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In t
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m
m
uni
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G
a
nes
h K
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A.
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Un
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Ch
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ticle
his
to
r
y:
R
ec
eiv
ed
No
v
21
,
201
7
R
ev
i
s
ed
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an
2
9
,
2
0
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8
A
cc
ep
ted
Feb
1
7
,
2
0
1
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T
h
e
a
i
m
o
f
th
is
p
a
p
e
r
is
to
m
o
d
e
l
th
e
P
o
rtab
le
M
a
n
a
g
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r
a
n
d
a
ll
o
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it
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a
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i
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o
m
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d
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th
e
m
o
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e
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o
d
e
s
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th
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rk
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In
th
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a
rti
c
le,
M
o
d
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li
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P
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M
a
n
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r
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id
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th
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A
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m
m
u
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(M
M
A
C)
is
p
ro
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lt
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se
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t
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ra
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d
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a
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k
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t
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d
d
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la
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th
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m
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h
e
P
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M
a
n
a
g
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r
(P
M
)
is
u
se
d
to
f
in
d
o
u
t
th
e
re
la
y
n
o
d
e
in
th
e
n
e
tw
o
rk
.
T
h
e
w
o
rk
in
g
o
f
t
h
e
P
M
w
it
h
a
m
in
im
a
l
n
u
m
b
e
r
o
f
n
o
d
e
s
is
a
n
a
ly
z
e
d
a
n
d
p
re
se
n
ted
th
r
o
u
g
h
t
h
e
sim
u
latio
n
s in
th
e
n
e
tw
o
rk
si
m
u
lato
r.
K
ey
w
o
r
d
s
:
Dela
y
L
o
s
s
M
o
b
ile
ad
h
o
c
n
et
w
o
r
k
P
o
r
tab
le
Ma
n
ag
er
P
ac
k
et
r
ec
eiv
ed
Co
p
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rig
h
t
©
2
0
1
8
In
stit
u
te o
f
A
d
v
a
n
c
e
d
E
n
g
i
n
e
e
rin
g
a
n
d
S
c
ien
c
e
.
Al
l
rig
h
ts
re
se
rv
e
d
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Gan
es
h
K
u
m
ar
,
A
ME
T
Un
i
v
er
s
it
y
,
C
h
en
n
ai,
I
n
d
ia.
1.
I
NT
RO
D
UCT
I
O
N
A
M
ANE
T
co
n
tain
s
n
u
m
b
er
o
f
m
o
v
ab
le
n
o
d
es.
T
h
ese
m
o
v
a
b
le
n
o
d
es a
r
e
ab
le
to
tr
an
s
m
it
th
e
d
ata
to
ev
er
y
n
o
d
e
w
it
h
o
u
t
th
e
a
s
s
i
s
tan
ce
o
f
b
ase
s
tatio
n
s
.
Qu
al
i
t
y
o
f
Ser
v
ice
(
Qo
S)
p
r
er
eq
u
is
ite,
f
o
r
ex
a
m
p
le,
th
o
s
e
f
o
r
m
u
l
ti
m
ed
ia
ap
p
licatio
n
s
w
it
h
tr
an
s
f
er
s
p
ee
d
an
d
v
i
talit
y
i
m
p
er
ativ
e
h
as
b
ee
n
s
er
i
o
u
s
l
y
co
n
s
id
er
ed
as
o
f
late
as
an
is
s
u
e
f
o
r
M
A
N
E
T
s
.
No
d
e
Mo
v
em
e
n
t
a
n
d
w
ir
eless
r
ad
io
p
r
o
p
er
ties
m
a
k
e
it
m
o
r
e
d
if
f
ic
u
lt
to
p
r
o
v
id
e
q
u
alit
y
o
f
s
er
v
ice
i
n
MA
NE
T
s
.
Fi
g
u
r
e.
1
s
h
o
w
s
th
e
ex
a
m
p
le
s
ce
n
ar
io
o
f
M
A
NE
T
.
T
h
er
ef
o
r
e,
in
th
is
ar
ticle,
Mo
d
elin
g
P
M
aid
in
g
in
t
h
e
M
A
NE
T
C
o
m
m
u
n
icatio
n
is
p
r
o
p
o
s
ed
.
