I
nd
o
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s
ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
nd
Co
m
pu
t
er
Science
Vo
l.
3
8
,
No
.
2
,
Ma
y
20
2
5
,
p
p
.
928
~
9
39
I
SS
N:
2
502
-
4
7
52
,
DOI
: 1
0
.
1
1
5
9
1
/ijee
cs
.v
3
8
.
i
2
.
pp
928
-
9
39
928
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l ho
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e
:
h
ttp
:
//ij
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cs
.
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Fuzzy ba
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clus
te
r head
sele
ction w
ith
ba
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nced cluste
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forma
tion in
w
ire
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senso
r net
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rks
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a
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a
nu
m
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ntha
pp
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ha
nd
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,
P
o
o
rnim
a
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o
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a
s
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m
y
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D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
o
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c
s a
n
d
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o
m
mu
n
i
c
a
t
i
o
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En
g
i
n
e
e
r
i
n
g
,
G
o
v
e
r
n
m
e
n
t
En
g
i
n
e
e
r
i
n
g
C
o
l
l
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e
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u
sh
a
l
n
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g
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r
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n
d
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D
e
p
a
r
t
me
n
t
o
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El
e
c
t
r
o
n
i
c
s a
n
d
C
o
m
mu
n
i
c
a
t
i
o
n
En
g
i
n
e
e
r
i
n
g
,
B
M
S
C
o
l
l
e
g
e
o
f
En
g
i
n
e
e
r
i
n
g
,
B
e
n
g
a
l
u
r
u
,
I
n
d
i
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Feb
2
4
,
2
0
2
4
R
ev
is
ed
Oct
2
7
,
2
0
2
4
Acc
ep
ted
No
v
1
1
,
2
0
2
4
Th
e
imp
o
rtan
c
e
o
f
e
n
e
rg
y
c
o
n
se
r
v
a
ti
o
n
p
re
se
n
ts
a
c
o
n
si
d
e
ra
b
le
c
h
a
ll
e
n
g
e
i
n
wire
les
s
se
n
so
r
n
e
two
rk
s
(W
S
Ns
),
wh
e
re
th
e
se
n
so
r
n
o
d
e
s
(
S
Ns
)
th
a
t
c
o
n
stit
u
te
th
e
n
e
two
rk
d
e
p
e
n
d
o
n
b
a
tt
e
ry
p
o
we
r.
Re
c
h
a
rg
i
n
g
th
e
b
a
tt
e
ries
o
f
S
Ns
in
t
h
e
fiel
d
is
c
h
a
ll
e
n
g
in
g
.
Th
e
c
lu
ste
rin
g
tec
h
n
i
q
u
e
is
a
c
o
m
m
o
n
ly
e
m
p
lo
y
e
d
m
e
th
o
d
fo
r
a
tt
a
in
i
n
g
e
n
e
rg
y
e
fficie
n
c
y
.
In
th
is
a
rt
icle
,
we
a
re
p
ro
p
o
sin
g
a
fu
z
z
y
-
b
a
se
d
e
n
e
rg
y
e
fficie
n
t
c
lu
ste
r
h
e
a
d
(CH)
se
lec
ti
o
n
with
t
h
e
b
a
lan
c
e
d
c
lu
ste
r
fo
rm
a
ti
o
n
(F
EE
CH
-
BCF
)
tec
h
n
iq
u
e
.
It
is
a
h
y
b
rid
o
f
t
h
e
k
-
m
e
a
n
s
a
lg
o
r
it
h
m
,
lo
w
e
n
e
rg
y
a
d
a
p
ti
v
e
c
l
u
ste
rin
g
h
iera
rc
h
y
-
u
n
ifo
rm
siz
e
c
lu
ste
r
(LE
ACH
-
USC)
tec
h
n
i
q
u
e
,
a
n
d
f
u
z
z
y
l
o
g
ic
tec
h
n
iq
u
e
.
T
o
c
re
a
te
th
e
c
lu
ste
rs,
th
e
k
-
m
e
a
n
s
a
p
p
r
o
a
c
h
is
e
m
p
lo
y
e
d
.
T
h
e
id
e
a
o
f
LE
ACH
-
U
S
C
is
u
se
d
fo
r
lo
a
d
b
a
la
n
c
in
g
to
p
r
o
d
u
c
e
c
lu
ste
rs
with
u
n
if
o
rm
siz
e
b
y
a
ss
ig
n
i
n
g
m
e
m
b
e
r
n
o
d
e
s
(M
Ns
)
fr
o
m
lar
g
e
r
c
lu
ste
rs
to
sm
a
ll
e
r
c
lu
ste
rs.
O
p
ti
m
ize
d
CHs
a
re
se
lec
ted
u
sin
g
f
u
z
z
y
b
a
se
d
CH
se
lec
ti
o
n
tec
h
n
i
q
u
e
.
T
h
e
k
-
m
e
a
n
s
a
lg
o
rit
h
m
is
sim
p
le
a
n
d
q
u
ick
to
se
t
u
p
,
a
ss
ig
n
in
g
th
e
m
e
m
b
e
rsh
i
p
o
f
S
Ns
to
th
e
n
e
x
t
b
e
st
c
lu
ste
r
b
a
se
d
o
n
c
e
n
tr
o
id
l
o
c
a
ti
o
n
s
o
f
c
lu
ste
rs
re
d
u
c
e
s
in
tra
-
c
lu
st
e
r
d
istan
c
e
a
m
o
n
g
c
lu
ste
rs,
a
n
d
with
th
e
h
e
lp
o
f
f
u
z
z
y
lo
g
ic,
o
p
ti
m
ize
d
CH
s
will
b
e
se
lec
ted
.
Th
e
p
ro
p
o
se
d
a
lg
o
rit
h
m
p
e
rfo
rm
s
e
x
c
e
p
ti
o
n
a
ll
y
we
ll
i
n
a
tt
a
in
in
g
u
n
if
o
rm
e
n
e
rg
y
c
o
n
su
m
p
ti
o
n
a
m
o
n
g
st
c
l
u
ste
rs
a
n
d
e
x
te
n
d
s
t
h
e
n
e
two
rk
’
s
li
fe
ti
m
e
to
a
g
re
a
ter ex
te
n
t.
K
ey
w
o
r
d
s
:
B
alan
ce
d
clu
s
ter
s
C
lu
s
ter
h
ea
d
s
elec
tio
n
E
n
er
g
y
ef
f
icien
cy
Fu
zz
y
lo
g
ic
K
-
m
ea
n
s
alg
o
r
ith
m
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
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
:
Ma
r
u
th
i H
an
u
m
a
n
th
ap
p
a
C
h
an
d
r
ap
p
a
Dep
ar
tm
en
t o
f
E
lectr
o
n
ics an
d
C
o
m
m
u
n
icatio
n
E
n
g
in
ee
r
i
n
g
,
Go
v
er
n
m
e
n
t
E
n
g
in
ee
r
in
g
C
o
lleg
e
Ku
s
h
aln
ag
r
,
5
7
1
2
3
4
I
n
d
ia
E
m
ail:
m
ar
u
th
ib
elag
e
r
e@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
A
wir
eles
s
s
en
s
o
r
n
etwo
r
k
(
W
SN)
co
n
s
i
s
ts
o
f
s
en
s
o
r
n
o
d
es
(
SNs
)
th
at
ar
e
co
m
p
ac
t,
co
s
t
-
ef
f
ec
tiv
e,
s
im
p
le,
an
d
ca
n
b
e
d
ep
lo
y
ed
q
u
ick
ly
[
1
]
,
[
2
]
.
SNs
in
ter
ac
t
with
ea
ch
o
th
er
an
d
p
e
r
ce
iv
e
th
eir
en
v
ir
o
n
m
e
n
t,
en
co
m
p
ass
in
g
f
ac
to
r
s
s
u
ch
as
lig
h
t,
tem
p
er
at
u
r
e,
v
ib
r
at
io
n
,
s
o
u
n
d
,
m
o
tio
n
,
an
d
n
u
m
er
o
u
s
ad
d
itio
n
al
p
ar
am
eter
s
.
E
ac
h
n
o
d
e
f
r
eq
u
e
n
tly
lin
k
s
to
o
th
er
n
o
d
es
in
o
r
d
er
to
e
x
ch
an
g
e
in
f
o
r
m
atio
n
r
eg
ar
d
in
g
p
o
t
e
n
tial
ev
en
ts
th
at
m
ay
tak
e
p
lace
in
a
s
p
ec
if
ic
en
v
ir
o
n
m
en
t.
T
h
e
c
lu
s
ter
in
g
tech
n
iq
u
e
is
wid
ely
u
tili
ze
d
f
o
r
e
n
er
g
y
-
ef
f
icien
t
co
m
m
u
n
icatio
n
b
etw
ee
n
th
e
SNs
an
d
th
e
b
ase
s
tatio
n
(
B
S)
.
T
h
e
BS
ca
n
eith
e
r
b
e
m
o
b
ile
o
r
f
ix
e
d
.
A
clu
s
ter
ed
W
SN
co
m
p
r
is
es
m
u
ltip
le
clu
s
ter
s
,
with
e
ac
h
clu
s
ter
co
n
tain
i
n
g
a
clu
s
ter
h
ea
d
(
C
H)
a
n
d
its
ass
o
ciate
d
m
em
b
er
n
o
d
es
(
M
Ns)
.
SNs
g
ath
er
in
f
o
r
m
atio
n
a
n
d
r
ec
o
r
d
v
alu
es
b
ef
o
r
e
s
en
d
in
g
th
em
to
th
e
B
S
[
3
]
,
[
4
]
.
T
h
e
f
u
n
ctio
n
o
f
C
H
is
to
g
ath
er
d
ata
f
r
o
m
its
MN
s
an
d
tr
an
s
m
it
it
to
th
e
B
S
th
r
o
u
g
h
eith
er
s
in
g
le
-
h
o
p
o
r
m
u
lti
-
h
o
p
d
ata
t
r
an
s
m
is
s
io
n
[
5
]
.
T
h
e
clu
s
ter
in
g
tech
n
iq
u
e
en
h
an
ce
s
n
etwo
r
k
lo
n
g
e
v
ity
b
y
r
e
d
u
cin
g
en
e
r
g
y
u
s
ag
e
an
d
c
o
m
m
u
n
icatio
n
o
v
e
r
h
ea
d
[
6
]
,
[
7
]
.
A
t
y
p
ical
clu
s
ter
ed
W
SN m
o
d
el
is
s
h
o
wn
in
F
ig
u
r
e
1.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
F
u
z
z
y
b
a
s
ed
en
erg
y
efficien
t c
lu
s
ter h
ea
d
s
elec
tio
n
…
(
Ma
r
u
th
i H
a
n
u
ma
n
t
h
a
p
p
a
C
h
a
n
d
r
a
p
p
a
)
929
Fig
u
r
e
1
.
