Wireless Sensor Network, 2011, 3, 92-105
doi:10.4236/wsn.2011.33010 Published Online March 2011 (http://www.SciRP.org/journal/wsn)
Performance Evaluation of Routing P rotocols on the
Reference Region Group Mobility Model for MANET
Yan Zhang, Chor Ping Low, Jim Mee Ng
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Received January 31, 2011; revised February 23, 2011; accepted February 28, 2011
Abstract
Group mobility is prevalent in many mobile ad hoc network (MANET) applications, such as disaster recov-
ery, military operations, searching and rescue activities. Group partition, as an inherent phenomenon in
group mobility, may occur when mobile nodes move in diverse mobility patterns and it causes the network to
be partitioned into disconnected components. It may result in severe link disconnections, which interrupts
network communications. To address this concern, we proposed a novel group mobility model in this paper,
namely the Reference Region Group Mobility model, which can be used to mimic group operations in MA-
NETs, i.e. group partitions and mergers. Based on this model, a comprehensive study on the impact of group
partitions to the performance of network routing protocols are carried out by evaluating two well-known
routing protocols, namely the Ad Hoc On-demand Distance Vector Routing protocol (AODV) and the Dy-
namic Source Routing protocol (DSR). The simulation results reflect that group partitions have a significant
impact to the performance of network routing protocols.
Keywords: Ad Hoc Network, Group Mobility Model, Group Partition, Routing, AODV, DSR
1. Introduction
Mobility models are used in simulation studies to de-
scribe the dynamic behaviors of mobile devices in the
real world for analyzing and evaluating the performance
of ad hoc network protocols under various scenarios [1].
Mobility models play a significant role in the develop-
ment of MANETs. Most existing mobility models, such
as the Random Waypoint Mobility model [2] and the
Random Walk Mobility model [3], are designed to si-
mulate the movement of each individual, which are re-
ferred to as entity mobility models [4]. However, with
the emergence of group-oriented applications, several
group mobility models have been recently proposed. The
applications requiring group mobility can be found in
various scenarios which include military operations,
searching and rescue in disaster recovery, visiting an
exhibition hall, and firefighters operating in a building.
The common characteristic of the above applications is
that mobile nodes can be organized in the unit of grou ps,
which could be further partitioned into many subgroups
or merged with other groups. However, among all the
existing group mobility models, none of them can simu-
late the inherent group operations, i.e., partitions and
group mergers wh ich are very common in most practical
group mobility related scenarios. In add ition, some gr oup
mobility models can only be app lied to specific scenarios
with the restrictions in the aspects of, e.g., fixed group
membership, fixed velocity, and predefined paths for
group’s movement. By consideri ng these rest rictions, most
of existing models are unable to describe the behaviors
of group mobility realistically.
To address this issue, we proposed a novel mobility
model in this paper, namely th e Reference Region Group
Mobility (RRGM) model. This model is a generic and
parameterized mobility model which is able to model
groups’ movement. The novelty of this model is its abil-
ity to mimic group operations, such as group partitions
and mergers. In addition, we introduce the concept of
node density of a group. With a fixed number of group
members, node density can be used to control the cover-
age area of a group (the range of an area that group
members move within). Unlike existing group mobility
models, RRGM allows mobile nodes to move indepen-
dently without relying on the coordination of group
leaders. By taking advan tage of this, group partition s and
mergers b e come possible.
Network routing protocols, as an important research

Y. ZHANG ET AL.
93
topic in MANETs, have gained a lot of interest among
the research community. A network routing protocol is
used to exchange data packets between network users. In
MANETs, each node learns about nodes nearby and how
to reach them, and may also announce that it can reach
them. Such discovery mechanisms allow routing infor-
mation to be exchanged among all mobile nodes. Mobil-
ity patterns have an impact on the performance of net-
work routing protocols, which has been discussed in
some previous research works [5-7]. However, most ex-
isting works for studying the performance of routing
protocols uses the entity mobility mode ls which describe
individual’s mobility behaviors. On the other hand, we
note that limited studies have been done on the impact of
group mobility on network performance and they may
usually assume that the network is connected, i.e. there
are no group partitions and mergers. With the aid of
RRGM model, we will evaluate and compare the per-
formance of two well-known network routing protocols,
namely Ad Hoc On-demand Distance Vector Routing
(AODV) [8] and Dynamic Source Routing protocol
(DSR) [9], under a networ k with the occurren ce of group
partitions and mergers in group mobility.
2. Literature Review
In this section, we will review some of the mobility
models for MANETs first. Following that, review of the
network routing protocols in MANETs will be presented.
2.1. Review on Mobility Models in MANETs
Mobility models in MANETs are generally classified
into two categories, namely entity mobility models and
group mobility models. Entity mobility models are used
to describe the mobility of each individual’s mobility
while group mobility models mimic the movement of
groups in MANETs.
The Random Waypoint Mobility model (RWP) [2] is a
well-known entity mobility model. In this model, each
mobile node randomly chooses a point as the destination
and moves towards it with a randomly selected speed
which is uniformly distributed in a range of [Vmin, Vmax].
After reaching the destination, the node may be statio-
nary for a moment before generating a new destination.
This process is repeated until the simulation ends.
Several group mobility models are designed for MA-
NETs, although they may not be as widely used as entity
mobility models. Reference Point Group Mobility
(RPGM) model [10] is a generic group mobility model.
In this model, the movement path of a group is prede-
fined by a series of points which are referred to as “ref-
erence points”. Each group has a group leader which
serves as the logical center of the group. Every mobile
node follows the movement of the logical center with a
random deviation in its position to that of the logical
center. It is compulsory to predefine group membership
and group leaders before running a simulation , which are
not allowed to chan ge d uring the simulat i on.
We note that group partitions and mergers could take
place as a result of group mobility in MANETs. Howev-
er, the existing models assume the membership of each
group does not chan ge which in turn does not allow mo-
bile nodes to partition from groups or merge into other
groups. We will address this issue in this paper.
2.2. Review on Network Routing Protocols
In ad hoc networks, routing protocols are typically cate-
gorized into two classes, table-driven routing protocols
and on-demand routing protocols [11,12]. The two
classes of routing protocols are differentiated by the me-
chanisms which they use to maintain and update routes
in ad hoc networks [6,13-15]. In table-driven routing
protocols, when a source has a packet to send, the
routing information will be available immediately from
its routing table which is updated periodically by adver-
tisements, e.g. hello messages. However, in on-demand
routing protocols, the source, which wants to send a
packet, has to trigger a route discovery process if it can
not find any fresh enough route from its routing table or
the routes in its routing table are no long er available, and
thus the routing information is updated by request. Both
table-driven and on-demand routing protocols use more
control overhead than the traditional static networks. In
dynamic network environments such as MANETs, fast
change of network topology will result in massive
routing overhead generated to update routing tables of
each mobile node, especially for the nodes using ta-
ble-driven routing protocols. Table driven routing proto-
cols are not adaptive to fast changes of network topology.
On the other hand, on-demand routing protocols only
need to update their routing information when they have
packets to deliver. Hence, on-demand routing protocols
generally outperform table-driven routing protocols in
dynamic network environment. Thus, we choose two
well-known on-demand routing protocols, i.e. AODV
and DSR, for the study of the impact of group partitions
and mergers on the network performance in this work.
Next, we will review these two routing protocols.
“AODV minimizes the number of required broadcasts
by creating routes on a demand basis” [8,14]. In AODV,
when a source node desires to send a packet but does not
have a valid path to the destination, it initiates a route
discovery process to locate the destination by broadcast-
ing a route request (RREQ) message to its neighbors,

