Conference Paper

A flexible visual simulator for wireless ad-hoc networks of mobile nodes

Pavia Univ.
DOI: 10.1109/ETFA.2005.1612552 Conference: Emerging Technologies and Factory Automation, 2005. ETFA 2005. 10th IEEE Conference on, Volume: 1
Source: IEEE Xplore
ABSTRACT
The management of ad-hoc networks raises interesting problems, that are particularly challenging for networks of mobile nodes. Considering the inherent complexity of these systems, the development of distributed applications relying on wireless communication protocols would be greatly simplified by the use of specific tools for supporting testing and step-by-step debugging. In this paper we describe WISE, a flexible interactive simulation environment for the development of wireless ad-hoc networks consisting of mobile units. A graphical interface allows the user to create/delete nodes, change their positions and parameters, and select specific mobility models in order to verify the network behavior in dynamic conditions. The simulator also provides a useful support for the verification of agreement protocols, synchronization algorithms and distributed scheduling, allowing the user to display a step-by-step evolution of the algorithms in a suitable graphical representation

Full-text

Available from: Tullio Facchinetti
A
Flexible
Visual
Simulator
for
Wireless
Ad-Hoc
Networks
of
Mobile
Nodes
*
Tullio
Facchinetti
University
of
Pavia
Pavia,
Italy
tullio.facchinetti
@unipv.it
Giorgio
Buttazzo
University
of
Pavia
Pavia,
Italy
buttazzo
@unipv.it
Luis
Almeida
DET
/
IEETA
-
University
of
Aveiro
Aveiro,
Portugal
Ida@det.ua.pt
Abstract
The
management
of
ad-hoc
networks
raises
interesting
problems,
that
are
particularly
challenging
for
networks
of
mobile
nodes.
Considering
the
inherent
complexity
of
these
systems,
the
development
of
distributed
applica-
tions
relying
on
wireless
communication
protocols
would
be
greatly
simplified
by
the
use
of
specific
tools
for
sup-
porting
testing
and
step-by-step
debugging.
In
this
paper
we
describe
WISE,
a
flexible
interactive
simulation
environment
for
the
development
of
wireless
ad-hoc
networks
consisting
of
mobile
units.
A
graphical
interface
allows
the
user
to
create/delete
nodes,
change
their
positions
and
parameters,
and
select
specific
mobil-
ity
models
in
order
to
verify
the
network
behavior
in
dy-
namic
conditions.
The
simulator
also
provides
a
useful
support
for
the
verification
of
agreement
protocols,
syn-
chronization
algorithms
and
distributed
scheduling,
al-
lowing
the
user
to
display
a
step-by-step
evolution
of
the
algorithms
in
a
suitable
graphical
representation.
Keywords:
wireless
networks,
simulation
environment,
mobility.
1
Introduction
Recent
advances
in
wireless
communication
technol-
ogy
and
a
progressive
reduction
in
the
associated
costs
are
boosting
the
use
of
wireless
networks
in
many
di-
verse
domains,
either
to
integrate
office
equipment,
per-
sonal
equipment,
or
even
to
interconnect
sensory
and
ac-
tuating
devices.
One
of
the
fields
in
which
there
is
strong
interest
in
the
use
of
wireless
networks
is
the
interconnection
of
mobile
units
with
sensing,
processing,
and
communication
capa-
bilities
for
monitoring
and
exploration
purposes.
In
some
cases,
the
possibility
of
controlling
the
po-
sition
of
the
nodes
(through
teleoperated
or
autonomous
mobile
robots)
would
allow
much
higher
flexibility,
be-
cause
the
network
could
be
configured
for
a
better
cover-
age
of
the
sensed
area,
or
for
actively
following
the
evo-
lution
of
the
phenomena
[9,
12].
When
nodes
move,
how-
*This
work
has
been
partially
supported
by
the
Italian
Ministry
of
University
Research
under
contract
2003094275
(COFIN03)
and
con-
tract
2004095094
(COFIN04).
ever,
they
need
to
interact
with
the
environment
(e.g.,
to
avoid
obstacles)
and
with
the
other
nodes
of
the
network;
hence,
most
of
the
activities
carried
out
by
the
team
need
to
be
executed
under
timing
constraints,
that
must
be
en-
forced
on
tasks
to
guarantee
a
minimum
level
of
perfor-
mance.