T
y
p
ical
c
lu
s
ter
ed
W
SN m
o
d
el
On
e
o
f
th
e
p
r
o
m
in
en
t p
r
o
to
c
o
l
s
in
th
e
clu
s
ter
in
g
tech
n
iq
u
e,
l
o
w
en
er
g
y
a
d
ap
tiv
e
clu
s
ter
in
g
h
ier
ar
ch
y
(
L
E
AC
H
)
[
8
]
,
co
n
s
id
er
s
SNs
to
b
e
h
o
m
o
g
en
e
o
u
s
an
d
d
is
tr
ib
u
ted
in
th
e
d
ep
lo
y
m
e
n
t
ar
ea
r
an
d
o
m
ly
.
T
h
is
p
r
o
t
o
co
l
h
as
th
r
ee
p
h
ases
p
er
r
o
u
n
d
:
th
e
ad
v
er
tis
em
en
t
p
h
ase,
th
e
s
etu
p
p
h
ase,
an
d
th
e
s
tead
y
s
tate
p
h
ase.
E
v
er
y
r
o
u
n
d
,
SNs
will c
o
m
p
ete
to
b
ec
o
m
e
C
H
u
s
in
g
th
e
th
r
e
s
h
o
ld
f
o
r
m
u
la.
(
)
=
{
1
−
(
1
)
,
∈
0
,
ℎ
(
1
)
W
h
er
e
,
K
Pre
f
er
r
ed
p
er
ce
n
tag
e
o
f
C
Hs
,
r
C
u
r
r
en
t r
o
u
n
d
,
S
Set o
f
n
o
d
es th
at
wer
e
n
o
t CHs
in
r
o
u
n
d
s
1
/K
,
T
r
(
n
)
T
h
r
esh
o
ld
v
alu
e
o
f
n
th
n
o
d
e
.
Usi
n
g
(
1
)
,
ea
ch
SN
ev
alu
ate
s
r
an
d
o
m
n
u
m
b
er
s
th
e
y
g
en
e
r
ate
(
r
an
g
in
g
f
r
o
m
0
to
1
)
a
g
ain
s
t
th
e
estab
lis
h
ed
th
r
esh
o
ld
v
alu
e.
Sh
o
u
ld
th
e
p
r
o
d
u
ce
d
r
a
n
d
o
m
n
u
m
b
er
f
all
b
elo
w
th
e
th
r
esh
o
ld
v
alu
e,
th
e
d
esig
n
ate
d
n
o
d
e
ass
u
m
es
th
e
r
o
le
o
f
C
H
f
o
r
th
at
r
o
u
n
d
,
s
u
b
s
eq
u
en
tly
a
n
n
o
u
n
ci
n
g
its
el
f
as
C
H.
T
h
e
r
em
ain
in
g
SNs
co
n
n
ec
t
to
th
e
ch
o
s
en
C
H
ac
co
r
d
in
g
to
th
e
s
ig
n
al
s
tr
en
g
th
o
f
th
e
ad
v
er
tis
in
g
C
H
th
ey
r
ec
eiv
e.
Du
r
in
g
th
e
s
etu
p
p
h
ase,
MN
s
in
f
o
r
m
th
eir
m
em
b
er
s
h
ip
s
tatu
s
to
th
e
C
H
u
s
in
g
c
ar
r
ier
s
en
s
e
m
u
ltip
le
ac
ce
s
s
/co
llis
io
n
a
v
o
id
a
n
ce
(
C
SMA/
C
A)
.
A
tim
e
d
iv
is
io
n
m
u
ltip
le
ac
ce
s
s
(
T
DM
A)
s
ch
e
d
u
le
is
im
p
le
m
en
ted
,
f
ea
tu
r
i
n
g
a
v
ar
iab
le
n
u
m
b
er
o
f
tim
e
s
lo
ts
th
at
co
r
r
esp
o
n
d
t
o
th
e
n
u
m
b
e
r
o
f
MN
s
in
v
o
lv
e
d
.
Du
r
in
g
th
e
s
tead
y
s
tate
p
h
a
s
e,
MN
s
will
s
leep
u
n
til
th
eir
s
ch
ed
u
led
tim
e
a
n
d
t
r
an
s
m
it
d
u
r
i
n
g
t
h
eir
tim
e
s
lo
t.
C
H
g
ath
er
s
in
f
o
r
m
atio
n
f
r
o
m
MN
s
,
ag
g
r
eg
ates
all
th
e
d
ata
f
r
o
m
its
MN
s
,
an
d
tr
a
n
s
m
its
it
to
th
e
B
S.
C
lu
s
ter
s
c
r
ea
ted
b
y
L
E
AC
H
ar
e
u
n
b
ala
n
ce
d
as
th
e
n
u
m
b
er
o
f
n
o
d
es
p
er
cl
u
s
ter
is
u
n
e
q
u
a
l,
lead
in
g
to
s
m
all
-
s
ized
clu
s
ter
s
h
av
in
g
m
o
r
e
tim
eslo
ts
in
th
e
d
ata
tr
a
n
s
m
is
s
io
n
p
h
ase
an
d
co
n
s
u
m
in
g
m
o
r
e
e
n
er
g
y
co
m
p
ar
ed
to
lar
g
e
-
s
ize
d
clu
s
ter
s
as
th
o
s
e
MN
s
tr
an
s
m
it
th
eir
d
ata
m
o
r
e
o
f
ten
co
m
p
ar
ed
to
lar
g
e
r
clu
s
ter
s
.
T
h
e
b
alan
ce
d
clu
s
ter
s
ize
f
o
r
m
atio
n
(
B
C
F)
ap
p
r
o
ac
h
was
in
tr
o
d
u
ce
d
b
y
Pal
et
a
l.
[
9
]
to
c
r
ea
te
clu
s
ter
s
h
av
in
g
b
ala
n
ce
d
s
ize.
T
h
e
clu
s
ter
g
en
er
atio
n
p
r
o
ce
d
u
r
e
in
B
C
F
is
d
iv
id
ed
in
to
two
s
tep
s
.
T
h
e
r
escu
e
p
h
ase
f
o
llo
ws
th
e
in
itial
cl
u
s
ter
f
o
r
m
atio
n
.
No
d
es
will
jo
in
u
p
wi
th
th
e
n
ea
r
est
C
H
d
u
r
in
g
th
e
i
n
itial
p
h
ase,
r
e
f
er
r
e
d
to
as
in
itial
clu
s
ter
f
o
r
m
atio
n
,
d
eter
m
in
ed
b
y
th
e
s
ig
n
al
in
ten
s
ity
o
f
th
e
ad
v
er
tis
em
en
ts
r
ec
eiv
ed
f
r
o
m
th
e
C
Hs.
,
an
d
ea
ch
cl
u
s
ter
ca
n
h
a
v
e
m
ax
im
u
m
T
h
cluster
MN
s
,
wh
ich
is
g
iv
en
b
y
th
e
(
2
)
:
ℎ
=
(
2
)
N
d
en
o
tes
th
e
to
tal
co
u
n
t
o
f
S
Ns,
wh
ile
X
s
ig
n
if
ies
th
e
n
u
m
b
er
o
f
C
Hs.
T
h
e
Th
cluster
co
n
s
tr
ain
t
m
ay
r
esu
lt
in
a
lim
ited
n
u
m
b
er
o
f
n
o
d
es
r
em
ain
in
g
u
n
clu
s
ter
ed
.
Du
r
in
g
th
e
r
escu
e
p
h
ase,
u
n
clu
s
ter
ed
n
o
d
es
wi
ll
co
n
n
ec
t
t
o
th
e
C
H
th
at
is
with
i
n
a
d
is
tan
ce
eq
u
al
to
o
r
less
th
an
Th
distance
an
d
h
as
a
n
u
m
b
er
o
f
MN
s
f
ewe
r
th
an
Th
cluster
.
Ho
wev
er
,
clu
s
ter
s
f
o
r
m
ed
b
y
th
is
m
eth
o
d
will o
v
er
l
ap
in
n
atu
r
e
an
d
q
u
ick
l
y
d
ep
le
te
en
er
g
y
.
T
o
s
o
lv
e
th
is
is
s
u
e
Sin
g
h
et
a
l
.
[
1
0
]
in
tr
o
d
u
ce
d
t
h
e
lo
w
en
er
g
y
ad
ap
ti
v
e
clu
s
ter
in
g
h
ier
ar
c
h
y
u
n
i
f
o
r
m
s
ize
clu
s
ter
(
L
E
AC
H
-
USC
)
a
p
p
r
o
ac
h
.
T
h
is
ap
p
r
o
ac
h
also
em
p
lo
y
s
th
e
clu
s
ter
f
o
r
m
atio
n
an
d
r
ef
u
r
b
is
h
m
en
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
8
,
No
.
2
,
May
20
2
5
:
9
2
8
-
9
39
930
p
h
ase.
B
y
u
s
in
g
th
e
L
E
AC
H
tech
n
iq
u
e
clu
s
ter
s
ar
e
f
o
r
m
e
d
in
th
e
clu
s
ter
f
o
r
m
atio
n
p
h
ase.
I
n
th
e
r
ef
u
r
b
is
h
in
g
p
h
ase,
clu
s
ter
s
ar
e
ar
r
an
g
ed
in
d
ec
r
ea
s
in
g
o
r
d
er
b
y
co
n
s
id
er
in
g
ea
ch
clu
s
ter
’
s
to
tal
n
u
m
b
er
o
f
MN
s
.
T
h
e
b
ig
g
est
clu
s
ter
is
f
o
u
n
d
f
ir
s
t.
T
h
e
e
x
c
ess
n
o
d
es,
k
=
MN
s
−
T
h
cluster
,
ar
e
ass
ig
n
ed
to
th
e
n
e
x
t
b
est
clu
s
ter
b
ased
o
n
th
e
d
is
tan
ce
f
r
o
m
SNs
to
o
th
er
C
Hs
p
r
o
v
id
ed
k
<
0
f
o
r
t
h
e
n
ex
t
b
est
C
H.
Un
if
o
r
m
-
s
ize
d
clu
s
ter
s
d
ec
r
e
ase
in
tr
a
-
clu
s
ter
d
is
tan
ce
wh
ile
en
ab
lin
g
ef
f
ec
tiv
e
d
ata
f
lo
w
o
n
t
h
e
n
etwo
r
k
.
C
r
ea
tin
g
u
n
if
o
r
m
clu
s
ter
s
b
ased
o
n
C
H
lo
ca
tio
n
af
ter
ea
ch
r
o
u
n
d
in
cr
ea
s
es
th
e
c
o
m
p
u
tatio
n
co
m
p
lex
ity
a
n
d
r
ec
l
u
s
ter
in
g
t
h
e
n
etwo
r
k
in
cr
ea
s
es
en
er
g
y
co
n
s
u
m
p
tio
n
.