MA
is
a
p
r
o
g
r
am
m
i
n
g
en
tit
y
t
h
at
f
o
llo
w
s
u
p
f
o
r
th
e
b
en
ef
it
o
f
t
h
eir
cr
ea
to
r
s
an
d
m
o
v
e
in
d
e
p
en
d
en
tl
y
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et
w
ee
n
n
o
d
es.
I
n
g
en
er
al,
a
P
M
ex
ec
u
t
es
o
n
a
m
ac
h
i
n
e
th
at
id
ea
ll
y
p
r
o
v
id
es
th
e
r
eso
u
r
ce
s
o
r
s
er
v
ices
th
at
it
n
ee
d
s
to
d
o
its
w
o
r
k
s
.
Fig
u
r
e
1
.
E
x
a
m
p
le
M
A
NE
T
Scen
ar
io
S
o
u
r
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Node
U
n
r
e
li
ab
le
N
o
d
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De
s
ti
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a
t
io
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Node
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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J
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p
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N:
2502
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4752
Mo
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Ma
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a
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A
id
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e
MANET Co
mmu
n
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tio
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(
Ga
n
esh
K
u
ma
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573
2.
RE
L
AT
E
D
WO
RK
S
P
r
o
d
u
ctiv
e
as
s
et
d
is
clo
s
u
r
e
a
n
d
o
r
d
er
in
g
is
th
e
g
u
ar
an
teed
ap
p
r
o
ac
h
to
g
iv
e
m
i
n
i
m
al
ef
f
o
r
t
alter
ed
ass
et
r
ec
o
v
er
y
b
en
e
f
it
in
a
f
l
ex
ib
le
s
p
ec
iall
y
ap
p
o
in
ted
co
n
d
itio
n
.
R
o
u
tin
g
I
n
tel
lig
e
n
t
Mo
b
ile
A
g
e
n
ts
[
1
]
f
r
eq
u
en
tl
y
g
at
h
er
av
ailab
ilit
y
o
f
r
eso
u
r
ce
s
,
r
o
u
tin
g
an
d
in
d
e
x
.
I
n
[
2
]
an
al
y
ze
d
th
e
n
o
d
e
ca
p
ac
it
y
an
d
d
ela
y
in
MA
NE
T
s
.
I
t
r
ec
eiv
ed
o
p
ti
m
al
s
ch
ed
u
lin
g
p
ar
a
m
eter
s
.
A
c
r
o
s
s
la
y
er
ap
p
r
o
ac
h
h
ad
p
r
o
p
o
s
ed
to
u
tili
ze
th
e
m
ea
s
u
r
ed
SN
R
v
a
lu
e
o
n
t
h
e
p
h
y
s
ical
la
y
er
as
a
r
o
u
ti
n
g
m
etr
ic.
T
h
e
p
r
o
p
o
s
ed
tech
n
iq
u
e
h
a
s
th
e
ad
v
a
n
tag
e
o
f
p
r
o
v
id
in
g
a
g
o
o
d
q
u
alit
y
m
e
asu
r
e
m
en
t
to
th
e
li
n
k
w
it
h
o
u
t
an
y
ad
d
itio
n
a
l
tr
af
f
ic
r
eq
u
i
r
ed
.
T
h
e
p
r
o
p
o
s
ed
tech
n
iq
u
e
is
u
s
ed
i
n
th
e
D
y
n
a
m
ic
Seq
u
e
n
ce
R
o
u
ti
n
g
P
r
o
to
c
o
l (
DSDV)
m
o
d
u
le
[
3
]
.
A
d
y
n
a
m
ic
co
m
p
u
tatio
n
u
s
i
n
g
d
is
tr
ib
u
ted
alg
o
r
it
h
m
f
o
r
m
i
n
i
m
u
m
h
o
p
p
ath
s
is
p
r
o
p
o
s
ed
;
h
er
e
B
ell
m
an
Fo
r
d
alg
o
r
it
h
m
i
s
ad
d
ed
w
it
h
d
i
s
tr
ib
u
ted
al
g
o
r
ith
m
f
o
r
t
h
e
d
eter
m
i
n
atio
n
o
f
s
h
o
r
test
p
at
h
co
m
p
u
tatio
n
.
