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,
Dec
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er
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p
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33
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A new
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M
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b
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g
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S
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h
a
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n
t
h
e
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T
h
e
p
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d
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c
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l
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e
v
a
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ted
b
y
c
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g
th
e
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a
n
c
e
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n
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ly
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u
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e
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a
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imp
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e
m
e
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t
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two
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a
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d
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v
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ty
wh
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e
n
e
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o
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p
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m
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re
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se
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th
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sy
ste
m
li
fe
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to
2
0
%
.
K
ey
w
o
r
d
s
:
C
B
R
P
C
lu
s
ter
b
ased
MA
NE
T
R
ed
u
n
d
an
t
SC
B
R
P
T
h
is i
s
a
n
o
p
e
n
a
c
c
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ss
a
rticle
u
n
d
e
r
th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Salm
a
S.
Mo
h
am
ed
,
Dep
ar
tm
en
t o
f
E
lectr
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n
ics an
d
C
o
m
m
u
n
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n
E
n
g
in
ee
r
i
n
g
,
Facu
lty
o
f
E
n
g
in
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r
in
g
,
Ma
n
s
o
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r
a
Un
iv
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r
s
ity
,
Ma
n
s
o
u
r
a,
E
g
y
p
t
.
E
m
ail:
s
alm
a_
s
u
b
h
@
y
ah
o
o
.
c
o
m
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
ex
ten
s
iv
e
s
p
r
ea
d
o
f
wir
eless
co
m
m
u
n
icatio
n
ap
p
licatio
n
an
d
th
e
q
u
ick
l
y
in
c
r
ea
s
in
g
l
o
ad
s
o
v
e
r
th
e
last
f
ew
y
ea
r
s
h
av
e
g
u
id
e
th
e
r
esear
ch
es
o
n
m
o
b
ile
a
d
h
o
c
n
etwo
r
k
s
(
MA
NE
T
s
)
in
m
an
y
co
n
ce
n
tr
atio
n
co
n
tex
ts
[
1
]
.
T
h
ese
a
p
p
licatio
n
co
n
te
x
ts
m
ay
v
a
r
y
f
r
o
m
d
an
g
er
o
u
s
s
o
cial
n
etwo
r
k
s
to
s
af
e
ty
d
o
m
ai
n
s
s
u
ch
as
r
escu
e
ac
tio
n
an
d
f
ield
[
2
,
3
]
.
T
h
e
MA
NE
T
s
r
o
u
tin
g
p
r
o
to
c
o
ls
ar
e
g
en
er
ally
class
if
ied
as
p
r
o
ac
tiv
e,
r
ea
ctiv
e
an
d
h
ier
ar
ch
ical
r
o
u
ter
[
4
]
.
T
h
e
m
ain
d
r
awb
ac
k
o
f
th
e
r
ea
c
tiv
e
r
o
u
tin
g
p
r
o
to
co
l
is
n
o
t
o
n
ly
ex
tr
a
tr
af
f
ic
f
o
r
co
m
m
u
n
icatio
n
alo
n
g
e
x
is
tin
g
lin
k
s
b
u
t
also
,
th
er
e
is
a
s
ig
n
if
ican
t
d
ela
y
in
d
eter
m
i
n
in
g
th
e
r
o
u
te,
wh
il
e
th
e
m
ain
d
is
ad
v
a
n
tag
e
o
f
p
r
o
a
ctiv
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p
r
o
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c
o
l is h
ig
h
f
ix
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d
h
e
ad
in
m
ain
tain
in
g
u
p
d
ated
p
e
r
i
o
d
ic
r
o
u
tin
g
tab
les.
T
h
e
h
ier
ar
ch
ical
r
o
u
tin
g
p
r
o
t
o
co
ls
d
iv
id
e
th
e
m
o
b
ile
n
o
d
es
i
n
th
e
n
etwo
r
k
i
n
to
s
u
b
s
ets
o
f
n
o
d
es
ca
lled
clu
s
ter
s
,
in
wh
ich
a
clu
s
ter
h
ea
d
n
o
d
e
(
C
H)
is
u
s
ed
to
co
m
m
u
n
icate
d
ata
with
in
th
e
clu
s
ter
.
E
lectio
n
o
f
a
C
H
n
o
d
e
o
cc
u
r
s
ac
co
r
d
in
g
to
ce
r
tain
tec
h
n
iq
u
es
an
d
s
p
ec
if
ic
m
etr
ics.
T
h
e
o
th
er
n
o
d
es
ca
n
s
er
v
e
as
o
r
d
in
ar
y
n
o
d
es
in
s
id
e
th
e
clu
s
ter
o
r
g
atew
ay
s
b
etwe
en
clu
s
ter
s
ac
co
r
d
in
g
to
th
e
cl
u
s
ter
f
o
r
m
atio
n
tech
n
iq
u
e.
Ma
n
y
alg
o
r
ith
m
s
h
av
e
b
ee
n
p
r
o
p
o
s
ed
f
o
r
d
ea
lin
g
wi
th
th
e
clu
s
ter
in
g
p
r
o
b
lem
[
5
]
.
An
ex
am
p
le
o
f
th
is
ty
p
e
is
th
e
clu
s
ter
-
b
ased
r
o
u
tin
g
p
r
o
to
co
l
(
C
B
R
P)
[
6
]
.
Ma
n
y
a
lg
o
r
ith
m
s
o
f
clu
s
ter
-
b
ased
r
o
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p
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to
c
o
ls
wer
e
p
r
o
p
o
s
e
d
.
T
h
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al
g
o
r
ith
m
s
wer
e
im
p
r
o
v
ed
b
y
m
an
y
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esea
r
ch
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u
s
in
g
clu
s
ter
h
ea
d
-
b
ase
d
r
o
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tin
g
p
r
o
to
co
ls
.
R
.
T
o
r
r
es
an
d
L
.
Me
n
g
u
al,
[
7
]
p
r
o
p
o
s
ed
a
h
ier
ar
c
h
ical
r
o
u
t
in
g
p
r
o
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co
l
ca
lled
b
ac
k
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p
cl
u
s
ter
h
ea
d
p
r
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to
co
l
(
B
C
HP)
,
wh
ich
is
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a
s
ed
o
n
t
h
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C
B
R
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p
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C
H
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p
clu
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B
C
H)
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A
n
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as
C
H
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r
B
C
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p
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th
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B
C
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im
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a
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ailab
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m
p
ar
e
d
to
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A
ODV
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e
C
B
R
P
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
1
6
9
3
-
6
9
3
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T
E
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KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
18
,
No
.
6
,
Dec
em
b
e
r
2
0
2
0
:
3
3
39
-
33
45
3340
p
r
o
to
co
ls
.
T
o
r
r
es,
R
o
m
m
el,
et
a
l
.
[
8
]
p
r
o
p
o
s
ed
th
e
en
h
a
n
ce
d
b
ac
k
u
p
cl
u
s
ter
h
ea
d
p
r
o
t
o
c
o
l
(EB
C
HP)
.
I
t
h
as
b
ee
n
r
ea
lized
,
as
an
im
p
r
o
v
em
en
t
to
B
C
H
P
b
u
t,
u
n
lik
e
B
C
H
P,
it
u
s
es
a
r
esid
u
al
en
er
g
y
lev
el
s
tr
ateg
y
to
ch
an
g
e
th
e
B
C
H
n
o
d
e
s
tatu
s
to
C
H,
to
im
p
r
o
v
e
t
h
e
n
etwo
r
k
life
tim
e
in
th
e
p
r
o
ce
s
s
o
f
clu
s
ter
m
ain
t
en
an
ce
.
Sru
n
g
ar
am
,
K.
an
d
Kr
is
h
n
a
Pra
s
ad
[
9
]
p
r
o
p
o
s
ed
th
e
e
n
h
an
ce
d
C
B
R
P
(
E
C
B
R
P).
T
h
ey
u
s
ed
a
weig
h
ted
clu
s
ter
in
g
alg
o
r
ith
m
in
C
H
elec
tio
n
.
