Density-Aware Hop-Count Localization (DHL) in Wireless Sensor Networks with Variable Density

Sau Yee Wong1,2, Joo Chee Lim1, SV Rao1, Winston KG Seah1

1Communications and Devices Division, Institute for Infocomm Research2National University of SingaporeIEEE WCNC 2005

Shao-Chun Wang

Outline

Introduction Background and Related Work Density-Aware Hop-Count

Localization (DHL) Simulation Result Conclusion

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Introduction-(cont.)-

Hop-count localization algorithm simple sensor networks are multi-hop sensors usually have low mobility packet size is small and constant

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ReferenceNode

Introduction-(cont.)-

conventional hop-count localization algorithms only provide good location estimation if the node distribution in the network is dense and uniform

The node distribution in a sensor network is not always uniform terrain contour hostile environment

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Introduction

Goal improve the accuracy of location

estimation when the node distribution is non-uniform

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Background and Related Work-(cont.)-

hop-count localization algorithm triangulation

distance between a Reference Node (RN) and any node can be estimated by D = HC x R D : distance HC : min. hop-count from the RN R : transmission range

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Background and Related Work-(cont.)-

Case A

Reference Node

Forwarding Node

Destination Node

Node

Transmission Range : R

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Background and Related Work-(cont.)-

Case B

Reference Node

Forwarding Node

Destination Node

Node

Transmission Range : R

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Background and Related Work-(cont.)-

Case C

Reference Node

Forwarding Node

Destination Node

Node

Transmission Range : R

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Background and Related Work-(cont.)-

Case D

Reference Node

Forwarding Node

Destination Node

Node

Transmission Range : R

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Background and Related Work-(cont.)-

R 2R 3R 4R

ActualDistance

Case A

Case B

Case C

Case D

EstimatedDistance

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Background and Related Work-(cont.)-

“Ad hoc positioning system (APS)” Globecom 2001 DV-Hop

Background and Related Work-(cont.)-

DV-Hop

R2

R1R3

A

R1,R2,R3:Refernece Node

1.Flooding Beacon:Location Information

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Background and Related Work-(cont.)-

DV-Hop

R2

R1R3

A

2.Each node maintains a table:{ Xi , Yi , hi }hi: Min. Hop Count

{ X1 , Y1 , 3 }

{ X2 , Y2 , 2 }

{ X3 , Y3 , 3 }

{ X1 , Y1 , 0 }{ X2 , Y2 , 2 }{ X3 , Y3 , 6 }

{ X1 , Y1 , 2 }{ X2 , Y2 , 0 }{ X3 , Y3 , 5 }

{ X1 , Y1 , 5 }{ X2 , Y2 , 6 }{ X3 , Y3 , 0 }

Background and Related Work-(cont.)-

DV-Hop

R2

R1R3

A

3.Reference Node estimates anaverage size for one hop

100m

75m40m

42.1652

4075

5.1726

40100

90.15

56

75100

Background and Related Work-(cont.)-

DV-Hop

R2

R1R3

A

4.Flooding Beacon:Average size for one hop

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Background and Related Work-(cont.)-

DV-Hop

R2

R1R3

A

5.Estimate distance to the three Reference Nodes

R1: 3 x 16.42R2: 2 x 16.42R3: 3 x 16.42

6.Node A perform a triangulation to get its location

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Background and Related Work

The distance per hop is greater in dense regions and smaller in sparse regions

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Density-Aware Hop-Count Localization-(cont.)-

Assumptions network is connected sensors have low mobility each node is assumed to know its

number of neighbors

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Density-Aware Hop-Count Localization-(cont.)-

Local density is defined as the number of neighbors Nngbr

Range ratio the ratio of hop-distance to the

transmission range μ Σμ

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hop-distance

Density-Aware Hop-Count Localization-(cont.)-

Density categories p < Nngbr < q

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Density-Aware Hop-Count Localization-(cont.)-

μ=0.7

μ=0.8

μ=0.6

μ=0.6

Reference Node

Forwarding Node

Destination Node

Node

Transmission Range : R

Low density μ=0.6Medium density μ=0.7High density μ=0.8

Σμ=

Σμ=

Σμ= Σμ=A

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Density-Aware Hop-Count Localization-(cont.)-

μ=0.7

μ=0.8

μ=0.6

μ=0.6

Reference Node

Forwarding Node

Destination Node

Node

Transmission Range : R

Low density μ=0.6Medium density μ=0.7High density μ=0.8

1.Flooding Beacon:•Location Information

Σμ=

Σμ=

Σμ= Σμ=A

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2. Σμ + μ

Density-Aware Hop-Count Localization-(cont.)-

μ=0.7

μ=0.8

μ=0.6

μ=0.6

Reference Node

Forwarding Node

Destination Node

Node

Transmission Range : R

Low density μ=0.6Medium density μ=0.7High density μ=0.8

1.Flooding Beacon:•Location Information

Σμ= 0.8

Σμ=

Σμ= Σμ=A

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2. Σμ + μ

Density-Aware Hop-Count Localization-(cont.)-

Hop information update method

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Density-Aware Hop-Count Localization-(cont.)-

μ=0.7

μ=0.8

μ=0.6

μ=0.6

Reference Node

Forwarding Node

Destination Node

Node

Transmission Range : R

Low density μ=0.6Medium density μ=0.7High density μ=0.8

3.forwards accumulated range ratio to their neighbors

Σμ= 0.8

Σμ=1.5

Σμ=2.1 Σμ=2.7A

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Density-Aware Hop-Count Localization

μ=0.7

μ=0.8

μ=0.6

μ=0.6

4.Estimate distance to the Reference NodesD = 2.9 x R

Σμ= 0.8

Σμ=1.5

Σμ=2.1 Σμ=2.7

Reference Node

Forwarding Node

Destination Node

Node

Transmission Range : R

Low density μ=0.6Medium density μ=0.7High density μ=0.8

5.Node A perform a triangulation to get its location

A

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Simulation Results

Range ratio determination Distance accuracy comparisons Position accuracy comparisons Overhead comparisons

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Simulation Results-Range Ratio Determination (cont.)-

50m x 50m square area Transmission range : 5m Ratio range : 0.1 – 0.9

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Simulation Results-Range Ratio Determination (cont.)-

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Simulation Results-Range Ratio Determination-

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Simulation Results-Distance Accuracy Comparisons-

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Simulation Results-Position Accuracy Comparisons-

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Simulation Results-Overhead Comparisons (cont.)-

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Simulation Results-Overhead Comparisons-

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Conclusion

We described a DHL method that address network non-uniformity by using range ratios improve localization accuracy lower packet transmission overhead

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