Abstract—Mobile ad hoc network (MANET) is a group of

mobile nodes communicating through wireless channels

without the necessity of any pre-established network

infrastructure or centralized administration. Because of the

limited transmission range of wireless nodes, multiple "hops"

may be needed for effective communication across the network.

Consequently, many routing algorithms have come into

existence to satisfy the needs of communication in such

networks. Researchers have conducted many

experiments/simulations comparing the performance of these

routing protocols under various conditions and constraints.

One question that arises is how scalability and mobility of

nodes together, affects the performance of routing protocols.

This paper addresses the question by simulating two routing

protocols AODV and DSR using QualNet and was compared in

terms of throughput and average end-to-end delay. Simulation

results illustrate that the throughput of DSR increases as

compared to AODV with the increase in number of nodes and

pause time, whereas average delay for AODV decreases with

mobility and scalability.

Index Terms—AODV, DSR, MANET, mobility,

scalability, throughput and average end-to-end delay.

I. INTRODUCTION

A mobile ad-hoc network represents an arrangement of

wireless mobile nodes that can freely and dynamically self-

organize into arbitrary and temporary network topologies,

allowing people and devices to internetwork in areas

without any pre-existing communication infrastructure.

Each node in the networks also acts as a router, forwarding

data packets for other nodes [1]. The nodes are generally

mobile; they are free to move arbitrarily resulting in

frequently and drastic changes in the network topology.

Because of the freedom of mobility, the set of application

for MANETs is diverse, ranging from small networks like

conference rooms, meetings etc. to large-scale, sensitive

networks like military communications by soldiers, search

and rescue operations [1]. A key challenge in ad-hoc

network design is to develop a high quality and efficient

routing protocol which can be used to communicate using

mobile nodes.

The most prominent challenge in ad-hoc networks is the

Manuscript received August 10, 2012; revised November 29, 2012.

Charu Wahi is with the Birla Institute of Technology, Mesra, Noida

Campus (U.P.), India (email: charu@bitmesra.ac.in).

Sanjay K. Sonbhadra is with the Shri Shankracharya Institue of

Technology & Management, Bhilai (C.G.), India. (email:

sksonbhadra@ssitm.ac.in).

Shampa Chakraverty is with the Netaji Subhash Institute of Technology,

Delhi, India. (email: apmahs.nsit@gmail.com).

Vandana Bhattacharjee is with the Birla Institute of Technology, Mesra,

Lalpur Campus, India. (email: vbhattacharya@bitmesra.ac.in).

development of dynamic routing protocols that can

efficiently find routes between two communicating &

mobile nodes. The routing protocol must be able to keep up

with the high degree of node mobility that often changes the

network topology drastically and unpredictably. Hence, the

protocols must be adaptive and be able to maintain routes

despite the change in the topology of the network, caused by

mobility of nodes.

There are many ways to classify MANET routing

protocols, depending on how the packet is delivered from

source to destination. They can be broadly classified as

proactive, reactive and hybrid routing [2]. In the proactive

routing approach, every node maintains one or more tables

to provide information about the routes to establish

communication between any two nodes of the network.

Some of the existing proactive routing algorithms are

DSDV [3], Optimized link state routing (OLSR) [4] and

Fisheye state routing (FSR) [5]. In reactive routing,

information is collected only when it is needed, which

include the Dynamic Source Routing (DSR) [6], Ad-hoc On

Demand Distance Vector (AODV) [7] and Associativity

based routing (ABR) [8].

Section II presents the related work & motivation

required for this research. Section III provides an overview

of the protocols evaluated in this paper. Section IV

enumerates the different parameters used in the simulation.

We describe the performance metrics used in our study and

simulation based results in Section V. Conclusion and future

work is presented in Section VI.

II. RELATED WORK AND MOTIVATION

Many on-demand routing algorithms have come into

existence to facilitate effective and efficient routing in

MANETs. However, these algorithms have revealed a wide

range of performance results under different network

conditions and parameters. Therefore, it is quite difficult to

determine which protocols may perform best under a

number of different network scenarios, such as increasing

pause time and node density.

