A BROADCASTING ALGORITHM USING ADJUSTABLE

TRANSMISSION RANGES IN MOBILE AD HOC NETWORKS

Toshihiko Sasama, Yasuhiro Abe

Department of Information and Knowledge Engineering, Tottori Univercity, Koyama town, Tottori prefecture, Japan

Hiroshi Masuyama

Department of Information and Knowledge Engineering, Tottori Univercity, Koyama town, Tottori prefecture, Japan

Keywords: Mobile ad hoc networks, virtual backbone, protocol, broadcast, 2-level clustering approach, 1-level flat

approach, 2-level clustering mesh approach, 1-level flat mesh approach, energy consumption.

Abstract: Reducing energy consumption is one of the major subjects in designing a good broadcasting algorithm for

mobile ad hoc networks. This paper discussed 2 approaches to communication algorithms; 2-level clustering

mesh approach and 1-level flat mesh approach, and proposes one of them which makes it appear that the

total amount of expended energy becomes lesser. (Wu and Dai, 2004) previously proposed 2 approaches; 2-

level clustering approach and 1-level flat approach. In mobile ad hoc networks mobile hosts move

frequently, and these moves may cause a change in communicating relationships. In designing a minimum

energy routing protocol for these mobile ad hoc networks with this inherent property, the use of a virtual

backbone has become popular. This study (Wu and Dai, 2004) is based on the virtual backbone conception.

Our 2 proposed approaches change the clustering performed in (Wu and Dai, 2004) into mesh so that energy

consumption becomes smaller. The efficiency of the 1 level flat mesh approach is confirmed through our

simulation study.

1 INTRODUCTION

Mobile ad hoc networks (simply MANET) consist of

wireless mobile hosts that communicate without the

need of any fixed infrastructure. Broadcasting is a

process in which the same massage is delivered to

every node. An overhead in MANET comes from

this broadcasting or blind flooding which is a

process to determine a necessary route in ordinary

one-to-one routing protocols in MANET.

Broadcasting or flooding may generate excessive

redundant message derivation. This redundant

message derivation causes not only a broadcast

storm problem (Tseng, Ni, Chen and Sheu, 2002)

but also serious redundant energy consumption. An

efficient broadcasting route is a conventional Steiner

tree which leads to NP-hard. Although MANET has

no physical backbone infrastructure, a virtual

backbone can be formed by nodes in a connected

dominating set (CDS) of unit-disk graph (Wu and

Dai, 2004) of a given MANET. More concisely, a

virtual backbone is an exclusive communication

path framed among imaginary partitioned groups.

The concept of this virtual backbone is powerful for

saving communication energy. Fig.1 (a) and (b)

shows the two broadcast processes; one using the

concept of a virtual backbone and the other without,

respectively. By way of the arrows depicted in the 6

frames of each graph, all necessary one-to-one

communications necessary to perform a broadcast

from source node s is described. Fig.1 shows that the

broadcasting process using the concept of a virtual

backbone requires fewer arrows, this means less

energy consumption.

Virtual Multicast Backbone (VMB) structures

are commonly used in current multicast protocols.

Instead of the conventional Steiner tree model, the

optimal shared VMB in ad hoc networks is modeled

as a Minimum Steiner Dominating Set in Unit-Disk

Graphs (Ya-feng, 2004) which leads also to NP-

hard.

Energy-efficient broadcasting has been widely

studied. Several protocols have been proposed to

123

Sasama T., Abe Y. and Masuyama H. (2008).

A BROADCASTING ALGORITHM USING ADJUSTABLE TRANSMISSION RANGES IN MOBILE AD HOC NETWORKS.

In Proceedings of the Fourth International Conference on Web Information Systems and Technologies, pages 123-128

DOI: 10.5220/0001521201230128

 SciTePress

manage energy consumption by adjusting

transmission ranges. For a comprehensive survey on

various aspects of broadcasting in MANET, refer to

(Stojmenovic and Wu, 2004). In this paper, we use

the static and source-independent approach for CDS

construction since it is more genetic. It is also

assumed that no location information is provided, as

was similarly mentioned in (Wu and Dai, 2004).

The remainder of this paper is organized as

follows: In Section 2, we introduce some

preliminary knowledge required to understand 2 new

protocols. The 2 level clustering mesh approach and

1 level flat mesh approach are introduced in Section

3. Section 4 shows our simulation experiences and

results. Finally, we will conclude in Section 5.

