Maximum Lifetime Routing in Wireless Sensor Networks

by

Collins Adetu

Nicole Powell

Course: EEL 5784

Instructor: Dr. Ming Yu

Overview

What are Wireless Sensor Network (WSN) Applications of WSN The Energy Efficiency Problem Solution: Flow Augmentation Algorithm Simulation Results Conclusions Questions

What is a Wireless Sensor Network?

A wireless sensor network is an ad hoc network of sensors and gateways communicating wireless amongst each other.

GatewaySensor

Fig. 1. Diagram Illustrating a Wireless Sensor Network

Applications of Wireless Sensor Networks

Used in military applications for battlefield surveillance

Used for detecting seismic activity in earthquake and volcanic prone regions

Used in ecosystem monitoring e.g. firetower sensors for monitoring forest fires

Used in weather forecasting and hurricane prediction

The Energy Efficiency Problem

Because of the compact nature of wireless sensors they are normally equipped with small-sized batteries e.g. AA batteries

Smaller batteries mean less power available for communication

Therefore, optimizing sensor battery lifetime is a matter of utmost concern

Collectively optimizing battery lifetime for all nodes in the network increases the network’s lifetime

Flow Augmentation Algorithm

The paper we researched provides a solution to the energy efficiency problem by using the flow augmentation algorithm

The algorithm uses a relative energy metric, which it dynamically updates, to compute the most energy efficient communication path

Data flows through the most energy efficient path at all times, hence maximizing network lifetime

Flow Augmentation Algorithm

Compute Energy

Cost Metric

Calculate MostEnergy-Efficient

Path

ComputeResidual Energy

Continue until first node dies

Calculated using Dijkstra,Bellman-Ford etc.

Computes residual energyonly on nodes traveled

on shortest path.

Uses energy-cost metric formula

Flow Augmentation Algorithm

The cost metric is computed using the formula:

where Energy expended transmitting data (J/bits)

Energy used in processing received data (J/bits)

Ei and Ej = Initial energy of the transmitting and receiving node (J)

and = Residual energy of the transmitting and receiving node (J)

x1, x2, x3 = positive weights

Residual Energy is computed as follows:

Note: This applies for both transmitting and receiving nodes, lambda = packet size

ijte

ijre

iE jE

ijoldnew eEE

Simulation Results The objective of our simulation was to obtain

similar results as proposed in the paper In our simulation,

20 nodes were distributed randomly over a 50m by 50m area

Sensors were initialized with 10J of energy Source and destination nodes were randomly

selected 50 instances were simulated with different

source and destination nodes in order to compute an average network lifetime

The input parameters to the Flow Augmentation algorithm were the weights, x1, x2, and x3 i.e. FA(1,1,1) means x1=x2=x3=1 are passed as input parameters to the algorithm

All simulations were done using MATLAB

Simulation Results

Average and Worst Case Performance of FA(x 1,x 2,x 3)

0.4

0.5

0.6

0.7

0.8

0.9

1

1 5 10 15 20 25 30R, n

orm

aliza

ed n

etw

ork

lifeti

me

FA(1,x,x) AVERAGE

FA(1,x,x) WORST

FA(1,x,0) AVERAGE

FA(1,x,0) WORST

Average and Worst Case Performance of FA(x 1,x 2,x 3)

00.10.20.30.40.50.60.70.80.9

1

1 5 10 15 20 25 30

R, n

orm

alize

d ne

twor

k life

time

FA(1,x,x) AVERAGE

FA(1,x,x) WORST

FA(0,x,x) AVERAGE

FA(0,x,x) WORST

Performance of FA(1,x,x) compared with FA(1,x,0)

Simulation ResultsPerformance of FA(1,x,x) for various λ = Data Packet Size

Worst Performance of FA(x 1,x 2,x 3)

0.7

0.75

0.8

0.85

0.9

0.95

1

1 10 20 30R, n

orm

aliza

ed n

etw

ork

lifeti

me

λ=5000

λ=10000

λ=20000

Average Performance of FA(x 1,x 2,x 3)

0.90.910.920.930.940.950.960.970.980.99

1

1 10 20 30

R, n

orm

aliza

ed n

etw

ork

lifeti

me

λ=5000

λ=10000

λ=20000

Conclusion

The network lifetime increases as the sensor energy weights are increased when using the Flow Augmentation algorithm

An increase in data packet size (lambda), produces an adverse effect on the network lifetime

Our simulation results match closely to those obtained in the paper

The paper went further to compare the flow augmentation algorithm with other energy-efficient routing algorithm. The flow augmentation algorithm out performed the other algorithms

References

Chang, J.-H., and L. Tassiulas. "Maximum Lifetime Routing in Wireless Sensor Networks." IEEE ACM TRANSACTIONS ON NETWORKING. 12 (2004): 609-619.

Tanenbaum, Andrew S. Computer Networks. 4th ed. New Jersey: Prentice Hall PTR, 2003.

Questions