I
n
o
u
r
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
,
we
h
av
e
u
s
ed
th
e
k
-
m
ea
n
s
alg
o
r
ith
m
t
o
cr
ea
te
in
itial
clu
s
ter
s
.
T
h
e
l
ar
g
est
clu
s
ter
is
id
en
tifie
d
am
o
n
g
all.
B
ased
o
n
Th
cluster
,
th
e
ex
ce
s
s
n
u
m
b
er
s
o
f
MN
s
f
r
o
m
th
at
clu
s
ter
ar
e
as
s
ig
n
ed
to
th
e
n
ex
t b
est clu
s
ter
.
T
h
e
ce
n
tr
o
id
o
f
th
e
clu
s
ter
is
u
s
ed
in
s
tead
o
f
C
H
f
o
r
ass
ig
n
in
g
m
em
b
e
r
s
h
ip
to
t
h
e
n
ex
t
b
est
clu
s
ter
.
T
h
e
cr
ea
ted
cl
u
s
ter
will
b
e
u
n
to
u
c
h
ed
f
u
r
th
er
.
Am
o
n
g
th
e
r
est
o
f
th
e
cl
u
s
ter
s
,
th
e
lar
g
es
t
clu
s
ter
is
id
en
tifie
d
ag
ain
an
d
th
e
s
am
e
p
r
o
ce
s
s
co
n
tin
u
es
u
n
til
all
th
e
clu
s
ter
s
h
av
e
an
e
q
u
al
n
u
m
b
e
r
o
f
M
Ns.
On
ce
th
e
u
n
i
f
o
r
m
-
s
ized
c
lu
s
ter
s
ar
e
cr
ea
ted
,
n
o
f
u
r
th
er
r
ec
lu
s
ter
in
g
is
r
eq
u
ir
ed
.
Am
o
n
g
MN
s
in
ea
ch
clu
s
ter
,
C
H
will
b
e
ch
o
s
en
u
s
in
g
f
u
zz
y
l
o
g
ic.
Netwo
r
k
lo
n
g
e
v
ity
is
in
cr
ea
s
ed
b
y
an
e
f
f
ec
tiv
e
C
H
s
elec
tio
n
m
eth
o
d
[
1
1
]
.
T
h
e
attr
ib
u
tes u
s
ed
f
o
r
th
is
p
u
r
p
o
s
e
ar
e
th
e
n
o
d
e
’
s
r
em
ain
i
n
g
en
e
r
g
y
an
d
n
o
d
e
ce
n
tr
ality
.
T
h
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
d
em
o
n
s
tr
ates
im
p
r
o
v
e
d
u
n
if
o
r
m
-
s
ized
clu
s
ter
s
,
wh
ich
lead
s
to
a
r
ed
u
ctio
n
in
i
n
tr
a
-
clu
s
ter
c
o
m
m
u
n
icatio
n
d
is
tan
ce
an
d
a
n
ex
ten
d
e
d
n
etwo
r
k
life
tim
e
wh
en
co
m
p
ar
ed
to
L
E
AC
H,
B
C
F,
an
d
L
E
A
C
H
-
USC
.
T
h
e
s
u
b
s
eq
u
en
t
s
ec
tio
n
s
o
f
th
e
ar
ticle
ar
e
s
tr
u
ctu
r
ed
as
f
o
llo
ws:
s
ec
tio
n
2
p
r
esen
ts
th
e
p
r
o
b
lem
s
tatem
en
t,
s
ec
tio
n
3
r
ev
iews
r
elat
ed
wo
r
k
s
,
s
ec
tio
n
4
o
u
tlin
es
th
e
p
r
o
p
o
s
ed
ap
p
r
o
a
ch
,
an
d
s
ec
tio
n
5
ad
d
r
ess
es
r
esu
lts
an
d
d
is
cu
s
s
io
n
.
I
n
s
ec
tio
n
6
p
r
o
v
id
es
th
e
co
n
clu
s
io
n
o
f
th
is
ar
ticle.
2.
P
RO
B
L
E
M
ST
A
T
E
M
E
NT
E
n
er
g
y
ef
f
icie
n
cy
is
cr
u
cial
wh
ile
d
esig
n
in
g
th
e
W
SN.
T
h
e
clu
s
ter
in
g
tech
n
i
q
u
e
ca
n
in
cr
ea
s
e
th
e
en
er
g
y
e
f
f
icien
cy
.
Ho
we
v
er
,
cr
ea
tin
g
ef
f
icien
t
clu
s
ter
s
an
d
s
elec
tin
g
o
p
tim
al
C
Hs
ar
e
th
e
k
ey
co
n
c
er
n
s
.
T
h
e
is
s
u
e
ass
o
ciate
d
with
th
e
o
v
er
lap
p
i
n
g
o
f
clu
s
ter
s
as
in
B
C
F
is
ad
d
r
ess
ed
in
L
E
AC
H
-
U
SC
.
T
h
e
clu
s
ter
s
ar
e
f
o
r
m
ed
b
ased
o
n
th
e
C
H.
Ho
wev
er
,
clu
s
ter
f
o
r
m
atio
n
is
in
ef
f
ec
tiv
e,
as
C
Hs
ar
e
s
elec
ted
b
as
ed
o
n
th
e
p
r
o
b
a
b
ilit
y
v
alu
e
as
u
s
ed
in
t
h
e
L
E
AC
H
p
r
o
to
co
l.
Fu
r
th
e
r
,
b
ased
o
n
t
h
e
in
itial
clu
s
ter
s
ize,
if
k
<=
0
f
o
r
th
e
p
ar
ticu
lar
clu
s
ter
,
th
e
MN
s
alr
ea
d
y
ass
ig
n
ed
to
th
at
co
r
r
esp
o
n
d
in
g
C
H
will
b
e
u
n
to
u
ch
e
d
.
Ho
wev
er
,
t
h
e
d
i
s
tan
ce
b
etwe
en
th
e
MN
s
an
d
C
H
is
n
o
t
co
n
s
id
e
r
ed
.
Kee
p
in
g
th
o
s
e
MN
s
u
n
t
o
u
ch
ed
an
d
o
n
ly
th
e
r
e
q
u
ir
e
d
n
u
m
b
er
o
f
MN
s
(
i.e
.
,
m
=
T
h
cluster
-
MN
s
)
to
th
at
clu
s
ter
will b
e
g
iv
en
m
em
b
er
s
h
ip
f
r
o
m
o
th
e
r
clu
s
ter
s
.
I
t
will lea
d
to
in
cr
ea
s
ed
in
tr
a
-
clu
s
ter
d
is
tan
ce
.
T
h
e
co
n
v
en
tio
n
al
L
E
AC
H
tech
n
iq
u
e
s
elec
ts
C
H
in
ea
ch
r
o
u
n
d
,
wh
ic
h
will
n
o
t
g
u
ar
an
tee
h
ig
h
er
en
er
g
y
ef
f
icien
c
y
.
T
h
e
f
r
eq
u
en
c
y
with
wh
ich
t
h
e
s
am
e
n
o
d
e
s
b
ec
o
m
e
C
H
ag
ain
m
ig
h
t
af
f
ec
t
th
e
n
etwo
r
k
’
s
lo
n
g
e
v
ity
as
C
H
s
a
r
e
p
ick
ed
r
an
d
o
m
ly
.
Als
o
,
r
ec
lu
s
ter
in
g
is
d
o
n
e
af
ter
ea
ch
r
o
u
n
d
an
d
co
n
s
u
m
es
s
ig
n
if
ican
t
en
er
g
y
.
T
o
r
eso
lv
e
th
ese
is
s
u
es,
f
u
zz
y
-
b
ased
en
er
g
y
ef
f
icien
t
C
H
s
elec
tio
n
with
th
e
b
alan
ce
d
clu
s
ter
f
o
r
m
atio
n
FEE
C
H
-
B
C
F,
wh
ich
ac
h
iev
es
b
alan
ce
d
clu
s
ter
s
,
r
ed
u
ce
d
i
n
tr
a
-
clu
s
ter
co
m
m
u
n
icatio
n
d
is
tan
ce
,
an
d
ef
f
icien
t CH selectio
n
,
is
p
r
o
p
o
s
ed
in
th
is
wo
r
k
.
3.
RE
L
AT
E
D
WO
RK
E
ac
h
n
o
d
e
g
at
h
er
s
d
ata
f
r
o
m
th
e
en
v
ir
o
n
m
e
n
t
an
d
tr
an
s
m
i
ts
it
to
its
C
H
in
th
e
L
E
A
C
H
p
r
o
to
co
l.
Data
is
co
m
p
r
ess
ed
b
ef
o
r
e
b
ei
n
g
s
en
t
to
th
e
s
in
k
.
R
ed
u
ce
d
c
o
m
m
u
n
icatio
n
p
ac
k
ets
ar
e
s
en
t,
an
d
th
e
life
s
p
an
o
f
W
SN
s
is
ex
ten
d
ed
[
1
2
]
.
Ne
v
er
th
eless
,
it
p
r
esen
ts
s
ev
er
al
lim
itatio
n
s
,
s
u
ch
as
th
e
ar
b
itra
r
y
s
elec
tio
n
o
f
CH
s
an
d
th
e
n
ec
ess
ity
o
f
f
o
r
m
in
g
cl
u
s
ter
s
in
ea
ch
iter
atio
n
.
W
ib
o
wo
et
a
l.
[
1
3
]
e
x
p
lo
r
es
h
o
w
th
e
m
ac
h
in
e
lear
n
in
g
(
ML
)
m
eth
o
d
s
em
p
lo
y
ed
in
W
SN
s
af
f
ec
t
en
er
g
y
e
f
f
icien
cy
b
y
c
o
m
p
a
r
in
g
th
em
to
th
e
L
E
AC
H
p
r
o
t
o
co
l
an
d
p
r
o
p
o
s
in
g
clu
s
ter
-
b
ased
r
o
u
tin
g
al
g
o
r
ith
m
s
th
at
tak
e
ad
v
an
tag
e
o
f
t
h
e
k
-
m
ea
n
s
an
d
t
h
e
o
p
tim
al
v
alu
e
f
o
r
clu
s
ter
in
g
.
T
h
is
s
o
lu
tio
n
r
e
d
u
ce
s
en
er
g
y
u
s
ag
e,
r
esu
ltin
g
in
a
b
ala
n
ce
b
etwe
en
th
e
en
er
g
y
co
n
s
u
m
p
tio
n
o
f
th
e
C
Hs.
Pu
r
i
an
d
B
h
u
s
h
an
[
1
4
]
in
clu
d
e
d
th
e
k
-
m
ea
n
s
clu
s
ter
in
g
ap
p
r
o
ac
h
in
th
ei
r
m
eth
o
d
u
s
ed
in
u
n
s
u
p
er
v
is
ed
ML
u
n
d
er
clu
s
ter
in
g
s
in
ce
it
is
b
en
ef
icial
in
p
r
o
lo
n
g
in
g
th
e
n
etwo
r
k
’
s
life
.