One of the issues associated with routing algorithms is

the mobility of nodes, which in turn changes the topology of

the network in an unpredictable manner. Mobility of nodes

will largely affect the routes between communicating and

intermediate nodes and hence it will make a significant

influence on the performance of the routing algorithms. It

causes frequent path breaks, packet collisions, transient

loops etc.

Scalability is another issue associated with routing in

MANETs. It is the ability of a routing protocol to scale well

(i.e. perform efficiently) in a network with large number of

Charu Wahi, Sanjay K. Sonbhadra, Shampa Chakraverty, and Vandana Bhattacharjee, Member, IACSIT

Lecture Notes on Software Engineering, Vol. 1, No. 1, February 2013

12

Effect of Scalability and Mobility on On-Demand Routing

Protocols in a Mobile Ad-Hoc Network

DOI: 10.7763/LNSE.2013.V1.3

nodes. Hence, any routing algorithm that has shown good

performance in a small-sized network, should be scalable i.e.

it should illustrate similar performance in medium-sized or

large networks. This requires minimization of control

overhead and adaptation of the routing protocol to network

size.

Researchers have conducted many simulations comparing

the performance of these routing protocols under various

conditions and constraints [9]-[11].

Now, one question that arises is how scalability and

mobility of nodes, together affects the performance of

routing protocols being studied. The motivation of this

research is derived from this question. This paper has made

an attempt to address this issue by studying the effect of

mobility (using the pause time parameter) and scalability

(by varying number of nodes) through simulation of two on-

demand routing protocols AODV [7] and DSR [6] using

QualNet simulator. The survey will definitely help designers

choose the most adequate routing protocol while designing

MANETs wherein mobility and scalability are the most

important criteria under consideration.

III. OVERVIEW OF ROUTING PROTOCOLS

A. Ad-Hoc on-Demand Distance Vector (AODV) [7]

The Ad Hoc On-demand Distance Vector Routing

(AODV) protocol is a reactive approach for mobile ad hoc

networks [7]. Being reactive in nature, AODV only needs to

maintain the routing information about the active paths. The

routing information is maintained in the routing tables at

each and every node in the network. Every mobile node

keeps a nexthop routing table, which maintains route to

different destinations within the network. An entry of the

routing table expires if it has not been used for a pre-

specified expiration time.

In AODV, when a node wants to send packets to any

other node but no route is available, it initiates a route

discovery operation. In the route discovery mechanism, the

source node broadcasts route request (RREQ) packets which

includes Destination Sequence Number. When the

destination or any intermediary node that has a route to the

destination receives the RREQ, it checks the destination

sequence numbers it currently knows and the one specified

in the RREQ. To guarantee the freshness of the routing

information, a route reply (RREP) packet is created and

forwarded back to the source only if the destination

sequence number is equal to or greater than the one

specified in RREQ.

AODV uses only symmetric links and a RREP follows

the reverse path of the respective RREQ [7]. Upon receiving

the RREP packet, each intermediate node along the route

updates its table entries for the specified destination. The

RREP packets with lower destination sequence number will

be dropped. The advantage of this protocol is low

Connection setup delay and the disadvantage is more

number of control overheads due to many route reply

messages for single route request.

B. Dynamic Source Routing (DSR) [6]

The Dynamic Source Routing (DSR) is a reactive unicast

routing protocol that utilizes source routing algorithm [6]. In

DSR, each node uses cache technology to maintain route

information of all the nodes. There are two major phases in

DSR such as:

1) Route discovery

2) Route maintenance

When a source node wants to send a packet, it first

consults its route cache [12]. If there exists a route to the

destination, the source node sends the packet along the path.

Otherwise, the source node initiates a route discovery

operation by broadcasting route request packets (RREQ).

Upon receiving a route request packet, a node checks its

route cache. If the node doesn’t have routing information for

the requested destination, it appends its own address to the

route record field of the route request packet. Then, the

request packet is forwarded to its neighbors.