I
n
t
h
is
a
lg
o
r
it
h
m
,
ea
ch
n
o
d
e
m
a
in
ta
in
s
its
n
e
x
t
h
o
p
i.
e.
s
u
cc
es
s
o
r
n
o
d
e
an
d
f
o
r
ea
ch
d
esti
n
at
io
n
in
t
h
e
n
et
w
o
r
k
t
h
e
s
h
o
r
test
d
is
tan
ce
i
n
n
u
m
b
er
o
f
h
o
p
s
ar
e
d
eter
m
i
n
ed
.
T
h
e
m
o
d
if
ied
al
g
o
r
ith
m
w
o
u
ld
h
a
v
e
to
m
ai
n
tai
n
t
h
e
le
n
g
t
h
a
n
d
h
o
p
co
u
n
t
o
f
t
h
e
s
h
o
r
test
p
at
h
to
ea
ch
n
et
w
o
r
k
d
es
tin
a
tio
n
[
4]
.
Dis
tr
ib
u
ted
co
r
e
s
elec
tio
n
a
n
d
m
ig
r
atio
n
p
r
o
to
co
ls
f
o
r
M
A
NE
T
’
s
w
i
th
d
y
n
a
m
icall
y
c
h
an
g
i
n
g
n
e
t
w
o
r
k
to
p
o
lo
g
y
w
a
s
p
r
esen
ted
.
I
n
s
tatic
n
et
w
o
r
k
s
co
r
e
s
elec
ti
o
n
p
r
o
to
co
ls
a
r
e
n
o
t
s
u
itab
le
ad
h
o
c
n
et
w
o
r
k
s
,
s
in
ce
t
h
ese
al
g
o
r
ith
m
s
d
ep
en
d
o
n
k
n
o
w
led
g
e
o
f
w
h
o
le
n
et
w
o
r
k
to
p
o
lo
g
y
a
n
d
n
o
t
s
u
itab
le
f
o
r
d
y
n
a
m
ic
to
p
o
lo
g
y
.
A
n
ei
g
h
b
o
u
r
co
v
er
ag
e
-
b
ased
p
r
o
b
a
b
ilis
tic
r
eb
r
o
ad
ca
s
t
p
r
o
to
co
l
f
o
r
r
ed
u
cin
g
r
o
u
tin
g
o
v
er
h
ea
d
in
M
A
NE
T
s
is
p
r
o
p
o
s
ed
.
T
o
ef
f
ec
ti
v
el
y
ex
p
lo
it
th
e
n
ei
g
h
b
o
u
r
co
v
er
a
g
e
k
n
o
w
led
g
e
a
n
o
v
el
r
eb
r
o
ad
c
ast
d
ela
y
is
p
r
o
p
o
s
ed
alo
n
g
w
i
th
t
h
e
p
r
o
b
ab
ilis
tic
r
eb
r
o
a
d
ca
s
t
p
r
o
to
c
o
l
w
h
ic
h
is
u
s
ed
to
d
eter
m
i
n
e
th
e
r
eb
r
o
ad
ca
s
t
o
r
d
er
an
d
ac
cu
r
ate
ad
d
iti
o
n
al
co
v
er
ag
e
r
atio
b
y
s
en
s
i
n
g
t
h
e
n
e
ig
h
b
o
u
r
n
o
d
e
s
.
C
o
n
n
ec
ti
v
it
y
f
ac
to
r
is
d
e
f
in
ed
to
p
r
o
v
id
e
th
e
n
o
d
e
d
en
s
it
y
ad
ap
tatio
n
an
d
th
e
ad
d
itio
n
al
co
v
er
ag
e
r
atio
is
co
m
b
in
ed
i
n
o
r
d
er
to
s
et
r
ea
s
o
n
ab
le
r
eb
r
o
ad
ca
s
t
p
r
o
b
ab
ilit
y
[
5
]
.
T
h
e
co
r
e
lo
ca
tio
n
m
et
h
o
d
i
m
p
le
m
en
ted
h
er
e
is
b
ased
o
n
th
e
n
o
tio
n
o
f
m
ed
ia
n
n
o
d
e
o
f
t
h
e
c
u
r
r
en
t
m
u
lticas
t
tr
ee
in
s
tead
o
f
th
e
m
ed
ian
n
o
d
e
o
f
th
e
w
h
o
le
n
et
w
o
r
k
an
d
h
e
n
ce
t
h
e
m
u
lticast
t
r
ee
is
d
ec
lar
ed
as
g
o
o
d
ap
p
r
o
x
i
m
atio
n
f
o
r
e
n
tire
n
et
w
o
r
k
.