I
n
th
is
p
r
o
ce
d
u
r
e
,
K
p
o
in
ts
o
r
m
ea
n
s
ar
e
in
itially
ass
ig
n
ed
at
r
an
d
o
m
,
an
d
th
e
n
ea
ch
item
is
class
if
ied
u
s
in
g
th
e
m
ea
n
th
at
is
clo
s
est
to
it.
T
h
e
av
er
ag
es
o
f
th
e
elem
en
ts
f
o
r
m
er
ly
d
esig
n
ated
as
th
e
m
ea
n
ar
e
u
p
d
ated
af
ter
th
e
m
ea
n
’
s
p
lace
m
en
ts
h
av
e
b
ee
n
m
o
d
i
f
ied
.
T
h
e
p
r
o
ce
s
s
is
co
n
tin
u
ed
u
n
ti
l
n
o
n
ew
m
o
d
if
icatio
n
s
to
th
e
p
r
o
ce
d
u
r
es
ar
e
f
o
u
n
d
.
T
h
is
ap
p
r
o
ac
h
is
ca
lled
iter
ativ
e
r
ef
in
in
g
.
A
n
o
v
el
co
n
ce
p
t
f
o
r
W
SNs
th
at
in
teg
r
ates
an
t
co
lo
n
y
o
p
tim
iz
atio
n
with
k
-
m
ea
n
s
clu
s
ter
in
g
f
o
r
en
er
g
y
-
ef
f
icien
t
r
o
u
tin
g
is
s
h
o
wn
in
[
1
5
]
.
T
h
e
f
in
d
in
g
s
in
d
icate
th
at
th
e
m
eth
o
d
(
AOC
+
k
-
m
ea
n
s
)
s
u
r
p
ass
es
th
e
m
o
s
t
p
r
ev
alen
t
p
o
wer
-
awa
r
e
p
r
o
to
c
o
ls
.
Fu
zz
y
lo
g
ic
is
f
r
e
q
u
en
tly
em
p
lo
y
ed
in
clu
s
ter
in
g
al
g
o
r
it
h
m
s
b
ec
au
s
e
to
its
r
elativ
ely
lo
wer
co
m
p
u
tatio
n
a
l e
x
p
en
s
e,
r
ed
u
ce
d
p
r
o
ce
s
s
in
g
d
em
an
d
s
,
ef
f
icien
t im
p
lem
e
n
t
atio
n
,
an
d
ex
ten
d
ed
n
etwo
r
k
lo
n
g
ev
ity
[
1
6
]
–
[
1
8
]
.
T
h
e
o
v
er
h
e
ad
lin
k
ed
to
s
elec
tin
g
CH
is
d
im
in
is
h
ed
b
y
th
e
ap
p
licatio
n
o
f
f
u
zz
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
F
u
z
z
y
b
a
s
ed
en
erg
y
efficien
t c
lu
s
ter h
ea
d
s
elec
tio
n
…
(
Ma
r
u
th
i H
a
n
u
ma
n
t
h
a
p
p
a
C
h
a
n
d
r
a
p
p
a
)
931
lo
g
ic
-
b
ased
clu
s
ter
in
g
tech
n
i
q
u
es.
E
x
am
p
les
o
f
f
u
zz
y
lo
g
ic
-
b
ased
alg
o
r
ith
m
s
in
clu
d
e
th
e
f
u
zz
y
lo
g
ic
-
b
ased
clu
s
ter
in
g
p
r
o
to
c
o
l
f
o
r
u
n
if
o
r
m
s
ize
clu
s
ter
f
o
r
m
atio
n
(
FUS
A)
[
1
9
]
,
CH
elec
tio
n
with
f
u
zz
y
lo
g
ic
(
C
HE
F)
[
2
0
]
,
FLE
C
H
[
2
1
]
,
en
er
g
y
awa
r
e
u
n
eq
u
al
clu
s
ter
in
g
with
f
u
zz
y
lo
g
ic
(
E
AUCF
)
[
2
2
]
,
an
d
en
er
g
y
ef
f
icien
t
alg
o
r
ith
m
-
f
u
zz
y
C
-
m
ea
n
s
(EEA
-
FC
M)
[
2
3
]
.
No
tab
ly
,
th
ese
f
u
zz
y
lo
g
ic
-
b
ased
clu
s
ter
in
g
m
eth
o
d
s
ex
t
en
d
th
e
lo
n
g
ev
ity
o
f
n
etwo
r
k
s
.
4.
P
RO
P
O
SE
D
WO
RK
T
h
e
p
r
o
p
o
s
ed
FEE
C
H
-
B
C
F a
p
p
r
o
ac
h
h
as th
e
f
o
llo
win
g
o
b
j
ec
tiv
es:
−
Gen
er
ate
clu
s
ter
s
o
f
u
n
i
f
o
r
m
s
ize.
−
R
ed
u
ce
in
tr
a
-
clu
s
ter
d
is
tan
ce
.
−
E
m
p
lo
y
a
n
ef
f
icien
t CH selectio
n
m
eth
o
d
.
−
I
n
cr
ea
s
e
n
etwo
r
k
life
tim
e.
E
u
clid
ian
d
is
tan
ce
is
u
s
ed
in
th
e
k
-
m
ea
n
s
alg
o
r
ith
m
to
f
o
r
m
t
h
e
clu
s
ter
s
.
C
en
tr
o
id
s
ar
e
in
itially
s
elec
ted
r
an
d
o
m
l
y
with
in
th
e
n
etwo
r
k
.
No
d
e
I
D,
its
r
e
m
ain
in
g
en
er
g
y
,
a
n
d
lo
ca
tio
n
ar
e
co
llected
[
2
4
]
.
T
h
e
ce
n
tr
o
id
clo
s
est
to
th
e
n
o
d
e
s
h
o
u
ld
b
e
ch
o
s
en
af
ter
ca
lcu
latin
g
th
e
E
u
clid
ian
d
is
tan
ce
b
etwe
en
e
ac
h
n
o
d
e
a
n
d
ea
c
h
ce
n
tr
o
id
a
n
d
u
p
d
atin
g
th
e
lo
c
atio
n
o
f
th
e
ce
n
tr
o
id
till
th
e
o
p
tim
al
lo
ca
tio
n
is
f
o
u
n
d
.
Ho
wev
er
,
th
e
cl
u
s
ter
s
cr
ea
ted
will b
e
o
f
n
o
n
-
u
n
if
o
r
m
s
izes in
itially
.
W
e
ar
e
in
s
p
ir
ed
b
y
L
E
AC
H
-
USC
to
ass
ig
n
ex
ce
s
s
MN
s
f
r
o
m
a
lar
g
e
r
clu
s
ter
to
a
s
m
aller
clu
s
ter
b
y
co
n
s
id
er
in
g
th
e
d
is
tan
ce
b
etwe
en
th
e
n
ex
t
b
est
ce
n
tr
o
id
s
an
d
ex
ce
s
s
SNs
o
f
t
h
e
lar
g
er
clu
s
ter
.
T
o
d
eter
m
i
n
e
th
e
Th
cluster
,
we
ca
lcu
lated
th
e
to
tal
n
u
m
b
er
o
f
SNs
with
in
th
e
d
ep
lo
y
m
e
n
t
ar
ea
an
d
d
iv
id
e
d
it
b
y
th
e
r
eq
u
ir
e
d
clu
s
ter
s
.
T
wo
ca
s
es
ex
is
t.
I
n
th
e
f
ir
s
t
s
ce
n
ar
io
,
wh
e
n
th
e
r
e
m
ain
d
er
is
ze
r
o
,
it
in
d
icate
s
t
h
at
ea
ch
clu
s
ter
will
co
n
tain
an
id
en
tical
n
u
m
b
er
o
f
MN
s
.
I
n
c
ase
2
,
wh
e
n
th
e
r
em
ain
d
er
is
n
o
n
-
ze
r
o
,
it c
an
b
e
o
b
s
er
v
ed
th
at
all
b
u
t
o
n
e
clu
s
ter
will
co
n
tain
a
n
eq
u
al
n
u
m
b
er
o
f
MN
s
.
Fo
r
ex
am
p
l
e,
if
th
e
to
tal
n
u
m
b
e
r
o
f
SNs
is
5
0
an
d
th
e
r
e
q
u
ir
e
d
clu
s
ter
s
ar
e
3
,
th
en
two
clu
s
ter
s
will h
av
e
1
7
MN
s
,
an
d
o
n
e
clu
s
ter
h
av
e
1
6
MN
s
.
T
h
e
r
em
a
in
d
er
was r
o
u
n
d
ed
o
f
f
b
y
c
o
n
s
id
er
in
g
th
e
d
ig
it
in
t
h
e
ten
th
s
p
lace
;
if
it
is
les
s
th
an
5
,
b
o
t
h
th
e
ten
th
s
p
lace
an
d
th
e
s
u
b
s
eq
u
en
t
p
lace
ar
e
s
et
to
0
.
W
h
en
th
e
d
ig
it
in
th
e
ten
th
s
p
lace
is
5
o
r
h
ig
h
er
,
th
e
d
ig
it
in
th
e
o
n
es
p
lace
is
in
cr
em
en
ted
b
y
1
,
an
d
all
s
u
b
s
eq
u
en
t
d
ig
its
a
f
ter
th
e
d
ec
im
al
p
o
i
n
t
ar
e
s
et
to
0
.
MN
s
o
f
s
m
aller
cl
u
s
ter
s
will
also
b
e
co
n
s
id
er
e
d
to
b
e
ass
ig
n
ed
to
th
e
n
ex
t
b
est
cl
u
s
ter
wh
ile
cr
ea
tin
g
b
alan
ce
d
clu
s
ter
s
.
B
alan
ce
d
clu
s
ter
s
cr
ea
ted
b
y
th
is
m
eth
o
d
r
em
ain
th
e
s
am
e
u
n
til
th
e
e
n
d
o
f
t
h
e
n
etwo
r
k
life
tim
e,
i.e
.
,
th
er
e
will
b
e
n
o
r
ec
l
u
s
ter
in
g
.
Af
ter
m
ak
i
n
g
th
e
u
n
if
o
r
m
-
s
ized
clu
s
ter
s
,
C
Hs
w
ill
b
e
ch
o
s
en
u
s
in
g
th
e
f
u
zz
y
l
o
g
ic
ap
p
r
o
ac
h
u
s
in
g
r
esid
u
al
e
n
er
g
y
a
n
d
ce
n
tr
ality
p
ar
am
eter
s
.
4
.
1
.