Y. ZHANG ET AL.
94
which then fo rward the request to their neighbors and so
on, until either the destination or an intermediate node
with a “fresh enough” route to the destination is located.
Each node that forwards the RREQ creates a reverse
route for itself back to the source node. The routing table
is updated with the address of the neighbor from which
the first copy of the broadcast message is received; the-
reby the reverse routes are established. Other additional
copies of the same RREQ arrived later are discarded.
The destination or any intermediate node with a “fresh
enough” route to the destination responds by unicasting a
route reply (RREP) packet back to the neighbor from
which it first received the RREQ. The RREP is routed
back along the reverse path hop-by-hop. The interme-
diate nodes update their route tables with the node from
which the RREP is received as forward route entries. If
an intermediate node moves, its upstream neighbors no-
tices it and sends a link failure notification message to all
its upstream neighbors to inform them of deletion of that
route. The link failure notification message is relayed to
the source which will choose to re-initiate a new route
discovery process or discard.
DSR is a source-routed on-demand routing protocol
[9]. In DSR, a node maintains route cache containing the
source routes that it is aware of and updates entries in the
route cache when it learns about new routes. The proto-
col consists of two major phases: route discovery and
route maintenance. The route discov ery phase is initiated
by broadcasting a route request (RREQ) when the source
node does not find a route to the destination in its route
cache or if the route has expired. This RREQ contains
the address of the destination, along with the source
nodes’ address and a unique identification number. To
limit the number of RREQs propagated, a node processes
the RREQ only if it has not already seen it before. Each
node receiving the RREQ checks whether it knows of a
route to the destination. If it does not, it adds its own
address to the route record of the packet and then for-
wards the packet along its outgoing links. A route reply
(RREP) is generated when either the destination or an
intermediate node with current information about the
destination receives the RREQ. In the ro ute maintenance
phase, each node transmitting the packet is responsible
for confirming that the packet has been received by the
next hop along the source route. Hello message is used to
maintain the local connectiv ity of a node. By periodically
broadcasting a hello message, a node may determine
whether the next hop is within communication range. If
no hello message is received, the node returns a route
error (RRER) message to the original sender of the pack-
et which can send the packet using another existing route
or perform a new route discovery and remove the expired
route information from its routing table.
Both AODV and DSR protocols employ a route dis-
covery procedure. However, they have several important
distinctions between each other. The most notable of
these is that DSR uses more overhead in route construc-
tions and route maintenance since each packet in DSR
keeps much more routing information than that of
AODV, whereas in AODV packets only contain the des-
tination and source address. DSR is intended for net-
works in which the mobile nodes move at a moderate
speed and the network is relatively small [9,16]. Addi-
tionally, DSR allows nodes to keep multiple routes to a
destination in their route cache [12,17]. When a link on a
route is broken, the source node can check its route cache
for another route. However, DSR does not contain any
mechanism to validate route entries when it faces with a
choice of multiple routes. This leads to stale route entries,
particular at high mobility environment. On the other
hand, AODV allows nodes to keep only one route entry
to each destination in the cache. The route discovery
process will be reinitiated if the route in the route table of
the source node is invalid.
3. The Reference Region Group Mobility
Model (RRGM)
3.1. Overview
In this section, we will give an overview of our proposed
mobility model that can be used to simulate group parti-
tions and group mergers, namely the Reference Region
Group Mobility model (RRGM). The generic case of
group mobility in MANETs will be discussed where
group partitions will be triggered by the events of gene-
rating new destinations. This can model the scenarios
when a new task is assigned to a group, such as in a mil-
itary operation or in search and rescue operations in dis-
aster recovery. In the following parts of this section, we
will introduce the group mobility in RRGM by different
cases: a group assigned with a single destination and a
group assigned with multiple destinations. In addition,
group operations in RRGM, i.e. group partitions and
group mergers, will also be described.
(a) (b) (c) (d)
Figure 1. Mobility of a group (with a single destination).