If the RREQ packet reaches the destination or an

intermediate node has routing information to the destination,

a route reply packet (RREP) is generated. When the route

reply packet is generated by the destination, it comprises

addresses of nodes that have been traversed by the route

request packet. Otherwise, the route reply packet comprises

the addresses of nodes the route request packet has traversed

along with the route in the intermediate node’s route cache.

Whenever the data link layer detects a link disconnection,

a ROUTE_ERROR (RERR) packet is sent backward to the

source in order to maintain the route information. When the

source node receives this RERR packet, it initiates another

route discovery operation. Additionally, all routes

containing the broken link should be removed from the

route caches of the immediate nodes. The advantage of this

protocol is reduction of route discovery control overheads

with the use of route cache and the disadvantage is the

increasing size of packet header with route length due to

source routing.

IV. SIMULATION AND PERFORMANCE METRICS

In this study, we have analyzed the performance of two

on-demand routing protocols AODV and DSR, by varying

pause time and number of nodes. The simulations have been

performed using QualNet 5.0.2 [13].

Mobility is an important issue affecting the performance

and scalability of MANETs. Frequent link breakage due to

the node mobility limit the scalability of mobile ad-hoc

networks. To investigate the consequence of node mobility

and scalability, we ran simulation of 2 different protocols by

varying pause time and number of nodes, with the following

parameters (Table I)

TABLE I: SIMULATION PARAMETERS

Parameters Value

Protocols AODV, DSR

Simulation Area 700 x 700

Simulation Time 300 sec

Number of Nodes 30, 50 and 70 Nodes

Speed 0-10mps

Traffic pattern CBR

Mobility Model Random Waypoint

Pause Time 0, 30s, 60s, 90s, 100s, 120s, 150s,

200s, 300s

Lecture Notes on Software Engineering, Vol. 1, No. 1, February 2013

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V. SIMULATION RESULTS

We have investigated the performance of routing

protocols AODV & DSR by varying pause time from 0s to

300s for a MANET ranging from 30, 50 & 70 nodes. When

the nodes are continuously moving (0s pause time) the

number of link changes are very high. It decreases with an

increase in pause time and converges to 0 when the pause

time reaches 300s. At this stage the network becomes stable.

The results obtained from simulations are presented in fig. 1

to 8.

To evaluate the efficiency of a routing protocol in

MANET, we have evaluated the following metrics in our

study:

1) Throughput: - it is defined as the average rate of

successful message delivery over communication

channel. It is the ratio of the total amount of data that

reaches a receiver from a sender to the time it takes for

the receiver to get the last packet.

Fig. 1 shows the effect of variation in node density (i.e.

scalability) on AODV & DSR for stationary nodes. Since

throughput measures the effectiveness of the routing

protocol, it is clear from the figure that DSR is more

effective as compared to AODV, especially with an increase

in the number of stationary nodes.

Fig. 1. Effect of scalability on throughput of AODV & DSR for stationary

nodes

The effect of variation in pause time and number of nodes

on thoughput of AODV & DSR is shown in fig. 2 & 3

respectively. Fig. 4 depicts the relative performance of both

the protocols. As the network size grows, AODV’s

throughput has declined because of increase in control

overhead. However, there is an increase in throughput when

network size grows from 50 to 70 nodes. This is because of

the increase in the number of neighboring nodes (for 70

nodes), any route reply will reach the source node faster,

resulting in less control overhead.

Fig. 2. Effect of varying pause time and number of nodes on throughput of

AODV for mobile nodes

Fig. 3. Effect of varying pause time and number of nodes on throughput of

DSR for mobile nodes

Fig. 4 reveals that DSR has higher throughput as

compared with AODV for all network sizes and pause times.

This is because of the reduction of route discovery control

overhead with the use of route cache. AODV has more

control overhead due to the requirement for issuing many

route replies for a single route request in comparison with a

single route reply required in the case of DSR.

Fig. 4. Relative performance of AODV & DSR in terms of throughput

2) Average End-to-End delay: - The end-to-end delay is

the average time a packet takes to traverse through the

network. It includes all possible delays such as buffer

queues, transmission time and delays causes by routing

activities. It is averaged over all successfully received

data packets.