Net
w
o
rk
c
o
n
f
ig
ura
t
io
n
C
o
n
s
id
er
a
W
SN
in
clu
d
in
g
‘
N
’
SNs
p
lace
d
with
in
a
M×
M
m
2
ar
ea
.
T
h
ese
SN
s
d
etec
t
th
e
en
v
ir
o
n
m
en
tal
p
h
y
s
ical
f
ac
to
r
s
.
T
h
e
n
etwo
r
k
m
o
d
el
a
n
d
its
ass
u
m
p
tio
n
s
ar
e
o
u
tlin
ed
as
f
o
llo
ws:
No
d
es
ar
e
u
n
if
o
r
m
,
s
tatic,
a
n
d
o
b
liv
io
u
s
t
o
th
eir
p
o
s
itio
n
.
E
v
er
y
SN
p
o
s
s
ess
es
a
s
leep
m
o
d
e.
No
d
es
ca
n
m
o
d
if
y
th
eir
s
ig
n
al
p
o
wer
b
ased
o
n
f
r
ee
s
p
ac
e
o
r
m
u
ltip
ath
p
r
o
p
ag
atio
n
co
n
d
itio
n
s
.
4
.
2
.
E
nerg
y
m
o
del
T
h
e
f
ir
s
t
-
o
r
d
er
r
a
d
io
m
o
d
el
ca
lcu
lates
th
e
n
ec
ess
ar
y
en
er
g
y
f
o
r
ex
ec
u
tin
g
v
ar
io
u
s
o
p
er
atio
n
s
.
T
h
is
m
o
d
el
p
o
s
its
th
at
th
e
en
er
g
y
ex
p
en
d
e
d
in
d
ata
tr
an
s
m
is
s
io
n
co
n
s
is
t
s
o
f
two
co
m
p
o
n
en
ts
:
en
er
g
y
lo
s
t
in
o
p
er
atin
g
elec
tr
o
n
ic
cir
cu
itry
an
d
en
er
g
y
u
tili
ze
d
in
s
ig
n
al
am
p
lific
atio
n
.
Fig
u
r
e
2
s
h
o
ws
an
en
er
g
y
m
o
d
el.
T
h
e
en
er
g
y
ex
p
en
d
e
d
in
tr
a
n
s
m
itti
n
g
a
l
-
b
it m
ess
ag
e
ac
r
o
s
s
a
d
is
tan
ce
d
is
r
ep
r
esen
ted
b
y
(
3
)
.
=
{
.
+
.
∊
.
2
<
.
+
.
∊
.
4
≥
(
3
)
T
h
e
elec
tr
o
n
ic
en
er
g
y
E
elec
t
r
ep
r
esen
ts
th
e
en
er
g
y
d
is
s
ip
atio
n
p
er
b
it
o
f
th
e
tr
a
n
s
m
itter
o
r
r
ec
eiv
er
cir
cu
itry
,
wh
ile
ε
fs
an
d
ε
mp
d
e
n
o
te
th
e
am
p
lifie
r
m
o
d
els.
Her
e
,
d
s
ig
n
if
ies
th
e
d
is
tan
ce
b
etw
ee
n
th
e
tr
a
n
s
m
itter
an
d
r
ec
ei
v
er
,
a
n
d
d
co
is
th
e
r
e
f
er
en
ce
d
is
tan
ce
v
alu
e.
I
f
d
is
less
th
an
d
co
,
t
h
e
f
r
ee
-
s
p
ac
e
m
o
d
el
is
em
p
l
o
y
ed
.
I
f
d
≥
d
co
,
a
m
u
ltip
ath
p
r
o
p
ag
atio
n
m
o
d
el
is
em
p
lo
y
ed
.
I
n
f
r
ee
s
p
ac
e,
en
er
g
y
d
im
in
is
h
es
in
v
er
s
ely
with
th
e
s
q
u
ar
e
o
f
t
h
e
d
is
tan
ce
.
I
n
th
e
ε
mp
m
o
d
el,
en
e
r
g
y
d
im
in
is
h
es in
v
er
s
ely
to
th
e
d
4
.
T
o
r
ec
eiv
e
th
e
d
ata,
th
e
e
n
er
g
y
r
eq
u
i
r
ed
is
(
4
)
.
(
)
=
.
(
4
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
8
,
No
.
2
,
May
20
2
5
:
9
2
8
-
9
39
932
Fig
u
r
e
2
.
E
n
er
g
y
m
o
d
el
o
f
W
SN
4
.
3
.
K
-
m
e
a
ns
clus
t
er
ing
T
h
e
FEE
C
H
-
B
C
F a
p
p
r
o
ac
h
g
en
er
ates c
lu
s
ter
s
v
ia
th
e
k
-
m
ea
n
s
alg
o
r
ith
m
[
2
5
]
as o
u
tlin
ed
b
elo
w.
a.
T
o
cr
ea
te
‘
k
’
clu
s
ter
s
,
in
itially
p
o
s
itio
n
‘
k
’
ce
n
tr
o
id
s
at
ar
b
itr
ar
y
p
lace
s
.
b.
T
h
e
ce
n
tr
o
id
n
ea
r
est
to
th
e
n
o
d
e
s
h
o
u
ld
b
e
s
elec
ted
af
te
r
co
m
p
u
tin
g
th
e
E
u
clid
ea
n
d
is
tan
ce
b
etwe
en
ea
ch
n
o
d
e
an
d
ea
ch
ce
n
tr
o
id
.
I
n
itial c
lu
s
ter
s
ar
e
g
en
er
ated
b
y
t
h
is
‘
k.
’
Ass
u
m
e
th
at
‘
n
’
n
o
d
es a
r
e
p
r
o
v
id
e
d
,
ea
ch
o
f
wh
ich
b
elo
n
g
s
to
R
d
.
T
h
e
c
h
allen
g
e
o
f
d
eter
m
in
in
g
th
e
m
in
im
u
m
v
ar
ian
ce
cl
u
s
ter
in
g
o
f
th
ese
n
o
d
es
in
to
‘
k
’
clu
s
ter
s
in
v
o
l
v
es id
en
tify
in
g
th
e
‘
k
’
ce
n
tr
o
id
s
m
j
k
=
1
i
n
R
d
s
u
ch
th
at
,
1
∑
(
2
(
,
)
)
=
1
(
5
)
w
h
er
e
d
2
(X
i
,
m
j
)
d
en
o
tes
th
e
E
u
clid
ea
n
d
is
tan
ce
b
etwe
en
X
i
an
d
m
j
.
T
h
e
p
o
in
ts
j
k
i
=
1
ar
e
k
n
o
wn
as
clu
s
ter
ce
n
tr
o
id
s
o
r
as c
lu
s
ter
m
ea
n
s
.
c.
R
ec
o
m
p
u
te
th
e
lo
ca
tio
n
o
f
ea
ch
clu
s
ter
’
s
ce
n
tr
o
id
s
an
d
id
en
tify
an
y
p
o
s
itio
n
al
alter
atio
n
s
f
r
o
m
th
e
p
r
io
r
iter
atio
n
.
d.
Pro
ce
ed
to
STE
P
2
if
an
y
ce
n
tr
o
id
p
o
s
itio
n
s
ch
an
g
e;
o
th
er
wis
e,
th
e
clu
s
ter
s
ar
e
f
in
alize
d
,
an
d
th
e
clu
s
ter
in
g
p
r
o
ce
d
u
r
e
is
co
m
p
leted
.
4
.
4
.
L
o
a
d ba
la
ncing
T
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
is
in
s
p
ir
ed
b
y
th
e
L
E
AC
H
-
US
C
lo
ad
-
b
alan
cin
g
tech
n
iq
u
e.
K
-
m
ea
n
s
clu
s
ter
in
g
o
u
tp
u
ts
MN
s
an
d
c
en
tr
o
id
s
o
f
ea
ch
clu
s
ter
.
T
h
e
p
r
o
p
o
s
ed
FEE
C
H
-
B
C
F
in
co
r
p
o
r
ates
a
m
o
d
if
ie
d
r
ef
u
r
b
is
h
m
e
n
t
p
h
ase
as
s
p
ec
if
i
ed
in
th
e
f
o
llo
win
g
s
tep
s
,
co
n
tin
g
en
t
u
p
o
n
th
e
to
tal
n
u
m
b
e
r
o
f
SNs
b
ein
g
wh
o
lly
d
iv
is
ib
le
b
y
th
e
e
n
tire
n
u
m
b
er
o
f
ce
n
tr
o
id
s
.
a.
B
ased
o
n
th
e
MN
s
in
th
e
clu
s
ter
,
th
e
clu
s
ter
s
ar
e
s
o
r
ted
i
n
d
e
s
ce
n
d
in
g
o
r
d
er
.
b.
T
h
e
lar
g
est clu
s
ter
,
wh
ich
h
as th
e
h
ig
h
est n
u
m
b
er
o
f
MN
s
is
id
en
tifie
d
.
c.
E
x
ce
s
s
n
o
d
es in
th
e
lar
g
est clu
s
ter
k
=
MN
s
-
Th
cluster
is
ca
lcu
lated
.
d.
T
h
e
d
is
tan
ce
b
etwe
en
e
x
ce
s
s
n
o
d
es a
n
d
o
th
er
ce
n
tr
o
id
s
is
ca
lcu
lated
.
e.
C
lu
s
ter
ce
n
tr
o
id
,
n
ea
r
est to
th
e
lar
g
est clu
s
ter
’
s
ex
ce
s
s
MN
s
,
is
id
en
tifie
d
.
f.
Ass
ig
n
ex
ce
s
s
n
o
d
es to
th
e
n
e
ar
est ce
n
tr
o
id
clu
s
ter
.
g.
No
d
es
f
r
o
m
wh
ich
n
o
d
es
ar
e
a
s
s
ig
n
ed
to
th
e
n
ex
t
b
est
clu
s
te
r
s
wh
o
s
e
‘
k
’
is
n
o
w
ze
r
o
will
b
e
ex
clu
d
ed
f
o
r
f
u
r
th
er
l
o
ad
b
ala
n
cin
g
.
h.
Go
to
s
tep
2
u
n
til all
clu
s
ter
s
h
av
e
an
eq
u
al
n
u
m
b
er
o
f
MN
s
.
T
h
e
co
n
ce
p
t
is
e
x
p
lain
ed
b
y
co
n
s
id
er
in
g
1
0
0
SNs
th
at
a
r
e
d
ep
l
o
y
ed
in
th
e
d
ep
lo
y
m
e
n
t
ar
ea
o
f
1
0
0
×
1
0
0
m
2
,
an
d
1
0
clu
s
ter
s
ar
e
f
o
r
m
e
d
.
Fig
u
r
e
3
s
h
o
ws
h
o
w
th
e
g
eo
g
r
ap
h
ically
d
is
tr
ib
u
t
ed
SNs
ar
e
ass
ig
n
ed
as
MN
s
to
clu
s
ter
s
.