2 PRELIMINARIES

Instead of a physical backbone infrastructure,

MANET can form a CDS, as mentioned before. (Wu

and Li, 1999) proposed the “marking process” which

is a self-pruning process to construct a CDS: Each

node is marked if it has two unconnected neighbors,

otherwise it is unmarked. The marked nodes form a

CDS, which can be further reduced by applying

pruning rules (Dai and Wu, 2003).

Step.[1] Step.[2] Step.[3]

Step.[4] Step.[5] Step.[6]

Step[1] : A source node uploads.

Step[2] : The □ node transfers the data to every node and other

□ nodes in a range.

Step[3] – [6] : Similarly, the □ node transfers the data.

Figure 1(a): A broadcast process using the concept of

virtual backbone.

Pruning rule k: A marked node can unmark itself if

its neighbor set is covered by a set of connected

nodes with higher priorities.

The clustering approach is commonly used to

offer scalability and is efficient in a dense network.

Basically, the network is partitioned into a set of

clusters, with one cluster-head in each cluster.

Cluster-heads form a DS which is a subset of

nodes in the network where every node is either in

the subset or a neighbor of a node in the subset. No

two cluster-heads are connected. Each cluster-head

connects to all its members (non-cluster-heads) in

most k hops, which originates from the k-level

clustering approach. The classical clustering cluster

formation works are stated in (Wu and Dai, 2004):

(1) A node v is a cluster-head if it has the highest

priority in its 1-hop neighborhood including v. (2) A

cluster-head and its neighbors form a cluster and

these nodes are covered. (3) Repeat (1) and (2) on

all uncovered nodes.

Two new approaches to construct a backbone

will be proposed and discussed in this paper. These

approaches originate from two approaches; 2-level

clustering and 1-level flat approaches. In the lower

level of 2-level clustering, the network is covered by

the set of cluster-heads under a short transmission

Step.[1] Step.[2] Step.[3]

Step.[4] Step.[5] Step.[6]

Step[1] : A source node transfer the data to every node in a range.

Step[2] : Receiving nodes transfer the data to every node in a

range.

Step[3] – [6] : Similarly, receiving nodes transfer the data.

Figure 1(b): A broadcast process using none of the

concepts of a virtual backbone.

（● ：Source node, ○：Node, □：The node which communicates between the groups,

Circle in broken line[

]：Group, ：Data transfer, ：Data transfer between groups）

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range. In the upper level, all cluster-heads are

covered by the set of marked cluster-heads under a

long transmission range. Conversely, the 1-level flat

approach constructs a flat backbone, where the

network is directly covered by the set of marked

cluster-heads having a long transmission range.

2.1 2-level Clustering Approach

As mentioned above, this approach uses different

transmission ranges at different levels to connect not

only non-cluster-heads and cluster-heads but also to

connect cluster-heads where gateway nodes are

required to make selections.

Marking process on cluster-heads and marked

cluster-heads:

1. Select a node with the highest priority among

nodes which belong to none of the cluster

heads and let it be a cluster-head. Every

node in the cluster-head’s range of (1/3)r

belongs to the cluster-head.

2. Continue process 1 until every node is a

cluster-head or belongs to any one of the

existent cluster-heads.

3. Select a cluster-head which has the most

cluster-heads laid in its range of r and at

least one of them does not lay in every other

cluster-head. Let this be the first marked

cluster-head.

4. Select a cluster-head which has the most

cluster-heads laid in its range of r and lays

itself within the range of any other marked

cluster-heads of r.

5. Continue process 4 until all such cluster-

heads are gone.

Broadcast process:

1. A source node uploads its own data to the

cluster-head.

2. The cluster transfers the data to a marked

cluster-head located within the range of r.

3. The marked cluster-head transfers the data to

every cluster-head and marked cluster-head

within the range of r.

4. Receiving marked cluster-heads change into

transferors for the data if the data is new.

Conversely, receiving cluster-heads

automatically broadcast data within their

own range.

5. The process 4 terminates when every node

receives data sent by the source.

Figure 2 (a) shows a broadcasting process based on

this approach.

2.2 1-level Flat Approach

Though the two marking processes for cluster-heads

and marked cluster-heads are the same as in the

above approach, using a uniform transmission range

can prevent redundant energy consumption.

