To Evaluate the Imapct of Vector mobilty model over
Routing Protocols in MANET
Suryakant
Suryak111@gmail.com
GEHU Dehradun,Uttarakhand, India
ABSTRACT
In Mobile Ad-hoc Network (MANET) , the nodes are free to move
randomly. Thus the network's wireless topology may be
unpredictable and may change rapidly. Widely varying mobility
characteristics are expected to have a significant impact on the
performance of the routing protocols. This work shows the impact of
vector mobility on the performance of a MANET routing protocols
Neetu Kushwaha
neetumits@gmail.com
Galgotia University,India
the transmission of a significant amount of control traffic. Hence,
reactive MANET protocols are most suitable for networks with high
node mobility or where the nodes transmit data infrequently. Reactive
routing protocols are enumerated as Ad Hoc on Demand Distance
Vector (AODV).
Keywords
MANET; Routing Protocols; Vector Mobility; AODV; GRP
1. INTRODUCTION
This Mobile ad-hoc network (MANET) research field has grown fast
in recent years. It was basically designed to make the user free from
any pre-deployed infrastructure [1][4]. MANET allows the mobile
nodes to communicate with each other via a wireless medium without
any infrastructure i.e. forms a temporary network. There is no need of
access points, each node act as a router and node at the same time.
These mobile nodes (router) can disappear and appear in the network
according to their own wish. MANETs have a wide range of
applications such as collaborative, distributed mobile computing
(e.g., sensors, conferences), disaster relief (e.g., flood, earthquake),
war front activities and communication between automobiles on
highways. Most of these applications demand multicast or group
communication.
In MANET every node finds the route on the basis of the request.
Routing protocol perform a vital role to send the data from source to
destination that help to find the optimal path between the two
communication nodes. Every protocol has its own rules (algorithm)
to discover the route and maintain the route. There are a vast number
of routing protocols proposed by researchers [5][6].
MANETs are facing various challenges for e.g. No central
controlling authority, Mobility models, limited power ability,
constantly maintain the information needed to properly route the
traffic. Mobility models are also a point that puts a great impact on
the performance of MANET and which is needed to be concerned.
2. The Routing Protocols
The Efficient routing protocols can offer major benefits to mobile ad
hoc networks, in the criteria of both performance and reliability.
2.1. Reactive Routing Protocols:
Reactive MANET protocols only discover a route to the destination
node when there is a request to send data. The source node will start
by transmitting route requests throughout the network. The sender
will then wait for the destination node or an intermediary node (that
has a route to the destination) to take action in response with a list of
intermediate nodes between the source and destination. It is
recognized as the global flood search, which in turn brings about a
significant delay prior to the packet can be transmitted. It also needed
Fig 1: MANET
Ad Hoc on Demand Distance Vector (AODV) [3][8]discover the
route merely when there is data to be transmitted according to on
demand by the flooding in the network and as a result, generate low
control traffic and routing overhead. AODV is a reactive routing
protocol that minimizes the number of broadcasts by creating routes
on demand. When the source node wants to generate a new route to
the destination, the requesting node broadcast a RREQ message in
the network.
2.2. Proactive Routing Protocols
The Proactive MANET protocols are table-driven and will
vigorously determine the layout of the network. Through a regular
exchange of network topology packets between the nodes of the
network, a complete picture of the network is maintained at every
single node. There is hence minimal delay in determining the
route to be taken. This is especially important for time-critical traffic.
However, a drawback to a proactive MANET of protocol is that the
life span of a link is notably short. This phenomenon is brought about
by the increased mobility of the nodes, which will render the routing
information in the table invalid quickly. Thus, proactive MANET
protocols work best on networks that have low node mobility or
where the nodes transmit data frequency. Reactive routing protocols
are enumerated as Optimized Link State Routing (OLSR).
OLSR[7] is a modular proactive hop by hop routing protocol. Its
provide the fresh path of destination bases of table driven approach. It
is an optimization of pure link state algorithm in ad hoc network.
The routes are always immediately available when needed due to its
proactive nature. The key concept of the protocol is the use of
"multipoint relays" (MPR). Each node selects a set of its neighbor
nodes as MPR. Only nodes, selected as such MPRs are responsible
for generating and forwarding topology information, intended for
diffusion into the entire network.
2.3. Hybrid routing Protocols
Since proactive and reactive routing protocols each work best in
oppositely different scenarios, there is good reason to develop hybrid
routing protocols, which use a mix of both proactive and reactive
routing protocols. These hybrid protocols can be used to find a
balance between the proactive and reactive protocols. The basic
concept behind hybrid routing protocols is to use proactive routing
mechanisms in some areas of the network at certain times and
reactive routing in the rest of the network. The proactive operations
are restricted to a small domain in order to overcome the control
overheads and delays. The reactive routing protocols are used for
locating nodes outside that domain, as this is more bandwidthefficient in a constantly changing network.