T
h
is
en
ab
les a
n
en
h
an
ce
d
clu
s
ter
in
g
a
p
p
r
o
ac
h
.
Al
-
k
ah
tan
i
S.
M.
a
n
d
M
o
u
f
ta
h
H.
T
.
[
1
0
]
s
u
g
g
ested
a
n
e
w
m
eth
o
d
to
r
estru
ctu
r
ea
clu
s
ter
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n
am
ely
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an
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f
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n
t
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e
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cl
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SERC
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p
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co
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I
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SERC
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ea
ch
C
H
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t
s
a
s
ec
o
n
d
ar
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C
H
(
SC
H)
.
W
h
en
th
e
C
H
d
ies,
th
e
SC
H
will
b
e
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m
ain
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H.
Sin
ce
SC
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is
r
ec
o
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n
ize
to
all
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ter
n
o
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es
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th
e
clu
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b
e
r
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o
r
m
e
d
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awa
y
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d
th
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cl
u
s
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lo
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k
s
b
ala
n
ce
d
.
Yass
ein
M.
B
.
an
d
Hijazi
N
[
1
1
]
p
r
o
p
o
s
ed
th
e
Vice
C
lu
s
ter
Hea
d
o
n
clu
s
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ased
r
o
u
tin
g
p
r
o
to
co
l
(
VC
H
-
C
B
R
P)
b
y
im
p
r
o
v
e
th
e
C
B
R
P.
T
h
e
C
H
s
en
d
s
a
h
ello
m
ass
ag
e
to
ev
er
y
n
o
d
e
ab
o
u
t
th
is
VC
H,
I
f
th
e
f
ir
s
tC
Hex
p
ir
ef
o
r
s
o
m
e
p
u
r
p
o
s
e,
th
en
th
e
VC
H
m
ar
k
et
it
s
elf
as
C
H,
wh
ich
l
o
wer
in
g
th
e
r
ate
o
f
ca
llin
g
clu
s
ter
co
n
s
tr
u
ctio
n
p
r
o
t
o
co
l
d
u
e
to
m
o
b
ilit
y
o
f
th
e
C
H.
Af
ter
all,
Sh
ak
ar
am
i
et
a
l
.
,
[
1
2
]
p
r
o
p
o
s
ed
a
p
r
o
to
co
l
wh
i
ch
h
as
s
ep
ar
ated
th
e
clu
s
ter
in
to
r
eliab
lean
d
u
n
r
eliab
lez
o
n
es.
I
f
a
C
H
s
h
if
t
to
th
e
u
n
r
eliab
lezo
n
e
th
en
th
e
ch
an
ce
o
f
b
r
ea
k
in
g
r
o
u
te
r
aises
.
So
,
th
e
alg
o
r
ith
m
ch
o
o
s
es
a
n
ew
n
o
d
e
as
a
C
H,
b
ef
o
r
e
t
h
e
ex
is
tin
g
C
H
m
o
v
es o
u
t to
u
n
r
eliab
lezo
n
e.
Ho
wev
e
r
,
n
o
n
e
o
f
th
e
r
esear
c
h
er
s
[
1
3
-
2
4
]
h
as c
o
n
s
id
er
ed
th
e
n
etwo
r
k
life
tim
e
i
n
h
ig
h
n
o
n
-
u
n
if
o
r
m
n
o
d
e
d
en
s
ities
MA
N
E
T
o
r
tr
ied
to
d
ec
r
ea
s
e
en
e
r
g
y
co
n
s
u
m
p
tio
n
.
I
n
th
is
co
n
tr
ib
u
tio
n
we
d
ev
el
o
p
ar
eso
u
r
ce
f
u
l,
r
eliab
le
an
d
s
ca
lab
le
r
o
u
tin
g
p
r
o
to
c
o
l
f
o
r
MA
NE
T
,
wh
er
e
we
p
r
o
p
o
s
e
th
e
s
q
u
ar
e
clu
s
ter
b
ased
r
o
u
tin
g
p
r
o
to
co
l
b
ased
o
n
r
e
p
licatio
n
p
r
o
to
co
l.
I
n
th
is
p
r
o
to
c
o
l
th
e
C
H
n
o
d
e
is
n
o
m
in
ated
ac
co
r
d
in
g
to
th
r
ee
m
etr
ics
in
clu
d
in
g
,
th
e
r
em
ain
i
n
g
en
er
g
y
,
th
e
d
eg
r
ee
an
d
th
e
m
o
b
ilit
y
.
A
b
ac
k
u
p
m
in
o
r
clu
s
ter
h
ea
d
(
MCH)
d
ep
e
n
d
in
g
o
n
th
e
clu
s
ter
s
ize
is
u
s
ed
to
en
s
u
r
e
av
ailab
ilit
y
with
lar
g
e
MA
NE
T
.
A
t
h
r
esh
o
ld
v
al
u
e
α
,
is
u
s
ed
to
h
a
n
d
l
e
th
e
s
ca
lab
ilit
y
o
f
th
e
MA
N
E
T
n
etwo
r
k
d
u
r
in
g
th
e
r
o
u
tin
g
p
r
o
ce
s
s
.
I
n
s
tead
o
f
u
s
in
g
co
m
m
o
n
g
atew
ay
s
b
etwe
en
C
Hs
we
u
s
e
a
d
esti
n
atio
n
-
s
eq
u
en
ce
d
d
is
tan
ce
-
v
ec
to
r
(
DSDV)
p
r
o
to
c
o
l
to
d
ec
r
ea
s
eth
e
en
er
g
y
c
o
n
s
u
m
p
ti
o
n
in
s
id
e
t
h
e
clu
s
ter
,
an
d
en
s
u
r
e
th
e
r
elia
b
ilit
y
b
etwe
en
clu
s
ter
s
.
2.
T
H
E
P
RO
P
O
SE
D
P
RO
T
O
CO
L
AL
G
O
RI
T
H
M
T
h
e
s
q
u
ar
e
clu
s
ter
-
b
ased
r
o
u
tin
g
p
r
o
to
co
l
(
SC
B
R
P
)
alg
o
r
ith
m
d
iv
id
es
th
e
n
etwo
r
k
in
to
eq
u
ally
n
o
n
-
o
v
er
lap
p
i
n
g
s
q
u
a
r
e
zo
n
es;
e
ac
h
co
n
tain
s
a
ce
r
tain
n
u
m
b
e
r
o
f
an
o
d
es.
T
h
e
n
o
d
es
in
s
i
d
e
th
e
clu
s
ter
ar
e
ca
teg
o
r
ized
in
to
th
r
ee
p
o
s
s
ib
le
s
tates a
s
s
h
o
wn
in
Fig
u
r
e
1
.
−
A
C
H
n
o
d
e
as
a
co
o
r
d
in
ato
r
i
n
s
id
e
ea
ch
clu
s
ter
.
All
o
th
er
n
o
d
es
with
in
a
clu
s
ter
ar
e
o
n
e
-
h
o
p
n
eig
h
b
o
r
s
o
f
th
e
C
H.
−
An
MCH n
o
d
e
as th
e
s
ec
o
n
d
-
b
est
n
o
d
e
at
th
e
cl
u
s
ter
.
−
A
n
o
r
m
al
n
o
d
e
(
NN
)
.
No
n
o
d
e
ca
n
b
e
ex
cited
b
etwe
en
cl
u
s
ter
s
ea
ch
n
o
d
e
m
u
s
t jo
in
t
o
clu
s
t
er
ac
co
r
d
in
g
t
o
r
ec
eiv
in
g
s
ig
n
al
s
tr
en
g
th
(
R
SS
)
,
s
o
all
n
o
d
es in
a
clu
s
ter
ar
e
i
n
tr
an
s
m
is
s
io
n
r
an
g
e
o
f
clu
s
ter
h
ea
d
.