C
o
r
e
-
b
ased
m
u
ltica
s
t
r
o
u
ti
n
g
al
g
o
r
ith
m
s
r
o
o
t
th
e
m
u
lticas
t
tr
ee
at
a
s
p
ec
if
ic
n
o
d
e
ca
lled
th
e
co
r
e
n
o
d
e.
T
h
e
co
r
e
n
o
d
e
is
also
ca
lled
a
ce
n
tr
e
n
o
d
e
o
r
a
r
en
d
e
zv
o
u
s
p
o
in
t.
Dis
tr
ib
u
ted
co
r
e
s
elec
tio
n
d
o
es
n
o
t
r
eq
u
ir
e
an
y
d
is
ta
n
ce
in
f
o
r
m
ati
o
n
b
u
t
u
s
es
t
h
e
s
u
m
o
f
w
ei
g
h
ts
o
f
all
th
e
lin
k
s
i
n
th
e
tr
ee
w
h
ic
h
s
ig
n
i
f
ie
s
th
e
to
tal
b
an
d
w
id
t
h
co
n
s
u
m
ed
f
o
r
m
u
lticas
tin
g
a
p
ac
k
et
[
6
]
.
T
h
e
ad
h
o
c
n
et
w
o
r
k
is
s
el
f
-
o
r
g
an
ized
b
y
ad
h
o
c
n
et
w
o
r
k
r
o
u
ti
n
g
p
r
o
to
co
ls
.
Du
e
to
th
e
m
o
b
ilit
y
o
f
n
o
d
es,
r
o
u
tin
g
p
r
o
to
co
ls
is
co
m
p
r
i
s
ed
o
f
s
ev
er
al
d
ir
ec
t
n
o
d
e
-
to
-
n
o
d
e
lin
k
s
ex
i
s
ts
o
n
l
y
f
o
r
a
ce
r
tain
p
er
i
o
d
.
T
h
er
ef
o
r
e,
th
e
esti
m
ated
p
r
o
b
ab
ilit
y
d
en
s
it
y
f
u
n
ct
io
n
h
ad
p
r
o
p
o
s
ed
to
im
p
r
o
v
e
th
e
r
o
u
tin
g
p
er
f
o
r
m
a
n
ce
.
T
h
e
ex
p
o
n
en
t
ial
d
is
tr
ib
u
tio
n
w
as
u
s
ed
to
p
r
ed
ict
r
o
u
te
’
s
b
e
h
av
i
o
r
.
A
n
d
d
i
s
cr
ete
Ga
m
m
a
d
is
tr
ib
u
tio
n
is
p
r
o
p
o
s
ed
to
esti
m
a
te
ti
m
e
d
is
tr
ib
u
tio
n
[
8
]
.
Neig
h
b
o
u
r
C
o
v
er
a
g
e
B
ased
P
r
o
b
a
b
ilis
tic
R
eb
r
o
ad
ca
s
t
(
NC
P
R
)
[
7
]
w
a
s
p
r
o
p
o
s
ed
.
T
h
is
p
r
o
to
co
l
co
m
p
letel
y
r
elie
s
o
n
p
r
eset
v
ar
ia
b
les,
w
h
ich
ar
e
r
eq
u
ir
ed
to
b
e
s
et
b
y
t
h
e
s
y
s
te
m
ad
m
in
i
s
tr
ato
r
b
ased
o
n
th
e
ad
-
h
o
c
s
ce
n
ar
io
.
T
h
e
r
o
u
tin
g
o
v
er
h
ea
d
cr
is
is
ca
u
s
ed
b
y
R
R
E
Q
r
ed
u
n
d
an
t
p
ac
k
et
s
co
u
ld
b
e
o
v
er
co
m
e
b
y
ap
p
l
y
in
g
th
e
N
C
P
R
p
r
o
to
co
l.