Marking process on cluster-heads and marked

cluster-heads:

1. Select a node with the highest priority among

nodes which belongs to no cluster head and

let it be a cluster-head. Every node in the

cluster-head’s range of (1/4)r belongs to the

cluster-head.

2. Continue process 1 until every node is a

cluster-head or belongs to any other cluster-

head.

3. Select a cluster-head which has the most

cluster-heads laid within its range of r and at

least one of them does not lay in every other

cluster-head. Let it be the first marked cluster-

head.

4. Select a cluster-head which has the most

cluster-heads laid within its range of r and

one which lays itself within the range of r of

any other marked cluster-heads.

5. Continue process 4 until such a cluster-heads

are gone.

Broadcast process:

1. A source node uploads its own data directly

to the marked cluster-head.

2. The marked cluster-head broadcasts the data

to every node (other marked cluster-heads,

cluster-heads, and nodes) located within its

range of r.

3. The process 4 terminates when every node

receives data sent by the source.

Fig.2(b) shows a broadcasting process based on this

approach.

3 2-LEVEL CLUSTERING MESH

APPROACH AND 1-LEVEL

FLAT MESH APPROACH

A mesh-clustering protocol is introduced to the

above two approaches. A given domain is divided by

N×N lattices. In the following marking process, let

R=r1 in the 2-level mesh approach and let R=r2 in

the 1-level mesh approach where r1 and r2 are

shown in Fig.3.

A BROADCASTING ALGORITHM USING ADJUSTABLE TRANSMISSION RANGES IN MOBILE AD HOC

NETWORKS

125

Marking process on cluster-heads and marked

cluster-heads:

1. Select the most central node in each lattice

and let it be the cluster-head in the lattice

and let randomly distributed nodes in the

lattice be subordinate nodes of the cluster-

head in the lattice.

2. Select a cluster-head which has the most

cluster-heads laid in its range of r and at

least one of them does not lay in every other

cluster-head. Let it be the first marked

cluster-head.

3. Select a cluster-head which has the most

cluster-heads laid within its range of r and

lays itself within the range r of any other

marked cluster-heads.

4. Continue process 3 until such cluster-heads

are gone.

Fig.4 (a) shows marked cluster-heads and cluster-

heads nominated based on this process and for

reference, and Fig.4 (b) shows them based on the

previous 2-level clustering approach.

(a)2-level clustering approach (b)1-level flat approach

Figure 2: Examples of broadcast processes based on two

approaches.

Figure 3: Two ranges in 2-level clustering and 1-level flat

mesh approaches.

Broadcast process: 2-level and 1-level mesh

approaches adopt the same broadcast

processes as those of the 2-level clustering

approach and the 1-level flat approach,

respectively.

Fig.5 (a) and (b) show a broadcasting process based

on these approaches.

4 SIMULATION EXPERIENCES

AND RESULTS

We adopt a commonly encountered model of a

network where n homogeneous nodes are randomly

thrown in a given region S, both uniformly and

independently. If more than two neighbors of a

node transmit simultaneously, the node is assumed

to receive no message. The neighbors of a node are

not permanent within a number of slots, because of

unstable network topology.

(a) 2-level clustering mesh (b) 2-level clustering

approach approach

Figure 4: Marked and non-marked cluster-heads

nominated based on two approaches.

（Shaded part is a duplication of clusters）

(a) 2-level clustering (b) 1-level flat

mesh approach mesh approach

Figure 5(a)(b): Examples of broadcast process based on

two new approaches.

( ●：Source node, ○：Node, △：cluster-head, □：marked cluster-head,

Circled by broken line[

]：Transmission range for upload, ：Data upload,

Circled by dotted line [ ]：Transmission range for broadcast, ：Data broadcast )

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4.1 Simulation Experience

This section describes the input parameters and

output measures for the evaluation of the volume of

energy consumption in 4 kinds of clustering. For the

purpose of our simulation, we consider a 100×100

square domain where 1000 nodes are randomly

distributed. In mesh approaches, we set the square

domain divided by1×1(=N×N), 2×2, …, 9×9, and 10

×10. We evaluate the volume of energy consumption

for the broadcasting in transmitting range r as r

(Wieselthier and Nguyan and Ephremides, 2000).