Y. ZHANG ET AL.
95
RRGM uses a novel concept, namely reference region,
which is a dynamic area associated with a group of nodes.
Location of a reference region changes dynamically dur-
ing the simulation. The size of a reference region is de-
termined by the number of nodes which are associated
with it. Next, we will introduce the idea of reference re-
gion and how it is used by a group to move towards its
destination in RRGM.
We bring out the idea of reference region and intro-
duce the mechanism of RRGM model with a basic case
first where a mobile group is assigned with a single des-
tination. Initially, a group of mobile nodes are deployed
in the simulation area and an area is created as the
so-called “reference region” (the white circle in the fig-
ures) for this group as shown in Figure 1(a). Next, a
destination is generated and it is assigned to the group
which was created previously as shown in Figure 1(b);
subsequently, a new reference region is generated in an
area between the group and the destination (the location
of the reference region and how to determine its size will
be introduced in the next section). Assuming that every
mobile node has the knowledge of the location of the
reference region of its group, each of them randomly
selects a point within the new reference region as its tar-
get and will move towards it. Later on, after all mobile
nodes arrive at their respective targets in the reference
region, the reference region will be relocated to a new
area which is closer to the destination as illustrated by
Figure 1(c). In this way, the reference region is itera-
tively relocated such that it is closer to the destination
after each iteration. This process will stop when the des-
tination falls within the most recent reference region be-
ing generated as shown in Figure 1(d). Finally, all mo-
bile nodes arrived at the destination , after which the des-
tination is removed to indicate the arrival of the group.
When mobile nodes arrive at the destination, they may
either pause for some time or continue their movement
within the reference region. A node can continue its
movement by randomly selecting a new point within the
reference region.
In group mobility of MANETs, it is possible for a
group to be assigned with multiple destinations simulta
neously. When that happens, a group partition will take
(a) (b) (c)
Figure 2. Mobility of a group (with multiple destinations).
place as illustrated by Figure 2(a) to Figure 2(c). In-
itially, a group of mobile nodes are created and deployed
into the simulation area, after which two destinations are
generated simultaneously and assigned to the group as
displayed in Figure 2(a). Correspondingly, two refer-
ence regions are created and each of them is placed be-
tween the group and one of the destinations respectiv ely.
Every mobile node in the original group randomly se-
lects a point within either reference region as its target as
shown in Figure 2(b). Finally, each mobile node moves
to their respective targets in the corresponding reference
regions as shown in Figure 2(c). The reference regions
are iteratively relocated such that it is closer to the desti-
nation after each iteration and eventually mobile nodes
will arrive at their respective destinations.
Reference region is also used for mergers between
groups in RRGM. Practically, it is likely for a small
group to merge with a larger group in MANETs. We
assume that every mobile nod e has the knowledge of the
location of all the groups, the location of the reference
region of its group’s, and the number of nodes in each
group during a simulation. Based on this information,
mobile nodes in a standby group can calculate the dis-
tance between its group and other groups respectively.
The closest group, which has the smallest distance to the
standby group, will be selected as the target for the
standby group to merge with. As displayed in Figure
3(a), there are two groups in the simulation area of which
one group is bigger than the other. In RRGM, for a group
not assigned with any destination, it can merge with
another group. To do so, group members from the small-
er group change their membership to the bigger group.
As a result of more mobile nodes joining into the bigger
group, the resultant reference region, the size of which is
proportional to the number of nodes in the group, is also
enlarged (the details will be introduced in Section 3.2) as
illustrated in Figure 3(b). Every mobile node from the
smaller group randomly selects a point within the new
reference region and moves towards it. When all mobile
nodes from the smaller group have reached the larger
group’s reference region, the merger between these two
groups is completed as shown in Figure 3(c).
It is easy to see that RRGM can be used to model the
(a) (b) (c)
Figure 3. Merger of two groups.

Y. ZHANG ET AL.
96
occurrence of grou p partitions and mergers in g roup mo-
bility of MANETs. An example of such an event taking
place is in the search and rescue operations. For such an
operation, a rescue team may be assigned with several
tasks simultaneously. As a result, some team members
have to move apart from the original team that leads to a
group partition. After a team of rescuers reached its des-
tination and carried ou t tasks, they may merge with other
teams.
3.2. Model Configurations and Implementations
Table 1 summarizes the input parameters used in RRGM
and their default values. Their specific usages will be
discussed along with the introduction of model imple-
mentations. Note as stated in Table 1, the reference re-
gion used could take the shape of either a rectangle or a
circle, which is controlled by the parameter  . During
implementatio n of th e model, when  = 0, it indicates th a t
a circle is used as the shape of the reference region. Next,
we give the definitions of some terms used in RRGM.
1) Center of a group/location of a group: it refers to
the point whose coordinates are obtained by taking the
average of the coordinates of all mobile nodes in the group.
Table 1. Input parameters of RRGM.
Spatial parameters Default
values
T-length,
T-width Dimensions of the simulation area (terrain size) in length and width (in meters). 1000 m, 1000 m
(x0, y0) Center’s coordinates of the initial group. (500,
500)
Group and node related parameters
Ntotal-node Total number of mobile nodes in the simu-
lation. 50
N
I
nitial-dest Number of destinations initially generated. 3
N
s
tandb
y
-
g
Standby groups initially deplo yed. 0
 Density of nodes in a group. (nodes/100 m2) 0.1
v0 Average node velocity. (m/s) 10

Velocity coefficient. 0.5
Timing parameters
T Simulation time. 1000 s
Td Interval for generating new destinations. 15 s

0 Pause time for a mobile node at a location. 0 s

1 Pause time for a reference region at a loca-
tion. 2 s

2 Idle time for a group at a destination. 10 s
Miscellaneous
 Ratio between the length and the width of a
reference region (for rectangular reference
region). If
 = 0, it represents circular
reference r egion is used.
1
dx, dy
Distance granularity for defining move-
ment trajectories of groups’ in the range of
(0,1).
0.3, 0.3
 A distance threshold between the center of
a group and a destination (in meters). 10
(Mx1,My1)
,...,
(Mx
k
,M
yk
)
Intermediate checkpoints of reference
regions (optional, used in scenarios with
predefined destinations).
n.a.
2) Center of a reference region/location of a refer-
ence region: it refers to the midpoint of a diagonal in the
rectangle reference region, or the center of the circular
reference region.
3) Distance between two groups: it refers to the dis-
tance between the centers of two groups.
Initially, all mobile nodes (i.e. Ntotal-node nodes) are
deployed in the simulation area as a single group. A ref-
erence region will be created at the center of the initial
group, whose coordinates are (x0, y0).
If a rectangle is used as the shape of the reference re-
gion, the length l and width w of the reference region are
jointly determined by both Ntotal-node and density of nodes
in a group, namely
 . Their relationship can be expressed
by:

total node
Nlw 
 (1)
As the ratio between the length l, and the width w, of a
reference region, namely
 , is specified, where  = l/w, l
and w can be calculated by:
,
total nodetotal node
NN
lw