In
some
applications
the
communication
among
distant
units
is
based
on
a
wired
backbone.
However,
in
the
considered
above
situations,
a
wired
infrastructure
cannot
be
used,
hence
a
full
autonomy
of
the
team
units
can
only
be
achieved
using
an
ad-hoc
network.
Design,
analysis
and
test
of
mobile
ad-hoc
wireless
net-
works
take
great
advantages
from
specific
tools.
Although
some
basic
network
and
communication
protocol
proper-
ties
can
be
theoretically
proved,
in
other
cases
the
net-
works
performance
and
their
behavior
in
particular
condi-
tions
can
only
be
tested
by
simulation.
In
particular,
this
is
true
for
networks
made
by
mobile
units,
since
several
different
topology
configurations
are
possible
and
the
net-
work
connectivity
changes
dynamically.
Moreover,
the
analysis
of
MANETs
include
several
issues:
area cover-
age,
localization,
connectivity,
message
routing,
and
time-
liness
in
message
exchanging
[13].
Several
simulation
environments
are
currently
avail-
able
in
the
academic
world.
The
Network
Simulator
ns-
2
[1]
is
one
of
the
most
widely
used
tool
for
the
perfor-
mance
analysis
and
evaluation
of
network
protocols.
It
recently
included
features
to
simulate
wireless
networks
with
the
introduction
of
the
MobileNode
class.
However,
it
cannot
be
used
for
online
demonstrations
and
interac-
tive
debugging,
since
it
does
not
provide
online
graphical
output.
The
Cnet
simulator
[11]
is
an
easy-to-use
sim-
ulation
tool.
It
implements
the
ISO/OSI
stack
paradigm
and
can
simulate
both
Ethernet
based
LANs
and
token
ring
based
LANs
,
but
it
does
not
support
wireless
com-
munication
and
does
not
provide
online
graphical
out-
put.
Netsim
[5]
is
a
powerful
simulation
tool,
but
it
does
not
support
wireless
networks,
neither
a
graphical
inter-
face.
The
GloMoSim
[4]
simulation
environment
was
de-
veloped
for
simulating
large-scale
wireless
networks:
it
is
multi-platform
and
provides
a
graphical
interface,
but
it
requires
the
use
of
the
PARSEC
environment
[2]
as
a
parallel
simulation
engine
to
provide
high
computational
power.
This
paper
describes
WISE,
Wireless
Interactive
Sim-
ulation
Environment.
WISE
is
a
flexible
visual
simula-
0-7803-9402-X/05/$20.00
©
2005
IEEE
397
VOLUME
1
Page 1
ENVIRONMENT
obstacles
interferences
NETWORK
NETWORK
number
of
nodes
NODE
topology
NODE
position
transmiission
power
individual
behaviour
Figure
1.
WISE
simulation
levels.
tor
specifically
developed
for
ad-hoc
networks
of
mobile
units.
The
simulator
provides
a
basic
infrastructure
to
simplify
both
the
implementation
and
debug
of
new
algo-
rithms.
WISE
has
been
designed
to
be
user-friendly
and
can
be
used
to
analyze
a
protocol
and
to
present
a
graphic
step-by-step
evolution
of
the
algorithm
behavior.
For
this
purpose
the
package
combines
the
simulation
engine
with
a
highly
customizable
graphical
interface.
The
rest
of
the
paper
is
organized
as follows:
Section
2
presents
the
general
architecture
of
the
simulator;
Sec-
tion
3
describes
the
most
relevant
implementation
details;
Section
4
illustrates
the
the
operational
modes
of
WISE;
Section
5
introduces
the
topics
related
with
the
graphic
engine;
Section
6
provides
an
example
of
usage;
finally,
Section
7
states
our
conclusions
and
future
work.
2
The
simulator
WISE
has
been
designed
to
simulate
distributed
pro-
tocols
for
wireless
ad-hoc
networks
consisting
of
mobile
nodes.
The
main
features
of
the
simulator
include:
*
Native
support
for
node
mobility,
to
test
the
behavior
of
the
network
in
dynamic
environments;
*
Modular
software
structure;
*
Object-oriented
programming;
*
Interactive
graphical
interface
to
simplify
the
design
of
a
network
and
the
verification
of
network
proto-
cols.
