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Localization in WSN
Presented by: Yara Ali
Supervised by: Dr. Ahmed
Akl
Localization in WSN

1
Agenda










Introduction to WSN
Localization
Usage
GPS .. Why not ?
Localization methods taxonomy
Classifications of Localization Methods
Summary
Future work
References
Localization in WSN

2
Introduction to WSN


A large number of self-sufficient nodes



Nodes have sensing capabilities



Can perform simple computations



Can communicate with each other

Localization in WSN

3
Introduction to WSN (Cont.)


Beacon (Anchor) node:
It’s a node that’s aware of it’s location,
either through GPS or manual preprogramming during deployment.

Localization in WSN

4
Introduction to WSN (Cont.)


In a Wireless sensor nodes thousands of
sensors need to know their position

Many applications need position info:
 in-home
 forest-fire detection
 atmospheric (temperature,
pressure, … )
 military (target detection, …)
 police
Localization in WSN

5
Introduction to WSN (Cont.)

1.
2.

3.

4.

Advantages:
It avoids a lot of wiring
It can accommodate new devices at
any time
It's flexible to go through physical
partitions
It can be accessed through a
centralized monitor
Localization in WSN

6
Introduction to WSN (Cont.)

1.

2.

3.

Disadvantages
It's easy for hackers to hack it as we
cant control propagation of waves
Comparatively low speed of
communication
Gets distracted by various elements
like Blue-tooth
Localization in WSN

7
Localization






Localization is a process to compute the
locations of wireless devices in a network
WSN Composed of a large number of
inexpensive nodes that are densely
deployed in a region of interests to measure
certain phenomenon.
The primary objective is to determine the
location of the target
Localization in WSN

8
Localization (CONT.)

Localization in WSN

9
Localization (CONT.)

Localization in WSN

10
Usage







Coverage
Deployment
Routing
Location service
Target tracking
rescue
Localization in WSN

11
GPS .. Why not ?




We need to determine the physical
coordinates of a group of sensor nodes in
a wireless sensor network (WSN)
Due to application context and massive
scale, use of GPS is unrealistic, therefore,
sensors need to self-organize a coordinate
system
Localization in WSN

12
GPS .. Why not ? (Cont.)
1.

2.

3.

4.

Expensive
GPS satellite signals are weak (when compared to, say,
cellular phone signals), so it doesn't work as well indoors,
underwater, under trees, etc.
The highest accuracy requires line-of-sight from the receiver
to the satellite, this is why GPS doesn't work very well in an
urban environment
The US DoD (dept of defense) can, at any given time, deny
users use of the system (i.e. they degrade/shut down the
satellites)

Localization in WSN

13
Localization methods taxonomy

Localization in WSN

14
1- Target/Source Localization




Most of the source localization methods
are focused on the measured signal
strength.
To obtain the measurements, the node
needs complex calculating process.

Localization in WSN

15
1- Target/Source Localization
(Cont.)
1. The received signal strength of single
target/source localization in WSN during
time interval t:

Localization in WSN

16
1- Target/Source Localization
(Cont.)
2. The received signal strength of multiple
target/source localization in WSN during
time interval t:

Localization in WSN

17
1- Target/Source Localization
(Cont.)


The Above methods require transmission of a
large amount of data from sensors which may
not be feasible under communication
constraints.

3-4. The binary sensors sense signals
( infrared, acoustic, light, etc. ) from their
vicinity, and they only become active by
transmitting a signal if the strength of the
sensed signal is above a certain threshold.
Localization in WSN

18
1- Target/Source Localization
(Cont.)






The binary sensor only makes a binary
decision (detection or non-detection)
regarding the measurement.
Consequently, only its ID needs to be sent to
the fusion center when it detects the target.
Otherwise, it remains silent.
So, the binary sensor is a low-power and
bandwidth-efficient solution for WSN.
Localization in WSN

19
Taxonomy

Localization in WSN

20
2- Node Self-localization




Range-based Localization: uses the
measured distance/angle to estimate the
indoor location using geometric principles.
Range-free Localization: uses the
connectivity or pattern matching method to
estimate the location. Distances are not
measured directly but hop counts are used.
Once hop counts are determined, distances
between nodes are estimated using an
average distance per hop and then geometric
principles are used to compute location.
Localization in WSN

21
2-1 Range based localization

Localization in WSN

22
2-1 Range based localization
(Cont.)
1.





Time of arrival: (TOA)
It’s a method that
tries to estimate
distance between 2
nodes using time
based measures.
Accurate but needs synchronization
Localization in WSN

23
2-1 Range based localization
(Cont.)
2. Time Difference Of Arrival: (TDOA)


It’s a method for
determining the distance
between a mobile station
and a nearby synchronized
base station. (Like AT&T)



No synchronization
needed but costly.
Localization in WSN

24
2-1 Range based localization
(Cont.)
3. Received Signal Strength Indicator:
(RSSI)
 Techniques to translate signal strength
into distance


Low cost but very
sensitive to noise
Localization in WSN

25
2-1 Range based localization
(Cont.)
4. Angle Of Arrival: (AOA)
 It’s a method that allows
each sensor to evaluate
the relative angles
between received radio
signals.


