pci 2005 volos, greece 11-13 nov 2005 efficient active clustering of mobile ad-hoc networks damianos...

PCI 2005Volos, Greece

11-13 Nov 2005

Efficient Active Clustering of Efficient Active Clustering of Mobile Ad-Hoc NetworksMobile Ad-Hoc Networks

Damianos Gavalas, Grammati Pantziou, Charalampos Konstantopoulos, Basilis Mamalis

Department of Cultural Technology and Communication

University of the Aegean

Email: [email protected]

Presented by D. Gavalas


11-13 Nov 2005

Outline

Introduction to Mobile Wireless Ad Hoc Networks

Differences in routing among conventional and

Ad Hoc networks

Clustering in Ad Hoc Networks

Existing algorithms for Ad Hoc Networks clustering

& their disadvantages

Adaptive Broadcast Period clustering algorithm

Simulation results

Conclusions


11-13 Nov 2005

Mobile Ad Hoc Networks

Formed by wireless hosts which may be mobile

Without (necessarily) using a pre-existing

infrastructure

Routes between nodes may potentially contain

multiple hops


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Mobile Ad Hoc Networks

Two mobile nodes are ‘linked’ if they are within transmission range of each other

May need to traverse multiple links to reach a destination


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Mobile Ad Hoc Networks (MANETs)

Mobility causes route changes


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Why Ad Hoc Networks ?

Ease of deployment Speed of deployment Decreased dependence on infrastructure


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Many Applications

All applications where a network infrastructure does not exist Civilian environments

taxi cab network meeting rooms, electronic conferences, e-classrooms sports stadiums boats, small aircraft

Personal area networking cell phone, laptop, ear phone, wrist watch

Emergency operations search-and-rescue policing and fire fighting

Military environments soldiers, tanks, planes


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Challenges

Limited wireless transmission range

Broadcast nature of the wireless medium

Packet losses due to transmission errors

Mobility-induced route changes

Mobility-induced packet losses

Battery constraints

Potentially frequent network partitions

Routing


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Why is Routing in MANET different ?

Host mobility link failure/repair due to mobility may have different

characteristics than those due to other causes Rate of link failure/repair may be high when nodes

move fast New performance criteria may be used

route stability despite mobility energy consumption

Difficult to assign hierarchical IP-like addresses (sub-networks which could share the same ‘domain name’ are not fixed)


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Unicast Routing Protocols

Many protocols have been proposed

Some have been invented specifically for MANET

Others are adapted from previously proposed

protocols for wired networks

No single protocol works well in all environments some attempts made to develop adaptive protocols


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A promising approach to ease routing process in MANETs is to is to build hierarchies among the nodes, such that the network topology can be abstracted Logical grouping of mobile nodes in separate clusters

This process is commonly referred to as clustering A mobile node in every cluster is elected as cluster

head (CH) CHs store routing tables They also route incoming messages from their cluster

members to neighboring clusters Different clustering schemes may differ in

how clusters are determined the way cluster head is chosen duties assigned to the cluster head


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S

DCluster Head

Gateway

Ordinary Node

S: Source

D: Destination


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Objectives for efficient clustering in Ad Hoc Networks

Cluster stability Cluster formations should not frequently change over

time (that causes exchange of significant volume of control messages)

Energy preservation Mobile nodes are highly dependant to their battery

power Energy consumption should be balanced among

mobile nodes Minimal usage of network resources for cluster

control Network bandwidth should be available for data

exchange, not control messages exchange


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Clustering Algorithms: Lowest ID (LID)

Mobile nodes are assigned unique IDs

Nodes transmit their ID (through a special ‘Hello’

message) in a given Broadcast Period

Each node ‘elects’ as cluster head the node with

the lowest-ID in the neighborhood


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1 6

11

Clustering Algorithms: Lowest ID (LID)

1

Cluster Head

Ordinary Node

2

4 3

8

12

6

7

9

13

11

1415

510


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Clustering Algorithms: Highest Degree (HD)

Cluster Head

Ordinary Node

12

4 3

8

12

6

7

9

13

11

1415

510

3

8

15

Clustering based on location information the node with the largest number of

neighbors is elected as CH


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Clustering Algorithms: Vote-Based Clustering (VC)