Figure
1
illustrates
the
hierarchial
model
adopted
for
WISE.
The
model
is
node-centric,
meaning
that
the
Node
is
the
elementary
component
of
the
system.
Nodes
can
be
grouped
into
one
or
more
Networks,
fully
interacting
among
themselves.
The
simulator
also
supports
a
model-
ing
of
the
Environment
where
the
nodes
move.
Each
hierarchical
level
is
characterized
by
specific
properties:
nodes
are
characterized
by
their
position,
in-
dividual
behavior
(i.e.,
moving
strategy),
transmission
power,
etc.
Networks
may
have
a
maximum
number
of
nodes,
positioning
limitations,
and
other
constraints.
The
Environment
may
introduce
obstacles,
sources
of
interfer-
ence
and
noise.
The
elements
of
a
level
may
affect
the
properties
of
the
elements
in
another
level.
For
example,
the
network
topol-
ogy
is
influenced
by
the
nodes
position;
its
connectivity
is
affected
by
the
presence
of
obstacles
and
by
the
environ-
mental
interferences,
which
may
disturb
the
communica-
tion
between
two
nodes.
Actually,
the
interaction
between
a
Node
and
the
Environment
is
unidirectional,
since
the
Environment
may
affect
the
behavior
of
the
Node
through
obstacles
and
interferences,
but
the
Node
cannot
affect
the
Environment.
Nodes
can
be
freely
inserted
in
the
environment,
and
they
can
be
manually
moved
during
the
simulation
in
or-
der
to
test
particular
topological
configurations
of
the
net-
work.
A
manual
control
of
the
node
position
during
a
step-
by-step
session
can
be
very
useful
to
verify
the
effects
of
hidden
terminals
on
the
behavior of
the
tested
algorithm.
3
Implementation
of
the
model
The
implementation
WISE
aims
at
achieving
two
levels
of
flexibility:
1.
portability
of
the
kernel
on
different
operating
sys-
tems;
2.
independence
among
different
logical
modules.
The
WISE
core
is
implemented
in
the
C++
language.
On
one
hand,
it
ensures
high
efficiency
and
strong
opti-
mizations
in
the
WISE
simulation
core;
on
the
other
hand,
it
achieves
good
portability
between
different
operating
systems.
However,
portability
problems
may
arise
from
the
graphical
interface:
typically,
the
graphic
engine
is
strongly
operating
system
dependent.
In
our
implementation,
the
simulator
kernel
is
sepa-
rated
from
the
graphical
interface,
thus
allowing
the
simu-
lation
even
in
the
absence
of
graphical
support.
For
exam-
ple,
the
simulation
results
may
be
collected
in
a
text
file
to
be
used
later
for
off-line
analysis
with
specific
tools.
An
additional
advantage
of
separating
the
simulator
kernel
from
the
graphical
interface
is
the
fact
that
the
same
sim-
ulation
results
can
be
represented
under
different
views,
thus
making
their
interpretation
easier
and
immediate.
For
example,
two
different
windows
may
be
used
to
separate
different
representations
of
the
same
data
and
a
third
win-
dow
may
compare
the
two
representations.
The
kernel
has
been
implemented
by
taking
full
advan-
tage
from
the
object
oriented
hierarchical
paradigm
pro-
vided
by
the
C++
language.
At
the
bottom
of
the
hier-
archy
there
is
the
TBasicNode
class,
that
forms
the
data
background
common
to
almost
all
wireless
environments,
mainly
concerning
the
node
position.
The
TDrawNode
class
extends
the
basic
node
representation
by
adding
few
properties
needed
to
simplify
the
graphic
node
represen-
tation.
Other
classes
are
derived
from
TBasicNode
and
TDrawNode
in
order
to
represent
specific
types
of
nodes.
They
just
add
the
data
structures
and
functions
needed
for
specialized
simulations,
like
transmission
ranges
and
channel
frequencies.
Every
node
is
a
member
of
a
network.
From
the
im-
plementation
point
of
view,
this
means
that
the
TNetwork
class
is
a
collector
of
TBasicNode
objects.
In
the
same
way,
TEnvironment
collects
a
set
of
TNetwork
classes,
since
all
the
networks
reside
in
the
environment.
