A Distributed Broadcast Algorithm

for Ad Hoc Networks

Li Layuan, Li Chunlin, Sun Qiang

School of Computer Science, Wuhan University of Technology, Wuhan, 430063, P. R. China

Abstract. In mobile ad hoc networks, many unicast and multicast protocols

depend on broadcast mechanism to finish control and route establishment

functionality. In a straightforward broadcast by flooding, each node will

retransmit a message to all it neighbors until the message has been propagated

to the entire network. So it will become very inefficient and will be easy to

result the broadcast storm problem. Thus an efficient broadcast algorithm

should be used to less the broadcast storm caused by broadcast. Due to the

dynamic nature of ad hoc networks, global information of the network is

difficult to obtain, so the algorithm should be distributed. In this paper, an

efficient distributed heuristic-based algorithm is presented. The algorithm is

based on joint distance-counter threshold scheme. It runs in a distributed

manner by each node in the network without needing any global information.

Each node in an ad hoc network hears the message from its neighbors and

decides whether to retransmit or not according to the signal strength and the

number of the receiving messages. By using the JDCT algorithm, it’s easy to

find the nodes that consist of the vertices of the hexagonal lattice to cover the

whole networks. The algorithm is very simple and it is easy to operate and has a

good performance in mobile wireless communication environments. A

comparison among several existing algorithms is conducted. Simulation results

show that the new algorithm is efficient and robust.

1 Introduction

In mobile ad hoc networks, the research of routing is still at the beginning and some

routing protocols have been put forward [1-10]. Most of these protocols depend on a

broadcast mechanism [9-10]. In flooding, each node that receives a message

retransmits that message to all it neighbors until the message has been propagated to

the entire network. Despite its poor scalability and inefficient bandwidth usage [9],

flooding is very useful because it can achieve maximal coverage, distance

preservation, and redundancy. Without any reliance on knowledge about the network

topology, flooding performance does not degrade with increased node mobility [10].

In this paper, we assume that mobile nodes in the mobile ad hoc networks share a

single common channel and global network topology information is unavailable for

each node. So each node of such a network can only communicate by broadcast. In

order to less the broadcast storm [9], an efficient broadcast algorithm based on joint

distance-counter threshold is proposed, which can run without any neighborhood

Layuan L., Chunlin L. and Qiang S. (2006).

A Distributed Broadcast Algorithm for Ad Hoc Networks.

In Proceedings of the 5th International Workshop on Wireless Information Systems, pages 86-93

 SciTePress

information. This drastically reduces the effect of the mobility and no exchanged

messages and control messages are needed. The goal of joint distance-counter

threshold is to provide both a satisfied coverage and less broadcast and average

latency, which a high coverage is guaranteed by distance threshold and a high saved

broadcast and less average latency are guaranteed by counter threshold.

2 Notations and Assumptions

The symbols and definitions used in this paper are defined as follows:

Definition 1: The distance

(

)

yxd ,

between two nodes x and y in

(

)

is defined the

distance between x and y within their transmission range r,

(

)

ryxd

≤

Definition 2:

)(xc

denotes the number of received messages in node x during

broadcast.

Definition 3:

denotes a distance threshold, where

≤

Definition 4:

denotes a counter threshold, where

0≥

Definition 5:

()

is a set of neighbors of node x, where for each neighbor

(

)

ryxd ≤,

. For example, in Fig.2, the neighbors of node 1 consist of node 2, 3 and

they can represent as

() { }

3,21 =N

Definition 6:

()

is a subset of

(

)

(

)

xNxI ⊆)(

where for each of its member y,

()

xIy ∈

and

(

)

Dyxd ≤,

. In Fig. 2,

(

)

{

}

Definition 7:

()

is a subset of

(

)

(

)

xNxE ⊆)(

where for each of its member y,

()

xEy ∈

and

()

ryxdD

≤< ,

. For instance, in Fig. 2,

(

)

{

}

Definition 8:

()

SRt

is a set of nodes that retransmit the message from source node

S, where

{}{}

{}

{ }

()

12 12

()

| ()() () ()() (),()

,,,

kkTH

Rt S

x x Ex Ex Ex x Ex Ex Ex cx C

xx x Nx

∈∉<

∈

∩∩ ∪ ∩∩



3 Joint Distance-Counter Threshold Broadcast Algorithm

In this section, an efficient distributed heuristic-based algorithm is presented. The

goal of the proposed algorithm is to reduce the number of rebroadcasts without

consume much resources of the network, such as bandwidth and energy.

3.1 Details of the Algorithm

When a transmission of a broadcast message M by the source node occurred, all its

neighbors will receive M in the same time. In order to alleviate the broadcast storm

problem [9], a node has to assess the redundancy of a broadcast and decide whether to

rebroadcast or not. The redundancy of a broadcast associates with the additional

coverage caused by the source node and all its neighbors. [9] has revealed the

relationship between the redundancy of a broadcast and the additional coverage. The

further the distance between the source node and its neighbors is, and the larger

additional coverage can be acquired. Moreover, the more neighbors of a node are, the

less additional coverage is acquired.