Fig
u
r
e
s
3
(
a
)
a
n
d
3
(
b
)
s
h
o
w
th
e
g
e
o
g
r
ap
h
ical
d
is
tr
ib
u
tio
n
o
f
SNs
an
d
th
e
p
r
o
b
ab
ilit
y
d
is
tr
ib
u
tio
n
o
f
MN
s
in
ea
c
h
clu
s
ter
a
f
ter
k
-
m
ea
n
s
clu
s
ter
in
g
.
Fig
u
r
e
3
(
c
)
s
h
o
ws
th
at
clu
s
ter
s
ar
e
ar
r
an
g
e
d
in
d
escen
d
in
g
o
r
d
e
r
.
Fig
u
r
e
4
s
h
o
ws
h
o
w
MN
s
ar
e
eq
u
ally
ass
ig
n
ed
to
ea
c
h
clu
s
ter
.
MN
s
o
f
lar
g
er
c
lu
s
ter
s
tak
e
m
em
b
er
s
h
ip
in
th
e
n
ex
t
b
est
clu
s
t
er
s
b
ased
o
n
th
e
d
is
tan
ce
b
etwe
en
th
e
MN
s
an
d
t
h
e
ce
n
tr
o
id
.
Hen
ce
f
o
r
m
ed
clu
s
ter
s
a
r
e
well
-
b
alan
ce
d
an
d
h
av
e
cr
is
p
b
o
u
n
d
a
r
ies,
as
s
h
o
wn
in
Fig
u
r
e
s
4
(
a)
an
d
4
(
b
)
.
4
.
5
.
F
uzzy
lo
g
ic
-
ba
s
ed
clus
t
er
hea
d select
io
n
Key
co
m
p
o
n
en
ts
o
f
a
f
u
zz
y
lo
g
ic
s
y
s
tem
ar
e
th
e
f
u
zz
i
f
ier
,
in
f
er
e
n
ce
en
g
i
n
e,
r
u
le
b
ase,
an
d
d
ef
u
zz
if
ier
.
T
h
e
f
u
zz
y
if
ier
is
u
s
ed
to
co
n
v
e
r
ts
d
is
cr
ete
d
ata
in
to
f
u
zz
y
s
ets.
T
h
e
f
u
zz
y
r
u
le
b
ase
is
u
s
ed
to
g
en
er
ate
o
u
tp
u
ts
b
y
Ma
m
d
an
i
’
s
f
u
zz
y
in
f
er
en
ce
en
g
i
n
e.
Fig
u
r
e
5
s
h
o
ws
th
e
f
u
z
zy
lo
g
ic
s
y
s
tem
’
s
b
lo
ck
d
ia
g
r
am
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
F
u
z
z
y
b
a
s
ed
en
erg
y
efficien
t c
lu
s
ter h
ea
d
s
elec
tio
n
…
(
Ma
r
u
th
i H
a
n
u
ma
n
t
h
a
p
p
a
C
h
a
n
d
r
a
p
p
a
)
933
(
a)
(
b
)
(
c)
Fig
u
r
e
3
.
Sh
o
ws th
e
ap
p
r
o
ac
h
to
cr
ea
te
clu
s
ter
s
o
f
eq
u
al
s
ize
:
(
a)
g
eo
g
r
ap
h
ical
d
is
tr
ib
u
tio
n
o
f
SNs
,
(
b
)
s
h
o
ws
th
e
p
r
o
b
ab
ilit
y
d
is
tr
ib
u
tio
n
o
f
MN
s
in
ea
ch
clu
s
ter
,
an
d
(
c)
s
h
o
ws th
at
MN
s
ar
e
s
o
r
ted
in
d
escen
d
in
g
o
r
d
er
(
a)
(
b
)
Fig
u
r
e
4
.
Sh
o
ws th
e
p
r
o
p
o
s
ed
m
eth
o
d
(
a
)
o
f
cr
is
p
b
o
u
n
d
a
r
y
clu
s
ter
s
an
d
(
b
)
d
is
tr
ib
u
tio
n
o
f
MN
s
eq
u
ally
in
ev
er
y
clu
s
ter
Fig
u
r
e
.
5
Sh
o
ws th
e
ty
p
ical
f
u
zz
y
lo
g
ic
s
y
s
tem
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
8
,
No
.
2
,
May
20
2
5
:
9
2
8
-
9
39
934
1
)
Fu
zz
if
icatio
n
:
t
h
e
f
o
llo
win
g
f
u
zz
y
d
escr
ip
to
r
s
ar
e
f
ed
in
t
o
th
e
f
u
zz
if
ier
in
t
h
e
p
r
o
p
o
s
ed
FE
E
C
H
-
B
C
F.
R
esid
u
al
en
er
g
y
:
th
e
en
er
g
y
o
f
a
n
o
d
e
is
cr
u
cial
in
th
e
ch
o
o
s
in
g
o
f
th
e
C
H.
A
C
H
n
o
d
e
m
u
s
t
p
o
s
s
ess
h
ig
h
er
en
er
g
y
le
v
els to
ac
co
m
m
o
d
ate
ag
g
r
eg
atio
n
an
d
tr
an
s
m
is
s
io
n
d
em
an
d
s
.
No
d
e
ce
n
tr
ality
:
h
o
w
ce
n
tr
al
a
n
o
d
e
is
am
o
n
g
its
n
eig
h
b
o
r
s
in
a
clu
s
ter
is
k
n
o
wn
as
n
o
d
e
ce
n
tr
ality
[
2
6
]
.
No
d
e
ce
n
tr
ality
nc
i
is
m
ath
em
atica
lly
d
ef
in
ed
as
(
6
)
.
=
√
∑
(
)
∊
2
(
,
)
|
(
)
|
ℎ
(
6
)
w
h
er
e
th
e
s
ize
o
f
th
e
n
etwo
r
k
is
th
e
len
g
th
o
f
t
h
e
ed
g
e
o
f
t
h
e
n
etwo
r
k
ar
ea
M×
M
m
2
.
n
n
br
(
i)
d
en
o
tes
th
e
n
u
m
b
er
o
f
n
eig
h
b
o
r
in
g
n
o
d
es
ass
o
ciate
d
with
n
o
d
e
i,
wh
ile
d
2
(
i,j)
s
ig
n
if
ies
th
e
d
is
tan
ce
b
et
wee
n
n
o
d
e
i
an
d
n
o
d
e
j.
A
s
m
aller
n
o
d
e
ce
n
tr
al
ity
v
alu
e
is
ad
v
an
ta
g
eo
u
s
s
in
c
e
it r
esu
lts
in
d
im
in
is
h
ed
en
er
g
y
co
n
s
u
m
p
tio
n
.
2)
Fu
zz
y
r
u
le
b
ase:
th
e
f
u
zz
y
d
e
s
cr
ip
to
r
s
in
th
e
f
u
zz
y
r
u
le
b
ase
f
o
r
I
F
-
t
h
en
r
u
les
ar
e
n
o
d
e
e
n
er
g
y
an
d
n
o
d
e
ce
n
tr
ality
.
W
e
u
tili
ze
f
u
zz
y
A
ND
an
d
OR
o
p
er
ato
r
s
to
g
en
er
ate
f
u
zz
y
r
u
les.
T
h
e
f
u
zz
y
i
n
f
er
en
ce
en
g
i
n
e
em
p
lo
y
s
a
r
u
le
b
ase
to
d
eter
m
i
n
e
th
e
f
in
al
p
r
o
b
a
b
ilit
y
o
f
ea
ch
n
o
d
e
b
ec
o
m
in
g
C
H.
Ver
y
s
m
a
ll,
s
m
all,
r
ath
er
s
m
all,
m
id
s
m
all,
m
i
d
,
m
id
la
r
g
e,
r
ath
er
lar
g
e,
lar
g
e,
an
d
v
er
y
lar
g
e
ar
e
th
e
ter
m
s
u
s
ed
t
o
d
escr
ib
e
lo
ca
l
q
u
alif
icatio
n
.
T
a
b
le
1
illu
s
tr
ates a
f
u
zz
y
r
u
le
b
ase.
3)
Def
u
zz
if
icatio
n
:
t
h
e
d
ef
u
zz
if
i
er
tr
an
s
f
o
r
m
s
th
e
f
in
al
o
u
tp
u
t
in
to
a
v
alu
e
r
ef
er
r
e
d
to
as
lo
ca
l
q
u
alif
icatio
n
.
Her
e,
th
e
lo
ca
l
q
u
alif
icatio
n
o
f
th
e
n
o
d
e
with
“
v
e
r
y
lar
g
e”
will
b
e
th
e
m
o
r
e
s
u
itab
le
ca
n
d
id
ate
to
b
ec
o
m
e
C
H,
an
d
th
e
least,
wh
ich
h
as
a
“
v
er
y
s
m
all”
lo
ca
l
q
u
alif
icatio
n
.
T
h
e
p
lo
t
o
f
th
e
m
em
b
er
s
h
ip
f
u
n
ctio
n
s
is
p
r
esen
ted
in
Fig
u
r
e
6
.
T
h
e
p
lo
ts
o
f
th
e
m
em
b
er
s
h
ip
f
u
n
ctio
n
s
f
o
r
en
e
r
g
y
,
ce
n
tr
ality
,
a
n
d
l
o
ca
l q
u
alif
icatio
n
ar
e
p
r
esen
ted
in
Fig
u
r
e
s
6
(
a
)
-
6
(
c)
r
esp
ec
tiv
ely
.
T
ab
le
1
.
Fu
zz
y
r
u
les f
o
r
C
H
s
elec
tio
n
R
u
l
e
R
e
si
d
u
a
l
e
n
e
r
g
y
C
e
n
t
r
a
l
i
t
y
Lo
c
a
l
q
u
a
l
i
f
i
c
a
t
i
o
n
1
Lo
w
H
i
g
h
V
e
r
y
s
m
a
l
l
2
Lo
w
M
i
d
S
mal
l
3
Lo
w
Lo
w
R
a
t
h
e
r
s
ma
l
l
4
M
i
d
H
i
g
h
M
i
d
s
m
a
l
l
5
M
i
d
M
i
d
M
i
d
6
M
i
d
Lo
w
M
i
d
l
a
r
g
e
7
H
i
g
h
H
i
g
h
R
a
t
h
e
r
l
a
r
g
e
8
H
i
g
h
M
i
d
La
r
g
e
9
H
i
g
h
Lo
w
V
e
r
y
l
a
r
g
e
(
a)
(
b
)
Fig
u
r
e
6
.