New
nodes
are
added
to
existing
networks,
and
new
networks
may
be
added
to
the
environment.
The
TNetwork
and
TEnvironment
containers
provide
the
functions
to
deal
VOLUME
1
398
Page 2
Figure
2.
The
main
window
of
the
simulator.
with
their
members.
For
example,
TEnvironment
provide
a
function
to
evaluate
the
distance
between
two
nodes
and
this
function
is
used
to
check
whether
a
node
is
able
to
listen
to
another
node
transmission.
Whenever
a
node
with
a
new
behavior
is
needed,
the
class
hierarchy
has
to
be
extended
to
derive
the
new
el-
ement
from
the
TBasicNode
class.
For
example,
a
node
moving
accordingly
with
a
specific
mobility
model
inher-
its
the
characteristics
from
a
common
node,
but
imple-
ments
the
new
behavior
for
the
moving
strategy.
4
Running
a
simulation
The
simulation
goes
on
as
a
potentially
infinite
series
of
steps,
called
ticks.
At
each
tick,
an
event
is
generated
within
the
simulation
environment,
and
every
component
executes
the
corresponding
action.
For
example,
a
node
may
update
its
current
position
according
to
the
mobility
model
parameters,
and/or
it
may
need
to
broadcast
a
mes-
sage
acting
upon
its
communication
algorithm.
WISE
can
run
a
simulation
under
three
modes:
*
in
step-by-step
mode;
*
in
live
mode;
*
in
batch
mode
with
(optional)
online
graphical
out-
put.
The
three
simulation
modes
depend
on
how
the
ticks
are
generated:
in
step-by-step
mode,
each
tick
is
gener-
ated
after
an
explicit
command
issued
by
the
user;
in
live
mode,
the
ticks
are
triggered
periodically
by
an
internal
timer
with
selectable
period;
finally,
in
batch
mode,
each
event
associated
with
a
tick
is
forthwith
generated
after
the
end
of
the
computation
started
by
the
previous
tick.
The
last
mode
is
the
fastest
and
may
not
retrieve
a
graphic
feedback.
The
three
options
have
been
proposed
for
different
pur-
poses.
The
step-by-step
update
is
useful
to
tune
the
system
parameters
and
to
debug
the
algorithm.
The
periodic
up-
date
may
be
used
to
monitor
the
online
system
behavior,
common
v
sualiatiIon
Figure
3.
Relationships
among
WISE
win-
dows.
by
observing
the
dynamics
in
link
establishment
or
break-
ing
together
with
the
system
data
flow.
The
batch
mode
can
be
used
to
perform
simulations
in
which
the
output
data
are
made
available
for
an
off-line
evaluation.
WISE
is
expressly
developed
to
simulate
networks
of
mobile
nodes.
It
actually
implements
the
Gauss-Markov
mobility
model
[10]
as
well
as
the
Random
Waypoint
mo-
bility
model
[6].
Moreover,
the
step-by-step
mode
al-
lows
the
user
to
manually
implement
an
adversary-based
mobility
strategy
[3]
and
other
models
based
on
the
cre-
ation/deletion
of
specific
links
among
the
nodes
[8,
14].
This
means
that
the
user
can
opportunely
change
the
net-
work
connectivity
during
the
simulation
to
easily
build
specific
test
case
situations.
The
user
can
switch
between
the
step-by-step
mode
and
the
live
mode
at
run-time.
This
is
useful
to
let
the
system
run
until
a
specific
condition
is
reached
and
then
to
analyze
the
system
behavior
more
in
details.
5
Interactive
graphic
interface
A
good
graphic
feedback
is
one
of
the
primary
goals
of
WISE.
It
may
help
to
better
understand
the
algorithm
behaviors
and
gives
an
appealing
representation
of
proto-
col
data
flow
and
network
performance.
This
may
be
used
to
show
complex
situations
in
a
real-time
fashion,
and
it
is
highly
desirable
in
order
to
make
live
presentations,
i.e
for
teaching
purposes.
The
visual
interface
is
made
by
a
main
window
(shown
in
Figure
2)
which
displays
the
graphic
overview
of
the
network
deployment,
with
options
to
show
or
hide
links
among
the
nodes
and
transmission
ranges
(both
options
are
set
in
the
example
of
Figure
2).