Based on these relationships, joint distance-counter threshold broadcast algorithm

is proposed in this paper. In this algorithm, according to the distance of its neighbors

and the number of the received message, each node decides whether to retransmitting

M or not. First, when a node x send a broadcast message M, all its neighbors will hear

M and compute

()

yxd ,

according the receiving signal strength [24]. If

(

)

,,()

iThi

dxy D y Nx>∈

then wait for a short time which is determined by a distance

and counter relevant function. The delaying helps to avoid many nodes to transmit all

at once. If node

hasn’t received any messages during this short delay, it will

transmit M at once. Otherwise; it will compute the distance from the sending node

again. If

(

)

,,()

iThi

dxy D y Nx≤∈

then depend on the number of the received message in

node

to decide whether to retransmitting M or not. And if

()

iTh

cy C

, node y

will

wait a short delay and if there is not any other messages heard in this period, it will

transmit M immediately. If

Thi

Dyxd ≥),(

then wait for a short time again.

3.2 Analysis

In flooding, each node has to retransmit the broadcast message. However, if a node is

“covered” by other nodes, it needn’t retransmit ever. The goal of an efficient

broadcast algorithm has to find the covered nodes and let those “uncovered” nodes

retransmit the message.

In [25], Kershner has pointed out that the hexagonal lattice is the most efficient

arrangement to cover the plane (Fig.1. a). If the vertices of such hexagonal lattice are

consisted by nodes of ad hoc networks, the broadcast message transmitted only by

these nodes can reach all nodes in a network.

(a) (b) (c)

Fig. 1. The coverage problem.

Lemma 1: The JDCT algorithm can find the nodes that consist of the vertices of

the hexagonal lattice if these nodes exist.

Proof. As we know, in a regular polygon that each side is d (Fig.1. b), we can get

Proof. According to lemma 1 and lemma 2, through adjust the value of

and

the algorithm gets a high rebroadcast saving both in even and uneven distributed ad

hoc networks. According to lemma 3, each node decides whether to retransmit or not

only with limited steps. And according to lemma 4, the algorithm is distributed,

parameter-less and less communication overhead. Therefore, the JDCT algorithm

satisfies the properties of the efficient distributed broadcast algorithm.

□

4 Simulation Results

To evaluate the new broadcast algorithm and compare it to existing algorithms,

simulations are performed. A Mobility Framework for OMNeT++ (a discrete event

simulator written in C++, described in [25]) is used as a tool. The size of the network

is 100 nodes in a 10

00*1000 meter square. The nodes are uniformly distributed all

over the region. Nodes in the simulation move according to “random waypoint”

model [27]. The mobility speed of a node is set from 0m/s to 30m/s. The CSMA/CA

is used as the MAC layer in our experiments. The transmitting radius of each node is

about 231 meters and channel capacity is 10Kbits/sec. Four distributed broadcast

algorithms are chose to be compared and they are listed below.

− SB: straightforward broadcast algorithm

− DB: distance-based broadcast algorithm

− CB: counter-based broadcast algorithm

− JDCT: JDCT broadcast algorithm

The performance measures of interest are:

• Average latency: defined as the interval between its arrival and the moment

when either all nodes have received it or no node can rebroadcast it further.

• Ratio of Saved Rebroadcast (RSR): The total number of nodes not delivered

broadcast packets is divided by the total number of nodes receiving the broadcast

message.

• Ratio of Collision (RC): The total number of collision is divided by the total

number of packets supposed to be delivered during broadcast.

• Total Number of Contention (TNC): the total number of contention during

broadcast.

• Total Number of Received Messages (TNRM): the total number of received

messages is the sum of the number of messages heard by each node during broadcast.

The first set of experimental results (Fig.2) demonstrates average RSR versus

distance threshold using distance-based algorithm and JDCT algorithm with R=1. The

result shows that JDCT algorithm obtains higher SRS than the distance-based

algorithm. When

0.9 210meters

Dr≈=

, the RSR of both distance-based algorithm

and JDCT algorithm get their maximum value of SRS, about 52% in JDCT and 28%

in DB. This is understandable, because with the increase in threshold value, number

of retransmitting nodes decrease. When

0.9

, the distance-based algorithm can’t

cover the whole network in our simulation scenarios, however, the JDCT can cover

the whole network. When

0.87

rD r

≤

, the JDCT can find nodes to consist of the

vertices of the hexagonal lattice. Thus a high RSR value can be acquired. As the

threshold value increases, there are not enough nodes to be found by DB to cover the

whole network. However, although nodes selected by the distance threshold are not

enough to consist of the vertices of the hexagonal lattice, as the counter threshold is

used, the JDCT can also keep a full coverage to the network.