T
h
e
s
u
g
g
ested
tech
n
iq
u
e
s
h
ap
es
a
clu
s
ter
b
y
ch
o
o
s
in
g
all
th
e
n
o
d
es
in
o
n
e
clu
s
ter
th
at
ar
e
clo
s
est
to
C
H.
I
n
th
e
s
am
e
m
eth
o
d
as
th
e
C
H
co
llectio
n
,
MCH
ch
o
s
e
b
u
t
th
e
p
r
esen
t
o
f
MCH
with
in
th
e
clu
s
ter
r
elies
o
n
ly
o
n
th
e
n
o
d
e
d
en
s
ity
with
in
th
e
clu
s
ter
.
B
o
th
n
o
d
es
ass
ig
n
ed
to
th
e
clu
s
ter
r
etain
th
e
C
H
an
d
MCH
r
ef
er
en
ce
n
o
d
es.
Via
r
estrictin
g
th
e
n
u
m
b
er
o
f
MCH
p
er
clu
s
ter
,
we
'
d
h
av
e
lo
a
d
b
alan
ci
n
g
ac
r
o
s
s
clu
s
ter
s
,
an
d
we
ca
n
av
o
id
h
av
in
g
lar
g
e
n
u
m
b
er
s
o
f
n
o
d
es
p
er
s
in
g
le
clu
s
ter
h
ea
d
,
wh
ich
m
ak
es
it
d
if
f
icu
lt
to
s
ch
ed
u
le
an
d
h
an
d
l
e
th
e
clu
s
ter
'
s
r
eso
u
r
ce
s
.
C
lu
s
ter
s
ar
e
f
o
r
m
ed
ar
o
u
n
d
th
e
lo
west
m
o
b
ile
an
d
th
e
h
i
g
h
e
s
t
en
er
g
y
n
o
d
e.
Ou
r
p
r
o
p
o
s
ed
alg
o
r
ith
m
co
n
s
id
er
s
th
r
ee
m
etr
ics
f
r
o
m
n
o
d
es
p
ar
am
eter
f
o
r
th
e
ele
ctio
n
o
f
C
H.
T
h
ese
m
etr
ics
ar
e
m
o
b
ilit
y
s
tate,
r
em
ain
in
g
e
n
er
g
y
an
d
n
o
d
e
d
eg
r
ee
.
B
y
s
elec
tin
g
th
e
m
o
s
t
s
u
itab
le
n
o
d
e
as
C
H
s
ta
b
ilit
y
o
f
clu
s
ter
in
cr
ea
s
ed
.
E
ac
h
C
Hs
h
av
e
two
tab
les
w
h
er
ein
th
e
in
f
o
r
m
atio
n
a
b
o
u
t
th
e
o
th
er
n
eig
h
b
o
r
C
Hs
an
d
in
f
o
r
m
atio
n
ab
o
u
t
th
e
clu
s
ter
n
o
d
es
NN.
I
n
ter
c
o
m
m
u
n
icatio
n
b
etwe
en
C
Hs
h
as
d
o
n
e
u
s
in
g
DSDV
r
o
u
tin
g
p
r
o
t
o
co
l,
wh
ile
th
e
in
tr
a
co
m
m
u
n
icatio
n
in
s
i
d
e
ea
ch
clu
s
ter
u
s
e
u
s
in
g
th
e
C
B
R
P
r
o
u
tin
g
p
r
o
t
o
co
l.
T
h
e
DSD
V
ex
h
ib
its
attr
ac
tiv
e
p
er
f
o
r
m
an
ce
wh
e
n
th
e
n
etwo
r
k
lo
ad
a
n
d
m
o
b
ilit
y
ar
e
m
o
d
er
atew
h
ich
ar
e
ap
p
r
o
p
r
iate
f
o
r
C
Hs n
etwo
r
k
.
Fig
u
r
e
1
.
Mo
d
el
p
r
o
p
o
s
ed
s
tr
u
ctu
r
e
f
o
r
th
e
MA
NE
T
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
A
n
ew clu
s
teri
n
g
tech
n
iq
u
e
b
a
s
ed
o
n
r
ep
lica
tio
n
f
o
r
MANET
r
o
u
tin
g
p
r
o
to
c
o
ls
(
S
a
lma
S
.
Mo
h
a
med
)
3341
2.
1
.
Clus
t
er
hea
d det
er
m
ina
t
io
n
I
n
a
MA
NE
T
,
e
v
er
y
n
o
d
e
s
en
d
s
HE
L
L
O
m
ess
ag
es
to
o
th
er
s
to
esti
m
ate
th
e
n
u
m
b
er
o
f
it
s
n
eig
h
b
o
r
n
o
d
es.
B
y
esti
m
atin
g
th
r
ee
r
atio
s
ac
co
r
d
in
g
to
f
o
llo
win
g
(
1
)
ea
ch
n
o
d
e
d
ec
id
es
its
weig
h
t
(
NW
)
th
e
n
o
d
es
with
th
e
h
ig
h
est
w
eig
h
t
v
alu
e
elec
tio
n
as
C
H
a
n
d
it
p
r
o
d
u
ce
s
a
clu
s
ter
.
Oth
er
co
n
tact
n
o
d
es
in
th
e
co
v
er
a
g
e
ar
ea
ar
e
NN,
an
d
co
n
tact
b
y
C
H.
NW
i
= w
1
D
i
+ w
2
E
ti
+ w
3
S
i
(
1
)
wh
er
e
,
N
n
etwo
r
k
s
ize,
Di
r
ep
r
esen
ts
n
o
d
e
d
en
s
ity
,
E
i
is
th
e
r
esid
u
al
en
er
g
y
at
th
e
n
o
d
e
an
d
Mi
r
ef
er
s
t
o
m
o
b
ilit
y
s
tate
o
f
th
e
n
o
d
e,
wh
i
le
w1
,
w2
an
d
w3
ar
e
t
h
e
weig
h
t f
ac
to
r
s
.
W
ith
in
cr
ea
s
in
g
in
th
e
im
p
o
r
tan
ce
o
f
m
etr
ic
th
ey
will
b
e
g
r
ea
ter
,
w
1
+w
2
+w
3
=
1
.
I
n
itially
w
1
=
0
.
2
5
,
w
2
=
0
.
5
an
d
w
3
=
0
.
2
5
,
a
n
d
a
d
ju
s
ted
th
em
ad
a
p
tiv
ely
ac
co
r
d
in
g
to
n
etwo
r
k
s
tate.
Th
is
NW
i
v
alu
e
in
d
icate
s
th
e
s
tab
ilit
y
o
f
th
e
n
o
d
e
with
r
ef
er
e
n
ce
to
all
n
ei
g
h
b
o
r
n
o
d
s
,
n
o
d
e
with
t
h
e
m
a
x
im
u
m
NW
i
v
alu
e
(
i.e
.
less
m
o
b
ile
an
d
h
i
g
h
en
er
g
y
)
c
h
o
s
en
as
a
C
H
an
d
tr
an
s
m
its
a
m
ess
ag
e
co
n
tain
in
g
its
C
H
I
D
to
th
e
n
eig
h
b
o
r
in
g
n
o
d
es.
W
h
en
th
e
n
eig
h
b
o
r
in
g
n
o
d
es o
b
tain
th
e
C
H
n
o
tific
ati
o
n
,
t
h
ey
r
esp
o
n
d
to
th
e
C
H
to
jo
in
th
e
clu
s
ter
,
an
d
all
n
o
d
es
in
s
id
e
th
e
clu
s
ter
tak
e
th
e
aler
t.
I
t
is
n
ec
ess
ar
y
to
r
o
tate
th
e
C
H
elec
tio
n
alg
o
r
ith
m
am
o
n
g
n
o
d
es
o
n
ce
th
e
C
H
r
u
n
s
o
u
t
o
f
en
er
g
y
o
r
m
o
v
e
awa
y
f
r
o
m
clu
s
ter
n
o
d
es,
it
is
n
o
lo
n
g
er
o
p
er
atio
n
al,
a
n
d
all
th
e
n
o
d
es
with
in
th
e
clu
s
ter
lo
s
e
co
m
m
u
n
icatio
n
ab
ilit
y
.