B
ased
o
n
th
e
s
el
f
-
p
u
n
n
in
g
s
c
h
e
m
e,
th
e
n
u
m
b
er
o
f
r
ed
u
n
d
an
t
R
R
E
Q
m
e
s
s
a
g
es
is
r
ed
u
ce
d
r
el
y
i
n
g
o
n
all
th
e
n
o
d
es
in
th
e
n
e
t
w
o
r
k
.
B
asical
l
y
,
d
u
e
to
m
u
ltip
le
v
ar
ieties
in
n
o
d
e
d
ep
lo
y
m
e
n
t,
th
is
n
u
m
b
er
i
s
i
n
s
u
f
f
ic
ien
t
wh
en
th
e
n
et
w
o
r
k
is
co
n
g
es
ted
.
I
n
[
9
]
,
th
e
q
u
an
tit
y
o
f
clien
t
s
an
d
r
ad
io
w
ir
es
w
i
th
th
e
s
a
m
e
tr
a
n
s
m
itted
p
o
w
er
,
th
e
clu
s
ter
p
ick
u
p
in
cr
e
m
en
ts
d
ir
ec
tl
y
.
T
h
e
en
h
a
n
ce
d
clu
s
ter
p
ick
u
p
ca
n
b
e
ex
p
an
d
ed
u
n
d
er
en
o
r
m
o
u
s
MI
MO
f
r
a
m
e
w
o
r
k
,
w
h
ile
t
h
e
v
ie
w
ab
le
p
ath
w
a
y
s
u
b
s
eq
u
en
t
to
ex
p
an
d
i
n
g
t
h
e
q
u
an
ti
t
y
o
f
r
ec
ep
tio
n
ap
p
ar
atu
s
e
s
to
1
0
0
M
is
as
y
et
s
o
a
k
e
d
.
T
h
e
ad
d
itio
n
o
f
clu
s
ter
p
ick
u
p
w
ill
en
h
a
n
ce
t
h
e
Qo
S
an
d
s
co
p
e
r
an
g
e.
T
h
u
s
,
th
e
q
u
a
n
tit
y
o
f
r
ec
ep
tio
n
ap
p
ar
atu
s
co
m
p
o
n
e
n
ts
o
n
ac
co
u
n
t
o
f
t
h
e
v
ie
w
ab
le
p
ath
w
a
y
in
cr
e
m
en
ts
,
an
d
t
h
e
tr
an
s
m
itted
f
lag
ad
d
itio
n
al
l
y
i
n
cr
e
m
en
t
s
in
li
g
h
t
o
f
th
e
co
n
d
itio
n
o
f
th
e
c
h
a
n
n
el
d
e
m
o
n
s
tr
ate
an
d
ac
ce
s
s
ib
le
id
ea
l tr
an
s
m
itted
p
o
w
er
.
3.
P
RO
P
O
SE
D
WO
RK
T
h
e
p
r
o
p
o
s
ed
w
o
r
k
is
a
s
i
m
p
le
an
al
y
s
i
s
o
f
th
e
d
ata
th
at
h
as
b
ee
n
u
s
ed
b
y
t
h
e
m
o
b
ile
n
o
d
es
to
en
h
a
n
ce
co
m
m
u
n
icatio
n
.
A
p
er
f
o
r
m
an
ce
p
ar
a
m
eter
ca
l
led
α
h
as
b
ee
n
p
r
o
p
o
s
ed
to
ass
es
s
e
ac
h
n
o
d
e
s
o
t
h
at
it
s
p
o
s
s
ib
ilit
y
o
f
b
ein
g
s
elec
ted
as
th
e
n
e
x
t n
o
d
e
is
i
n
cr
ea
s
ed
.
I
n
o
r
d
er
to
r
ea
ch
t
h
e
s
o
u
r
ce
d
ata
to
d
esti
n
atio
n
in
t
h
e
m
o
s
t
E
n
er
g
y
e
f
f
icie
n
t
r
o
u
te
s
ele
ctio
n
i
s
a
n
i
m
p
o
r
tan
t
p
r
o
ce
s
s
.
T
h
e
P
M
m
o
n
ito
r
s
t
h
e
all
n
o
d
e
r
eliab
ilit
y
o
f
d
ata
co
m
m
u
n
icatio
n
o
p
er
atio
n
s
a
n
d
it
s
e
n
d
s
th
e
i
n
f
o
r
m
atio
n
to
ev
er
y
n
o
d
e.