80 100 120 140 160 180 200 220 240 260

RSR (%)

Distance Treshold (m)

JDCT

Fig. 2. Distance threshold

vs. RSR (R=1).

In Fig.3-5, the results are gotten with the parameters of

3,9.0,1 =

ThTh

CrDR

Fig.6 shows the ratio of saved rebroadcast using different algorithms with varying

node speeds (from 0 to 30m/sec). The average latency of different broadcast

algorithms with varying node speeds is reported in Fig.4. Fig.5 gives the ratio of

collision in different algorithms with varying node speeds.

0 5 10 15 20 25 30

RSR(%)

Mobility Speed (m/s)

JDCT

Fig. 3. Ratio of Saved Rebroadcast vs. Mobility speed.

0 5 10 15 20 25 30

200

250

300

350

400

450

500

550

600

Average Latency (ms)

Mobility Speed (m/s)

JDCT

Fig. 4. Average Latency vs. Mobility speed Ratio of Saved Rebroadcast vs. Mobility speed.

0 5 10 15 20 25 30

0.0

0.1

0.2

JDCT

RC(%)

Mobility Speed (m/s)

Fig. 5. Ratio of Collisions vs. Mobility speed.

5 Conclusion

Building efficient broadcast algorithm for ad hoc networks is challenging due to the

dynamic of the nodes. In ad hoc networks, centralized algorithms are not suitable

because the global information is impossible to get. And as ad hoc network is a

multihop networks, there always exists hidden/exposed terminals. Many broadcast

algorithms depended on local information such as k-hop neighbor information will

not get a desirable performance when local information cannot be acquired correctly.

As ad hoc networks are resource-limited networks, algorithms based on exchanging

control messages such as

hello message are also unsuitable. And some algorithms

used GPRS are constrained by nodes’ limited energy.

In this paper, an efficient distributed heuristic-based algorithm named JDCT

algorithm is presented. The algorithm is based on joint distance and counter threshold

scheme. It runs in a distributed manner by each node in the network without needing

any global information. The experiments have demonstrated the efficiency of

proposed broadcast algorithm. The broadcast storm problem is alleviated by

significant reduction in the number of rebroadcast nodes, contention and collision in

the network. Its efficiency and robustness in mobile networks make it a good choice

for mobile ad hoc networks. Our future work includes a performance evaluation of the

JDCT broadcast algorithm in realistic simulation environments with packet collision

and node mobility. In addition, we will embed our JDCT algorithm to some routing

protocols such as AODV protocol to investigate its efficiency in ad hoc networks.

Acknowledgments

This work is proudly supported in part by the Grand Research Problem of the

National Natural Science Foundation of China under Grant No. 90304018 and Wuhan

key project.

References

1. Li Layuan, Li Chunlin. A QoS multicast routing protocol for dynamic group topology [J].

Inf. Sci., 2005,169(1-2): 113-130.

S.Ramanathan, Martha Steenstrup. A survey of routing techniques for mobile

communications networks [J]. Mobile Networks and Applications, 1996, 1(2): 89-104.

C. E. Perkins, E. M. Royer. Ad hoc on-demand distance vector (AODV) routing[C]. In

Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications,

Feb. 1999.

Li Layuan,Li Chunlin.Ａ routing protocol for dynamic and large computer networks with

clustering topology [J]. Computer Communications, 2000, Elsevier, UK, 23(2): 171-176.

Sung-Ju Lee, William Su, Mario Gerla. Ad hoc Wireless Multicast with Mobility

Prediction[C]. IEEE ICCCN'99, Boston, MA, Oct. 1999.

David Johnson, David Maltz. Dynamic source routing in ad hoc wireless networks [J].

Mobile Computing, Boston: Kluwer Academic Publishers, 1996

Li Layuan, Li Chunlin. A distributed QoS-aware multicast routing protocol [J]. Acta

Informatica, Springer, Germany, 2003, 40 (3): 221-233.

J. Cartigny and D. Simplot, Border Node Retransmission Based Probabilistic Broadcast

Protocols in Ad-Hoc Networks [C]. In Proc. 36th International Hawaii International

Conference on System Sciences (HICSS’03), Hawaii, USA. 2003.

Y.-C. Tseng, S.-Y. Ni, Y.-S. Chen, and J.-P. Sheu. The Broadcast Storm Problem in a

Mobile Ad Hoc Network [J]. Wireless Networks, 2002, 5 (8): 153-167.

10.

E. Royer and C-K. Toh. A Review of Current Routing Protocols for Ad-Hoc Mobile

Wireless Networks [J]. IEEE Personal Communications Magazine, 1999,4: 46-55.