Fin
d
th
e
d
en
s
ity
ar
o
u
n
d
e
ac
h
n
o
d
e
o
f
ea
ch
n
o
d
e
b
y
c
o
u
n
tin
g
its
n
eig
h
b
o
r
s
,
D
i
=
|
d
i
–
N
4
(
2
)
wh
er
e
,
d
i
=
s
u
m
[
d
is
tan
ce
(
x
,
y
)
<
r
an
g
e
].
T
h
e
s
ize
o
f
th
e
cl
u
s
ter
is
an
im
p
o
r
tan
t
m
etr
ic.
T
h
er
e
is
a
tr
ad
e
-
o
f
f
b
etwe
en
th
e
clu
s
ter
d
im
en
s
io
n
an
d
th
e
n
u
m
b
e
r
o
f
C
Hs.
I
f
th
e
clu
s
ter
s
ize
i
s
d
ec
r
ea
s
ed
,
th
e
e
n
er
g
y
co
n
s
u
m
p
tio
n
with
in
ea
ch
clu
s
ter
is
s
m
aller
,
b
u
t
with
co
m
p
le
x
MA
NE
T
d
u
e
to
i
n
cr
ea
s
e
in
th
e
n
u
m
b
er
o
f
C
H.
L
ar
g
er
clu
s
ter
s
ize
g
iv
es h
ig
h
er
en
e
r
g
y
in
ea
ch
clu
s
ter
,
with
s
im
p
ler
MA
NE
T
n
etwo
r
k
.
Su
p
p
o
s
in
g
cu
r
r
en
t
r
em
ain
in
g
en
er
g
y
o
f
a
n
o
d
e
is
(
E
r
)
an
d
d
ef
in
ed
th
r
esh
o
ld
en
e
r
g
y
E
th
,
wh
ich
is
E
t
α
wh
er
e
p
ar
am
eter
α
s
et
d
ep
en
d
s
o
n
th
e
s
ize
o
f
MA
NE
T
.
On
l
y
th
e
n
o
d
e
with
ad
eq
u
ate
en
e
r
g
y
h
as a
h
ig
h
m
etr
ic
to
av
o
i
d
n
o
d
e
f
ailu
r
e
r
esu
ltin
g
f
r
o
m
e
x
h
au
s
ted
en
er
g
y
.
T
h
e
en
er
g
y
weig
h
t
f
o
r
ca
lc
u
latio
n
o
f
d
elay
,
E
ti
ca
lcu
lated
ac
co
r
d
in
g
to
th
e
r
atio
b
etwe
en
r
ec
eiv
in
g
en
er
g
y
to
to
tal
en
er
g
y
E
ti
=
.
A
n
o
d
e
en
g
ag
e
in
l
o
w
m
o
b
ilit
y
s
h
o
u
ld
b
e
elec
ted
as
C
H.
T
h
e
m
o
b
il
ity
o
f
th
e
n
o
d
e
S
i
is
co
n
s
id
er
ed
with
th
e
d
if
f
er
e
n
ce
in
n
o
d
e
lo
ca
tio
n
an
d
tim
e
ac
co
r
d
in
g
to
f
o
r
m
u
la
,
S
i
=
√
(
x
t
−
x
t
−
1
)
^
2
–
(
y
t
−
y
t
−
1
)
^
2
T
(
3
)
2.
2
.
M
ino
r
clus
t
er
hea
d e
lect
io
n
C
h
an
g
ea
b
len
o
d
es
d
en
s
ities
in
clu
s
ter
s
ef
f
ec
ts
o
n
th
e
o
p
er
at
io
n
o
f
th
e
MA
NE
T
,
to
a
d
d
r
ess
th
is
is
s
u
e
SC
B
R
P
u
s
e
M
C
H,
wh
ich
is
th
e
s
ec
o
n
d
-
b
est
n
o
d
e
in
th
e
cl
u
s
ter
,
ch
o
s
en
d
u
r
in
g
th
e
s
am
e
p
r
o
ce
d
u
r
eo
f
an
elec
tio
n
th
e
C
H.
I
n
n
o
n
-
u
n
if
o
r
m
d
e
n
s
ity
clu
s
ter
o
r
lar
g
e
s
ize
clu
s
ter
,
wit
h
a
n
u
m
b
er
o
f
n
o
d
es
ex
ce
s
s
es
a
ce
r
tain
t
h
r
esh
o
ld
C
H
ca
n
n
o
m
in
ate
a
s
ec
o
n
d
C
H
to
h
elp
in
in
ter
n
al
d
ata
ex
ch
an
g
e
b
etwe
en
n
o
d
es
in
th
e
s
am
e
clu
s
ter
.
C
h
ar
ac
ter
izin
g
th
e
im
p
ac
to
f
a
n
o
n
-
h
o
m
o
g
e
n
eo
u
s
n
o
d
e
d
en
s
ity
o
n
SC
B
R
P
o
p
er
atio
n
an
d
d
eter
m
in
i
n
g
th
e
leastp
er
f
o
r
m
an
ce
le
v
el
is
s
ig
n
if
ican
t
in
o
u
r
s
tu
d
y
SC
B
R
P
s
et
t
h
e
M
C
H
cr
ea
tio
n
th
r
esh
o
ld
to
N
α
.
T
h
is
p
ar
am
eter
h
elp
s
m
an
ag
e
th
e
tr
ad
e
-
o
f
f
b
etwe
en
cl
u
s
ter
s
ize
an
d
n
u
m
b
er
o
f
MCHs
to
k
ee
p
MA
NE
T
co
n
g
esti
o
n
with
in
th
e
s
am
e
clu
s
ter
s
im
p
le,
h
ig
h
a
v
ailab
ilit
y
an
d
c
o
n
tr
o
l.
T
h
e
cr
ea
tio
n
o
f
th
e
SC
B
R
P
cl
u
s
ter
an
d
th
e
c
h
o
ice
o
f
C
H
an
d
th
e
MCH a
lg
o
r
ith
m
ar
e
s
h
o
wn
in
T
ab
le
1.
3.
SQ
UARE C
L
US
T
E
R
B
A
SE
D
RO
UT
I
NG
P
RO
T
O
CO
L
CL
US
T
E
RING
CO
M
M
U
NI
CATI
O
N
T
h
er
e
ar
e
two
le
v
els o
f
r
o
u
tin
g
:
−
W
ith
in
th
e
clu
s
ter
:
th
er
e
ar
e
two
way
s
to
ex
ch
an
g
e
d
ata
b
e
twee
n
n
o
d
es
.
I
n
th
e
s
am
e
clu
s
ter
n
o
d
es
ca
n
co
m
m
u
n
icate
d
ir
ec
tly
(
with
in
s
m
all
s
ize
clu
s
ter
)
,
wh
ich
t
h
e
n
o
d
es
ca
n
b
e
r
etr
iev
e
d
ir
ec
tly
s
in
ce
th
ey
h
av
e
s
co
p
e
b
etwe
en
th
em
an
d
ar
e
d
i
r
ec
tly
v
is
ib
le.
Oth
er
wis
e
(
in
ca
s
e
o
f
lar
g
e
s
ize
n
etwo
r
k
)
,
t
h
e
s
o
u
r
ce
n
o
d
e
a
nd
d
esti
n
atio
n
n
o
d
e
m
u
s
t e
x
ch
a
n
g
e
d
ata
th
r
o
u
g
h
C
Hs o
r
MCH.
−
Ou
ts
id
e
th
e
clu
s
ter
: n
o
d
e
d
ec
i
d
es th
at
th
er
e
is
n
o
w
p
ath
to
th
e
d
esire
d
lo
ca
tio
n
wh
en
t
h
e
p
a
ck
et
is
r
ec
eiv
ed
to
th
e
C
H.