T
h
e
n
o
d
es
r
eliab
ilit
y
ca
lcu
la
tio
n
d
ep
en
d
s
o
n
P
ac
k
et
Del
iv
er
y
R
ate
an
d
Dela
y
R
ate
an
d
L
o
s
s
r
ate
o
f
d
ata
tr
an
s
m
i
s
s
io
n
.
T
h
e
No
d
e
R
eliab
ilit
y
(
α
)
co
m
p
u
ta
tio
n
i
s
g
i
v
e
n
.
11
PRR
P
L
R
D
R
(
1
)
W
h
er
e,
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l
.
9
,
No
.
3
,
Ma
r
ch
2
0
1
8
:
5
7
2
–
5
7
6
574
PRR
P
ac
k
et
R
ec
ei
v
ed
R
ate
P
L
R
P
ac
k
et
L
o
s
s
R
ate
DR
Dela
y
R
ate
T
h
e
P
M
g
ath
er
in
g
all
n
o
d
es
s
tatu
s
an
d
it
d
ec
id
es
w
h
ic
h
n
o
d
e
is
r
eliab
le
an
d
u
n
r
eli
ab
le
in
MA
NE
T
.
T
h
en
it
s
e
n
d
n
o
ti
f
ic
atio
n
m
ess
a
g
e
to
all
n
o
d
es.
I
f
a
s
o
u
r
ce
d
esire
s
t
h
e
d
ata
to
d
esti
n
a
tio
n
,
it
v
er
i
f
ie
s
th
e
n
o
d
e
is
r
eliab
le
o
r
n
o
t
t
h
e
n
s
o
u
r
ce
s
elec
t
t
h
at
n
o
d
e
is
n
e
x
t
h
o
p
.
T
h
is
p
r
o
ce
s
s
is
co
n
ti
n
u
ed
u
n
til
t
h
e
s
o
u
r
ce
r
ea
ch
es th
e
d
es
tin
a
tio
n
.
4.
P
E
RF
O
RM
ANCE E
VA
L
U
AT
I
O
N
I
n
o
u
r
s
i
m
u
la
tio
n
a
n
al
y
s
is
,
t
h
e
f
o
llo
w
in
g
m
etr
ics ar
e
u
s
ed
to
an
al
y
ze
t
h
e
r
es
u
lt
s
in
M
A
NE
T
s
.
P
a
ck
et
Delive
r
y
R
a
te
(
P
DR
)
:
is
d
ef
i
n
ed
as
th
e
r
atio
o
f
to
tal
d
ata
p
ac
k
ets
r
ec
eiv
ed
b
y
th
e
d
esti
n
a
tio
n
to
to
tal
s
en
d
p
ac
k
ets
b
y
s
o
u
r
ce
m
u
lt
ip
lied
w
it
h
n
u
m
b
e
r
o
f
r
ec
eiv
er
s
.
T
h
e
P
DR
is
ca
lcu
lated
b
y
th
e
E
q
u
atio
n
(
2
)
.
T
o
t
a
l
P
a
c
k
R
e
c
e
i
v
e
d
P
D
R
T
o
t
a
l
P
a
c
k
S
e
n
d
(
2
)
P
a
ck
et
Lo
s
s
R
a
tio
(
P
LR)
:
T
h
e
P
ac
k
et
L
o
s
s
R
ate
(
P
L
R
)
i
s
th
e
r
atio
o
f
th
e
n
u
m
b
er
o
f
p
ac
k
e
ts
d
r
o
p
p
ed
to
th
e
n
u
m
b
er
o
f
d
ata
p
ac
k
et
s
s
en
t.
T
h
e
P
L
R
i
s
ca
lcu
la
ted
b
y
E
q
u
atio
n
(
3
).
T
o
t
a
l
P
a
c
k
D
r
o
p
p
e
d
P
L
R
T
o
t
a
l
P
a
c
k
S
e
n
d
(
3
)
Dela
y
:
I
t
is
d
ef
in
ed
as
th
e
av
er
ag
e
ti
m
e
t
h
at
a
p
ac
k
et
tak
es
to
tr
an
s
m
it
t
h
e
n
et
w
o
r
k
f
r
o
m
s
o
u
r
ce
to
d
esti
n
atio
n
.
