ANALYSIS OF AD HOC ROUTING PROTOCOLS

FOR EMERGENCY AND RESCUE SCENARIOS

Liliana Enciso Quispe

, Rommel Torres Tandazo

and Luis Mengual Galan

Research Institute of Computer Science, Technical University of Loja, San Cayetano alto, Loja, Ecuador

Department of Computing, Politechnical University of Madrid, Monte de Boadilla, Madrid, Spain

Keywords:

Ad Hoc Networks, MANET, Routing, Mobility Models, AODV, DSDV, CBRP.

Abstract:

A mobile ad hoc network MANET is a collection of wireless mobile nodes that can dynamically conﬁgure a

network without a ﬁxed infrastructure or centralized administration. This makes it ideal for emergency and

rescue scenarios where information sharing is essential and should occur as soon as possible. This article

discusses which of the routing strategies for mobile ad hoc networks: proactive, reactive and hierarchical,

have a better performance in such scenarios. Using a real urban area being set for the emergency and rescue

scenario, we calculate the density of nodes and the mobility model needed for validation. The NS2 simulator

has been used in our study. We also show that the hierarchical routing strategies are beffer suited for this type

of scenarios.

1 INTRODUCTION

Mobile Ad Hoc Networks(MANET), are self conﬁg-

uring and temporary networks . Their nodes can be

the source, destination and bridge information.

In case of emergency and rescue scenario, the to-

pography is different in the amount of obstacles that

may arise due to the occurrence of a undesired events

causing the normal mobility pathways to alter. There-

fore, the algorithm of motion is determined according

to the topography, and the corresponding nodes must

be moved depending on the obstacles. The number

of nodes depends if the MANET network is in an ur-

ban or in a rural area. When an unwanted event has

occurred, it changes the pathways of normal mobil-

ity. Therefore new routes for evacuation and or rescue

should be calculated.

When MANET are used in emergency and res-

cue scenarios, the choice of robust network protocol

is essential, because it involves indirect integrity of

the person using the mobile device. If a device is not

reachable by the network, the events of personal seach

and rescue should be desconected from the device.

The main objetive of this paper is to determine

wich one of the ad hoc routing strategies proactive, re-

active and hierarchical performs better in emergency

and rescue operations. For this reasor we have chosen

en area of the city of Loja Ecuador to simulate these

protocols supported by the NS2 tool.

2 RELATED WORK

2.1 Routing Protocols for Mobile Ad

Hoc Networks

The network layer (Ali et al., 2008), with respect to

the OSI reference model, is where one performs and

identiﬁes the processes of ad hoc networks. There-

fore, any improvement effort in this layer is directly

visible in the upper layers.

The routing protocols of ad hoc networks are gen-

erally grouped into proactive, reactive and hierarchi-

cal routing (Overview and Selangor, 2007).

2.1.1 Proactive Routing

Proactive routing protocols maintain information on

all routes throughout the network even if they are not

required so each node maintains routes to all nodes

in the network. These protocols exchange control in-

formation between nodes on a regular basis which

keeps updated routes for each node in the network.

These protocols react when a new node appears or

another node, is no longer within the network topol-

ogy. The known protocols are: Destination-Sequence

Distance-Vector DSDV (Perkins and Bhagwat, 1994)

and Optimized Link State Routing OLSR (rfc3626).

781

Enciso Quispe L., Torres Tandazo R. and Mengual Galan L..

ANALYSIS OF AD HOC ROUTING PROTOCOLS FOR EMERGENCY AND RESCUE SCENARIOS.

DOI: 10.5220/0003941107810786

In Proceedings of the 8th International Conference on Web Information Systems and Technologies (WEBIST-2012), pages 781-786

ISBN: 978-989-8565-08-2

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

Figure 1: Clustered ad hoc network.

2.1.2 Reactive Routing

Reactive routing protocols allow updating of the ta-

bles on demand, for example, when a node wants to

exchange information with another node in the net-

work. They usually have two components: route dis-

covery, which occurs when a node wants to commu-

nicate with a speciﬁc destination and route mainte-

nance, used to manage the path failure caused by the

mobility of the nodes.