T
h
e
C
H
in
clu
d
es
an
ad
d
itio
n
al
DSDV
f
o
r
war
d
in
g
tab
le
f
o
r
in
ter
-
clu
s
ter
c
o
m
m
u
n
icatio
n
.
T
h
e
C
H
p
ass
es th
e
d
ata
to
th
e
d
ep
ar
tu
r
e
p
o
in
t CH.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
18
,
No
.
6
,
Dec
em
b
e
r
2
0
2
0
:
3
3
39
-
33
45
3342
A
m
e
s
s
a
g
e
h
as
i
n
f
o
r
m
a
t
i
o
n
a
b
o
u
t
a
n
o
d
e
’
s
I
D
a
n
d
t
a
s
k
s
,
t
o
k
e
e
p
t
h
e
n
e
i
g
h
b
o
r
t
a
b
l
e
a
n
d
C
H
i
n
f
o
r
m
a
t
i
o
n
u
p
d
a
t
e
d
.
I
f
n
o
H
e
l
l
o
m
ess
a
g
e
is
es
t
a
b
l
is
h
e
d
f
r
o
m
a
n
e
i
g
h
b
o
r
th
e
n
e
i
g
h
b
o
r
i
s
t
h
o
u
g
h
t
g
o
n
e
a
n
d
r
e
m
o
v
e
d
f
r
o
m
i
t
s
t
a
b
l
e
.
I
f
n
o
C
H
i
s
f
o
u
n
d
,
a
n
e
w
o
n
e
i
s
c
h
o
s
e
n
.
F
o
r
i
l
l
u
s
t
r
at
i
o
n
s
c
o
n
s
i
d
e
r
t
h
e
c
l
u
s
t
e
r
s
m
e
n
t
i
o
n
ed
b
e
l
o
w
:
−
I
n
Fig
u
r
e
2
,
n
o
d
e
S
ac
t
as
s
o
u
r
ce
an
d
wan
ts
to
s
en
d
d
ata
to
n
o
d
e
D,
th
e
y
h
ea
r
ea
ch
o
t
h
er
s
o
th
ey
ca
n
s
en
d
d
ata
d
ir
ec
tly
with
o
u
t
aid
o
f
C
H.
−
I
n
Fig
u
r
e
3
,
S
m
u
s
t
s
en
d
a
r
eq
u
est
to
its
attac
h
ed
clu
s
ter
C
H
o
r
to
MCH
at
f
ir
s
t,
an
d
th
en
S
s
en
d
s
th
e
m
ess
ag
e
to
D
th
r
o
u
g
h
C
H
in
ca
s
e
o
f
Fi
g
u
r
e
3
(
a
)
o
r
MCH Fig
u
r
e
3
(
b
)
.
−
I
n
Fig
u
r
e
4
,
th
e
s
o
u
r
ce
n
o
d
e
S
r
eq
u
ests
to
its
attac
h
ed
C
H
an
d
th
en
th
e
C
H
will
b
r
o
ad
ca
s
t
th
is
r
eq
u
est
to
its
n
eig
h
b
o
u
r
s
C
H
th
r
o
u
g
h
DSD
V
r
o
u
tin
g
p
r
o
to
co
l,
a
n
d
th
e
p
r
o
ce
s
s
will
co
n
tin
u
e
u
n
til
th
e
r
eq
u
est
ar
r
iv
es
at
th
e
clu
s
ter
wh
ich
b
elo
n
g
s
to
th
e
d
esti
n
atio
n
n
o
d
e.
Fin
ally
,
D
s
en
d
s
a
r
ep
lay
alo
n
g
t
h
e
d
is
co
v
er
ed
p
ath
to
S th
r
o
u
g
h
C
Hs.
T
ab
le
1
.
SC
B
R
P A
lg
o
r
ith
m
A
l
g
o
r
i
t
h
m1
S
C
B
R
P
c
l
u
s
t
e
r
d
e
v
e
l
o
p
men
t
a
n
d
se
l
e
c
t
i
o
n
o
f
C
H
a
n
d
t
h
e
M
C
H
R
e
q
u
i
r
e
:
R
o
u
t
i
n
g
t
a
b
l
e
o
f
t
h
e
n
e
i
g
h
b
o
r
n
o
d
e
s
K
=
{N
N
…
.
N
N
n
}
E
n
su
r
e
:
N
o
d
e
S
t
a
t
u
s
(
ξ
n
)
u
p
d
a
t
e
d
f
r
o
m S =
{U
N
M
E
M
B
E
R
,
N
N
,
C
H
,
M
C
H
}
1:
if
(ξ
n
= UNDECIDED) then
2:
ξ
n
← CH
3:
while
(K ≠ φ) do
4:
get the neighbors from K and
α
5:
get neighbor status ξ
n
and neighbor
weight
NW
i
6:
end while
7:
Sort K by NW
i
8:
NN
1
← K[1]
9:
NN
2
← K[2]
1
0
:
if
(NN1
st
∩ { UNMEMBER; MEMBER; MCH}
then
1
1
:
if
(K
i
≥ NN1
st
) then
1
2
:
ξ
n
← CH
1
3
:
else if
(NN
i
≥ NN2
nd
&& MCH
thr
=
n
α
) then
1
4
:
ξ
n
← MCH
1
5
:
Else
1
6
:
ξ
n
← MEMBER
1
7
:
end if
1
8
:
end if
1
9
:
return
ξ
n
Fig
u
r
e
2
.
C
o
m
m
u
n
icatio
n
i
n
s
id
e
s
m
all
clu
s
ter
(
a)
(
b
)
Fig
u
r
e
3
.
C
o
m
m
u
n
icatio
n
i
n
s
id
e
lar
g
e
clu
s
ter
,
th
r
o
u
g
h
;
(
a)
C
H,
(
b
)
MCH
Fig
u
r
e
4
.
C
o
m
m
u
n
icatio
n
b
et
wee
n
clu
s
ter
s
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
A
n
ew clu
s
teri
n
g
tech
n
iq
u
e
b
a
s
ed
o
n
r
ep
lica
tio
n
f
o
r
MANET
r
o
u
tin
g
p
r
o
to
c
o
ls
(
S
a
lma
S
.
Mo
h
a
med
)
3343
4.
RE
SU
L
T
S
A
ND
D
I
SCU
SS
I
O
N
Simu
latio
n
is
ca
r
r
ied
o
u
t
o
n
NS
-
3
s
im
u
lato
r
[
2
5
]
to
ass
ess
th
e
clu
s
ter
in
g
m
eth
o
d
.
A
s
er
ies
o
f
s
im
u
latio
n
ex
p
e
r
im
en
ts
d
esig
n
ed
to
ass
ess
o
u
r
p
r
o
p
o
s
ed
SC
B
R
P,
E
B
C
HP,
E
C
B
R
P
an
d
VC
H
-
C
B
R
P
test
in
g
p
er
f
o
r
m
an
ce
.
2
0
0
n
o
d
es
wer
e
r
an
d
o
m
l
y
p
lace
d
i
n
s
id
e
a
1
0
0
0
x
1
0
0
0
m
wh
e
n
s
im
u
latio
n
b
e
g
an
.
Simu
late
ag
ilit
y
with
a
p
a
u
s
e
tim
e
o
f
0
s
ec
o
n
d
an
d
s
im
u
latio
n
o
f
3
0
0
-
s
ec
o
n
d
.
Oth
e
r
p
ar
am
eter
s
f
o
r
s
im
u
latio
n
ar
e
s
ee
in
g
in
T
ab
le
2.
SC
B
R
P,
E
B
C
H
P,
E
C
B
R
P,
an
d
VC
H
-
C
B
R
P
ef
f
icie
n
cy
is
m
ea
s
u
r
ed
in
ter
m
s
o
f
p
ac
k
et
d
eliv
er
y
r
atio
(
PDR
)
,
E
2
E
laten
cy
,
an
d
av
er
ag
e
en
er
g
y
u
s
ag
e.
