relative accuracy based location estimation in wireless ad hoc sensor networks may wong 1 demet...
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Relative Accuracy based Location Estimation in Wireless Ad Hoc Sensor Networks
May Wong1 Demet Aksoy2
1Intel, Inc. 2University of California, Davis
ICC 2007
Outline
Introduction Related Work QUAD ( Quadrant-Based estimation)
Localization algorithm Performance evaluation Conclusions
Introduction
In WSNs, Sensors are used in a wide range of
applications. Ex. scientific research, military, healthcare, and
environmental monitoring. Every user has to depend on the location
provided by the sensor to analyze observations Location information is important for data
analysis.
Introduction Sensor are not known where were they deployed. There are two ways to get sensor’s position by
themselves. Equip GPS.
High Cost, Big size and power consumption Localization algorithm .
Location errors are inevitable in estimations. The precise location of each sensor is not
necessary in most sensor network applications.
Introduction
AB
Observer Considers that pollution is from B to A.
B’A’
Introduction
AB
B’’A’’
Observer Considers that pollution is from A to B, but real condition is from B to A.
Introduction
Motivation Reduce hardware cost. Previous work in localization focus on
individual accuracy position. Goal
Minimal Specialized Hardware Eliminate error relative location. Robustness to Network Density.
Related Work
A,(x1,y1), Hop 2B,(x2,y2), Hop 4C,(x3,y3), Hop 6
A(x1,y1)
B(x2,y2)
C(x3,y3)
X
(C,(Xc,Yc), Hop Count)
Reference Node
Unlocalized Node
Localized Node
Related Work
X
Reference Node
Unlocalized Node
Localized Node
50m60m
100mA(x1,y1)
B(x2,y2)
C(x3,y3)
m 2035
60100
m 18.3333
6050
m 18.7553
10050
Hop
Hop
Hop
DistC
DistB
DistAA,(x1,y1), Hop 2B,(x2,y2), Hop 4C,(x3,y3), Hop 6
Related Work
DV-Hop could not estimate a position.
Quad Localization algorithm
Phase1 Hop distance dissemination
DV Based
Phase2 Position vote
Determine sensor relative location
Phase3 Location estimation
Determine location
Quad Localization algorithm
Hop distance dissemination
A,(x1,y1), Hop 2B,(x2,y2), Hop 4C,(x3,y3), Hop 6
V(x1,y1)
U(x2,y2)
T(x3,y3)
A
(C,(Xc,Yc), Hop Count)
Quad Localization algorithm
Position vote
A,(x1,y1), Hop 2B,(x2,y2), Hop 4C,(x3,y3), Hop 6
V(x1,y1)
U(x2,y2)
T(x3,y3)
A
(C,(Xc,Yc), Hop Count)Near Set: AFar Set: B,C
Quad Localization algorithm
Location estimation
B C
A
W
Z
Y
(49,49)
(50,48)(50,48)
(50,50)
Near Set Y,(50,50),3Far Set
W,(49,49),5Z,(50,48),5
Near Set W,(49,49),1Far Set Y,(50,50),3 Z,(50,48),3
N
W
North
South
North
South
Performance evaluation
Simulator is implemented by C++ Radio range 5 unit 100 x 100 grid size Random number of nodes Different topology
Performance evaluation Smooth
(1) Hop by hop gradient propagation to get estimated distance to reference node.
(2) Local computation by each node using multilateration procedure.
Organizing a Global Coordinate System from Local Information on an Ad Hoc Sensor Network. In Proc. 2nd Intl. Workshop on Information Processing in Sensor Networks (IPSN)
b
c
a
a a
Performance evaluation DV-Hop Min-Max : corrections are done by local averagi
ng
The n-Hop Multilateration Primitive for Node Localization Problems (ACM) Mobile Networks and Applications 03
b+c b+c
X
Y
V
Set the center of the bounding box as the estimate.
Performance evaluation
Performance evaluation
X Coordinate Estimates using DV-Hop
Performance evaluation
X-Coordinate Estimates using Min-Max
Performance evaluation
X Coordinate Estimates using QUAD
Conclusions
In this paper, they use coordinate and relative position to estimate
location. provide a accuracy topology.
Thank You!