Gathering-based routing protocol (GRP) [9] combines the
advantages of Proactive Routing Protocol (PRP) and of Reactive
Routing protocol (RRP). PRP is suitable for supporting the delay
sensitive data such as voice and video but it consumes a great portion
of the network capacity. While RRP is not suitable for real-time
communication. The function of Gathering-based Routing Protocol
(GRP) for mobile ad hoc network is to gather network information
rapidly at a source node without spending a large amount of
overheads. It offers an efficient framework that can simultaneously
draw on the strengths of Proactive routing protocol (PRP) and
reactive routing protocol (RRP) collects network information at a
source node at an expense of a small amount of control overheads.
3. MOBILITY MODELS
In MANETs, mobile nodes roam in entire the network area. It is hard
to model the actual node mobility in a way that captures real life user
mobility patterns .Mobility models are designed to evaluate the
performance of ad-hoc networks and characterize the movements of
real mobile node in which variation in speed and direction must occur
during regular time interval. Therefore, many researchers attempted
to design approximate mobility models [10][17] to resemble real
node movements in MANETs such as follows:
3.1. Random way point mobility model
In this model, the position of each node is randomly chosen within a
fixed area and then moves to the selected position in a linear form
with random speed. This movement has to stop with a certain period
called pause time before starting the next movement. The pause time
is determined by model initialization and its speed is uniformly
distributed between its minimum speed and maximum speed.
3.2. Random walk mobility model
In this mobility model mobile host moves from current location to
the new location by choosing random direction and speed from the
predefined ranges between minimum speed and maximum speed.
3.3. Group mobility model
In Group mobility models that represent multiple MNs whose
actions are completely independent of each other. In this mobile
nodes moves in groups. In an ad hoc network, however, there are
many situations where it is necessary to model the behavior of MNs
as they move together.
3.4. Vector mobility model
This model is used to avoid the unrealistic behavior which is
physically impossible. By remembering mobility state of a node and
allowing only partial changes in the current mobility state, natural
motions can be reproduced. Advantages of this model are:
simplification of position updates, ease of implementation and
opportunity for mobility prediction.
3.5. Gauss-Markov Mobility Model
The Gauss-Markov Mobility Model was first introduced by Liang
and Haas and widely utilized .In this model, the velocity of the
mobile node is assumed to be correlated over time and modeled as a
Gauss-Markov stochastic process.
3.6. Reference Point Group Mobility model
The Reference Point Group Mobility model (RPGM) has a special
mobile node known as the logical center. The motion of this mobile
node defines the entire group’s features like location, speed,
direction, acceleration, etc. Thus, the group trajectory is determined
by providing a path to the center. Generally nodes are uniformly
distributed within the geographic range of a group. Each node is
assigned a reference point which follows the group movement. This
reference point allows independent random motion behavior for each
node, in addition to the group motion.
3.7. Manhattan Mobility Model
Manhattan Mobility Model is used to emulate the movement pattern
of mobile nodes on the streets. It can be useful in modeling
movement in an urban area. In this network maps are used.The Maps
contain a number of horizontal and vertical streets. The mobile nodes
are restricted to move along the horizontal and vertical streets on the
map. At an intersection of a horizontal and a vertical street, the
mobile node can move left, right, straight with certain probability.
The speed of a mobile node at any time is dependent on its previous
time speed and on the speed of the front node in the same direction.
4. RELATED WORK
Juan-Carlos Cano et.al[11] present an analysis of the effect that
mobility models have over the performance of a mobile ad hoc
network. They concentrate on group mobility. They investigate the
effect that the mobility model has on the performance of CBR traffic
and TCP traffic. Bai, Fan, et.al[10] discussed about the mobility
model which plays a very important role in determining the protocol
performance. Beside the commonly used Random Waypoint model
and its variants, they also discuss various models that exhibit the
characteristics of temporal dependency, spatial dependency and
geographic constraint V(maximum allowable velocity) and T(pause
time)are the two key parameters that determine the mobility behavior
of nodes for every mobile node. S. R. Biradaret.al[12] compare the
performance of two on-demand routing protocols for mobile ad hoc
networks Dynamic Source Routing (DSR) and Ad Hoc On-Demand
Distance Vector Routing (AODV). They demonstrate that even
though DSR and AODV both are on-demand protocol, the
differences in the protocol mechanics can lead to significant
performance differentials. The performance differentials are analyzed
using varying mobility. Liu Tie-yuanet.al[13] presents a comparative
study on entity mobility models. Firstly, both the advantages and
disadvantages of four typical entity mobility models are summarized;
these models include the Random Walk model (RW), the Random
Way Point model (RWP), the Random Direction model (RD)and the
Markov Random Path model (MRP). Secondly, focus on primary
parameters of these models, effects of both the speed and the pause
time on the performance metric of MANET routing protocols are
analyzed. Finally, with the help of the NS-2 simulator, the effect of
different entity mobility models on the performance of MANET
routing protocols is analyzed. Sabina Baraković et.al[27] compares
performances of three routing protocols: Destination Sequenced
Distance Vector (DSDV), Ad Hoc On demand Distance Vector
(AODV) and Dynamic Source Routing (DSR). K. Sreenivasulu,
et.al[14] focused on the stability of a routing path, which is subject to
link failures caused by node mobility.