 (2)
Note that the center of the reference region, whose
coordinate is (x0, y0), is the midpoint of a diagonal in the
rectangle reference region as illustrated in Figure 4. So
the range of the reference region would be from the bot-
tom left (x0 – l/2, y0 – w/2) t o the top right (x0 + l/2, y0 + w/2).
Similarly, if circle is considered as the shape of a ref-
erence region, the center of the circular reference region
is (x0, y0) and its radius r can be calculated as:
total node
N
r


 (3)
Subsequently, NInitial-des t destinations are randomly
generated. The initial group is logically partitioned into
NInitial-dest + Nstandby-g subgroups which are composed of
NInitial-dest active subgroups (equivalent to the number of
destinations) and Nstandby-g standby subgrou ps as specified
in the configuratio ns (Table 1). Standby groups are us ed
Figure 4．Illustration of a reference region.

Y. ZHANG ET AL.
97
to model situations where groups do not have destina-
tions to move towards. The default value of Nstandby-g in
our implementation is zero. The destinations which have
been generated are assigned to the active subgroups. As a
result each active subgroup has one destination. For mo-
bile nodes, each of them randomly selects a subgroup to
join in.
Next, a reference region will be generated for each ac-
tive subgroup. For a standby su bgroup, the lo cation of its
reference region is placed at the center of the subgroup.
The dimensions (the length and the width of a rectangle
reference region, or the radius of a circular reference
region) can be calculated using (2) or (3) respectively by
replacing Ntotal-node with the number of nodes in the sub-
group. For an active subgroup, the location of its refer-
ence region can be calculated by the following steps:
Step 1: Given an active group i, let the coordinates of
its destination be (xd, yd), and the number of nodes in the
subgroup be Ni.
Step 2: As it is already known that the coordinates of
the initial group’s location is (x0, y0), we can calculate the
location of the reference region of group i, namely (xi, yi),
by:
 
00id x
x
xx drandx  (4)
 
00id y
y
yydrand y  (5)
where d
x
and d
y
, in the range of (0,1], are the dis-
tance granularity for defining the trajectory of a refer-
ence region to the destination.

rang is a random
seed to generate a random number in the range of (0, 1)
in order to avoid generating exactly same trajectory of a
reference region to a destinatio n by these equations.
Step 3: The dimensions (the length and the width of a
rectangle reference region, or the radius of a circular
reference region) of the reference region can be calcu-
lated using (2) or (3) respectively by replacing Ntotal-node
with Ni.
3.3. Node’s Movement and Displacement of a
Reference Region
Once a reference region is generated for a group, the
respective group member will randomly select a point
within the range of the reference region as its target for
movement as stated in section 3.1. The velocity that each
group member travels with, namely v, is varied by:

00
rang

   (6)
where v0 is a pre-defined average velocity of mobile
nodes, and the random seed rand () returns a random
value within the range of (0, 1).

is a coefficient of v0
and  ×v0 contributes a fixed value to v. Once a mobile
node arrives at the point it has previously selected, it may
pause for a period of time

0 before continuing its
movement by choosing a new point within the reference
region as its target. The mobility of a mobile no de within
the range of its reference region is similar to that of the
Random Waypoint Mobility in the sense that a mobile
node travels with a selected speed towards a selected
destination in each iteration. Practically, this can mimic
the mobility of a team of rescuers carrying out operation s
in a small area before moving to a new disaster venue.
After all group members arrive at the reference region,
the reference region may remain at its current location
for a certain period, namely pause time of a reference
region 
1, which is timed from the arrival of all group
members to the reference region till a new location of th e
reference region is generated. Assuming that the current
location of a reference region is (xi, yi), its new location
(xi+1, yi+1) can be calculated by.

 
1idix i
x
xxdrand x


  (7)

 
1idiy i
y
xydrand y


  (8)
The basic ideas of these two equations are a s same as (4)
and (5) respectively. By adjusting the values of d
x
and
d
y
, a group’s movement trajectories coul d be different.
When the dis tance from the locatio n of a refer ence re-
gion to its destination is smaller than a threshold  , it may
be considered that the group has reached the destination,
and the group may pause for duration 
2, namely group
idle time, at this location. This en sures sufficient time for
a group to move around the destination area to complete
their tasks. After 
2, if there is no new destination as-
signed to this group, it becomes a standby group to indi-
cate the completion of the task.
3.4. Simulation of Mobility and Discussion
Assuming that a reference region is stationary during the
simulation (this can be realized by giving a big value to
group partition interval), a node associated with this ref-
erence region will iteratively select a new target within
the reference region for movement and this process will
repeat until the simulation ends. The mechanism of this
mobility pattern can be considered the same as that of
Random Waypoint Mobility. In this section, simulations
are conducted for each of these scenarios. The simulation
is developed under C++ platform and visualized by
NS2-nam [18].
In this subsection, we will present the generic group
mobility operations of group partitions and mergers si-
mulated by RRGM model, where destinations are gener-
ated periodically during the simulation. The parameters
for the simulation setting are configured as in Table 2.