We used the same value of r (=24m) as shown by

(Wu and Dai, 2004). We also performed

experimentation in the case where N is fixed as 3 but

the total number of nodes are 100,200, …,1000.

4.2 Results

Fig.6 shows the number of marked cluster-heads for

different numbers of divisions. Fig.7 shows the

ranges of each cluster-head and marked cluster head

for different numbers of divisions. Figs.8 and 9

show the energy consumption for different numbers

of divisions and for different numbers of distributed

nodes, respectively. These results mean that 1-level

mesh approach provides excellent results, especially

when 3×3.

4.3 Improved Methods and the

Simulation Results

The above results show that the efficiency of 1-level

flat mesh approach can be confirmed. However, both

this approach and the 2-level clustering mesh

approach require an extremely large amount of

energy in special nodes (marked cluster-heads),

making this a problem. This problem is more

evident when the divided square domains become

smaller. We further evaluated the volume of energy

consumptions required in the case where two ranges

in 2-level clustering and 1-level flat mesh

approaches are restricted in the smaller sizes as

shown in Fig.10. These restrictions make the number

of marked cluster-heads larger but the load of each

marked cluster-head smaller. Figs.11 (a), (b) and (c)

show the energy consumption for different numbers

of divisions in the cases of 100, 500, and 1000

nodes, respectively. These results show that the

improved 1-level flat mesh approach proves to be

superior when the number of divisions becomes

larger.

12345678910

Number of divisions

Number of

marked clust er- heads

2- level clust ering

1- level flat

2- level mesh， 1-level mesh

Figure 6: Number of marked cluster-heads for different

number of divisions.

100

120

12345678910

Number of divisions

Transmission ranges

clust er- head (2- level mesh)

marked clust er- head (2- level mesh)

marked clust er- head

(

1- level mesh

)

Figure 7: Ranges of each cluster-head and marked cluster

head for different numbers of divisions.

10000

13000

16000

19000

22000

25000

12345678910

Number of divisions

Energy consumption

2- level clust ering 1- level flat

2- level mesh 1- level mesh

Figure 8: Energy consumption for different numbers of

divisions.

10000

12000

14000

16000

18000

20000

100 200 300 400 500 600 700 800 900 1000

Number of nodes

Energy consumption

2- level clust ering 1- level flat

2- level mesh

[

3× 3

]

1- level mesh

[

3× 3

]

Figure 9: Energy consumption for different numbers of

distributed nodes.

A BROADCASTING ALGORITHM USING ADJUSTABLE TRANSMISSION RANGES IN MOBILE AD HOC

NETWORKS

127

(a)2-level clustering (b)1-level flat mesh

mesh approach approach

Figure 10: Restricted range in (a) 2-level clustering mesh

and (b) 1-level flat mesh approaches.

（● ：Source node, ○：Node, △：cluster-head,

□：marked cluster-head）

10000

15000

20000

25000

30000

12345678

Number of divisions

Energy consumption

2- level mesh(8近傍) 2- level mesh(4近傍)

1- level mesh

(

8近傍

)

1- level mesh

(

4近傍

)

(a)The case of 100 nodes.

10000

13000

16000

19000

22000

25000

12345678910

Number of divisions

Energy consumption

2- level mesh(8近傍) 2- level mesh(4近傍)

1- level mesh(8近傍) 1- level mesh(4近傍)

(b)The case of 500 nodes.

10000

20000

30000

40000

12345678910

Number of divisions

Energy consumption

2- level mesh(8近傍) 2- level mesh(4近傍)

1- level mesh

(

8近傍

)

1- level mesh

(

4近傍

)

(c)The case of 1000 nodes.

Figure 11: Energy consumption for different numbers of

divisions in the cases of (a)100, (b) 500 and (c) 1000

distributed nodes.

5 CONCLUSIONS

Reducing energy consumption is one of the major

objectives in designing a good broadcasting

algorithm for mobile ad hoc networks. This paper

discussed 2 approaches to communication

algorithms; 2-level clustering mesh approach and 1-

level flat mesh approach, and proposes one of them

which makes it appear as though the total amount of

expended energy becomes lesser. Our 2 proposed

approaches not only use the concept of a virtual

backbone but also adopt mesh in clustering so that

energy consumption becomes less. The efficiency of

1-level flat mesh approach is confirmed through our

simulation study.

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