Transcript Three Beacon Sensor Network Localization through Self

Three Beacon Sensor Network
Localization through Self
Propagation
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Mohit Choudhary
Under Guidance of: Dr. Bhaskaran Raman
Sensor Network Defined
• Collection of communicating sensing
devices.
• collator
The base station is a master node.
• Data sensed by the network nodes
sent to the base station
collator
Central processing,
& rapid response
collator
Localization in Sensor Networks
• Spatial localization - determining
physical location of a sensor node in
the network.
• Localization is an essential tool for:
– The development of low-cost sensor
networks for use in location-aware
applications
– Geographic routing
Aim of the Thesis
• Distributed algorithm for a sensor
network localization in which nodes
have the ability to assimilate and
utilize the connectivity and
negativity information provided by
their nearby nodes.
– Presence of three beacon nodes that
are aware of their position apriori.
Problem Difficulty
• Often insufficient data to compute a
unique position assignment for all
nodes.
• Information itself may be erroneous
due to presence of noise and gray
areas
• Algorithm has to scale with the size
of the network
Contribution of the Thesis
• A novel distributed algorithm
• Evaluation using simulations for a
wide range of scenarios to establish
an optimal conditions required to
achieve effective localization with
the proposed scheme.
• Real life experiments with in-house
developed sensor nodes (based on
Atmel AT89C52 microcontroller and
radiometrix TX/RX)
Related Work
• Use of GPS.
• Use of multiple static
reference beacons.
– Use of signal-strength
estimation.
– Use of acoustic ranging.
– Use of connectivity
information.
• Use of Mobile Beacon.
– Expensive (cost, size, energy)
– Only works outdoors, on Earth
– Technology additional to the
requirement of the application.
– Technology additional to the
requirement of the application.
– Complex setup procedures
– Terrain uncertainties
– Expensive
– Not possible for ad hoc, sensor
networks
– Additional Technology
– Terrain uncertainties
Specific Related Work
• Doherty et al. - Centralized technique
using convex optimization.
• Bulusu et al. - Distributed algorithm
based on connectivity and multiple
beacons.
• Savarese et al.- Two-phase approach,
connectivity for initial position estimates
and trilateration for position refinement.
(multiple beacons but less in number.)
• Patwari et al. - One-hop multilateration
from reference nodes [received signal
strength (RSS) and time of arrival (ToA)]
Preliminaries
• Connectivity based RF Localization
Bounding Box - {[A, B, C, D]}.
Negativity based RF Localization
Bounding Box- {[A,B,C,G](K,J)}
Localization point and
Localization Error
• Let Bounding Box- {[B1, B2, B3, B4] (derived
points)} then LP is:
1. If (segments B1B3 and B2B4 intersect) LP = point of
intersection.
2. Else if (center points of both B1B3 and B2B4 lie inside
the polygon) LP =center point of B1B3 or B2B4 that lies
closer to the centroid of the polygon represented by
{[B1,B2,B3,B4](derivedpoints)}.
3. Else LP = center point of B1B3 or B2B4 that lies inside
the polygon represented by
{[B1,B2,B3,B4](derivedpoints)}.
• The localization error, εA - Length of the line segment
MLP .
Proposed Algorithm- Terminology
•
•
•
•
Beacons- Know their position apriori.
Non-Beacon- Location unknown at start.
Unique Node-ID – NID
Message ID - MID
– MID=1 is used by beacon nodes.
– MID=2 is used by pseudo-beacon nodes.
– MID=3 is used by other nodes.
• Negativity constraint set (NCS) – A set of
negativity constraints, each consisting of a 3tuple (NID, a, b).
• Message transmitted - A 5-tuple (NID, a, b,
MID, NCS).
Proposed Algorithm-Example Run
B2
Y
F
B3
A
X
E
B1
Step-2:
InBeacon
the second
stage,
the pseudo-beacon
localizes
Step-1:
nodes
transmit
their
location. We
assume
that
Step-2 (contd.):
Nodes
which
hear
a transmission
from
a itself,
there
and
transmits
is at least
itsthus
one
location
other
to
node
its neighbours.
which
can hear
This
all
transmission
three
pseudo-beacon
immediately
localize
themselves.
beacons.the
includes
A node
negativity
which constraint
hears all three
of allbeacon
the three
nodes
beacon
is termed
nodes.
as athis
For
pseudo-beacon
reason, this transmission
node.
is very expressive.
Valid Set of Messages
• A set of threshold number of
messages of MID=3, with the same
x and y values, but different NID’s
constitutes a valid set. These
different messages would be sent
by different non-beacon nodes
which localize themselves to the
same point.
• Also, a single message with MID=1
constitutes a valid set.
Example Run Contd.
F
A
Y
X4
X1
E X3
X2
X
Step-3: In the third stage, the algorithm proceeds in a distributed
Let us assume X1, X2, X3 and X4 are the nodes
fashion. Nodes which have localized themselves transmit their
in region E
Threshold
Threshold
=
1 2any negativity constraints
location to their neighbours,
along=with
as appropriate. This in turn helps in the localization of further
nodes.