Y. ZHANG ET AL.
98
Table 2. Input parameters for the simulation of generic
group mobility pattern.
T-length = 1000 N
total-node = 50 ρ = 0.1 T d =15
 = 0
T-width = 1000 N
Initial-dest = 3 v 0 =10

0 = 0 dx = 0.3
(x0 ,y0) = (500,0) N
standby-g = 0
 = 0.5 
1 = 2 dy = 0.3
T =1000

2 = 10

= 10
The size of simulation area is 1000 meters by 1000 meters
for the length and the width respectively (i.e. T – length
= 1000 and T – width = 1000). Each simulation is run for
1000 seconds (i.e. T = 1000). 50 mobile nodes (Ntotal-node =
50) are deployed at (500,0) initially (i.e. (x0,y0) =
(500,0)). 3 destinations (i.e. NInitial-dest = 3) are generated
initially and no standby group will be generated (i.e.
Nstandby-g = 0). Node density of each group is 0.1 node/100 m2
(i.e. ρ = 0.1 node/100 m2). The average speed of mobile
nodes is 10 m/s (i.e. v0 = 10) which is distributed in the
range of (5 m/s, 15 m/s) derived according to (7) where
the coefficient  is equal to 0.5. A new destination will
be generated at every 15 seconds (i.e. Td = 15). A node
will not pause during the simulation (i.e. 
0 = 0), and a
reference region pauses for 2 seconds (i.e. 
1 = 2 which
is timed from the arrival of all group members to the
reference region till a new location is generated for this
reference region). The group idle time 
2 is configured to
10 seconds. We use circle as the shape of reference re-
gions in the simulation (i.e.  = 0). The distance granu-
larity for group’s movement is 0.3 for both
x
d and
x
d.
When th e distance between the center of a gr oup and its
destination is less than 10 meters (i.e.  = 10), this
group is considered to have already arrived to the desti-
nation.
Traces of nodes’ movement are recorded and NS2-
Nam is used for visualization. Screenshots for mobile
nodes in the network are captured to demonstrate
their mobility. Figure 5 presents the occurrence of a
group that is partitioned into several subgroups which
subsequently merge. It is used to reflect group mobility
related applications in MANETs, such as military opera-
tions in battlefields, disaster recovery and scientific ex-
plorations. Destinations can be used to represent enemy’s
bases in military operations, or destroyed sites in disaster
recovery scenarios.
As shown in Figure 5(a), initially all nodes are dep-
loyed in a small area as the initial group. When three
destinations D1, D2 and D3 are generated, the initial
group is partitioned into three subgroups, A, B and C.
Meanwhile, reference regions are also generated for each
subgroup denoted by circles in the figures. Mobile nodes
move towards their corresponding reference regions
gradually. As shown in Figure 5(b) at the time t =15 s, a
new destination D4 is generated. The closest subgroup
Figure 5. Generic group mobility pattern with group parti-
tions and mergers.
B, which is moving towards D2, is split into two sub-
groups, B and D, and the subgroup D heads towards the
new destination D4. At t = 20 s, the subgroup C arrived
at D1 and it becomes a standby group, and D1 is re-
moved as illustrated in Figure 5(c). From Figure 5(d) to
Figure 5(f), screenshots for a group merger process are
captured. In Figure 5(d), the two smaller subgroups E
and F are standby su bgroups while the other subgro up G
is an active subgroup. In Figure 5(e), the reference re-
gion of the subgrou p E is merged with subgroup F’s ref-
erence region. The process of this group merger is com-
pleted at t = 85 s when all group members in F move into
the reference region of subgroup F as shown in Figure 5 (f).
4. Performance Evaluation of Network
Routing Protocols Using RRGM
In this section, we will evaluation the performance of
AODV and DSR under the group mobility network en-
vironment generated by the RRGM model.
4.1. Network Environment Configurations
The simulation studies are carried out using the mobile
network simulator QualNet [19]. To set up the simulation
network environment, we generate 50 mobile nodes
placed within a 1200 meters  600 meters grid (as ela-
borated in Table 3). Radio propagation range of each
node is 250 meters with channel capacity of 2 Mbits/s.
20 sender-receiver pairs are designated randomly and each
source can generate constant bit rate (CBR) traffic of
512 bytes data packet every second. Every simulation is run

