Presentation is loading. Please wait.

Presentation is loading. Please wait.

Range-free Localization Schemes for Large Scale Sensor Networks

Similar presentations


Presentation on theme: "Range-free Localization Schemes for Large Scale Sensor Networks"— Presentation transcript:

1 Range-free Localization Schemes for Large Scale Sensor Networks
Tian He Chengdu Huang Brian M. Blum John A. Stankovic Tarek Abdelzaher University of Virginia Charlottesville, VA

2 The first Sensor Networks
Mote say what training means? emphasize that only PREVIOUS solutions had the problem with the training time separate slide on related work with citations ************* RELATED WORK ******************** *********************************************** Research started in the 80s by DARPA Early sensor networks were used in the military Example: Sound Surveillance System (SOSUS)

3 Required in most applications:
Modern applications Physical security Detecting intruders Medical Patients in a hospital Habitat monitoring Wildlife, plants Environmental Tracking forest fires, pollution Smart buildings Air traffic control Surveillance Required in most applications: Location of the sensor

4 Time of arrival (TOA) Example: GPS
Uses a satellite constellation of at least 24 satellites with atomic clocks Satellites broadcast precise time Estimate distance to satellite using signal TOA Trilateration does not work indoors or under dense vegetation high power consumption high cost big antenna does not fit in small (unobtrusive) node B. H. Wellenhoff, H. Lichtenegger and J. Collins, Global Positioning System: Theory and Practice. Fourth Edition, Springer Verlag, 1997

5 Angle of arrival (AOA) Idea: Use antenna array to measure direction of neighbors Special landmarks have compass + GPS, broadcast location and bearing Flood beacons, update bearing along the way Once bearing of three landmarks is known, calculate position "Medusa" mote Dragos Niculescu and Badri Nath. Ad Hoc Positioning System (APS) Using AoA, IEEE InfoCom 2003

6 Basic APIT scheme Anchors are location aware sensors in the sensor network. APIT employs area-based approach to isolate triangular regions between beaconing nodes. Once the area is known the COG calculation is performed for the location.

7 Perfect PIT Test Proposition 1: If M is inside triangle ABC, when M is shifted in any direction, the new position must be nearer to (further from) at least one anchor A, b or C A M C B

8 Continued… Proposition 2: If M is outside triangle ABC, when M is shifted, there must exist a direction in which the position of M is further from or closer to all three anchors A, B and C. A M C B

9 Perfect PIT Test If there exists a direction such that a point adjacent to M is further/ closer to points A, B, and C simultaneously, then M is outside of ABC. Otherwise, M is inside ABC. Perfect PIT test is infeasible in practice.

10 Departure Test. Experiments show that, the receive signal strength is decreasing in an environment without obstacles. Therefore further away a node is from the anchor, weaker the received signal strength. M N A

11 Appropriate PIT Test. Use neighbor information to emulate the movements of the nodes in the perfect PIT test. If no neighbor of M is further from/ closer to all three anchors A, B and C simultaneously, M assumes that it is inside triangle ABC. Otherwise, M assumes it resides outside this triangle.

12 Inside Case Outside Case

13 Error Scenarios for APIT test.
In to out error Out to in error

14 However, from experimental results it is seen that the error percentage is small as the density increases.

15 APIT aggregation Represent the maximum area in which a node will likely reside using a grid SCAN algorithm. For inside decision the grid regions are incremented. For outside decision the grid regions are decremented.

16 Range Free Schemes. Centroid Localization.
Receive beacon from anchor nodes. It is simple and easy to implement.

17 Continued… DV-Hop localization. Amorphous localization.
Maintain a running hop count from beacon nodes. Find the average hop length Use tri-lateration to localize the unknowns. Amorphous localization. Algorithm is similar to DV-Hop algorithm except that different approach is used to estimate the average distance of a single hop.

18 Simulations Settings. Radio Model
The radio model used in the simulations have a upper bound and lower bound. Beyond the upper bound nodes are out of communication range and within the lower bound nodes are guaranteed to be within communication range. If in b/w there could be symmetric / uni-directional / no communication

19 Location error vs AH

20 Location error vs ND

21 Location error vs ANR.

22 Location error vs. DOI

23 Location error vs. GPS

24 Commn overhead vs. AH

25 Commn overhead vs ND

26 Evaluation summary

27 Conclusion Range-free localization schemes are cost effective.
Performs well in irregular radio patterns and random node deployment. APIT performs well even in smaller node-densities.

28 References T. He, C. Huang, B. M. Blum,J. A. Stankovic,and T. F. Abdelzaher. Range-Free Localization Schemes in Large Scale Sensor Networks, MobiCom 2003.


Download ppt "Range-free Localization Schemes for Large Scale Sensor Networks"

Similar presentations


Ads by Google