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A Distributed Algorithm for the Dead End Problem of Location Based Routing in Sensor Networks Le Zou, Mi Lu, Zixiang Xiong, Department of Electrical Engineering, Texas A &M University IEEE Transactions ,Vehicular Technology 2005

A Distributed Algorithm for the Dead End Problem of Location Based Routing in Sensor Networks Le Zou, Mi Lu, Zixiang Xiong, Department of Electrical Engineering,

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A Distributed Algorithm for the Dead End Problem of Location Based

Routing in Sensor Networks

Le Zou, Mi Lu, Zixiang Xiong,Department of Electrical Engineering, Texas A&M University

IEEE Transactions ,Vehicular Technology 2005

Outline

• Introduction• Network Model• The PAGER (partial-partition avoiding

geographic routing) Algorithm• Simulation• Conclusions

Introduction

Base Station

Sensor nodes

Sensor nodes forward data packets to BS in a multihop manner

IntroductionBase Station

The dead end problem

x

yGreedy forwarding

z

g

Concave Node:distance(x,BS) < distance(y,BS ) y N∀ ∈ (x),

Introduction

Sink Destination

• GPSR (RHR)

Introduction

s t

• Face Routing

Network Model

• A number of sensor nodes randomly deployed on an unobstructed two-dimensional sensing field with a BS.

• All sensor nodes within communication range r• The BS is located either adjacent to the

sensing field or inside it• Each node knows the location information of

the BS.

The PAGER Algorithm

• The Shadow Spread Phase• Divides a connected graph into subgraphs orig

inated from concave nodes

• The Cost Spread Phase• Establishes paths on a given subgraph obtain

ed in the first phase

The Shadow Spread Phase

Base Station

A

B C

DE

F

concave node

concave node

The Shadow Spread Phase

Base Station

A

B C

DE

F

shadow node

bright nodes

Shadow Area

Bright Area

The Shadow Spread Phase

• Nodes exchange information by means of periodically broadcasting beacon messages beacon(status, location)

• the shadow spread phase converges in n rounds in terms of beacon broadcast interval B

The Cost Spread Phase

5

12

7

16

20

Base Station

18

8

15

16

2019

23

A

B C

DE

F

Euclidian distance to the BS

19+∆

∆ should be set to the average Euclidean distance between neighboring sensor nodes

∆ is set to 3 in this example

22

The Cost Spread Phase

5

12

7

16

20

Base Station

18

8

15

16

2019

23

A

B C

DE

F

22+∆

22

25

The Cost Spread Phase

5

12

7

16

20

Base Station

18

8

15

16

2019

23

A

B C

DE

F

23+∆

22

25 26

The Cost Spread Phase

5

12

7

16

20

Base Station

18

8

15

16

2019

23

A

B C

DE

F

26+∆

2625

2229

The Cost Spread Phase

• Once the status of a sensor node turns from bright to shadow, the cost spread phase can be triggered on that node immediately

• The convergence length of the cost spread algorithm in the whole sensor network is only associated with the maximum size of these shadow areas

Multiple BSBS 1 BS 2

PAGER-M

The shadow spread and cost spread processes begin

PAGER-MA changes its status to “bright”, then sends out beacon message

Path Redundancy

• We use path redundancy to reduce forwarding failure• Choosing the neighbor with closest arrival time among available forwarding candidates

Simulation ~PAGER-S

Simulation ~PAGER-S

Simulation ~PAGER-S

Simulation ~PAGER-S

Simulation ~PAGER-M

Simulation ~PAGER-M

Simulation ~PAGER-M

Conclusions

• PAGER has the loop free guarantee delivery property

• The mobility adaptability of PAGE make it suitable for use in mobile sensor networks with frequent topology changes