Y. ZHANG ET AL.
99
Table 3. Configurations of the network environment.
Parameters Values
Terrain size 1200 meters  600 meters
Radio propagation range 250 meters
Channel capacity 2 Mbits/s
CBR traffic 512 bytes/second
Simulation time 900 second
Number of nodes 50
for 900 seconds. Each scenario is repeated for 20 times
and the average values are finally presented in the simu-
lation results. The simulation studies are carried out by
varying the speeds of mobile nodes and node density1.
Increase of speed can lead to fast change of network to-
pology whereas in turn affects the network performance.
Node density is used to describe the relative distance
between group members. When the node density is low,
it indicates that group members have a longer distance
between one another, whereas high node density (e.g. a
great many mobile nodes in a small area) means group
members will be closed to each other. With a fixed num-
ber of mobile nodes in a group, reducing the node densi-
ty will result in an increase in the average distance be-
tween group members. This in turn will result in an in-
crease of the coverage area of the group. We note that
the changes of group coverage will eventually have an
impact on the network performance especially for a net-
work where group partitions would take place frequently.
4.1.1. Experimental Settings—Investigation on Speeds
This experiment is conducted according to two different
scenarios, namely:
1) Scenario I—Group mobility with group partition
disabled.
2) Scenario II—Group mobility with group partition
enabled.
In Scenario I, group partitions are disabled by assign-
ing a big value (which is greater th an the simulation ti me)
to the “partition interval” in RRGM. Therefore, group
mergers would also not take place in this scenario. It is
notable that due to the random mobility of groups, the
transitory overlapping of groups is not considered as
group mergers in this work. On the other hand, group
partitions and mergers would take place in Scenario II by
assigning a suitable value to the “partition interval” (e.g.
every 40 seconds) in the RRGM model. Idle subgroups,
which do not have any assigned destinations for move-
ment, will merge with other subgroups.
In Scenario I, 50 nodes are initially deployed into
three different subgroups such that each of the subgroup
will consist of 16 or 17 group members. Since group
partitions are not allowed to take place in this scenario,
the membership of each group is fixed throughout the
simulation. We identify 20 source-destination pairs wher e
50% data packet transmission is made via inter-group
communications (the source and destination pairs are
placed in different subgroups respectively) and another
50% is via intra-group communications (the source and
destination pairs are placed in the same group).
In Scenario II, 50 nodes are initially deployed all to-
gether in one group. Group partitions will take place in
every 40 seconds interval with the RRGM model. How-
ever, if each subgroup has less than 10 nodes, it will not
be further partitioned and newly generated destinations
should be discarded. This is due to the fact that when
group size2 is very small, there will be many small sub-
groups generated during the simulation and the commu-
nications will mostly be in the manner of inter-group
communications. Hence, the experimental results will
not lose the nature of intra-group communications.
The node density is fixed at 500 nodes/km2 as confi-
gured in RRGM. We vary average node speeds from 1
m/s to 20 m/s to investigate its impact on the network
performance. When the average node speed is high, more
impetuous and arbitrary movement of groups will occur.
Hence group partitions are expected to take place more
frequently.
4.1.2. Experimental Settings—Investigation on Node
Densities
In this experim ent, node densi ty is varied from 200 nodes/ km 2
to 400 nodes/km2 in steps of 50 nodes/km2. Node speed
is randomly generated within the range of (15 m/s, 25 m/s ).
Group partitions and mergers are enabled in this experi-
ment. As discussed in the earlier part of this section,
changing node density will result in the change of
group’s coverage area. However, we notice that most
intra-group communications can be done via one hop. If
group partitions and mergers do not take place, changes
of node densities will not have a significant impact on
the network performance. Hence, the scenario where
group partitions and mergers are disabled is not consi-
dered for this experiment. The group partition interval is
fixed at 40 seconds in RRGM. Other parameters are the
same as those used in the experiment of investigating on
node speeds as described in the subsection 4.1.1.
4.2. Performance Metrics
The performance metrics which will be used in the si-
mulation include the packet delivery ratio (PDR), the
1Node density refers to the node density in a group, i.e. the number o
f
nodes in an area where mobile nodes can move for their local move-
ment in the group. 2Group size is defined as the number of nodes in a group.

Y. ZHANG ET AL.
100
average control packets per data packet sent (ACP), and
the end-to-end delay. PDR reflects the percentage of data
packets that can be successfully delivered, which is an
important metric to evaluate the efficiency of a network.
ACP refers to the amount of routing packets required to
set up and maintain routes in order to deliver data pack-
ets and it is then normalized by every data packet sent to
indicate the average overhead spent in order to deliver a
data packet. End-to-end delay measures the average time
spent in the period when a packet is successfully sent
from the source to the destinatio n. Next, we will specifi-
cally introduce each of these performance metrics.
PDR is calculated as the ratio of the number of data
packets delivered to the destinations to those generated
by the sources. Mathematically, it can be expressed as:
received
s
ent
p
PDR P 
 (9)
received
p
stands for the total number of data packets
received at receivers, while
s
ent
P

is the total number
of data packets sent during a simulation.
The control packets include route request (rreq), route
reply initiated by intermediate nodes (rrep(1)) and by
destinations (rrep(2)) separately, and route error mes-
sages (rerr). We calculate the sum of all the control
packets incurred during simulation, wh ich is then norma-
lized by the total number of data packet sent as repre-
sented by:
 
12
sent
rreq rreprreprerr
ACP P
 
 
 (10)
End-to-end delay refers to the time taken for a packet
to be transmitted across a network from a source to its
destination. This metric can reflect the quality of com-
munications between users. This includes all possible
delays caused by buffering during route discovery,
queuing at the interface queue, retransmission delays at
the MAC layer, propagation delay and transmission de-
lay. Node’s mobility may cause the breakage of estab-
lished links which result in the loss of data packets and
additional delay incurred as a result of packet retrans-
missions. The overall end-to-end delay can be defined as:

1
1receiv ed
p
ii
i
received
EEDr s
p

 (11)
where preceived is the number of successfully received
packets at destinations, i is the unique packet identifier,
and ri is the time at which a packet with the u nique id i is
received, while si is the time at which a packet with the
unique id i is sent.
4.3. Simulation Results of Routing Protocols
4.3.1. Varying the Average Speed
Figure 6 and Figure 7 presents the results which show
how the packet delivery ratio varies with mobility speeds.
As illustrated in Figure 7, the trends of packet delivery
ratio for both AODV and DSR increase as the average
speed increases when group partition is disabled. The
growth is 2% to 3% for both of AODV and DSR. Since
50% source-destination pairs are placed in different
groups respectively for inter-group communications,
they may not be connected initially if the sources can not
find routes to their destinations, which may be due to the
long distance beyond the transmission range or the lack
of intermediate nodes between each other. When the
network topology changes as nodes move faster, those
previously disconnected source-destination pairs which
are placed in different groups would possibly get con-
nected. As a result, more data packets can be received by
the destinations in inter-group communications. Hence,
the packet delivery ratio is increased as the speed in-
creases.
On the contrary, the performance of packet delivery
ratio for both DSR and AODV falls dramatically under
Figure 6. Packet delivery ratio vs. Average speed (m/s)—
Group partition disabled.
Figure 7. Packet delivery ratio vs. Average speed (m/s) —
Group partition enabled.