.
5. SIMULATION ENVIRONMENT
We used Network Simulation OPNET (optimized Network
Engineering Tool) Modeler version 14.5 in our evaluation. The
OPNET is a discrete event driven simulator [15][16]. It simulates the
network graphically and its graphical editors mirror the structure of
actual networks and network components. The users can design the
network model visually. The modeler uses an object-oriented
modeling approach. The nodes and protocols are modeled as classes
with inheritance and specialization. The development language is C.
The simulation is performed to evaluate the performance of routing
protocols with the vector mobility and scalability issue at FTP traffic.
Therefore, different simulation scenarios consisting of 25 nodes
initially and doubling amount nodes i.e. to 50 for AODV OLSR and
GRP is considered. The nodes were randomly placed within certain
gap from each other in 3.5×3.5 km office environment for 25 and 50
nodes respectively. The constant FTP traffic is generated in the
network explicitly i.e. user defined via Application configuration and
Profile Configuration. Every node in the network was configured to
execute AODV, OLST and GRP respectively. The simulation time
was set to 5 minutes and all the nodes were configured with defined
vector mobility in space.
TABLE I.


Delay: Represents the end to end delay of all the packets
received by the wireless LAN MACs of all WLAN nodes in
the network and forwarded to the higher layer. This delay
includes medium access delay at the source MAC, reception
of all the fragments individually, and transfers of the frames
via AP, if access point functionality is enabled.
Throughput: Represents the total number of bits (in bits/sec)
forwarded from wireless LAN layers to higher layers in all
WLAN nodes of the network.
6. RESULTS
The simulation results are shown in this section in the form graphs.
Graphs show comparison between the three protocols of varying
different numbers of sources on the basis of the above-mentioned
metrics :
6.1. End to End Delay
Figure 2 shows the performance of AODV, OLSR and GRP by
evaluating End to End Delay with Vector Mobility Model 25 and 50
numbers of sources(S) with FTP traffic. Besides the actual delivery
of data packets, the delay time is also affected by route discovery,
which is the important step to begin a communication session. The
AODV routing protocol has a long delay because its route discovery
takes more time as every intermediate node tries to extract
information before forwarding the reply. The same thing happens
when a data packet is forwarded hop by hop. Whereas in the
proactive protocol OLSR, the routing data are already maintained,
hence diminishing the delay period. In the case of GRP, there is an
initial delay because of its initial on-demand nature.
SIMULATION PARAMETERS
Parameter
Value
Simulator
Opnet 14.5
Area
3.5×3.5 Km
Wireless MAC
802.11
Number Of Nodes
25 , 50
Mobility Model
Vector
Data Rate
11 Mbps
Routing Protocols
AODV,OLSR And GRP
Simulation Time
5 minutes
Traffic
FTP
Fig 2: End to End Delay
Performance Metrics: the following Performance Metrics have been
used for evaluating the performance of various MANET routing
protocols:

Network Load: The statistic represents the total data traffic
(in bits/Sec) received by the entire WLAN BSS from the
higher layers of the MACs that is accepted and queued for
transmission
6.2. Throughput
The average throughput of the network with 25 and 50 nodes is
shown in Figure 3 which reflects the usage degree of the network
resources for the typical routing protocols.
Throughput increases quickly for OLSR with increased number of
nodes which communicate as the time passes. This is due to the
availability of routing tables with each node prior to the
communication. While AODV and GRP on the other hand have
difficulties in finding routes when number the data communication
starts, this is clear from the figure 3.
Fig 3: Average Throughput
Fig 5: Throughput wih 50 nodes
6.3. Network Load
Figure 6 shows Network Load Here Network Load is less with the
least number of nodes (25- nodes) and more with the number of
nodes (50-nodes) . Here AODV with the number of nodes having
lesser network loads than others. OLSR have the highest Network
Load in the network.
It is the total data traffic (in bits/sec) received by the entire WLAN.