I
n
ad
d
itio
n
,
we
f
in
d
th
e
n
u
m
b
er
o
f
clu
s
ter
s
cr
ea
ted
wh
ich
h
av
e
a
m
ajo
r
ef
f
ec
t
o
n
clu
s
ter
s
tab
ilit
y
an
d
r
ed
u
ce
s
th
e
o
v
er
h
ea
d
clu
s
ter
in
g
.
I
n
th
is
s
tu
d
y
α
eq
u
al
to
5
in
ca
s
e
o
f
a
s
m
all
n
etwo
r
k
o
r
1
0
i
n
lar
g
e
MA
NE
T
.
Fig
u
r
e
5
illu
s
tr
ates
th
e
av
er
a
g
e
E
2
E
d
ela
y
o
f
o
u
r
s
u
g
g
est
ed
tech
n
iq
u
e
an
d
t
h
e
ex
is
tin
g
clu
s
ter
in
g
p
r
o
to
co
ls
.
I
t
ca
n
b
e
s
ee
n
th
a
t
SC
B
R
P
p
r
o
to
co
l’
s
av
er
ag
e
E
2
E
d
elay
is
s
m
aller
th
an
o
th
er
s
.
T
h
e
p
ac
k
et
d
is
tr
ib
u
tio
n
r
atio
(
PDR
)
is
th
e
r
atio
o
f
th
e
am
o
u
n
t
o
f
p
ac
k
et
s
th
e
en
d
p
o
in
t
co
llects
to
th
e
n
u
m
b
er
o
f
p
ac
k
ets
th
e
s
o
u
r
ce
n
o
d
e
p
r
o
d
u
ce
s
.
T
h
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
d
o
es
th
e
h
ig
h
est
in
PDR
f
o
llo
wed
b
y
E
C
B
R
P
as
s
ee
n
in
Fig
u
r
e
6
,
th
is
is
attr
ib
u
ted
to
wo
r
k
in
g
p
r
ac
tically
with
lim
ited
s
u
b
n
etwo
r
k
s
(
i.e
.
clu
s
ter
)
s
u
c
h
th
at
SC
B
R
P
w
ill
attain
r
o
u
g
h
ly
c
o
n
s
tan
t
PDR
o
r
b
itin
g
th
e
r
ea
l
n
etwo
r
k
s
ca
le.
E
v
en
with
lar
g
e
clu
s
ter
s
,
b
y
d
e
cr
ea
s
in
g
co
n
g
esti
o
n
in
s
id
e
th
e
clu
s
ter
,
B
C
H
ca
n
i
m
p
r
o
v
e
PDR
.
W
ith
all
p
ac
k
et
s
p
r
o
v
id
e
d
b
y
th
e
r
ec
ip
ien
t,
t
h
e
en
er
g
y
u
s
ag
e
is
th
e
elec
tr
icity
u
s
ed
b
y
th
e
n
et
w
o
r
k
.
T
h
is
is
ca
lcu
lated
as
th
e
o
v
er
all
en
er
g
y
a
b
s
o
r
b
ed
d
iv
id
ed
b
y
th
e
to
tal
am
o
u
n
t
o
f
th
e
r
ec
ei
v
ed
p
ac
k
ets.
Fig
u
r
e
5
.
E
2
E
Dela
y
v
s
.
n
etwo
r
k
s
ize
Fig
u
r
e
6
.
PDR
v
s
.
n
etwo
r
k
s
ize
Fig
u
r
e
7
d
is
p
lay
s
av
er
a
g
e
en
er
g
y
co
n
s
u
m
p
tio
n
with
r
eg
ar
d
s
to
p
ar
ticu
lar
n
u
m
b
e
r
o
f
n
o
d
es.
Ou
r
p
r
o
p
o
s
ed
p
r
o
to
co
l
e
x
p
licitly
u
s
es
les
s
en
er
g
y
th
a
n
o
t
h
er
p
r
o
t
o
co
ls
.
T
h
e
SC
B
R
P
p
r
o
to
co
l
o
f
f
er
s
a
s
tan
d
ar
d
ize
d
en
v
ir
o
n
m
en
t
f
o
r
en
er
g
y
u
s
ag
e
in
MA
NE
T
an
d
th
u
s
ex
ten
d
s
MA
NE
T
s
'
life
tim
e
to
2
0
p
er
ce
n
t h
ig
h
er
th
a
n
o
th
e
r
p
r
o
to
co
ls
,
e
v
en
th
o
u
g
h
th
e
n
u
m
b
er
o
f
co
n
n
ec
ted
n
o
d
es
r
an
g
es
f
r
o
m
1
0
0
to
2
0
0
.
Fig
u
r
e
8
s
h
o
ws
th
e
b
o
n
d
b
etwe
en
am
o
u
n
to
f
n
o
d
es
in
MA
NE
T
an
d
n
u
m
b
er
o
f
cl
u
s
ter
f
o
r
m
atio
n
,
also
its
s
h
o
ws
th
at
SC
B
R
P
f
o
r
m
s
m
all
n
u
m
b
er
o
f
clu
s
ter
s
co
m
p
ar
in
g
t
o
o
t
h
er
p
r
o
to
c
o
ls
,
d
u
e
to
u
s
in
g
o
f
m
o
r
e
s
p
ec
if
ic
m
etr
ics.T
h
e
n
u
m
b
er
o
f
b
ac
k
u
p
C
H
in
o
th
er
p
r
o
to
co
ls
eq
u
al
to
C
H
at
al
l
n
e
two
r
k
s
izes,
b
ec
au
s
e
th
er
e
ar
e
n
o
r
u
l
es
to
cr
ea
te
b
ac
k
u
p
clu
s
ter
h
ea
d
o
n
th
ese
p
r
o
to
co
ls
,
in
o
th
er
h
a
n
d
SC
B
R
P
f
o
r
m
MCH
u
n
d
er
ce
r
tain
co
n
d
itio
n
s
o
,
it’s
n
o
t
n
ec
ess
ar
y
to
f
in
d
MCH in
all
clu
s
ter
s
.
T
ab
le
2
.
Simu
latio
n
p
ar
am
eter
s
P
a
r
a
me
t
e
r
V
a
l
u
e
s
Tr
a
n
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i
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o
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r
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e
2
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a
f
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c
t
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p
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R
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e
p
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o
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n
t
M
o
d
e
l
R
a
n
d
o
m
M
o
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t
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o
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Fig
u
r
e
7
.
T
o
tal
en
er
g
y
co
n
s
u
m
p
tio
n
Fig
u
r
e
8
.
Nu
m
b
er
o
f
C
H
at
ea
ch
alg
o
r
ith
m
s
a
n
d
n
u
m
b
er
o
f
MCH a
t SC
B
R
P
5
.
CO
NCLUS
I
O
N
A
n
ew
MA
NE
T
r
o
u
tin
g
p
r
o
t
o
co
l
b
ased
o
n
r
ep
licatio
n
p
r
o
t
o
co
l
ca
lled
s
q
u
ar
e
clu
s
ter
-
b
ased
r
o
u
tin
g
p
r
o
to
co
l
(
SC
B
R
P)
is
p
r
o
p
o
s
ed
.
SC
B
R
P
alg
o
r
ith
m
p
r
esen
ts
a
s
im
p
le,
lig
h
t
an
d
q
u
iet
s
o
lu
tio
n
t
o
MA
NE
T
r
o
u
tin
g
co
n
s
tr
ain
ts
.
T
h
e
SC
B
R
P
d
iv
id
es
th
e
tr
ad
itio
n
al
MA
NE
T
in
to
n
o
n
-
o
v
er
lap
p
in
g
clu
s
ter
s
an
d
c
o
n
n
ec
ts
th
em
u
s
in
g
a
p
r
o
ac
ti
v
e
r
o
u
tin
g
p
r
o
to
co
l.
T
h
e
SC
B
R
P
es
tim
ates
th
e
n
e
two
r
k
m
etr
ics
o
f
e
ac
h
n
o
d
e
i
n
n
etwo
r
k
a
n
d
an
ef
f
icien
t
C
H
is
s
elec
ted
b
ased
o
n
th
ese
m
etr
ics.