Tuning
• In our simulations, we have found that
the use of threshold=2 usually works well.
• A node which does not receive two valid
sets of messages, but only one valid set,
temporarily localizes itself with just this
information and sends a message. On
receiving the second set, it further refines
its position, and sends a second message
announcing this information.
Sources of Error Possible
• There is error inherent in the connectivitybased and negativity-based constraints.
• A negative constraint may be false, due to
non-receipt of a valid message
• The presence of gray areas and nonuniform radio connectivity can cause
further errors in calculations.
• Some nodes which are "far away" from
other nodes may not receive enough
information to localize themselves.
Simulation Setup
• Platform- Visual Sense that builds on
and leverages Ptolemy II.
• Two sets of simulations for various region
of operation.
– TX radius of 30mts/ node
– TX radius of 50mts/ node
• Study the effect of varying the value of
threshold(1,2 or 3) in each case.
• Nodes within a localization error of 20%
of transmission range turn green, those
within 10% turn red.
Example Simulation Run
Simulation Results
Area [0,300]x[0,300]
Node radius: 50 mts
Threshold: 1
Avg. Error: 7.306
50
47
45
43
40
Number of Nodes
49
39
35
33
30
26
25
20
15
13 14
10
5
0
1
5
3
2
2
3
5
4 5 6 7 8 9 10 11 12
Localization error (mts)
Simulation Results
Area: [0,300]x[0,300]
Node radius : 50 mts
Threshold: 2
Avg. Error: 5.4693
50
49
48
45
45
Number of Nodes
40
37
35
30
25
20
19
15
14
10
6
5
3
1
0
1
2
3
4
5
6
7
8
Localization error (mts)
9
10
Simulation Results
Area: [0,300]x[0,300]
Node radius : 50 mts
Threshold: 3
Avg. Error: 4.64
50
45
Number of Nodes
40
35
34
31
30
25
23
20
15
15
10
7
5
3
1
0
1
2
3
4
5
6
7
8
Localization error (mts)
9
10
Factors
• Node Density (Number of Nodes
deployed / Region of Operation)
• Node TX Range
• Value of Threshold
• We define:
Coverage=(Node Density) x (Node Tx Range)
Compiled Simulation Results
Node TX
Radius
Threshold
1
30
50
Region of
Operation
Coverage
[0,120]x[0,120]
9.8125
% of Nodes
localized
Avg. Localization
Error
72
6.0
82
5.6
2
[0,120]x[0,120]
3
[0,120]x[0,120]
100
3.9
1
[0,180]x[0,180]
82
5.022
2
[0,180]x[0,180]
98
3.97
3
[0,180]x[0,180]
74
3.81
1
[0,240]x[0,240]
54
5.206
2
[0,240]x[0,240]
32
5.17
1
[0,200]x[0,200]
82
8.44
2
[0,200]x[0,200]
86
7.06
3
[0,200]x[0,200]
100
5.437
1
[0,300]x[0,300]
86
7.306
2
[0,300]x[0,300]
98
5.469
3
[0,300]x[0,300]
68
4.64
1
[0,400]x[0,400]
58
7.096
2
[0,400]x[0,400]
38
5.952
4.36
2.452
9.8125
4.358
2.452
Analysis
• Coverage ≈ 4.36
• Value of threshold=2 is good both in terms of
percentage of nodes localized and the Avg.
Localization error.
• We now put forward the following questions
that we aim to answer:
– How well does the algorithm scale with
increased area of operation?
– Can the algorithm be used in harsh
environments such as indoors considering the
multipath effect and gray areas produced in
RF communication?
– What is the effect of unreliable
communication on the proposed scheme and
what are the measures needed to ensure
reliability in communication?
Large Area of Operation
Total Nodes: 272
Total nodes : 555
Area: [0,700]x[0,700]
Node radius : 50 mts
Threshold: 2
Avg. Error: 5.76
Area: [0,1000]x[0,1000]
Node radius : 50 mts
Threshold: 2
Avg. Error: 6.08
300
256
454
238
Number of Nodes
Number of Nodes
250
523
500
267269
200
156
150
100
98
76
404
400
321
300
200
178
123
100
50
16
4
0
1
2
65
29
9
10
26
7
0
3
4
5
6
7
8
Localization error (mts)
472
1
2
3
4
5
6
7
8
Localization error (mts)
9
94% nodes localize
10
Gray areas and multipath effect
• Zhao J et al. “Understanding Packet
Delivery Performance in Dense Wireless
Sensor Networks.”
– Extent of gray areas is less for lower transmission
ranges.
– Extent of gray areas varies greatly with the
environment (indoor, out door, habitat) even for
the same transmission range.
– For a given transmission range the extent of gray
area is the maximum for indoor.
– the extent
– of gray areas in indoor environment measures up
to 1/3rd of the transmission range.