I
t is
m
ea
s
u
r
ed
b
y
E
q
u
atio
n
(
4
).
P
a
c
k
R
e
c
v
d
T
i
m
e
P
a
c
k
S
e
n
t
T
i
m
e
D
e
l
a
y
t
i
m
e
(
4
)
Fig
u
r
e
2
.
P
ac
k
et
Deliv
er
y
R
at
e
Fro
m
F
ig
u
r
e
2
,
th
e
p
r
o
p
o
s
ed
p
r
o
to
co
l
MM
A
C
t
h
at
i
n
cr
ea
s
es
th
e
p
ac
k
et
r
ec
eiv
ed
r
ate
co
m
p
ar
ed
to
th
e
e
x
i
s
ti
n
g
p
r
o
to
co
l
R
R
MP
.
T
h
e
F
ig
u
r
e
3
i
n
d
icate
s
t
h
e
p
a
ck
et
lo
s
s
r
ate
o
f
t
h
e
p
r
o
p
o
s
ed
p
r
o
to
co
l
MM
A
C
is
less
er
th
a
n
t
h
e
R
R
MP
p
r
o
to
co
l sh
o
w
i
n
g
t
h
e
e
f
f
icien
c
y
o
f
t
h
e
MM
AC
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
Mo
d
elin
g
P
o
r
ta
b
le
Ma
n
a
g
er
A
id
in
g
I
n
th
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MANET Co
mmu
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(
Ga
n
esh
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r
)
575
Fig
u
r
e
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.
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ac
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ate
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u
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.
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u
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e
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ate
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elay
o
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d
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p
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5.
CO
NCLU
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ata
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ed
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etter
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o
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ilit
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itio
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r
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h
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e
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ate
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y
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n
t
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n
et
w
o
r
k
.
RE
F
E
R
E
NC
E
S
[1
]
Jia
R,
Ya
n
g
F
,
Ya
o
S
,
T
ian
X,
W
a
n
g
X
,
Z
h
a
n
g
W
,
X
u
J.
Op
ti
ma
l
C
a
p
a
c
it
y
–
De
la
y
T
r
a
d
e
o
ff
i
n
M
ANE
T
s
W
it
h
Co
rr
e
la
ti
o
n
o
f
No
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e
M
o
b
il
it
y
.
IE
EE
T
ra
n
sa
c
ti
o
n
s
o
n
Veh
icu
l
a
r T
e
c
h
n
o
l
o
g
y
.
2
0
1
7
;
6
6
(2
)
;
1
7
7
2
-
1
7
8
5
.
[2
]
V
a
lera
,
A
lv
in
C,
W
in
sto
n
Kh
o
o
n
G
u
a
n
S
e
a
h
,
S
V
Ra
o
.
Imp
ro
v
i
n
g
p
ro
t
o
c
o
l
ro
b
u
st
n
e
ss
in
a
d
h
o
c
n
e
two
rk
s
th
ro
u
g
h
c
o
o
p
e
ra
t
ive
p
a
c
k
e
t
c
a
c
h
in
g
a
n
d
sh
o
rte
st
mu
lt
i
p
a
t
h
ro
u
ti
n
g
,
IE
EE
T
ra
n
sa
c
ti
o
n
s
o
n
M
o
b
i
le
Co
mp
u
ti
n
g
.
2
0
0
5
;
4
(5
)
;
443
-
4
5
7
.
[3
]
G
a
r
c
ia
-
L
u
n
a
-
A
c
e
v
e
s,
Jo
se
J.
A
min
imu
m
-
h
o
p
ro
u
ti
n
g
a
l
g
o
ri
th
m
b
a
se
d
o
n
d
istrib
u
ted
i
n
f
o
rm
a
ti
o
n
.
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o
mp
u
ter
Ne
two
rk
s a
n
d
IS
DN
S
y
ste
ms
.
1
9
8
9
;
1
6
(5
)
;
3
6
7
-
3
8
2
.
[4
]
Zh
a
n
g
,
X
in
M
in
g
,
E
n
Bo
W
a
n
g
,
Jin
g
Jin
g
X
ia,
Da
n
Ke
u
n
S
u
n
g
.