C
o
n
g
esti
o
n
in
s
id
e
a
clu
s
ter
is
c
o
n
tr
o
lled
b
y
a
t
h
r
esh
o
ld
b
ase
d
o
n
n
etwo
r
k
s
ize
an
d
th
e
s
elec
tio
n
o
f
th
e
MCH.
T
h
is
h
as
im
p
r
o
v
ed
th
e
a
v
ailab
ilit
y
o
f
MA
NE
T
.
T
h
e
o
u
tco
m
es
o
f
th
e
ex
p
er
m
o
n
ts
im
u
latio
n
s
h
o
ws
th
at
th
e
in
tr
o
d
u
ce
d
cl
u
s
ter
in
g
m
eth
o
d
en
h
an
ce
s
th
e
MA
NE
T
's
n
etwo
r
k
ef
f
icien
cy
,
r
elia
b
ilit
y
,
av
ailab
i
lity
an
d
s
ca
lab
ilit
y
tak
in
g
i
n
to
ac
co
u
n
t th
e
e
f
f
ec
t o
f
n
etwo
r
k
s
ize.
RE
F
E
R
E
NC
E
S
[1
]
J
.
Lo
o
,
J.
L
lo
re
t
M
a
u
ri
,
e
t
a
l.
,
“
M
o
b
il
e
a
d
h
o
c
n
e
two
r
k
s: cu
rre
n
t
sta
tu
s a
n
d
fu
t
u
re
tren
d
s,
”
CRC
Pre
ss
,
2
0
1
6
.
[2
]
A
.
No
sra
ti
n
ia,
T
.
E.
Hu
n
ter
,
e
t
a
l.
,
“
Co
o
p
e
ra
ti
v
e
c
o
m
m
u
n
ica
ti
o
n
i
n
wire
les
s
n
e
two
rk
s
,”
IEE
E
c
o
mm
u
n
ica
t
io
n
s
M
a
g
a
zin
e
,
v
o
l.
42
,
n
o
.
1
0
,
p
p
.
74
-
80
,
2
0
0
4
.
[3
]
Lan
e
m
a
n
,
J.
N.,
Tse
,
D.
N.
C
.
,
&
Wo
rn
e
ll
,
G
.
W.
,
“
Co
o
p
e
ra
ti
v
e
Di
v
e
rsity
i
n
Wi
re
les
s
Ne
two
r
k
s:
Eff
icie
n
t
P
ro
to
c
o
ls
a
n
d
Ou
ta
g
e
Be
h
a
v
i
o
r,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s o
n
I
n
fo
rm
a
ti
o
n
T
h
e
o
ry
,
v
o
l.
50
,
n
o
.
1
2
,
pp.
3
0
6
2
-
3
0
8
0
,
2
0
0
4
.
[4
]
Ei
m
a
n
Alo
taib
i
,
Biswa
n
a
th
M
u
k
h
e
rjee
,
“
A
su
rv
e
y
o
n
r
o
u
ti
n
g
a
lg
o
rit
h
m
s
fo
r
wire
les
s
Ad
-
Ho
c
a
n
d
m
e
sh
n
e
two
rk
s
,”
Co
mp
u
ter
Ne
tw
o
rk
,
v
o
l.
56
,
n
o
.
2
,
p
p
.
9
4
0
-
9
6
5
,
2
0
1
2
.
[5
]
M
a
so
o
d
Ah
m
a
d
,
A
b
d
u
l
Ha
m
e
e
d
,
e
t
a
l.
,
“
S
tate
-
of
-
t
h
e
-
Art
Clu
s
terin
g
S
c
h
e
m
e
s
in
M
o
b
i
le
Ad
Ho
c
Ne
two
rk
s:
Ob
jec
ti
v
e
s
,
Ch
a
ll
e
n
g
e
s,
a
n
d
F
u
tu
r
e
Dire
c
ti
o
n
s,”
IEE
E
Acc
e
ss
,
n
o
.
7
,
p
p
.
1
7
0
6
7
-
1
7
0
8
1
,
2
0
1
9
.
[6
]
Hu
a
n
g
,
Jin
k
e
,
Xia
o
g
u
a
n
g
F
a
n
,
Xi
n
Xia
n
g
,
M
i
n
Wa
n
,
Zh
e
n
f
u
Zh
u
o
,
a
n
d
Y
o
n
g
ji
a
n
Ya
n
g
,
"
A
c
lu
ste
ri
n
g
ro
u
ti
n
g
p
r
o
to
c
o
l
fo
r
m
o
b
il
e
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ma
ti
c
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l
Pro
b
lem
s in
E
n
g
i
n
e
e
ri
ng
,
2
0
1
6
.
[7
]
R.
To
rre
s,
L
.
M
e
n
g
u
a
l,
O.
M
a
r
b
a
n
,
S
.
Ei
b
e
,
E.
M
e
n
a
sa
lv
a
s,
B.
M
a
z
a
,
“
A
m
a
n
a
g
e
m
e
n
t
a
d
h
o
c
n
e
two
rk
s
m
o
d
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l
fo
r
re
sc
u
e
a
n
d
e
m
e
rg
e
n
c
y
sc
e
n
a
rio
s,
”
Exp
e
rt S
y
ste
ms
wit
h
Ap
p
li
c
a
ti
o
n
s
,
v
o
l.
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,
n
o
.
10
,
p
p
.
9
5
5
4
-
9
5
6
3
,
2
0
1
2
.
[8
]
To
rre
s,
Ro
m
m
e
l,
e
t
a
l.
“
Im
p
ro
v
i
n
g
li
fe
ti
m
e
a
n
d
a
v
a
il
a
b
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d
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m
e
rg
e
n
c
y
a
n
d
r
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sc
u
e
sc
e
n
a
rio
s
,”
Ne
w
Co
n
trib
u
ti
o
n
s
in
I
n
fo
rm
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ti
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n
S
y
ste
ms
a
n
d
T
e
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h
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ie
s.
S
p
ri
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g
e
r,
Ch
a
m
,
v
o
l.
3
5
3
,
p
p
.
9
7
9
-
9
8
9
,
2
0
1
5
.
[9
]
S
ru
n
g
a
ra
m
,
K.,
&
Krish
n
a
P
ra
sa
d
,
M
.
H.
M
.
,
“
E
n
h
a
n
c
e
d
c
lu
ste
r
ba
se
d
ro
u
t
in
g
p
r
o
to
c
o
l
fo
r
M
AN
ET
S
,
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in
A
d
v
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n
c
e
s
in
c
o
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ter
sc
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e
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n
d
in
f
o
rm
a
ti
o
n
tec
h
n
o
lo
g
y
,
Ne
two
rk
s
a
n
d
c
o
mm
u
n
ica
ti
o
n
s,
S
e
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o
n
d
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ter
n
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t
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n
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l
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fer
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e
,
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2
0
1
2
,
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l.
8
4
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p
.
3
4
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5
2
,
Ja
n
u
a
ry
2
-
4
,
2
0
1
2
.
[
1
0
]
Al
-
k
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h
t
a
n
i
S
.
M
.
,
M
o
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t
a
h
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.
T.
,
“
E
n
h
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n
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m
e
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f
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l
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te
r
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s
t
a
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:
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Q
u
a
l
i
t
y
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f
s
e
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v
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c
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&
se
c
u
r
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ty
in
w
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a
n
d
m
o
b
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l
e
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t
w
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r
k
s
,
p
p
.
112
-
1
2
1
,
2
0
0
5
.
[1
1
]
Ya
ss
e
in
M
.
B.
a
n
d
Hijaz
i
N.
