Range-Based and Range-Free Localization Schemes for Sensor Networks

Localization

Critical service A sensor reading consists of <time, location,

measurement> E.g., target tracking, disaster recovery, fire

detection, patient location in a smart hospital, …

Needed for geographic routing Too expensive for an individual sensor to

have a GPS (Global Positioning System) Reference nodes (called anchor or beacon

nodes) + sensor nodes

Range-based localization schemes

TOA (Time of Arrival) Get range info via signal propagation delay E.g., GPS Expensive, power consuming, inaccurate

TDOA (Time Difference of Arrival) Transmit both radio and ultrasonic signals at the

same time to observe the arrival time difference Extra hardware, i.e., ultrasonic channel, is required Not only radio but also sound signals have multipath

effects affected by humidity, temperature, …

Received signal strength (RSS) Distance estimation based on RSS Hard due to radio signal vagaries

AoA (Angle of Arrival) A node estimates the relative angles

between neighbors Requires directional antennae

Range-free localization

Centroid algorithm Anchors beacon their positions to

neighbors (single hop broadcast) A sensor node computes the centroid

using all received beacon messages

DV-HOP Anchor locations are flooded through

the network Keep the running hop count Estimate average one hop distance

Amorphous Positioning Similar to DV-HOP Use offline one hop distance

estimation

Range-Free Localization Schmes for Large Scale Sensor NEtworks- APIT (Approximate Point In Triangulation)

Mobicom 2003

PIT (Point In Triangulation)

A node chooses three anchors from all audible anchors

Test whether it’s inside the triangle Repeat for all possible combinations

of audible three anchors Compute the COG of the

intersection of all the triangles

Perfect PIT test

For three given anchors, A, B, C, determine whether a point M with an unknown position is inside the triangle ABC or not

Proposition I: If M is inside the triangle, when M is shifted, the new position is nearer to (or farther from) at least one anchor A, B, or C

Proposition II: If M is outside the triangle, when M is shifted, there must exist a direction in which the position of M is farther from or closer to all three anchors A, B and C

Problems with Perfect PIT test

How can a sensor node perform the PIT test w/o actually moving?

How to do exhaustive tests considering all possible directions of departure?

APIT (Approximate PIT test)

In a certain propagation direction, the received signal strength is assumed to monotonically decrease in an environment w/o obstacles

Departure test

Signal strength at different distances (to justify the departure test)

APIT test

Basic idea: Use neighbor info, exchanged via beaconing, to emulate the node movement in the perfect PIT test

If no neighbor of M is farther from/closer to all three anchors A, B & C simultaneously, M assumes that it is inside the triangle.

Errors in the APIT test

InToOut Error OutToIn Error

APIT error measurements

14% error when a node has 6 one-hop neighbors in average – Small?

APIT aggregation: Mask errors in individual APIT tests

Aggregate individual APIT test results through a grid SCAN

Length of a grid side is 0.1R For each inside decision, the

values of the grid regions over which the triangle resides are incremented

Decrement for each outside decision

Find the area with max values Take the center of gravity for

position estimation

APIT algorithm

1. Each node maintains a table of anchor ID, location & signal strength

2. Nodes exchange anchor tables with the neighbors

3. Run the PIT test for each column of the table

4. Repeat step 3 for varying combinations of three anchors

5. Use the APIT aggregation alg. to determine the area w/ max overlap

6. Final location estimation = COG of that area

Performance evaluation

Radio model Upper & lower bounds on signal strength Beyond the UB, all nodes are out of communication

range Within the LB, every node is within the comm. range Between LB & UB, there is (1) symmetric

communication, (2) unidirectional comm., or (3) no comm.

Degree of irregularity (DOI)

Simulation parameters

Node density (ND) Anchors heard (AH) Anchor to node range ratio (ANR)

Avrg distance an anchor beacon travels/avrg distance a regular node signal travels

Anchor percentage (AP) DOI GPS error Placement: uniform or random

Localization error for varying AH

• APIT works better as AH increases. • Large errors when AH < 8

• It’s relatively less sensitive to random deployment.

Localization error for varying ND

• Amorphous has large errors when ND < 10• APIT & DV-Hop show good perf if ND >= 6• Amorphous is more sensitive to larger DOI

Localization error for varying ANR

• Error increases as ANR increases due to error accumulations• APIT has large errors when ANR < 3 due to large InToOut error

Localization error for varying DOI

Irregular hop count distribution in Amorphous & DV-Hop

Communication overhead for varied AH

Amorphous & DV-Hop rely on the flooding of anchor beacons

Communication overhead for varied ND

Summary

Localization error impact on geographic forwarding

Summary

APIT is resilient to irregular radio patterns and random deployment

Relatively low overhead compared to DV-Hop & Amorphous localization (but more overhead than Centroid)

Localization has been well studied but still needs more work

Location verification – SerLoc (Secure Range-independent localization)

Workshop on Wireless Security (WiSe) 2004

What is location verification?

Different assumptions from general localization What if some malicious nodes lie about their

lcoation? Sample attack scenario

Cliam to be very close to the sink Attract many packets Drop some or all of them Very easy DoS attack especially for geographic

routing protocols

How SerLoc works Node i claims its location is (x, y) Node i needs to send (x, y) a location verification

request msg to a nearby verifier A verifier can be a normal sensor node

The verifier sends a random nonce to node i and start the clock

Node i has to immediately return the challenge through both radio and ultrasonic channels

The verifier measures the time for node i returning the challenge and take the difference between the radio & ultrasonic signal propagation. Based on this observation, verify the claimed location

Weakness of SerLoc Requires extra hardware, i.e., ultrasonic channel Innocent victims may respond late due to backlog Not location verification but range verification

Verifier

M’s RealLocation

M’s claimedLocation

sink

Oops... Verifier cannot tellthe difference! Big trouble...

Possible Research Issues

Most localization work is mathematical and evaluated via (high level) simulations More realistic work is needed

Indoor localization is harder Look at CodeBlue project at Harvard

Location verification Can’t trust sensors

Secure localization Can’t trust anchors

Questions?