Fig. 5 illustrates the effect of scalability on average e-t-e

delay of MANETs using AODV & DSR routing protocol

for 30, 50 & 70 stationary nodes. AODV has less average

end to end delay (fig. 5 & 8) in comparison to DSR because

of its low connection delay. The packet header size

increases with route length because of the use of source

routing in DSR.

Fig. 5. Effect of scalability on average end-to-end delay of AODV & DSR

for stationary nodes

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The effect of variation in pause time and variation in node

size on end-to-end delay of AODV & DSR routing protocol

for mobile nodes is shown in Fig. 6 and Fig. 7 respectively.

It is clear that as the network size grows, the delay increases.

The behaviour of DSR with respect to average end-to-end

delay is similar for stationary and mobile nodes, viz. It

exhibits high delay in all ases

Fig. 6. Effect of varying pause time and number of nodes on average end-

to-end delay of AODV for mobile nodes

Fig. 7. Effect of varying pause time and number of nodes on average end-

to-end delay of DSR for mobile nodes

Fig. 8. Relative performance of AODV & DSR in terms of average end-to-

end delay

VI. CONCLUSION

In this paper, a simulation study was carried out to

analyze the performance of two most prominent on-demand

routing protocols AODV & DSR, by creating a scenario of

30, 50 & 70 nodes. We have shown the results for

throughput and average end-to-end delay for both stationary

and mobile nodes. Results show that DSR achieves higher

throughput than AODV with a variation in pause time and

network size. But the average delay of DSR increases with

an increase in mobility and scalability.

The studies of the performance of AODV & DSR

protocol hopefully can lead to the new finding of a new

optimal enhanced version of these protocols which can

maximize the routing performance and overcome the

limitation of the existing conventional protocols.

ACKNOWLEDGEMENT

Authors would like to thank Nihon Communication

Solutions, Bangalore for their simulation tool.

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[4] T. Clausen and P. Jacquet, “Optimized link state routing protocol

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[6] D. Johnson and D. A. Maltz, “Dynamic source routing in ad hoc

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eds., Kluwer Acad. Publ., 1996.

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performance comparison of multi-hop wireless Ad-Hoc network

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[13] QualNet. QualNet 5.0 Simulator. [Online]. Available:

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Charu Wahi is currently a Ph.D. candidate in the

Department of Computer Science and Engineering,

Birla Institute of Technology, Ranchi. She received her

B.E. degree in 2000 and M.Tech - Computer Science in

2008. She is currently working as Assistant Professor

in Department of Computer Science and Engineering,

Birla Institute of Technology, Ranchi. She is a member

of IACSIT. Her research areas include routing,

security, quality of service especially in mobile ad-hoc networks.

Sanjay Kumar Sonbhadra is currently an assistant

Professor in the Department of Computer Science and

Engineering, Shri Shankracharya Institute of

Technology & Management, Bhilai. His research

mainly focuses on Ad-hoc networks, especially

security in ad-hoc networks. He received his B.E.

degree in 2004 and M.Tech degree in 2008.

Lecture Notes on Software Engineering, Vol. 1, No. 1, February 2013

15

Shampa Chakraverty studied BE-Electonics and

Communication in Delhi Univ., and MTech-Integrated

Electronics and Circuits in IIT-Delhi and PhD-Delhi

University. She is Professor in the Department of

Computer Engineering in Netaji Subhas Institute of

Technology, New Delhi. Her research interests

include Hardware Software Codesign, Fault Tolerant

Computing, Machine Learning and Web technologies.

Vandana Bhattacherjee is working as a Professor,

Department of Computer Science and Engineering,

Birla Institute of Technology, Ranchi. She completed

her B. E. (CSE) in 1989 and her M. Tech and Ph. D in

Computer Science from JNU New Delhi in 1991 and

1995 respectively. She has over 60 National and

International publications in Journal and Conference

Proceedings. She is a member of IEEE Computer

Society and Life Member of Computer Society of India. Her research areas

include Software Process Models, Software Cost Estimation, Data Mining

and Software Metrics.

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