Network load are directly proportionalSec the stability of the
network. More network load, more stable the network is. In OLSR,
nodes are busy to send data information than the control information;
such that channel is utilized to end data in spite of sending routing
information. AODV belongs to the class of pure reactive protocols. It
does not carry any routing data until a request for the same is made
by the source. The source then generates the RREQ (route request)
message; which is replied with a RREP (route reply) or RERR (route
error) message from the neighbors. Thus the network load in AODV
is markedly reduced as compared to proactive protocols, which
require the routing tables to be maintained even when no request is
generated. GRP, being a hybrid protocol, typically shows values of
network load which lie in between the reactive and proactive
protocols.
Fig 4: Throughput with 25 nodes
Figure 4 and Figure 5 show Throughput with 25 and 50 nodes
respectively and from these figure it is clear that in OLSR perform
better than AODV and GRP routing protocols .
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
Fig 6: Network Load
[10]
[11]
7. CONCLUSION
This work have evaluated the three performance measures i.e.
Network Load, End-to-end delay and Throughput with Vector
mobility model and FTP as traffic type while taking 25 and 50 nodes
as the node density. From the extensive simulation results, it is found
that OLSR shows the best performance in terms of throughput, and
end-to-end delay.
In future, the node density can be varied to study its impact on the
performance of the routing protocols and thus check their efficiency
as the nodes increase. Doing so would bring out the contrast between
the two mobility models and thus help in making reaching accurate
conclusions.
8.
References
[12]
[13]
[14]
[15]
[16]
[17]
[1]
Zahian Ismail, Rosilah Hassan, Ahmed Patel, Rozilawati Razali, “A
Study of Routing Protocol for Topology Configuration Management in
Mobile Ad Hoc Network” International Conference on Electrical
Engineering and Informatics, Selangor, Malaysia pp 5-7 August 2009
Bai, Fan,Helmy, Ahmed (2006)“A Survey of Mobility Models in
Wireless Adhoc Networks.” (Chapter 1 in Wireless Ad-Hoc Networks.
Kluwer Academic. 2006).
C.E. Perkins and E.M.Royer, “Ad-Hoc On Demand Distance Vector
Routing”, Proceedings of the 2nd IEEE Workshop on Mobile
Computing Systems and Applications, New Orleans, LA, USA, pages
90-100, February 1999.
L. Hogie, P. Bouvry, and F. Guinand, "An Overview of MANET
Simulation," Electronic Notes in Theoretical Computer Science, vol.
150, no. 1, pp. 81-101, 2006.
Shima Mohseni, Rosilah Hassan, Ahmed Patel, and Rozilawati Razali,
Comparative Review Study of Reactive and Proactive Routing Protocols
in MANETs, 4th IEEE International Conference on Digital Ecosystems
and Technologies (IEEE DEST 2010).
E. Royer, C.K. Toh, A review of current routing protocols for ad hoc
mobile wireless networks, IEEE Personal Communications Magazine
(2), 1999.
Ying Ge,“Quality of Service Routing in Ad-Hoc Networks Using
OLSR” Proceedings of the 36th Hawaii International Conference on
System Sciences (HICSS’03)0-7695-1874-5/03 $17.00 © 2002 IEEE.
Anipakala Suresh, “Performance Analysis of Ad hoc OndemandDistance Vector Routing (AODV) Using OPNETSimulator
Communication Networks” University of Bremen.
Chang Wook Ahn, “Gathering-based routing protocol in mobile ad hoc
networks”, Computer Communications 30 (2006) 202–206
Bai, Fan,Helmy, Ahmed (2006)“A Survey of Mobility Models in
Wireless Adhoc Networks.” (Chapter 1 in Wireless Ad-Hoc Networks.
Kluwer Academic. 2006).
Juan-Carlos Cano and Pietro Manzoni “Group mobility impact over TCP
and CBR traffic in Mobile Ad Hoc Networks” IEEE (2011)
S. R. Biradar1, Hiren H D Sarma2, Kalpana Sharma3, Subir Kumar
Sarkar4 , Puttamadappa C5, “Performance Comparison of Reactive
Routing Protocols of MANETs using Group Mobility Model”
IEEE(2009).
Liu Tie-yuan，CHANG Liang，Gu Tian-long “Analyzing the Impact of
Entity Mobility Models on the Performance of Routing Protocols in the
MANET”. IEEE (2009).
K. Sreenivasulu1, Mr. A.L. Srinivasulu , “Improving Routing Efficiency
Based On Random Direction Mobility Model In Manets” International
Journal of Smart Sensors and Ad Hoc Networks (IJSSAN) Volume-1,
Issue-1, 2011
OPNET Modeler. Retrieved 20 Oct, 2008, from http://www.opnet.com.
X. Chang, "Network Simulations with OPNET," Presented at Simulation
Conference Proceedings, 1999 Winter, 1999, pp. 307-314.
Shaveta and Krishan Kumar Saraswat (2012)“Pursue Shortest Mobility
Model and
Its Comparison in MANET” VSRD International
Journal of CS & IT Vol. 2 (6) pp 462-472