1. Dynamic Location Discovery in Ad-Hoc Networks
Session 7
Dynamic Location Discovery in Ad-Hoc Networks
Andreas Savvides, Athanassios Boulis and Mani B. Srivastava
Networked and Embedded Systems Lab(NESL)
Electrical Engineering Department

2. What is location discovery?
Given a network of sensor nodes where a few nodes know their location how do we calculate the location of the nodes?
Known Location
Unknown Location

3. Why? Support Location Aware Applications Navigation Track Objects
Sensor Networks
– report event origins
evaluate network coverage
assist with routing

4. Basic Concepts Distance measuring methods Signal Strength
Uses RSSI readings and wireless propagation model
Time based methods
ToA, TDoA
Used with radio, IR, acoustic, ultrasound
Angle of Arrival (AoA)
Measured with directive antennas or arrays

5. Basic Concepts II Hyperbolic Trilateration Triangulation
Multi-lateration
Considers all available beacons A B C a b c
Sines Rule
Cosines Rule

6. Existing Technologies
INFRASTRUCTURE:
Automatic Vehicle Location system (AVL)
Base stations keep track of police cars ( uses time based and signal strength methods)
GPS, Loran
911 Emergency Location System (ToA, TDoA)
BAT System(AT&T Cambridge Labs), Cricket (MIT)
RADAR – indoor, uses signal strength maps
RFID tags – IR proximity
AD-HOC:
Picoradio (UC Berkeley) – indoor, based on signal strength maps
GPS-less outdoor localization (Bulusu et. al) – proximity based

7. Location Discovery in Ad-Hoc Networks
No infrastructure support
GPS may not always work
Costly, Power Hungry, does not work everywhere
Our Approach
Use RSSI for measuring node separation
But how should the beacons be placed?
Multiple tradeoffs still an open problem

8. Long Range Beaconing Long Range Beaconing Disadvantages: Advantages:
Multi-hop Coverage
Works well even in low densities
Disadvantages:
Low fault tolerance
Requires Dedicated Beacons
Some infrastructure is required B

9. Our Approach Single hop beaconing Iterative multilateration
Dynamic estimate the wireless channel parameters
Can be done in conjunction with routing
Advantages:
Data packets are also act as beacon signals
Distributed – relies on neighborhood information
Fault tolerant
Location discovery is almost free!!

10. Iterative Multilateration
Start with a small number of beacons
Number of beacons increases as more nodes estimate their positions
Initial Beacon
Step 1:
Step 2:
Step 3:
becomes beacon

11. Challenges Multi-path and shadowing effects
Difficult to work in indoor environments
Beacon placement problem
Bad geometry can affect the quality of the solution
Variable wireless channel characteristics
signal propagation differs from place to place
(n= )

12. Solution
Setup as an over-constrained optimization problem and solve for
Wireless propagation model parameters
Node Locations

13. Problem Setup
Wireless Channel Model
Error Distance Representation

14. Optimization Problem This is a non-linear optimization problem
Hard to compute in one step
We solve the problem in 2 phases over multiple iterations
Keep in mind beacon errors!

15. Two-Phase Approach
Obtain a propagation model estimate based on initial set of beacons
Certainly of node estimates used as weights for the channel estimate
Follow a rip-up and retry method until a predefined set of constraints is met
Channel
Estimator
Location
Convergence
Criteria?
Reset
Locations NO
YES

16. Simulations
100 Nodes
100 x 100 grid
Range = 10
Beacons = 10

17. Without Beacon Error

18. With Beacon Error = 10 %

19. Effect of Beacon Error

20. Implementation & Measurements
Implemented Location Discovery Algorithm as part of DSDV routing protocol in SensorSim
Obtained RSSI measurements using RSC nodes in outdoor environments
Analyzing the results

21. Conclusions and Future Work
Radio signal strength methods can provide a low cost scalable location discovery
BUT does not work well indoors
experimenting with ultrasound
Exploring Collaborative Multilateration
Beacon placement problem needs to be explored