. Evaluation • TOSSIM • 400 nodes in 300x300ft2 • 200x200ft2 obstructed area • 50ft radio range • 10% nodes have GPS • 15% nodes in open area can’t be localized by line of sight

  19. Evaluation

  20. Evaluation All nodes are localized

  21. Evaluation Reduced(wrt DV-Hop) overhead due to confined area of execution

  22. Localization - Issues • F(Many Parameters) • Cost (extra HW) • Beacons/Anchors (of different types - power levels) • Degree of accuracy needed • Average error or worst case error • Indoors/outdoors • Line of sight or not • 2D-3D • Efficiency (Energy budget) (Number of messages) • How long it takes to localize • Clock synchronization accuracy • Hostile/Friendly area • Error Assumptions • Security attacks

  23. Localization Summary • Critical issue for WSN/CPS • Accurate, Robust and Secure • Impacts MAC, Routing, Application Semantics • If fixed infrastructure – may be easy • What if mobile system • What if indoors

  24. Robustness • Use sets of protocols for other services • Security • MAC • Routing • Time synchronization • Topology Management • Etc.

  25. Class Summary • Think Open OpenOpen • Connection to the physical world will be so pervasive that systems will be open even if you think they are not • Think adaptive and robustness • Control theory Uncertainty

  26. Summary - Control Theory Issues • Lost messages • Delayed messages • Changing models • High uncertainty • Decentralized control • Competing loops • Systems of systems

  27. Summary – Physical Properties • Communication asymmetries • Consumption of energy • Location • Obstacles • Sensing (re)-calibration • Sensing algorithms • Clock drifts • Human actions • Etc.

  28. CPS - Enabler for Dramatic Innovation • New global-scale, personal medical delivery systems • New paradigms for scientific discovery • Smart (Micro) Agriculture • Towards the end of terrorism • Wireless Airplanes • Next Generation Internet

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