Sh
o
ws th
e
m
em
b
er
s
h
ip
f
u
n
ctio
n
p
l
o
t
:
(
a)
f
o
r
en
e
r
g
y
,
(
b
)
f
o
r
c
en
tr
ality
,
a
n
d
(
c)
f
o
r
lo
ca
l q
u
alif
icatio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
F
u
z
z
y
b
a
s
ed
en
erg
y
efficien
t c
lu
s
ter h
ea
d
s
elec
tio
n
…
(
Ma
r
u
th
i H
a
n
u
ma
n
t
h
a
p
p
a
C
h
a
n
d
r
a
p
p
a
)
935
T
h
e
wo
r
k
f
lo
w
alg
o
r
it
h
m
is
p
r
o
v
id
ed
b
elo
w
:
Alg
o
r
ith
m
1
.
W
o
r
k
f
lo
w
o
f
FE
E
C
H
-
B
C
F
Input:
Number of centroids (X), Each cluster
’
s node count (CLUSTER[]), Th
cluster
Important variables:
K, largest, MN, Centroid[], SecondBestCentroid[], k
Result:
CH, Uniform Size Clusters
k
-
means Algorithm
1: Indicate the requisite number of clusters.
2: Initialise K centroids in a random fashion.
3:
repeat
4: Assign SNs to their nearest Centroids[]
5: Calculate the updated mean for each CLUSTER[]
6:
until
The locations of the centroids remain unchanged.
Load Balancing Technique
7: Sort CLUSTER[] in Descending order
8:
for
i = 1; i ≤ X; i++
do
9:
largest = i
10.
MN = CLUSTER[largest]
11.
for
j = 1; j ≤ MN; j++
do
12.
SecondBestCentroid[] = Distance to second best centroid
13.
end for
14.
Sort SecondBestCentroid[] in Ascending order
15.
k = MN
-
Th
cluster
16.
if
k > 0
then
17.
Sort SecondBestCentroid[] and assign first k nodes.
18.
UPDATE CLUSTER[]
19
end if
20.
The formed cluster of k = 0 is removed from further load balancing consideration
21.
Sort CLUSTER[] in Descending order
22.
end for
23.
until
Uniform Size Clusters
Cluster Head Selection Technique
24.
for
each CLUSTER[]
do
25. MNs calculates localqualification //refer Table 1
26. Qualified MN becomes new CH
27. Steady state phase
28. Go back to step 24
until
network lifetime
29.
end for
5.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
W
SN
wil
l
b
e
o
p
er
atio
n
al
u
n
ti
l
th
e
en
er
g
y
is
p
r
esen
t
i
n
th
e
n
etwo
r
k
.
I
t
is
p
r
ac
tically
n
o
t
f
ea
s
ib
le
to
ch
ar
g
e
th
e
b
atter
y
o
f
SNs
wh
en
th
e
en
er
g
y
g
ets lo
w.
Hen
ce
en
er
g
y
c
o
n
s
er
v
atio
n
is
m
o
s
t im
p
o
r
tan
t to
co
n
s
id
er
wh
ile
co
n
f
ig
u
r
e
r
in
g
th
e
n
etw
o
r
k
.
I
n
o
u
r
p
r
o
p
o
s
ed
wo
r
k
we
co
n
s
id
er
ed
th
e
h
y
b
r
id
tech
n
i
q
u
e
alo
n
g
with
th
e
co
r
e
n
o
v
elty
c
o
n
ce
p
t.
T
h
e
s
im
u
latio
n
is
co
n
d
u
cted
u
s
in
g
M
AT
L
AB
.
T
ab
le
2
d
escr
ib
es th
e
p
r
im
ar
y
s
im
u
latio
n
p
ar
am
eter
s
.
T
ab
le
2
.
Netwo
r
k
p
ar
am
ete
r
s
Param
et
e
r
N
e
t
w
o
rk
s
i
ze
T
o
t
a
l
n
u
m
b
er
o
f
SN
s
In
i
t
i
a
l
e
n
er
g
y
o
f
eac
h
n
o
d
es
Si
ze
o
f
d
a
t
a
p
ac
k
e
t
Si
n
k
p
o
s
i
t
i
o
n
(x
,
y
)
co
o
r
d
i
n
a
t
e
Free
s
p
ace
mo
d
e
l
en
er
g
y
p
ara
me
t
er
(ε
fs
)
Mu
l
t
i
p
a
t
h
mo
d
e
l
en
er
g
y
p
ara
me
t
er
(ε
mp
)
D
a
t
a
ag
g
re
g
a
t
i
o
n
en
er
g
y
Req
u
i
re
d
en
er
g
y
t
o
ru
n
ci
rc
u
i
t
ry
(E
e
l
e
c
)
CH
p
erc
en
t
a
g
e
V
a
l
u
e
5
0
×
5
0
m
2
50
2
J
4
,
0
0
0
b
i
t
s
(2
5
,
4
8
)
1
0
p
J
/
b
i
t
/
m
2
0
.
0
0
1
3
p
J
/
b
i
t
/
m
4
5
n
J
/
b
i
t
/
s
i
g
n
al
5
0
n
J
/
b
i
t
5
I
n
itial c
lu
s
ter
s
ar
e
f
o
r
m
e
d
b
as
ed
o
n
k
-
m
ea
n
s
clu
s
ter
in
g
as sh
o
wn
in
Fig
u
r
e
7.
B
u
t
th
e
cr
ea
t
ed
clu
s
ter
s
ar
e
o
f
n
o
n
-
u
n
if
o
r
m
s
ize.
Her
e
th
e
clu
s
ter
s
wi
th
f
ewe
r
n
u
m
b
er
o
f
m
em
b
e
r
s
will
d
ie
ea
r
ly
d
u
e
to
m
o
r
e
o
f
te
n
tr
an
s
m
is
s
io
n
th
an
th
e
clu
s
ter
with
lar
g
er
n
u
m
b
er
o
f
m
em
b
er
s
.
T
o
r
eso
lv
e
th
is
s
ce
n
ar
io
,
L
E
A
C
H
-
US
C
alg
o
r
ith
m
ca
n
b
e
u
s
ed
to
ass
ig
n
th
e
SN
m
em
b
er
s
h
ip
in
s
u
ch
a
way
th
a
t
all
clu
s
ter
s
ar
e
o
f
e
q
u
al
s
ize.
B
u
t,
L
E
AC
H
-
US
C
is
co
m
p
lex
an
d
tim
e
-
co
n
s
u
m
i
n
g
to
r
ec
lu
s
ter
af
ter
ev
er
y
r
o
u
n
d
an
d
m
em
b
er
s
h
ip
is
t
o
b
e
ass
ig
n
ed
ea
c
h
tim
e
b
ased
o
n
C
H
lo
ca
tio
n
.
I
n
o
u
r
ap
p
r
o
ac
h
,
th
e
clu
s
ter
s
ar
e
f
o
r
m
ed
b
ased
o
n
ce
n
tr
o
id
s
u
s
in
g
k
-
m
ea
n
s
alg
o
r
ith
m
.
Me
m
b
er
s
ar
e
ass
ig
n
ed
b
ased
o
n
L
E
AC
H
-
USC
p
r
o
to
co
l.
W
e
d
o
n
o
t
p
er
f
o
r
m
r
ec
lu
s
ter
o
n
ce
cl
u
s
ter
s
ar
e
f
o
r
m
ed
an
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
8
,
No
.
2
,
May
20
2
5
:
9
2
8
-
9
39
936
m
em
b
er
s
h
ip
o
f
SNs
is
also
f
ix
ed
as
s
h
o
wn
in
Fig
u
r
e
8
.
I
t
s
av
es
tim
e
an
d
en
e
r
g
y
r
eq
u
ir
e
d
f
o
r
r
ec
lu
s
ter
in
g
an
d
s
elec
tin
g
C
H.
Po
ten
tial
C
H
s
ar
e
id
en
tifie
d
b
y
f
u
zz
y
lo
g
ic,
c
o
n
s
id
er
in
g
r
esid
u
al
en
er
g
y
a
n
d
n
o
d
e
ce
n
tr
ality
,
as
in
d
icate
d
in
T
ab
le
1
,
a
n
d
it is
n
o
t o
b
lig
at
o
r
y
to
alter
th
e
C
H
af
ter
ea
ch
r
o
u
n
d
.
Fig
u
r
e
7
.
Sh
o
ws th
e
clu
s
ter
s
tr
u
ctu
r
e
u
s
in
g
k
-
m
ea
n
s
alg
o
r
ith
m
Fig
u
r
e
8
.
Sh
o
ws th
e
clu
s
ter
s
tr
u
ctu
r
e
u
s
in
g
FEE
C
H
-
B
C
F
W
e
m
ad
e
th
e
ass
u
m
p
tio
n
t
h
at
e
v
er
y
n
o
d
e
i
n
th
e
r
eg
io
n
o
f
i
n
ter
est
is
id
en
tical
an
d
d
is
tr
ib
u
ted
at
r
an
d
o
m
.
T
h
e
n
u
m
b
er
o
f
r
o
u
n
d
s
,
en
er
g
y
u
s
ag
e,
an
d
ac
tiv
e
n
o
d
e
co
u
n
t
wer
e
u
s
ed
to
ass
ess
th
e
ef
f
icien
cy
o
f
th
e
s
u
g
g
ested
FEE
C
H
-
B
C
F
s
y
s
tem
.
T
h
e
n
et
wo
r
k
p
er
f
o
r
m
a
n
ce
ev
al
u
atio
n
’
s
r
esu
lts
h
av
e
b
ee
n
av
e
r
ag
ed
o
v
er
5
0
iter
atio
n
s
.
T
h
e
r
esu
ltin
g
clu
s
ter
s
tr
u
ct
u
r
es
an
d
t
h
eir
q
u
ality
a
r
e
c
o
m
p
ar
ed
am
o
n
g
L
E
AC
H,
B
C
F,
L
E
AC
H
-
USC
,
an
d
FEE
C
H
-
B
C
F.
Su
b
s
eq
u
en
tly
,
th
e
n
etwo
r
k
p
er
f
o
r
m
a
n
ce
is
ev
alu
ated
in
co
m
p
ar
is
o
n
to
o
n
e
a
n
o
th
er
.
5
.
1
.
Co
m
pa
riso
n ba
s
ed
o
n c
lus
t
er
s
t
ruct
ures
An
an
aly
s
is
o
f
th
e
clu
s
ter
s
cr
ea
ted
b
y
L
E
AC
H,
B
C
F,
L
E
A
C
H
-
USC
,
an
d
FEE
C
H
-
B
C
F
in
a
r
o
u
n
d
is
p
r
esen
ted
in
th
is
s
ec
tio
n
.
SNs
will jo
in
th
e
n
ea
r
est C
H
in
ca
s
e
o
f
L
E
AC
H
p
r
o
to
co
l,
s
o
th
er
e
is
n
o
g
u
ar
an
tee
o
f
eq
u
al
-
s
ize
clu
s
ter
s
.