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n
e
ig
h
b
o
r
c
o
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ra
g
e
-
b
a
se
d
p
ro
b
a
b
il
isti
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re
b
ro
a
d
c
a
st
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r
re
d
u
c
in
g
r
o
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ti
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g
o
v
e
rh
e
a
d
i
n
mo
b
il
e
a
d
h
o
c
n
e
two
rk
s
.
IEE
E
tr
a
n
sa
c
ti
o
n
s
o
n
mo
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il
e
c
o
m
p
u
t
in
g
.
2
0
1
3
;
1
2
(
3
);
4
2
4
-
4
3
3
.
[5
]
Ej
m
a
a
,
A
li
M
o
h
a
m
e
d
E,
S
h
a
m
a
l
a
S
u
b
ra
m
a
n
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m
,
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riati
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h
m
a
d
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k
a
rn
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i
n
,
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ri
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a
M
o
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d
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n
a
p
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ig
h
b
o
r
-
B
a
se
d
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n
a
mic
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n
n
e
c
ti
v
it
y
Fa
c
t
o
r R
o
u
ti
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g
Pr
o
to
c
o
l
fo
r
M
o
b
il
e
Ad
H
o
c
Ne
two
rk
.
IEE
E
Acc
e
ss
.
2
0
1
6
;
4
;
8
0
5
3
-
8
0
6
4
.
[6
]
G
u
p
ta,
S
a
n
d
e
e
p
K
S
,
P
ra
d
i
p
K,
S
rim
a
n
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Ad
a
p
ti
v
e
c
o
re
se
lec
ti
o
n
a
n
d
mi
g
ra
ti
o
n
me
t
h
o
d
fo
r
m
u
lt
ica
st
ro
u
ti
n
g
i
n
mo
b
i
le
a
d
h
o
c
n
e
two
rk
s
.
IEE
E
T
r
a
n
sa
c
ti
o
n
s
o
n
Pa
r
a
ll
e
l
a
n
d
Distri
b
u
ted
S
y
ste
ms
.
2
0
0
3
;
1
4
(
1
);
2
7
-
3
8
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
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lec
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l
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3
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Ma
r
ch
2
0
1
8
:
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7
2
–
5
7
6
576
[7
]
S
h
a
n
t
h
i,
H
J,
A
n
it
a
,
E
M
.
S
e
c
u
re
a
n
d
Ef
f
icie
n
t
Dista
n
c
e
Ef
fec
t
Ro
u
ti
n
g
Al
g
o
rith
m
f
o
r
M
o
b
il
i
ty
(
S
E_
DREA
M
)
in
M
ANE
T
s
.
In
P
r
o
c
e
e
d
in
g
s
o
f
th
e
3
rd
In
ter
n
a
ti
o
n
a
l
S
y
mp
o
si
u
m
o
n
Bi
g
Da
ta
a
n
d
Clo
u
d
Co
mp
u
ti
n
g
Ch
a
ll
e
n
g
e
s
(
IS
BCC
–
1
6
’).
2
0
1
6
;
65
-
8
0
.
S
p
rin
g
e
r In
ter
n
a
ti
o
n
a
l
Pu
b
li
sh
in
g
.
[8
]
S
h
a
n
t
h
i,
H J,
A
n
it
a
,
E
M
.
Per
fo
r
ma
n
c
e
a
n
a
lys
is
o
f
b
l
a
c
k
h
o
le a
t
ta
c
k
s in
g
e
o
g
ra
p
h
ica
l
ro
u
ti
n
g
M
AN
ET
.
2
0
1
4
.
[9
]
A
d
e
e
b
S
a
lh
,
L
u
k
m
a
n
A
u
d
a
h
,
No
r
S
h
a
h
i
d
a
M
.
S
h
a
h
,
S
h
i
p
u
n
A
.
Ha
m
z
a
h
.
M
a
x
imizin
g
En
e
rg
y
Ef
fi
c
ien
c
y
fo
r
Co
n
su
m
p
ti
o
n
Circ
u
it
Po
we
r
in
Do
wn
li
n
k
M
a
ss
ive
M
IM
O
W
ir
e
les
s
Ne
two
rk
s
.
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
a
n
d
Co
mp
u
ter
E
n
g
in
e
e
rin
g
(
IJ
ECE
)
.
2
0
1
7
;
7
(6
)
;
2
9
7
7
~
2
9
8
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.