Costly and needs
extensive signal processing.
Localization in WSN

26
2-2 Range-free localization




DV-Hop is the typical representation
It doesn’t need to measure the absolute
distance between the beacon node and
unknown node. It uses the average hop
distance to approximate the actual
distances and reduces the hardware
requirements.
Localization in WSN

27
2-2 Range-free localization
(Cont.)




Adv:
Easy to implement and applicable to
large network.
Disadv:
The positioning error is correspondingly
increased.
Localization in WSN

28
2-2-1 DV-Hop


1.
2.
3.

It is divided into 3 stages:
Information broadcast
Distance calculation
Position estimation

Localization in WSN

29
1-Information broadcast








The beacon nodes broadcast their location
information package which includes hop count and is
initialized to zero for their neighbors.
The receiver records the minimal hop of each beacon
nodes and ignores the larger hop for the same
beacon nodes.
The receiver increases the hop count by 1 and
transmits it to neighbor nodes.
All the nodes in a network can record the minimal hop
counts of each beacon nodes.
Localization in WSN

30
2-Distance calculation


According to the position of the beacon node
and hop count, each beacon node uses the
following equation to estimate the actual
distance of every hop

Localization in WSN

31
3- Position estimation






The beacon node will calculate the average
distance and broadcast the information to
network.
The unknown nodes only record the first
average distance and then transmit it to
neighbor nodes.
The unknown node calculates its location
through.
Localization in WSN

32
2-2-1 DV-Hop (Cont.)


Anchors




A-B: 15

3 hops
avg hop: 5

flood network with
own position
flood network with
avg hop distance

Nodes



4

1
1



B

3

A
count number
of hops to anchors
multiply with avg hop distance
Localization in WSN

2

1

3

2
2

1

33

C
4
2-2-1 Modified DV-Hop

Localization in WSN

34
2-2-2 Pattern Matching
Localization



1.
2.



Also called map-based or finger print algorithm.
It involves 2 phases:
The received signals at selected locations are
recorded in an offline database called radio map.
It works at the online state.
The pattern matching algorithms are used to infer
the location of unknown node by matching the
current observed signal features to the prerecorded
values on the map
Localization in WSN

35
Classifications of Localization
Methods


The localization techniques can be classified with
respect to various criteria:

1.

Centralized vs Distributed

2.

Range-free vs Range-based

3.

Mobile vs Stationary

4.

Coarse-grained vs fine-grained

Localization in WSN

36
Centralized vs Distributed




Centralized
 Data collected in the whole network are
transmitted to the central unit that calculates the
estimated location of each node in a network.
Distributed
 Computation is distributed among the nodes
 Each node estimates its own position based on
the local data gathered from its neighbors.

Localization in WSN

37
Range-Free vs Range-Based




Range-Free (connectivity)
 Makes no assumption about the availability or
validity of such information, and use only
connectivity information to locate the entire sensor
network.
 Hop-Counting Techniques
Range-Based (distance)
 Defined by protocols that use absolute point to
point distance estimates (range) or angle
estimates in location calculation.
Localization in WSN

38
Mobile vs Stationary


Mobile

Stationary

Localization in WSN

39
Coarse-grained vs finegrained




Coarse-grained:
finding approximate coordinates of
nodes in a network so it provide lower
precision estimates of this coordinates.
Fine-grained:
Determining precisely the coordinates
but require much more communication
and computation efforts.
Localization in WSN

40
Summary








WSN .. What & Why ?
Distance estimation VS position computation VS
localization algorithm
Single/Multiple localization in WSN/WBSN
Calculating the distance between sensor nodes
( TOA – TDOA – RSSI – AOA )
Localization in WSN

41
Summary






Range-based methods require extra hardware therefore have a
higher cost but provide more accurate distance measurements,
whereas range-free methods use only connectivity information
and so are less accurate.
Range-free localization ( DV-Hop , Modified DV-Hop , pattern
matching localization )
The localization techniques can be classified with respect to
various criteria. They differ on the assumed localization
precision, hardware capabilities, measurement and calculation
methods, computing organization, the assumed network
configuration, architecture, nodes properties and deployment,
etc.
Localization in WSN

42
Future Work


Few papers investigate multiple-source
localization in WSN and WBSN

Localization in WSN

43
References
1.

http://www.hindawi.com/journals/ijdsn/2012/96

2.

http://www.docslide.com/wireless-sensor-netw

3.

http://www.docstoc.com/docs/32678966/Loc
alization-in-Wireless-Sensor-Network--ELEC-619B-Presentation
Localization in WSN

44
References (Cont.)
4.https://www.cs.virginia.edu/~stankovic/psfiles/wsn.pdf
5.http://www.sersc.org/journals/IJCA/vol6_no3/7.pdf
6.http://www.docstoc.com/docs/130374399/Localization
-in-Wireless-Sensor-Networks
7. http://www.degruyter.com/view/j/amcs.2012.22.issue2/v10006-012-0021-x/v10006-012-0021-x.xml

Localization in WSN

45
Any Questions?

Localization in WSN

46
Thank You !

Localization in WSN

47

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Localization in WSN

Editor's Notes

  • #25: TDOA is the location determination method that AT&T uses to locate a caller when they dial 911 from their mobile phone. TDOA calculates the location of a mobile phone by using the difference in the time of arrival of signals at different cell sites.