Y. ZHANG ET AL.
101
the group partitioning scenario when nodes move faster
as shown in Figure 7. A larger number of group parti-
tions will occur when the node speed is increased. For
example, a pair of source-destination previously in a
same group would be easily separated into different
groups when more group partitions take place and con-
sequently data packets from the source can not be deli-
vered to the destination. As a result, packet delivery ratio
will drop, as reflected by the decreasing trend for both
AODV and DSR respectively. It is notable that AODV
still can retain a relatively high packet delivery ratio of
70% when the average speed is increased to 15 m/s to
20 m/s. Comparatively, only 50% packets can be re-
ceived in DSR at the speeds of 15 m/s to 20 m/s. As dis-
cussed in subsection 2.2, AODV reacts faster than DSR
when the network topology changes because AODV only
keeps one route entry and when it becomes invalid, it
will reestablish a new route. However, DSR has to
maintain multiple routes en tries before reinitiating a new
route discovery process. Hence, AODV is more adaptive
to frequent network topology changes than DSR and
consequently it yields a higher packet delivery ratio than
DSR. It is notable the packet delivery ratio for both
AODV and DSR is up to 95% to 98% where DSR is
slightly higher than AODV for about 1 % when the speed
is 1 m/s. As described in the earlier subsection 4.1.1, in-
itially all mobile nodes are deployed in on e big group for
this scenario. When the speed is lo w, nodes barely move
during the simulation (compared to the high speed cases).
Hence, routes maintained by both AODV and DSR can
be valid for longer period of time. Therefore, the packet
delivery ratio is higher for low average speeds.
Comparing with Figure 6 and Figure 7, we notice that
when group partition is enabled the packet delivery ratio
drops very fast, which is due to the frequent changes of
network topology. On the other hand, when group parti-
tion is disabled, the packet delivery ratio yielded from
the intra-group communications will not change dramat-
ically as a result the packet delivery ratio only varies in a
small range from 60% to 65% as illustrated in Figure 6.
Figure 8 and Figure 9 present the results which show
how average control packets by per packet sent varies
with mobility speeds. In Figure 8 where group partition
is disabled, the average contro l packets raises slightly as
the speed increases and approximately in average 0.55
and 0.77 control packet is generated per data packet sent
for AODV and DSR respectively. It tallies with the ear-
lier discussion in this subsection that DSR uses more
control overhead than AODV in route maintenance. The
control packets are mainly consisted of two portions:
control packets for inter-group communications and in-
tra-group communications. When group partition is
Figure 8. Average control packets per packet sent vs. Av-
erage speed—Group partition disable.
Figure 9. Average control packets per packet sent vs. Av-
erage speed—Group partition enabled.
disabled, th e control packets for intra-group communica-
tions will be relatively stable since the group member-
ship is not changed and hence routes can be valid for
longer period of time during the simulation. On the other
aspect, the control packets generated for inter-group
communications will vary with the mobility speeds.wh en
speed is increased, more control packets for route main-
tenance of inter-group communication s will be generated,
therefore, it results a slight increase in the number of
control packets for AODV and DSR in this scenario.
In the group partition enab led scenario as displayed in
Figure 9, more control packets are generated in both
DSR and AODV when speed is raised. As initially, all
mobile nodes are deployed together in one group, the
intra-group commutations dominates at the beginning. It
can be easily understood that intra-group communica-
tions are more stable than inter-group communications
when group partitions do not occur. Therefore, the con-
trol packets are relatively low when the speed is as low
as 1 m/s (which we can say they barely move compared
to the high speed cases). Correspondingly, it also can be
reflected by a high packet delivery ratio as illustrated in
Figure 7 when mobility speed is at 1 m/s. However,

Y. ZHANG ET AL.
102
group partition takes place more frequently when the
mobility speed increases as what we observ ed during the
simulation. When group partitions take place, the pre-
vious stable intra-group communications would be dis-
rupted, which results in massive route error messages
and control packets for new route discovery process
which would occur in both AODV and DSR. Thus, the
control packets increase dramatically with the increase of
mobility speeds as displayed in Figure 9.
The average control packets for the two scenarios as
displayed in Figure 8 and Figure 9 also appear diffe-
rently. The basic reason behind the trend of these simula-
tion results is similar to what has been described for
packet delivery ratio that group partitions lead to more
topology changes which result more control packets
generated for route maintenance.
Figure 10 and 11 illustrate the results of end-to-end
delay of data packet delivery in group partition disabled
and enabled scenarios respectively. In Figure 10, DSR
generates much higher end-to-end delay than that of
AODV, which is the same as what it does in Figure 11
(the end-to-end delay is small for both AODV and DSR
when the speed the at 1 m/s because all node are initially
deployed in one group as discussed in section 4.1). The
end-to-end delay in DSR is ov er 1.5 seconds whereas the
end-to-end delay of AODV is only less than 0.3 second
for both scenarios.
This great distinction in end-to-end delay between
AODV and DSR is due to the difference of their working
mechanisms. As introduce in subsection 2.2, caching is
designed for keeping routing information in AODV and
DSR. Caching is used in both route discovery process
and route recovery process to increase the possibility of
finding a route without initiating flooding of messages.
In AODV, only one cache entry is allowed to be kept for
each source-destination pair, while all possible routes are
cached in DSR. In a dynamic environment, network to-
pology changes very fast resulting in caching informa-
tion becoming obsolete more quickly. Therefore, when a
data packet is sent via a broken link in AODV, the node
detecting the disconnection would return a route error
message immediately and requests th e source to reinitiate
a new route discovery process. However, in DSR, the
node detecting the route breakage sends a route error to
the source node and the source would no t reinitiate a new
route discovery process until all route entries to the des-
tination in its cache are tried.
It is possible for a source in DSR to keep multiple
route entries via nodes in different groups to its destina-
tion. If a group, with which its intermediate nodes affili-
ate, has moved away, many of its route entries would
become invalid simultaneously. The source node has to
repair the broken links by trying all possible routes in its
cache which results in a much higher end-to-end delay.
On the contrary for AODV, as only one route entry is
Figure 10. End-to-end delay vs. Average speed—Group
partition disabled.
Figure 11. End-to-end delay vs. Average speed—Group
partition enabled.
maintained by the source, the source can reinitiate a new
route discovery process as soon as the route is no longer
available. Therefore, the delay generated during the route
recovery in DSR does not occur in AODV and thus the
end-to-end delay in AODV is much lower than that of
DSR as illustrated in Figure 10 and 11.
Comparing Figure 10 and 11, we notice that DSR ge-
nerates lower end-to-end delay when group partition is
enabled, which reduces from 1.7 seconds to 1.5 seconds
approximately when the speed is up to 15 m/s. As the
mobility speed increases, more group partitions would
take place and with the aid of more subgroups, the source
in DSR can find more alternative routes(via different
subgroups) to the destinations. Therefore, the end-to-end
delay in DSR can be reduced slightly. However, route
entries in the sources in AODV become obsolete quickly
when group partitions take place more frequently, and
hence it yields a slightly higher end-to-end delay, which
is about 0.05 second, in the partition enabled scenario.
4.3.2. Varying the Node Density
Figure 12 illustrates the chang e s in packet delivery ratio
for AODV and DSR with respect to node densities. As it