,
“
I
m
p
ro
v
e
m
e
n
t
o
n
Cl
u
ste
r
Ba
se
d
R
o
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ti
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g
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r
o
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o
c
o
l
b
y
Us
in
g
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e
Clu
ste
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d
,
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n
:
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AS
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'
1
0
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o
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rt
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ter
n
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ti
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l
Co
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fer
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x
t
Ge
n
e
ra
ti
o
n
M
o
b
il
e
A
p
p
li
c
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ti
o
n
s,
S
e
rv
ice
s
a
n
d
T
e
c
h
n
o
l
o
g
ies
IEE
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Co
m
p
u
ter
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o
c
iety
,
p
p
.
1
3
7
-
1
4
1
,
2
0
1
0
.
[1
2
]
M
.
S
h
a
k
a
ra
m
i
a
n
d
A.
M
o
v
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g
h
a
r,
"
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c
lu
ste
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lg
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h
m
t
o
imp
r
o
v
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ro
u
ti
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g
sta
b
il
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y
in
m
o
b
il
e
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2
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4
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h
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ter
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p
p
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8
3
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0
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/CS
ICC.
2
0
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5
3
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6
0
.
[1
3
]
K.
Na
tara
jan
,
G
.
M
a
h
a
d
e
v
a
n
,
“
Ev
a
lu
a
ti
o
n
o
f
se
v
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n
M
AN
ET
Ro
u
ti
n
g
P
r
o
to
c
o
ls
u
sin
g
S
c
a
lab
il
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y
S
c
e
n
a
rio
,”
In
t
e
rn
a
t
o
n
a
l
J
o
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rn
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l
C
o
mp
u
ter
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c
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e
,
v
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l.
6
,
n
o
.
2
,
p
p
.
1
3
1
-
1
41
,
2
0
1
7
.
[1
4
]
G
y
a
n
a
p
p
a
A.
Wali
k
a
r,
Ra
jas
h
e
k
a
r
C.
B
irad
a
r,
“
A
s
u
rv
e
y
o
n
h
y
b
ri
d
ro
u
ti
n
g
m
e
c
h
a
n
ism
s
in
m
o
b
i
le
a
d
h
o
c
n
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tw
o
rk
s,
”
J
o
u
rn
a
l
o
f
Ne
two
rk
a
n
d
Co
mp
u
te
r
Ap
p
l
ica
ti
o
n
s
,
v
o
l.
77
,
p
p
.
48
-
63
,
2
0
1
7
.
[1
5
]
Qa
y
y
u
m
,
M
.
,
Kh
a
n
,
K.
U.
R.
,
&
Na
z
e
e
r,
M
.
,
“
Clu
ste
r
b
a
se
d
d
a
ta
r
e
p
li
c
a
ti
o
n
tec
h
n
iq
u
e
b
a
se
d
o
n
m
o
b
il
it
y
p
re
d
i
c
ti
o
n
in
m
o
b
il
e
a
d
h
o
c
n
e
two
rk
s
,
”
In
Eme
rg
in
g
ICT
fo
r
Bri
d
g
i
n
g
t
h
e
Fu
t
u
re
-
Pro
c
e
e
d
in
g
s
o
f
th
e
4
9
th
A
n
n
u
a
l
Co
n
v
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n
t
io
n
o
f
th
e
Co
mp
u
ter
S
o
c
iety
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f
I
n
d
ia
,
S
p
rin
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r
,
n
o
.
2
,
p
p
.
3
1
5
-
3
2
8
,
2
0
1
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
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KA
T
elec
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m
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tech
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r
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MANET
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o
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p
r
o
to
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o
ls
(
S
a
lma
S
.
Mo
h
a
med
)
3345
[1
6
]
M
e
h
ta,
S
h
e
e
tal,
P
ri
y
a
n
k
a
S
h
a
rm
a
,
a
n
d
Ke
tan
K
o
tec
h
a
,
“
A su
r
v
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y
o
n
v
a
ri
o
u
s c
l
u
ste
r
h
e
a
d
e
lec
ti
o
n
a
lg
o
rit
h
m
s f
o
r
M
AN
ET
,”
In
Nirm
a
Un
ive
rs
it
y
In
ter
n
a
ti
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a
l
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n
fer
e
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En
g
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rin
g
,
IE
EE
,
p
p
.
1
-
6
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2
0
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1
.
[1
7
]
Be
n
tale
b
,
A
b
d
e
lh
a
k
,
Ab
d
e
l
h
a
k
Bo
u
b
e
tra,
a
n
d
S
a
a
d
Ha
ro
u
s,
“
S
u
rv
e
y
o
f
c
lu
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n
g
sc
h
e
m
e
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in
m
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le
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d
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c
n
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two
rk
s
,”
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o
mm
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n
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ti
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n
s
a
n
d
Ne
two
rk
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v
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l
.
5
,
n
o
.
2
,
p
p
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1
-
8
,
2
0
1
3
.
[1
8
]
Ja
b
b
a
r,
Wah
e
b
A
.
,
M
a
h
a
m
o
d
I
sm
a
il
,
Ro
sd
iad
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e
No
rd
in
,
a
n
d
S
u
k
i
Arif,
“
P
o
we
r
-
e
fficie
n
t
ro
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t
in
g
sc
h
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m
e
s
fo
r
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ET
s: a su
rv
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n
d
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issu
e
s,”
W
ire
les
s Ne
two
rk
s
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v
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l.
23
,
n
o
.
6
,
p
p
.
1
9
1
7
-
1
9
5
2
,
2
0
1
7
.
[1
9
]
Walik
a
r,
G
y
a
n
a
p
p
a
A.,
a
n
d
Ra
j
a
sh
e
k
a
r
C.
Birad
a
r
,
“
A
su
rv
e
y
o
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h
y
b
rid
r
o
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ti
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m
e
c
h
a
n
ism
s
in
m
o
b
i
le
a
d
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o
c
n
e
two
rk
s,”
J
o
u
rn
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l
o
f
Ne
two
rk
a
n
d
Co
m
p
u
ter
A
p
p
li
c
a
ti
o
n
s
,
v
o
l
.
7
7
,
pp.
48
-
63
,
2
0
1
7
.
[2
0
]
Hu
ss
e
in
,
Ab
d
u
l
n
Ra
h
m
a
n
H.
,
Am
e
r
O.
Ab
u
S
a
lem
,
a
n
d
S
u
fian
Y
o
u
se
f,
“
A
flex
ib
le
we
ig
h
ted
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lu
s
terin
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ri
th
m
b
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p
o
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r
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r
m
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b
i
le
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c
n
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tw
o
rk
s,”
I
n
IEE
E
i
n
ter
n
a
ti
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n
a
l
sy
mp
o
si
u
m
o
n
in
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tro
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ics
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p
p
.
2
1
0
2
-
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1
0
7
,
2
0
0
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.
[2
1
]
F
a
th
i,
Afs
a
n
e
h
,
a
n
d
Ha
sa
n
Ta
h
e
ri
,
“
En
h
a
n
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e
to
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o
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y
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o
n
tr
o
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p
ro
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(EC
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e
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b
a
se
d
c
lu
ste
rin
g
in
wire
les
s
a
d
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o
c
n
e
tw
o
rk
s
,”
In
3
rd
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Co
mp
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c
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n
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e
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d
In
f
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T
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y
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v
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l.
9
,
p
p
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3
5
6
-
3
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0
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2
0
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0
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[
2
2
]
K
a
u
r
,
S
a
t
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n
d
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,
R
.
C
.
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a
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s
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n
M
A
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,
"
I
n
I
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,
p
p
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1
4
1
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2
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3
]
S
a
x
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n
a
,
M
a
d
h
v
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,
Ne
e
lam
P
h
a
te,
K.
J.
M
a
th
a
i,
a
n
d
M
.
A.
Riz
v
i
,
“
Clu
ste
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g
b
a
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d
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y
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n
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a
lg
o
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h
m
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si
n
g
max
-
h
e
a
p
tree
fo
r
M
AN
ET
,”
I
n
Fo
u
rth
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
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c
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S
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m
s
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Ne
tw
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rk
T
e
c
h
n
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l
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ies
,
p
p
.
1
2
3
-
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2
7
,
2
0
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