B
C
F
f
o
r
m
s
th
e
clu
s
ter
s
in
a
well
-
b
alan
ce
d
m
an
n
er
i
n
ter
m
s
o
f
clu
s
ter
s
ize,
b
u
t
th
er
e
will
b
e
clu
s
ter
s
o
v
er
lap
p
in
g
.
L
E
AC
H
-
USC
f
o
r
m
s
clu
s
ter
s
o
f
eq
u
a
l
s
ize
an
d
h
av
e
c
r
is
p
b
o
u
n
d
a
r
ies
b
u
t
it
is
m
o
r
e
co
m
p
lex
an
d
tim
e
-
co
n
s
u
m
i
n
g
.
I
n
co
n
tr
ast,
th
e
p
r
o
p
o
s
ed
FEE
C
H
-
B
C
F
cr
ea
tes
well
-
b
alan
ce
d
clu
s
ter
s
as
s
h
o
wn
in
Fig
u
r
e
s
8
an
d
9
.
Fig
u
r
e
9
.
Sh
o
ws th
e
d
is
tr
ib
u
tio
n
o
f
MN
s
to
ea
ch
clu
s
ter
in
F
E
E
C
H
-
B
C
F
5
.
2
.
Co
m
pa
riso
n
ba
s
ed
o
n intr
a
-
clus
t
er
dis
t
a
nce
T
h
e
s
u
g
g
ested
a
p
p
r
o
ac
h
is
e
v
alu
ated
ag
ai
n
s
t
th
e
L
E
AC
H,
B
C
F,
an
d
L
E
AC
H
-
USC
tec
h
n
iq
u
es
to
d
eter
m
in
e
in
tr
a
-
cl
u
s
ter
d
is
tan
ce
.
T
ab
le
3
p
r
esen
ts
a
co
m
p
ilatio
n
o
f
th
e
to
tal
in
tr
a
-
clu
s
ter
d
is
tan
ce
d
u
r
in
g
d
if
f
er
en
t iter
atio
n
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
F
u
z
z
y
b
a
s
ed
en
erg
y
efficien
t c
lu
s
ter h
ea
d
s
elec
tio
n
…
(
Ma
r
u
th
i H
a
n
u
ma
n
t
h
a
p
p
a
C
h
a
n
d
r
a
p
p
a
)
937
T
ab
le
3
.
C
o
m
p
a
r
is
o
n
o
f
clu
s
ter
s
ize
an
d
to
tal
in
tr
a
-
cl
u
s
ter
co
m
m
u
n
icatio
n
d
is
tan
ce
A
p
p
r
o
a
c
h
LEA
C
H
BCF
LEA
C
H
-
U
S
C
F
EEC
H
-
B
C
F
I
t
e
r
a
t
i
o
n
1
2
3
1
2
3
1
2
3
1
2
3
S
i
z
e
o
f
c
l
u
st
e
r
1
20
16
17
18
17
17
17
17
17
17
17
17
S
i
z
e
o
f
c
l
u
st
e
r
2
9
13
24
15
17
23
16
16
16
17
16
17
S
i
z
e
o
f
c
l
u
st
e
r
3
21
21
9
17
16
13
17
17
17
16
17
16
To
t
a
l
i
n
t
r
a
-
c
l
u
st
e
r
d
i
s
t
a
n
c
e
6
9
5
6
9
4
7
9
1
8
9
2
8
7
0
9
9
5
7
5
8
7
3
5
8
8
9
6
0
8
6
6
1
5
0
2
T
h
e
in
tr
a
-
clu
s
ter
d
is
tan
ce
o
f
B
C
F
i
s
h
ig
h
est
d
u
e
to
th
e
p
r
ed
e
ter
m
in
ed
clu
s
ter
s
ize.
Du
r
in
g
t
h
e
r
escu
e
p
h
ase,
u
n
clu
s
ter
ed
n
o
d
es
will
j
o
in
th
e
clu
s
ter
s
b
ased
o
n
th
r
es
h
o
ld
d
is
tan
ce
an
d
th
e
m
ax
im
u
m
p
er
m
is
s
ib
le
MN
s
p
er
clu
s
ter
.
T
h
is
m
eth
o
d
r
esu
lts
in
a
b
alan
ce
d
clu
s
ter
;
h
o
wev
er
,
it
also
lead
s
to
an
in
cr
e
ase
in
in
tr
a
-
clu
s
ter
d
is
tan
ce
.
L
E
AC
H
-
US
C
d
em
o
n
s
tr
ates
a
r
ed
u
ce
d
in
tr
a
-
clu
s
ter
d
is
tan
ce
co
m
p
ar
ed
with
B
C
F,
as
th
e
MN
s
in
th
e
lar
g
est
clu
s
ter
s
s
elec
t
m
em
b
e
r
s
h
ip
with
th
e
n
ex
t
o
p
tim
al
c
lu
s
ter
b
ased
o
n
th
e
s
ec
o
n
d
-
b
es
t
CH
p
ar
am
eter
.
L
E
AC
H
r
esu
lts
in
a
r
ed
u
ce
d
in
tr
a
-
clu
s
ter
d
is
tan
ce
,
as
SNs
s
elec
t
th
e
n
ea
r
est
clu
s
ter
m
em
b
er
s
h
ip
;
h
o
wev
er
,
th
e
clu
s
ter
s
ex
h
ib
it
u
n
ev
en
s
i
ze
s
.
T
h
e
p
r
o
p
o
s
ed
FEE
C
H
-
B
C
F
p
r
o
to
co
l
ac
h
iev
es
th
e
m
in
im
u
m
in
tr
a
-
clu
s
ter
d
is
tan
ce
b
y
allo
win
g
ex
ce
s
s
S
Ns
f
r
o
m
th
e
lar
g
est
clu
s
ter
to
j
o
in
th
e
n
ex
t
b
est
clu
s
ter
,
d
eter
m
in
ed
b
y
p
r
o
x
im
ity
to
th
e
n
ea
r
est
ce
n
tr
o
id
d
is
tan
c
e
to
th
e
SN
s
.
T
h
e
d
is
tr
ib
u
tio
n
o
f
m
e
m
b
er
s
to
clu
s
ter
s
,
d
eter
m
in
ed
b
y
ce
n
tr
o
id
lo
ca
tio
n
,
m
in
im
izes in
tr
a
-
cl
u
s
ter
d
is
tan
ce
.
5
.
3
.
Net
w
o
rk
perf
o
rma
nce
T
h
e
m
etr
ics
tak
en
in
to
ac
co
u
n
t
f
o
r
n
etwo
r
k
a
n
aly
s
is
in
clu
d
e
th
e
co
u
n
t
o
f
ac
tiv
e
n
o
d
es
o
v
er
t
h
e
r
o
u
n
d
s
,
f
ir
s
t
n
o
d
e
d
ea
t
h
(
FND)
,
h
alf
n
o
d
e
d
ea
th
(
HND)
,
an
d
last
n
o
d
e
d
ea
th
(
L
ND)
.
Fig
u
r
e
1
0
ill
u
s
tr
ates
th
e
n
u
m
b
er
o
f
n
o
d
es
th
at
r
em
ain
e
d
o
p
e
r
atio
n
al
d
u
r
in
g
th
e
n
etwo
r
k
’
s
life
s
p
an
.
T
h
e
r
esu
lts
ar
e
p
r
esen
ted
in
T
ab
le
4
.
Fig
u
r
e
10
.
Sh
o
ws th
e
n
etwo
r
k
life
tim
e
T
ab
le
4
.
Netwo
r
k
life
tim
e
A
p
p
r
o
a
c
h
N
e
t
w
o
r
k
l
i
f
e
t
i
m
e
F
N
D
HND
LN
D
LEA
C
H
5
4
0
6
7
4
8
0
0
BCF
6
1
2
7
2
1
8
5
2
LEA
C
H
-
U
S
C
7
1
8
9
6
2
1
0
1
5
F
EEC
H
-
B
C
F
7
1
6
3
9
0
5
4
9
1
3
0
C
o
m
p
ar
ed
with
L
E
AC
H,
FEE
C
H
-
B
C
F
ac
h
iev
es
1
2
2
6
%,
1
2
4
3
%,
an
d
1
0
4
1
%
in
cr
ea
s
e
in
l
if
etim
e
f
o
r
FND,
HND,
an
d
L
ND,
r
esp
ec
ti
v
ely
.
W
h
ile
f
o
r
B
C
F,
FEE
C
H
-
B
C
F
ac
h
iev
es
1
0
7
0
%,
1
1
5
6
%,
an
d
9
7
2
%
in
cr
ea
s
e
in
life
tim
e
f
o
r
FND,
HND,
a
n
d
L
ND
r
esp
ec
tiv
ely
.
W
h
ile
f
o
r
L
E
AC
H
-
USC
,
FEE
C
H
-
B
C
F
ac
h
iev
es
8
9
8
%,
8
4
1
%,
an
d
7
9
8
% in
cr
ea
s
e
in
a
life
tim
e
f
o
r
FND,
HND,
an
d
L
ND
r
esp
ec
tiv
ely
.
Du
r
in
g
m
o
r
e
th
a
n
7
8
%
o
f
th
e
to
tal
n
etwo
r
k
life
s
p
an
,
all
n
o
d
es
r
em
ain
o
p
er
atio
n
al.
T
h
e
r
e
g
io
n
u
n
d
er
m
o
n
ito
r
in
g
is
co
n
s
is
ten
tly
m
o
n
ito
r
ed
d
u
r
in
g
th
e
n
etwo
r
k
’
s
life
s
p
an
.
I
n
co
m
p
ar
is
o
n
to
th
e
L
E
AC
H
-
US
C
,
B
C
F,
an
d
L
E
AC
H
m
eth
o
d
o
lo
g
ies,
th
e
p
r
o
p
o
s
ed
FEE
C
H
-
B
C
F
d
em
o
n
s
tr
ates
a
m
ar
k
ed
ly
lo
wer
in
cid
en
ce
o
f
n
o
d
e
d
ea
th
s
o
v
e
r
th
e
n
etwo
r
k
’
s
d
u
r
atio
n
.
T
h
e
s
u
g
g
ested
ap
p
r
o
ac
h
o
u
tp
er
f
o
r
m
s
p
r
ev
i
o
u
s
tech
n
iq
u
es
d
u
e
t
o
well
-
b
alan
ce
d
clu
s
ter
s
,
th
e
a
v
o
id
an
ce
o
f
r
ec
lu
s
ter
in
g
,
r
ed
u
ce
d
in
tr
a
-
clu
s
ter
co
m
m
u
n
ic
atio
n
d
is
tan
ce
,
an
d
ef
f
ec
tiv
e
s
elec
tio
n
o
f
C
Hs,
s
ig
n
if
ican
tly
en
h
a
n
cin
g
n
etwo
r
k
lo
n
g
ev
ity
.
Evaluation Warning : The document was created with Spire.PDF for Python.