Y. ZHANG ET AL.
103
is shown, packet delivery ratio drops from 71% to 60%
for AODV and from 68% to 54% for DSR with the node
density increases from 200 nodes/km2 to 400 nodes/km2.
AODV yields an approximate 10% higher packet deli-
very ratio than DSR. As discussed in the subsection 4.1.2,
group coverage area is inversely proportional to the node
density in the group. With a fixed number of mobile
nodes, increasing node density in a group (where mobile
nodes will be closer to other group members) will reduce
the coverage area of the group. Therefore, links between
connected groups may be broken because of the decrease
of the group coverage areas which leads to a longer dis-
tance between those previously connected groups. As a
result as illustrated in Figure 12, some data packets
would not be deliv ered to the destin ations via in ter-group
communications.
Figure 13 illustrates the changes of average control
packets per data packet sent for AODV and DSR with
respect to node densities. As the node density increases,
group’s coverage will be reduced as discussed in the
subsection 4.1.2. As a result, less inter-group communi-
cations would be occurred and sources would not main-
tain as many route entries as that when more inter-g roup
communications occur. Hence, the amount of mainten-
ance control packets can be reduced when density is in-
creased as shown in Figure 13. AODV uses nearly 50%
of the control packets that are used in DSR because
AODV only keeps one route entry whereas DSR has to
maintain multiple route entries wh ich requires more con-
trol packets in route maintenance.
Figure 14 presents the results which show the
end-to-end delay of AODV and DSR varied by node
density. As discussed in the last subsection, when the
node density increases, more links for inter-group com-
munications may be broken (due to the coverage of
groups become smaller which is inversely proportional to
the node density). Therefore, more data packets would be
lost which is illustrated in Figure 12 and retransmissions
are required. Hence, more time will be spent on estab-
lishing new routes and it results in a higher end-to-end
delay for both AODV and DSR. DSR generates a much
higher end-to-end delay due to their different mechan-
isms node density increases, more links for inter-group
communications may be broken (due to the coverage of
groups become smaller which is inversely proportional to
the node density). Therefore, more data packets would be
lost which is illustrated in Figure 12 and retransmissions
are required. Hence, more time will be spent on estab-
lishing new routes and it results in a higher end-to-end
delay for both AODV and DSR. DSR generates a much
higher end-to-end delay due to their different mechan-
isms to store and maintain route entries which has been
discussed in the subsection 4.3.1.
Figure 12．Packet delivery ratio vs. Node density—Group
partition enabled.
Figure 13. Average control packets per data packet sent vs.
Node density—Group partition enabled.
Figure 14. End-to-end delay vs. Node density—Group par-
tition enabled.
4.4. Discussion
From the above comparisons and discussions, AODV
shows its advantages in many aspects and outperforms
DSR in group mobility network environment. The fun-

Y. ZHANG ET AL.
104
damental difference between AODV and DSR is the
mechanism of maintaining routing cache tables. AODV
keeps only one route entry in its routing cache. Whenev-
er the route is stale, it will reinitiate a new route recovery
process. However, in DSR, multiple route entries are
kept in each route table, if any breakage of a link is de-
tected, a maintenance process has to be triggered to re-
pair the broken links first before a new route discovery
takes place. In dynamic network environment, routes
turn stale quickly. Thus, more control packets are gener-
ated during the route recovery operations in DSR and
therefore it has a longer delay. AODV is more adaptive
to the dynamic environment and it is able to response
quickly to link breakage by recon st ruct i n g a new ro ut e.
When a group partition takes place, some connections
may be broken and communications between sources and
destinations are interrup ted. It results in more packet loss
and packet delivery ratio is reduced. As almost every
routing protocol is implemented with a route recovery
mechanism, it takes more control packets to repair the
broken links which may prolong end-to-end delay. High
speed movement can greatly affect network performance.
Increase of node density can also weaken network per-
formance since it can change the coverage of groups
which affect the relative distance between connected
groups in the network. AODV has proven itself as a
more efficient network routing protocol than DSR in
group mobility environment of MANETs.
5. Conclusions
In this paper, we proposed RRGM model for simulation
studies in MANETs which can be used to simulate group
mobility. By taking the advantages of RRGM, group
operations, such as partitions and mergers, can be rea-
lized. Simulations are conducted in modeling a number
of different applications of ad hoc networks.
One step forward, we carried out a comprehensive
study on the impact of group partitions and mergers to
the network performance of two typical reactive routing
protocols, AODV and DSR. The network mobility pat-
terns are generated by RRGM model. AODV and DSR
are compared by changing the speed and node density.
Experiment results show that group partitions have a
significant impact on the network performance which has
never been revealed before. Frequent group partitions
can downgrade the performance of both AODV and DSR.
However, AODV shows its advantages in tackling with
such kinds of group operations better than DSR. In addi-
tion, AODV is also more adaptive to high speed envi-
ronment. On the other hand, DSR is suitable to a network
with less mobility where the load of route maintenance is
not heavy.
As a conclusion, it is impossible and not meaningful to
find a pervasive routing protocol that can be adaptive to
any network environment. Every network routing proto-
col may only work well under some particular network
circumstance. Selecting a suitable network routing pro-
tocol is very important for studying the operations and
performance of MANETs.
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