The difﬁculty with these protocols is the latency

to initiate communications, they also have a slower

reaction to detect changes in the network topology.

Among the best known protocols are the Dynamic

Source Routing (DSR rcf4728) and Ad Hoc Demand

Distance Vector AODV (Perkins et al., 2003).

2.1.3 Hierarchical Routing

Hierarchical routing protocols divide the network into

subsets of nodes called clusters, where a cluster head

node is used to concentrate and distribute the informa-

tion generated within the cluster. An example of this

type of protocol is the Cluster Based Routing Protocol

(CBRP) (Jiang et al., 1999). Figure 1 shows the ba-

sic components of a hierarchical routing protocol or

cluster.

There are some studies (Agarwal and Motwani,

2009; Biradar and Patil, 2006), that identify and

group the hierarchical routing algorithms or cluster-

ing. These protocols and hierarchical routing strate-

gies focus on the task of choosing the cluster head

and cluster maintenance. For example, (Er and Seah,

2004; Er and Seah, 2005); focus on the choice of clus-

ter based solely on the property of the node mobil-

ity. In turn, (Jiang et al., 1999; Gerla and chieh Tsai,

1995; Amis et al., 2000); perform cluster head elec-

tion used as the deciding factor node identiﬁcation.

(Chen et al., 2002) uses the distance between nodes or

the degree of connectivity for the election.(McDonald

and Znati, 1999) makes the choice of cluster head pe-

riodically in order to save energy. The protocols pro-

posed in (Er and Seah, 2004; Basagni et al., 2001;

Chatterjee et al., 2001) made the choice of cluster

head based on the combined weights of the charac-

teristics of each node.

2.2 Mobility Models for Mobile Ad Hoc

Networks

Mobility models are important because they deter-

mine the behavior of mobile nodes (MN) on stage

(Camp et al., 2002). They can be classiﬁed into two

types: those based on traces (logs of actual move-

ments) [14] and the synthetic (emulate reality by

mathematical equations). Some authors classify mo-

bility models into three groups (Camp et al., 2002):

models based on strokes (work with real mobility),

models based on topology restrictions (real scenario

simulations) and statistical models (study from ran-

domness).

Ad hoc networks do not work yet on models based

on traces on the network characteristics. Howerer, it

is expected that study will expand in future on the ap-

plication of these models (Camp et al., 2002). There-

fore, models of synthetic mobility are used fogether

with simulated scenarios. In order to prove this form

of controlled mobility, certain parameters are used,

which allow to obtain quantiﬁable date and thus to

transform them into useful informaties.

The synthetic models are classiﬁed according to

their relationship with the representation of human

mobility: synthetic mobility models unrealistic, for

example: random models (Divecha et al., 2007) (Ran-

dom Walk Mobility Model, Random Waypoint Mo-

bility Model), temporal dependency models (Hong

et al., 1999; Divecha et al., 2007) (Boundless Simu-

lation Area Mobility Model, Gauss-Markov Mobility

Model, Smooth Random Mobility Model) and real-

istic synthetic mobility models such as: spatial de-

pendence models (Hong et al., 1999; Chenchen et al.,

2010; Chenchen et al., 2010)(Reference Point Group

Mobility, Column Mobility Model, Pursue Mobility

Model, Nomadic Mobility Model) Geographic Re-

striction Models (Chenchen et al., 2010; Aschenbruck

et al., 2008) (Pathway Models, Obstacle Models, Hu-

man Obstacle Mobility Model).

3 PROPOSED SCENARIO

3.1 Emergency and Rescue Scenario for

Centre of the City of Loja

Random obstacles have been deﬁned in this area of

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Figure 2: Loja city map without obstacles.

1000mx500m of the city Loja is used in Ecuador, Fig-

ure 2, that disrupt normal mobility pathways of the

nodes.

3.2 Node Density

The calculation of the node density P

node

is supported

by information obtained from the census of Ecuador

in 2010.

An important factor for the calculation of

the nodes is the percentage of the PEA (Economically

Active Population).