CH elections are based not exclusively on location

but also on the battery power level of mobile nodes

nodes with high degree (large number of neighbors)

and sufficient battery power are elected as CHs


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Disadvantages of Existing Clustering Algorithms LID: CHs election is biased in favor of nodes with low IDs

these nodes are likely to serve as CHs for long time and their

energy supply rapidly depletes

HD and VC methods imply cluster instability losing contact of a single node (due to node movement), may

cause failure of the current CH to be re-elected

A CH may end up dominating so many nodes that its

computational, bandwidth and battery resources will rapidly

exhaust

Common disadvantage of LID, HD, VC: cluster formation

is based on the periodic broadcast of ‘Hello’ messages In relatively static MANETs (e.g. e-classrooms), this ‘storm’

of control messages only verifies that cluster structure

should remain unchanged


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Adaptive Broadcast Period (ABP) clustering algorithm: objectives

A quick method for cluster formation is needed required speed should not be achieved at the expense

of instable cluster configurations we extend VC algorithm so as to avoid frequent CH

‘re-elections’ Balanced distribution of energy consumption Cluster sizes should be controlled

not too large neither too small clusters For relatively static MANET topologies, broadcast

period should be dynamically adapted to avoid unnecessary control message exchanges


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ABP algorithm: cluster formation

We introduce the concept of “cluster head competence” (CHC) which represents the competence of a MH to undertake the role of a CH

Format of ‘Hello’ message:

MH_ID: the ID of the mobile node CH_ID: the ID of the mobile node’ s CH CHC: cluster head competence value of the mobile

node BP (Broadcast Period): used to adapt the broadcast

period within a particular cluster

MH_ID CH_ID CHC BP

8 bit 8 bit 8 bit 8 bit


11-13 Nov 2005

ABP algorithm: cluster formation

Cluster head competence (CHC) values are calculated according to:

CHC = (c1 × d + c2 × b) – p c1, c2: weighted coefficients of node degree and

battery availability, respectively (c1 + c2 = 1)

d: Number of neighbors (degree of MH) b: Remaining battery lifetime (percentage of

remaining over full battery power) p: ‘handover’ penalty coefficient (used to avoid

frequent CH re-elections)

Mobile nodes with maximum CHC value in the neighborhood (maximum degree and battery availability) become CHs


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ABP execution example

12

43

8

12

6

7

9

13

11

1415

5

10


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MH ID d b CHC

1 6 4 3,8

2 4 5 3,6

3 4 3 2,4

4 3 4 2,6

5 2 2 1

6 5 4 3,4

7 5 2 2,2

8 5 1 1,6

9 5 4 3,4

10 5 5 4

11 2 4 2,2

12 5 2 2,2

13 3 4 2,6

14 2 7 4

15 4 2 1,8


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12

4 3

8

12

6

7

9

13

11

1415

5

10

1

Cluster Head

Ordinary Node

2

4 3

8

12

6

7

9

13

11

1415

5

10

1 6

11


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Dynamically Adaptive Broadcast Period for control messages exchange

A principal objective of ABP algorithm is to reduce the number of control messages within the MANET

The broadcast period (BP) should adapt on mobility pattern of mobile nodes For highly mobile nodes, BP is shortened For relatively static MANETs (e.g. e-classrooms) BP is

lengthened, relaxing the MANET from unnecessary control messages


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Measuring mobility rate

Mobility rate is measured by CHs by keeping record of their neighbors at the end of every BP

Mobility rate: The sum of nodes removed and added between successive BPs

12

4 3

8

12

5

1

23

912

5

1

14

3

8

12

1

2

3

5

BP #1 BP #2

BP #3 BP #4

4

8 912

9

14 8

122

5


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Simulation results: number of control messages

0

200.000

400.000

600.000

800.000

1.000.000

1.200.000

1.400.000

1.600.000

1.800.000

2.000.000

0 3 6 9 12 15Average Speed of MHs (m/sec)

# C

on

tro

l Mes

sag

es

LID HD VC ABP


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Simulation results: cluster stability

0

5

10

15

20

25

30

20 40 60 80 100 120Network Size (# MHs)

Ave

rag

e C

H C

han

ges

LID HD VC ABP


11-13 Nov 2005

Simulation results: balancing energy consumption distribution

0

10

20

30

40

50

60

70

80

20 40 60 80 100 120Network Size (# MHs)

Var

ian

ce o

f P

ow

er L

evel

LID HD VC ABP


11-13 Nov 2005

Conclusions

A novel algorithm with the following strengths: clustering procedure is completed quickly (within

three ‘Hello’ cycles) both location and battery power metrics are taken into

account in clustering process derived cluster formations exhibit enhanced stability

by preventing unnecessary CH re-elections for relatively static network topologies, control traffic

volume is minimized Slightly increased control (‘Hello’) packet size


11-13 Nov 2005

Thank you!Thank you!Questions? Questions?

pci 2005 volos, greece 11-13 nov 2005 efficient active clustering of mobile ad-hoc networks damianos...

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