Gray areas and
Multipath effect
50
45
40
35
30
25
20
15
10
5
0
Area: [0,300]x[0,300]
Node radius : 35-50 mts (random)
Threshold: 2
Avg. Error: 6.097
50
50
45
40
42
40
Random
Ideal
24
12
0
1
1
4
Number of Nodes
Number of Nodes
Area: [0,300]x[0,300]
Node radius : 50-65 mts (random)
Threshold: 2
Avg. Error: 6.4
35
30
25
24
20
17
15
11
10
7
41
39
11
7
5
4
3
0
2 3
4 5
6 7
8 9
Localization error (mts)
1
1
2
3
4
5
6
7
8
Localization error (mts)
9
10
Effect of unreliable
communication
Number of Retransmissions/ node: 1
Area: [0,300]x[0,300]
Node radius : 50 mts
Threshold: 2
Avg. Error: 5.46
Area: [0,300]x[0,300]
Node radius : 50 mts
Threshold: 2
Avg. Error: 5.309
50
50
45
45
40
37
35
34
30
29
25
21
20
15
12
10
2
0
1
3
4
5
6
7
8
Localization error (mts)
9
10
39
30
25
24
20
15
12
9
5
2
2
37
35
10
7
5
45
40
38
Number of Nodes
Number of Nodes
49
4
3
0
1
2
Probability of transmission error : 0.2
3
4
5
6
7
8
Localization error (mts)
9
10
Experiment Setup
• Area of operation of [0,100] X
[0,100]
• Sensor nodes are made up of
onboard:
Atmel AT89C52 microcontroller.
– A radiometrix BiM-433-F radio
TX/RX. operating at 433 MHz
frequency.
– A voltage stabilization circuit .
– A 9V battery.
–
Block Diagram
Features:
1) Maximum Data Rate: 40 kbps.
2) Frequency: 433 MHz.
3) Output power: 6 dBm, Receiver sensitivity: -107dBm.
4) Rapid RX power up ( <1ms )
5) Simple UART interface
• Features
– 8K Bytes of In-System Reprogrammable
Flash Memory
– Endurance: 1,000 Write/Erase Cycles
– 256 x 8-bit Internal RAM
– 32 Programmable I/O Lines
– Three 16-bit Timer/Counters
– Eight Interrupt Sources
– Programmable Serial Channel
– Low-power Idle and Power-down Modes
– One Serial Interface
Circuit Diagram
Communication Protocol Details
• Microcontrollers configured to communicate
with the radio in UART mode 1 at 9600
Bauds.
Byte Transfer
UART Mode 1
• Microcontroller used to select the radio to
transmit or receive.
• CD (carrier detect) of the radio is connected
to INT0 to decide changeover.
Packet Structure
• Preamble: 3ms Preamble mandatory
for the receiver in the radiometrix chip
to stabilize.
• Control: We used a unique Byte pattern
(0xAA) to indicate the start of message
• Data: The data as used in the actual
implementation is as shown in Figure6.4.
• CRC: 16 Bit Checksum of control - data
fields has been used by the decoder to
verify the integrity of the packet.
Spatial Profile
Experiment Setup
• The experiment setup has been considered keeping in mind the
results obtained after simulation
Threshold=2
(Coverage = 4.358) ,
Coverage= [(Node density) X (TX Area / Node)]
For the transmission radius of 30 meters following node density is
desired
Node Density = 4.358/ (3.14x30x30)
Node Density = 0.00154
Thus, for area of 10,000 sq meters (100x100), the number of
nodes required would be
Number of nodes required = (Node density) x (Area)
Number of nodes
= 0.00154 x 10000
Number of nodes
= 15.4
Experiment Details
• Four sensor nodes available.
• Requirement of 15 nodes and three
beacons.
• Technique of rotating the nodes that had
once achieved localization.
Experiment Results
Total nodes: 15
Area: [0,100]x[0,100]
Node radius : 30 mts
Threshold: 2
Avg. Error: 4.266
Area: [0,100]x[0,100]
Node radius : 30 mts
Threshold: 2
Avg. Error: 3.56
15
14
14
12
Number of Nodes
Number of Nodes
12
14
10
8
6
4
4
3
3
2
8
6
4
4
4
2
1
1
0
1
10
2
3
4
5
6
7
8
Localization error (mts)
9
10
0
0
1
2
3
4
5
6
7
8
Localization error (mts)
9
10
Conclusions
• Proposed method of localization is a complete and
reliable process in itself.
• Applications based on sensor networks requiring
reasonable localization accuracy can effectively utilize the
proposed method to cut down on additional cost of
localization otherwise incurred.
• As a few numbers of nodes in each region localize to a
common point by the proposed method, this information
can be further utilized by the applications to either
perform power management by utilizing a very small
number of such nodes at one time or perform easy
clustering of all such nodes.
Future Work
• Analyzing the effect of using other radio models
such as a octagon instead of a square on the
proposed scheme.
• Attempt to extend the methodology to 3D
networks.
• On the hardware level as a first step attempt to
integrate the developed node with temperature
sensors in form of DS 1631 (Dallas semiconductor
digital thermometer chip).
• As a second step attempt to integrate RF-id reader
to the node as onboard sensor.
Thank you