An Energy-Efficient Voting-Based Clustering Algorithm for Sensor Networks Min Qin and Roger Zimmermann Computer Science Department, Integrated Media Systems.

An Energy-Efficient Voting-Based Clustering Algorithm for

Sensor Networks

Min Qin and Roger Zimmermann

Computer Science Department, Integrated Media Systems Center

5/24/2005

Presentation outline:

Clustering in sensor networksClustering in sensor networks

Issues of traditional clustering protocolsIssues of traditional clustering protocols

Voting-based clustering algorithm (VCA)Voting-based clustering algorithm (VCA)

Performance evaluationPerformance evaluation

ConclusionsConclusions

An Energy-Efficient Voting-Based Clustering Algorithm for Sensor Networks

The network is divided into many clustersThe network is divided into many clusters

Each cluster has one cluster headEach cluster has one cluster head

Data collected from sensors are sent to the cluster Data collected from sensors are sent to the cluster

head first, and then forwarded to the sinkhead first, and then forwarded to the sink

Cluster head is capable of aggregating data from all Cluster head is capable of aggregating data from all

sensorssensors

Clustering in sensor networksClustering in sensor networks

A sample clusterA sample cluster

sinkCluster head

Issues of traditional clustering protocols

Based on local weights or probabilitiesBased on local weights or probabilities

Often result in undesirable cluster formationsOften result in undesirable cluster formations

Many of them do not consider topology information Many of them do not consider topology information

Load balancing is hardLoad balancing is hard

Example: a network with 4 sensors

B

C

D

A

Desirable cluster formation

Clustering by traditional algorithms (HEED)

AB

C

D

1

0.7

0.6

0.9

Resulting cluster formation (HEED)

AB

C

D

Voting-based clustering algorithm (VCA)

Main ideas:Main ideas:

A sensor’s importance should be reflected from all A sensor’s importance should be reflected from all its neighbors (including itself) rather than from itselfits neighbors (including itself) rather than from itself

Use voting to reflect the importance of different Use voting to reflect the importance of different neighborsneighbors

Topology and residual energy are two primary Topology and residual energy are two primary factors in selecting cluster heads factors in selecting cluster heads

Assumptions about sensors:Assumptions about sensors:

Energy-aware Energy-aware

Quasi-stationaryQuasi-stationary

VCA : An example

AB

C

D

0.25

0.25 0.25

0.25

D vote for all its neighbors (including itself)

VCA : An example

AB

C

D

0.5

0.5

0. 5

0.50.5

D

0.5

D collect votes from all its neighbors

VCA : An example

1.75

AB

C

D

0.750.75

0.75

Each node calculates the total vote it has got

Rules for voting

The sum of the votes a node gives to all its neighbors The sum of the votes a node gives to all its neighbors

(including itself) is 1(including itself) is 1

A neighbor with high residual energy should get more A neighbor with high residual energy should get more

votes than a neighbor with low residual energyvotes than a neighbor with low residual energy

,( , )

0 ,ik

d R

jij

ki j

ij

ed R

ev v v

d R

Load balancing in VCA

If a sensor is covered by multiple cluster heads, the If a sensor is covered by multiple cluster heads, the

following two load balancing strategies are used :following two load balancing strategies are used :

Node degree Node degree

Join the head with the minimum node degree Join the head with the minimum node degree

Balance the size of all clustersBalance the size of all clusters

FitnessFitness

Join the cluster head with the highest fitnessJoin the cluster head with the highest fitness

Balance energy distribution of cluster headsBalance energy distribution of cluster heads

)(

)()(

i

ii vnodedegree

vevfitness

Procedures of VCA

1.Each sensor calculates its votes to all its neighbors1.Each sensor calculates its votes to all its neighbors

2.Sensors calculate and broadcast the total vote they 2.Sensors calculate and broadcast the total vote they have got from their neighbors. have got from their neighbors.

3.Cluster heads are elected from those nodes that have 3.Cluster heads are elected from those nodes that have the highest votes in their neighborhoodthe highest votes in their neighborhood

4. Sensors that are covered by at least one cluster head 4. Sensors that are covered by at least one cluster head withdraw from votingwithdraw from voting

5. the remaining sensors restart from step 2 by ignoring 5. the remaining sensors restart from step 2 by ignoring the votes from those sensors that have withdrawn from the votes from those sensors that have withdrawn from the votingthe voting

Head Election in Multiple Rounds

AB

C

D

0.5

0.33

0. 5

0.50.33

D

0.25

0.25 0.25

0.25

0.5

E

0.50.5

0.33

In the 1st round

Head Election in Multiple Rounds

AB

C

D

0. 75

0.751.08

D 1.58

E

0.83

After the 1st round

Head Election in Multiple Rounds

AB

C

DDE

0.50.5

0.33

In the 2nd round, E ignores vote from A

Head Election in Multiple Rounds

AB

C

D

0. 75

0.751.08

D 1.58

E

0.5

After the 2nd round

A is covered by 2 cluster heads, it chooses E since it has lower degree

Properties of VCA

Message complexity: O(N)Message complexity: O(N)

Time complexity:O(N)Time complexity:O(N)

•Normally finishes within 2-5 iterationsNormally finishes within 2-5 iterations

Cluster heads are well distributed, No two cluster Cluster heads are well distributed, No two cluster

heads covers each other heads covers each other

High-degree nodes tend to get more votes, and give High-degree nodes tend to get more votes, and give

less votes to others less votes to others

Simulation settings

Parameter Value

S [0, 100]2

Sink location (50,200)

Cluster radius 15 m

Data packet 250 bytes

Clustering packet 30 bytes

WITHDRAW packet 10 bytes

Network operation phase

5 TDMA frames

Energy for data fusion 5nJ/bit/signal

Initial Energy 2J

Threshold distance (d0) 100 m

Network lifetime (when the first node dies)

50 150 250 350 450 550100

150

200

250

300

350

# r

ou

nd

s u

ntil th

e f

irst

no

de

die

s

Number of nodes

VCA-fitness VCA-Min degree HEED

A sensor joins the cluster head with the highest fitness value in VCA-fitnessA sensors joins the cluster head with the minimum node degree in VCA-Min degreeAverage result from 100 independent simulations

Network lifetime (when the last node dies)

50 150 250 350 450 5501000

1100

1200

1300

1400

1500

1600 VCA-fitness VCA-Min degree HEED

# ro

unds

unt

il th

e la

st n

ode

dies

Number of nodes

VCA is completely distributed, energy-efficient and VCA is completely distributed, energy-efficient and

location unawarelocation unaware

Using fitness can balance the energy across the Using fitness can balance the energy across the

network, sensors tend to die at a similar timenetwork, sensors tend to die at a similar time

Using Min-degree can balance the size of all clusters, Using Min-degree can balance the size of all clusters,

some nodes may live much longer than otherssome nodes may live much longer than others

Democracy can be very helpful for sensor networks. Democracy can be very helpful for sensor networks.

Conclusions

Questions?Questions?

Comments?Comments?

http://dmrl.usc.edu/publications/http://dmrl.usc.edu/publications/

Conclusions

Thank you!