By
using
the
mouse,
each
node
can
be
freely
moved
in
order
to
obtain
the
de-
sired
network
configuration,
establishing
new
links
or
re-
moving
existing
ones.
New
nodes
can
be
added
in
just
a
mouse
click.
The
application
also
supplies
a
set
of
child
windows,
each
one
related
to
a
specific
simulation
view.
Figure
3
shows
the
relationships
among
the
windows
that
compose
the
application.
A
number
of
child
windows
(the
simulation
modules)
display
the
evolution
of
the
pro-
tocol
data
flow
and
every
simulation
module
may
have
a
related
window
containing
the
required
optional
parame-
ters.
During
the
simulation
in
step-by-step
and
live
mode,
VOLUME
1
399
Page 3
The
solution
proposed
in
this
work
is
WISE,
a
flexi-
ble
visual
simulator
specifically
developed
to
interactively
display
the
evolution
of
wireless
mobile
networks.
The
simulator
natively
integrates
the
most
common
used
mod-
els
to
describe
the
node
mobility.
One
of
its
primary
goals
is
a
good
visual
feedback
to
simplify
the
comprehension
of
the
problem
under
analysis.
Thanks
to
its
user-friendly
graphical
interface,
WISE
can
be
effectively
used
to
make
live
presentations,
i.e.
for
teaching
purposes.
References
Figure
4.
Example
of
simulation
of
a
dis-
tributed
topology
reconstruction
algorithm.
the
network
topology
represented
within
the
main
win-
dow
is
updated
after
every
tick.
While
a
step-by-step
sim-
ulation
is
running,
the
nodes
can
be
moved
and
the
node
parameters
may
be
changed
to
simulate
the
desired
situa-
tion.
6
Example
of
usage
The
WISE
simulator
has
been
profitably
used
to
derive
many
properties
of
the
MAC
level
communication
proto-
col
presented
in
[7].
WISE
has
been
used
to
optimize
the
algorithm
and
verify
the
convergence.
Moreover,
it
has
been
helpful
to
study
the
dynamic
behavior
of
the
method
by
manually
moving
the
nodes
in
order
to
change
the
net-
work
topology
configuration
during
step-by-step
simula-
tion.
This
feature
of
the
simulator
has
been
particularly
useful
to
investigate
worst-case
topologies
and
to
under-
stand
the influence
of
link
establishment/disruption
on
the
communication
system.
Figure
4
shows
the
output
produced
by
the
Topology
Simulation
window,
which
displays
the
evolution
of
an
al-
gorithm
for
the
distributed
network
topology
reconstruc-
tion.
In
this
simulation,
the
nodes
exchange
periodic
mes-
sages
about
their
own
view
of
the
global
network
topol-
ogy.
After
every
transmission,
such
an
information
is
used
by
the
nodes
which
receive
the
data
to
update
their
own
state,
making
all
the
nodes
views
iteratively
converge
to
the
correct
overall
network
topology.
Figure
4
shows
the
last
three
steps
of
the
topology
matrix
updating
process,
where
the
matrix
at
i-th
row
and
j-th
column
represents
the
matrix
owned
by
node
i
at
the
j-th
simulation
step.
The
highlighted
matrices
identify
those
corresponding
to
the
correct
global
topology
configuration,
to
simplify
the
identification
of
the
converged
matrices.
The
same
figure
also
shows
the
window
containing
both
the
simulation
and
visualization
options.
7
Conclusions
In
this
paper
we
discussed
the
importance
of
using
ap-
propriate
simulation
tools
for
the
development,
mainte-
nance,
and
testing
of
new
distributed
algorithms
for
wire-
less
ad-hoc
networks
of
mobile
nodes.
[1]
The
Network
Simulator
-
ns-2.
http://www.isi
.edu/nsnam/ns/.
[2]
PARSEC
-
The
Parallel
Simulation
Environment
for
Com-
plex
Systems.
http://pcl.cs.ucla.edu/projects/parsec/.
[3]
B.
Awerbuch,
P.
Berenbrink,
A.
Brinkmann,
and
C.
Schei-
deler.
Simple
routing
strategies
for
adversarial
systems.
In
Proceedings
of
the
42nd
IEEE
Symposium
on
Founda-
tions
of
Computer
Science
(FOCS),
pages
158-167,
Octo-
ber
2001.
