Murat Demirbas SUNY Buffalo Localization Murat Demirbas SUNY Buffalo

Localization Localization of a node refers to the problem of identifying its spatial co-ordinates in some co-ordinate system How do nodes discover their geographic positions in 2D or 3D space? Model: static wireless sensor networks

Location Matters Sensor Net Applications Geographic routing protocols Environment monitoring Event tracking Smart environment Geographic routing protocols GeoCast, GPSR, LAR, GAF, GEAR

Outline Range-based localization Range-free localization GPS Cricket APS RADAR Range-free localization Centroid DV-HOP APIT

Range-based localization Distances between nodes to nodes/anchors measured wirelessly TOA (Time of Arrival ) GPS TDOA (Time Difference of Arrival) Cricket AOA (Angle of Arrive ) APS RSSI (Receive Signal Strength Indicator) RADAR

Outline Range-based localization Range-free localization GPS Cricket APS RADAR Range-free localization Centroid DV-HOP APIT

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

Outline Range-based localization Range-free localization GPS Cricket APS RADAR Range-free localization Centroid DV-HOP APIT

Sound based ToF approach Because the speed of sound is much slower (approximately 331.4m/s) than radio, it is easier to be applied in sensor network. Some hurdles are: Line of sight path must exist between sender and receiver. Mono-direction. Short range.

Cricket Intended for indoors use where GPS don't work It can provide distance ranging and positioning precision of between 1 and 3 cm Active beacons and passive listeners

Outline Range-based localization Range-free localization GPS Cricket APS RADAR Range-free localization Centroid DV-HOP APIT

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

Outline Range-based localization Range-free localization GPS Cricket APS RADAR Range-free localization Centroid DV-HOP APIT

RADAR Bahl: MS research Offline calibration: Tabulate <location, RSSI> to construct radio map Real-time location & tracking: Extract RSSI from base station beacons Find table entry best matching the measurement

Problems with RSSI Sensors have wireless transceivers anyway, so why not just use the RSSI to estimate distances? Problem: Irregular signal propagation characteristics (fading, interference, multi-path etc.) Graph from Bahl, Padmadabhan: RADAR: An In-Building RF-Based User Location and Tracking System

Outline Range-based localization Range-free localization GPS Cricket APS RADAR Range-free localization Centroid DV-HOP APIT

Range-free localization Range-based localization: Required Expensive hardware Limited working range ( Dense anchor requirement) Range-free localization: Simple hardware Less accuracy

Outline Range-based localization Range-free localization GPS Cricket APS RADAR Range-free localization Centroid DV-HOP APIT

Range-free: Centroid Idea: Do not use any ranging at all, simply deploy enough beacons Anchors periodically broadcast their location Localization: Listen for beacons Average locations of all anchors in range Result is location estimate Good anchor placement is crucial! Anchors Nirupama Bulusu, John Heidemann and Deborah Estrin. Density Adaptive Beacon Placement, Proceedings of the 21st IEEE ICDCS, 2001

Outline Range-based localization Range-free localization GPS Cricket APS RADAR Range-free localization Centroid DV-HOP APIT

Hop-Count Techniques r DV-HOP [Niculescu & Nath, 2003] 4 DV-HOP [Niculescu & Nath, 2003] Amorphous [Nagpal et. al, 2003] 1 2 7 3 1 4 3 5 2 4 8 3 3 6 4 4 5 Works well with a few, well-located seeds and regular, static node distribution. Works poorly if nodes move or are unevenly distributed.

Outline Range-based localization Range-free localization GPS Cricket APS RADAR Range-free localization Centroid DV-HOP APIT

Overview of APIT 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).

Algorithm Anchor Beaconing Individual APIT Test Triangle Aggregation Center of Gravity Estimation 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);

Perfect PIT 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

Departure test Recognize directions of departure via neighbor exchange RSSI Problems with the assumption!!!

APIT approximation Test only directions towards neighbors Error in individual test exists, may be masked by APIT aggregation.

APIT: Approximate PIT Distances unknown for most adjacent points Use neighbor nodes only How to compare distances to beacons? Stronger RSS Distributed algorithm: Beacon nodes broadcast their location Each node builds a table of beacons it receives and the corresponding RSS Each node broadcasts this table once (1 hop only) 3mv 56 23 C 2mv 31 45 B 1mv 20 A MySS (X,Y) 7mv 1mv 3mv 6mv 2mv SSn .... SS1 Node M

Error Case PIT = IN while APIT = OUT PIT = OUT while APIT = IN 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

APIT Aggregation 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

Evaluation DOI =0 DOI = 0.05 DOI = 0.2 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 =0 DOI = 0.05 DOI = 0.2

Simulation Setup Setup Metrics 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

Error Reduction by Increasing #Anchors AH=10~28,ND = 8, ANR = 10, DOI = 0 Placement = Uniform Placement = Random

Error Reduction by Increasing Node Density AH=16, Uniform, AP = 0.6%~2%, ANR = 10 DOI=0.1 DOI=0.2

Error Under Varying DOI ND = 8, AH=16, AP = 2%, ANR = 10 Placement = Uniform Placement = Random

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

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