To calculate the density of nodes the following

formula has been proposed:

nodes

∗ F

uel

∗ F

PEA

∗ F

∗ A

(1)

nodes

= 97 (2)

Where:

• zu

- Number of people in the urban areas is 70%

(128910)

• zr

- Number of people in the rural areas is 30%

(85940).

• F

uel

- urban factor speciﬁed for the simulation area

• A

u - Urban area - 6Km x 12Km = 72Km

• F

PEA

- LOJA - PEA is 62% for urban area.

• F

- urban smartphone factor is 25% .

• A

- Chosen area for simulation 0.5km

It is important to describe the city of Loja for

which this study has been done, it is a city in the

southern part of Ecuador. Populatio it the city in-

creases during the holidays, and it grows also due to

arriving of tourists attracted by its location and biodi-

versity. Given this premise, we established percent-

ages of 25.75% (F

)and 30.8% (F

) to calculate the

other two densities nodes P

nodes

, substituting these

values into the formula(1) we ﬁnd that the rearsong

National Institute of Statistics and Censuses (INEC).

http://www.inec.gob.ec

nodes are equal to 100 (25.75%) and 120 ( 30.8%),

respectiving.

Consequently the number of nodes for the simula-

tion is: 97, 100 and 120.

3.3 General Parameters for Simulation

Table 1: General parameters for the simulation of protocols

AODV, DSDV and CBRP.

Parameter Value Observations and

related works

Simulation area 500m x 1000m Area established

within the centre of

the city of Loja

Mobility model Obstacle Mod-

els

Obstacle models

(Chenchen et al.,

2010; Aschenbruck

et al., 2008)

Number of

nodes

97,100 and 120 To determine the

behaviour of pro-

tocols for different

node density

Number of con-

nections

20, 40 random connec-

tions

Time of simula-

tion

150 In seconds

Network layer

protocols

CBRP, DSDV

and AODV

Hierarchical,

proactive and

reactive protocols

Transport layer

protocols

Transmission

control proto-

col (TCP)

A connection-

oriented communi-

cation is needed

Propagation

model

TwoRayGround For ﬂat and unob-

structed scenarios.

Type of antenna Omnidirectional Indispensable qual-

ity of mobile net-

work nodes

To deﬁne the simulation scenarios were used as

the basis used in (Kurkowski et al., 2007a; Kurkowski

et al., 2007b). The values of each one of these values

are shown in the Table 1.

In order to analyze results, some authors have re-

vised set of indicators. For our research we select

some particular indicaters from (Chenna Reddy and

ChandraSekhar Reddy, 2006; Corson and Macker,

1999) in order to measure behavior of protocols.

These indicators are: performance, protocol over-

head, packet loss, average delay and the variation of

the delay or jitter. These indicators are compared

with those of the following protocols: CBRP(Jiang

et al., 1999), AODV(Perkins et al., 2003) and

DSDV(Perkins and Bhagwat, 1994).

ANALYSISOFADHOCROUTINGPROTOCOLSFOREMERGENCYANDRESCUESCENARIOS

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4 SIMULATION RESULTS

The NS2 simulator (NS, 2012) is used to determine

the protocols behaviour with the data shown in Ta-

ble 1. In order to determine which is the best protocol,

we used the following indicators for comparison:

• Average Delay: This is very signiﬁcant to mea-

sure for our purpose because there is a need to

send and receive network managment information

as fast as possible.

Figure 3: Delay average - TCP - 20 connections.

Figure 4: Delay average - TCP - 40 connections.

In this parameter as shown in Figure 3 to 20 con-

nections with 97 nodos the 3 protocols behaviour

optimal according to their characteristics, but 100

and 120 nodes CBRP protocol suffers small de-

lay. Instead with 40 connections as seen in Fig-

ure 4 already panorama changes to demonstrate

advantage that protocol CBRP regarding proto-

cols AODV and DSDV. Data in Table 2, Table 3,

Table 4.

Table 2: AODV protocols analysis - delay average.

