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Muhamad Felemban, BasemShihada, and KamranJamshaid Department of Computer Science, CEMSE Division, KAUST, Saudi Arabia Optimal Node Placement in Underwater Wireless Network 1

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Page 1: Slideshare

Muhamad

Felemban, BasemShihada, and

KamranJamshaidDepartment of Computer Science, CEMSE Division,

KAUST, Saudi Arabia

Optimal Node Placement in Underwater

Wireless Network

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Presentation Outline

Introduction and Motivation

Objective

Network Model

Underwater Communication

Problem Formulation

Results

Simulation Setup and Results

Conclusion

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Introduction

Most of the Earth is covered by water

Underwater operations are difficult

Monitoring tasks:

Habitat monitoring

Data sampling

Critical tasks:

Oil spill, Mexico Gulf 2010

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Motivation

AUV Limitations:

Off-line configuration

Non real-time monitoring

Limited Bandwidth and high propagation delays

Use Underwater Wireless Sensor Network UWSN to

over come theses limitations

But

High cost deployment

Large power consumption

Limited hardware

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Paper’s Objective

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Find the optimal distance between two nodes such

that

Attains maximum coverage and connectivity

Minimizes transmission loss between nodes

Find an optimal node placement strategy to support

AUV’s operations such that

Minimum number of nodes is used for a given volume

Maximum coverage volume for certain number of nodes

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Network Model

Surface Gateways (SG): EM and acoustic transceivers

Relay Nodes (RN): homogenous transceivers

Uniform transmission power

Each node forms a communication sphere of

radius r

Two nodes are connected if inter-distance is

less than or equal r

Nodes are statically placed and maintain

their positions

Ocean is divided horizontally into regions

based on the depth

Propagation characteristic is different

in each region

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r

RN

SG

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Network Model

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Find a space-filling polyhedron that approximates the

communication sphere

The best polyhedron to approximate a sphere has a

large volumetric quotient

Truncated Octahedron (TO) has

volumetric quotient of 0.68

Node placement strategy is to

tessellate TOs of radius R using

where

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Underwater Communication

SNR is computed using the passive sonar equation

[Urick]

Transmission Loss δ

Two factors

Energy spreading

K = 15

Wave absorption

α is computed using Ainslie and McColm model

[Ainslie&McColm]

Temperature, frequency, depth, salinity, and acidity

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Underwater Communication

Absorption coefficient α

Increases with frequency

Decreases with depth

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Problem Formulation

Problem P given: k,f, d, T, Rmax, V, and N

Minimize

Subject to

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Results

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Transmission loss of deep water at 10000 m depth

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Results

There exists a range of frequencies with longer

transmission distance, because of the reduction in

ambient noise

As depth increases, higher frequencies can be used

for larger transmission distance

High BER can tolerate larger frequencies and further

transmission distance

Higher power increases transmission range

BPSK and QPSK perform better than 16-QAM

Small bit/symbol is better in low data-rate networks

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Results

Maximum transmission range at different depths with Ptx= 100

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Results

Maximum transmission range with different transmission power at depth of

10000 m14

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Results

Maximum transmission range with different BER at depth of

10000 m15

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Results

Maximum transmission range with different modulation schemes at depth of

10000 m16

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Simulation Setup

NS-3 simulator with UAN framework

Contributions to UAN framework

Added new propagation models

Added passive sonar equation to calculate SNR

Modified MAC AlOHA to work with UDP client and server

application

PER of 90% if received SNR ≥ SNRth

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Simulation Results

Maximum transmission range to maintain cut-off threshold of 19.47 at depthof

7500 m18

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Conclusions

Higher frequencies provide more channel capacity

but more susceptible to transmission loss

Optimal operating frequency is around 40 KHz in shallow

water, and 100 KHz in deep water

Low symbol modulation is more suitable for UWSN

BPSK and QPSK

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References

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[Urick] R. Urick, “Principles of underwater sound,”

New York, 1983.

[Ainslie&McColm] M. Ainslie and J. McColm, “A

simplified formula for viscous and chemical

absorption in sea water,” Journal of the Acoustical

Society of America, vol. 103, no. 3, pp. 1671–

1672, 1998.

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Questions and Discussion

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Conclusions