[4]
L.
Bajaj,
M.
Takai,
R.
Ahuja,
K.
Tang,
R.
Bagrodia,
and
M.
Gerla.
GloMoSim:
A
scalable
network
simulation
en-
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Technical
Report
990027,
May
1999.
[5]
B.
L.
Barnett.
An
ethernet
performance
simulator
for
undergraduate
networking.
In
Proceedings
of
the
ACM
SIGCSE
Technical
Symposium,
pages
145-150,
1993.
[6]
C.
Bettstetter.
Smooth
is
better
than
sharp:
A
random
mobility
model
for
simulation
of
wireless
networks.
In
Proceedings of
the
4th
ACM
International
Workshop
on
Modeling,
Analysis,
and
Simulation
of
Wireless
and
Mo-
bile
Systems
(MSWiM),
pages
19-27,
July
2001.
[7]
T.
Facchinetti,
L.
Almeida,
G.
Buttazzo,
and
C.
Marchini.
Real-time
resource
reservation
protocol
for
wireless
mo-
bile
ad
hoc
networks.
In
Proceedings
of
the
IEEE
Real-
Time
Systems
Symposium,
December
2004.
[8]
J.
Gao,
L.
Guibas,
J.
Hershberger,
L.
Zhang,
and
A.
Zhu.
Geometric
spanner
for
routing
in
mobile
networks.
In
Pro-
ceedings
of
the
ACM
Symposium
on
Mobile
Ad
Hoc
Net-
working
&
Computing
(MobiHoc),
pages
45-55,
October
2001.
[9]
Z.
Haas,
J.
Deng,
B.
Liang,
P.
Papadimitatos,
and
S.
Sa-
jama.
Wireless
ad
hoc
networks.
December
2002.
[10]
B.
Liang
and
Z.
J.
Haas.
Predictive
distance-based
mobil-
ity
management
for
PCS
networks.
In
Proceedings
of
the
18th
IEEE
INFOCOM,
pages
21-25,
March
1999.
[1
1]
C.
S.
McDonald.
A
network
specification
language
and
ex-
ecution
environment
for
undergraduate
teaching.
In
Pro-
ceedings
of
the
ACM
Computer
Science
Education
Tech-
nical
Symposium,
pages
25-34,
March
1991.
[12]
C.
E.
Perkins.
Ad
Hoc
Networking.
Addison
Wesley
Pro-
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January
2001.
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D.
D.
Perkins
and
H. D.
Hughes.
A
survey
on
qual-
ity
of
service
support
in
wireless
ad
hoc
networks.
The
Journal
of
Wireless
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&
Mobile
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ing
(WCMC),
Special
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on
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Hoc
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ing:
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Trends,
and
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Au-
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VOLUME
1
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Page 4
  • Source
    • "Some popular network simulators like OPNET [15], ns-2 [16], OMNeT++ [17] or GloMoSim [18] can simulate ad hoc networks. The others are dedicated to MANETs [19] or wireless sensor networks [10] simulation. The simulators provide the facility to simulate protocols in different layers, nodes mobility, energy consumption and various ad hoc networks application scenarios. "
    [Show abstract] [Hide abstract] ABSTRACT: Modeling and simulation are traditional methods used to evaluate wireless network design. This paper ad-dresses issues associated with the application of parallel dis-crete event simulation to mobile ad hoc networks design and analysis. The basic characteristics and major issues pertaining to ad hoc networks modeling and simulation are introduced. The focus is on wireless transmission and mobility models. Particular attention is paid to the MobASim system, a Java-based software environment for parallel and distributed sim-ulation of mobile ad hoc networks. We describe the design, performance and possible applications of presented simulation software. Keywords— ad hoc network, distributed simulation, mobile net-work, software systems.
    Full-text · Article · Jan 2009
  • Source
    [Show abstract] [Hide abstract] ABSTRACT: The paper addresses issues associated with modeling and simulation of wireless, mobile, and ad hoc networks. Particular attention is paid to an approach for federating parallel and distributed ad hoc networks simulators. We describe the design, functionality, implementation and performance of MobASim system. It is a Java-based software platform for MANETs simulation performed on parallel computers or computer clusters. The practical application is provided to illustrate the operation and efficiency of the presented software tool.
    Full-text · Conference Paper · Nov 2008