Number of

nodes

AODV(20c) AODV(40c)

97 0.498009 0.498009

100 0.483952 0.471993

120 0.613480 0.452916

Table 3: DSDV protocols analysis - delay average.

Number of

nodes

DSDV(20c) DSDV(40c)

97 0.411367 0.411367

100 0.432102 0.421802

120 0.582582 0.444208

Table 4: CBRP protocols analysis - delay average.

Number of

nodes

CBRP(20c) CBRP(40c)

97 0.383271 0.346918

100 0.597227 0.379617

120 0.660971 0.303840

• Packets Sent Rate: The rate obtained by the

number of packets sent to the number of pack-

ets received. For the formation and maintenance

the cluster needs the exchange of packets to have

updated information. As shown in Figure 5 and

Figure 6. The protocol that best responds to this

parameter is the CBRP protocol for both 20 as for

the 40 connections.

Figure 5: Send packet rate 20 connections.

Figure 6: Send packet rate 40 connections.

• Packet Delay Variation: It is the difference

in delay between communications end-to-end se-

lected packets. It serves to measure the network

stability and convergence, in Ad Hoc networks.

This parameter is related to the mean ﬂuctuation

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Figure 7: Jitter average TCP 20 connections.

Figure 8: Jitter average TCP 40 connections.

and helps us to determine which of the three pro-

tocols would be the most appropriate at the time

to emergency and rescue. as we can see that this

parameter as the two above parameters shows that

the protocol is nearest zero consequently has jitter

lower the protocol CBRP as seen in Figure 7 and

Figure 8. The simulation results are set to Table 5,

Table 6, Table 7.

Table 5: AODV protocols analysis - jitter average.

Number of

nodes

AODV(20c) AODV(40c)

97 -0.097499 -0.097499

100 -0.015795 -0.088908

120 -0.009072 -0.084256

Table 6: DSDV protocols analysis - jitter average.

Number of

nodes

DSDV(20c) DSDV(40c)

97 -0.102806 -0.102806

100 -0.015821 -0.085109

120 -0.01274 -0.079349

• Packet Loss: This is the amount of packets

dropped by intermediate nodes due to the effects

produced by the mobility of these nodes, timer ex-

pires, unreachable or erased destination by ARP

(Address Resolution Protocol).

The objective of the simulation was to determine

which of these three protocols behave better in emer-

gency and rescue scenarios and how we can seen in

Table 7: CBRP protocols analysis - jitter average.

Number of

nodes

CBRP(20c) CBRP(40c)

97 -0.041516 -0.024319

100 -0.000214 -0.027638

120 0.003136 -0.019921

Figure 9: Dropped packets - 20 connections.

Figure 10: Dropped packets - 40 connections.

Figure 9 Figure 10 CBRP protocol clears least pack-

ets with 20 connections and even better with 40 con-

nections. The data are shown in Table 8 y Table 9.

Table 8: Dropped packets - 20 connections.

Number of

nodes

AODV(20c) DSDV(20c) CBRP(20c)

97 2820 799 269

100 3207 631 245

120 2819 429 222

Table 9: Dropped packets - 40 connections.

Number of

nodes

AODV(40c) DSDV(40c) CBRP(40c)

97 2820 799 187

100 2206 751 196

120 2659 496 133

5 CONCLUSIONS

• Traditional routing algorithms cannot satisfy re-

quirements of an ad hoc networks, because of to-

ANALYSISOFADHOCROUTINGPROTOCOLSFOREMERGENCYANDRESCUESCENARIOS

785

pology dynamics and limited bandwidth charac-

terizing these networks. Consequently, there area

lot of investigation related to existing routing al-

gorithms land there is discovering of new routing

algorithms, which are more efﬁcient.

• This study evaluate and compare CBRP, AODV

and DSDV for emergency and rescue scenarios.

The experimental results show that the best pro-

tocol is CBRP that losses only few packets for

routing, where is the sending and receiving rate

of packets is stable. The mean ﬂuctuation and the

delay is much smaller in relation to the other two

protocols. This would support determine that us-

ing the protocol CBRP people in a disaster area

could be evacuated to more efﬁciently support

points as would be placed promptly.

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