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ineering
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Co
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p
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Science
Vo
l.
10
,
No
.
2
,
May
201
8
,
p
p
.
5
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4
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N:
2502
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4752
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DOI
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ex
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s
Reducing
To
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tal Ar
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Techniqu
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for N
etw
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u
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o
t
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larg
e
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e
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In
t
h
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p
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d
a
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e
o
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n
su
m
p
ti
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re
th
e
m
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.
Ex
p
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s sh
o
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th
a
t
th
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p
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m
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th
o
d
o
u
tp
e
rf
o
rm
a
s
th
e
e
x
isti
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g
w
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.
T
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e
c
lu
ste
rin
g
-
m
e
sh
b
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d
m
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th
o
d
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a
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it
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th
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p
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p
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m
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d
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K
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w
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s
:
A
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ea
C
lu
s
ter
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g
Me
s
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to
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Net
w
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k
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on
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ip
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p
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h
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©
2
0
1
8
In
stit
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te o
f
A
d
v
a
n
c
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d
E
n
g
i
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rin
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a
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d
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.
Al
l
rig
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ts re
se
rv
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d
.
C
o
r
r
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p
o
nd
ing
A
uth
o
r
:
Ng
Ye
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P
h
in
g
,
Sch
o
o
l o
f
C
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m
p
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ter
an
d
C
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m
m
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E
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g
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in
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,
Un
i
v
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it
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la
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au
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P
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tr
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Ma
in
C
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m
p
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s
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2
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A
r
au
,
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la
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s
ia.
E
m
ail:
n
y
e
n
p
h
in
g
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
I
n
r
ec
en
t
y
ea
r
,
th
er
e
ar
e
s
e
v
er
al
r
esear
ch
p
ap
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ab
o
u
t
th
e
b
asic
is
s
u
e
a
n
d
tr
ad
itio
n
al
ch
alle
n
g
e
s
o
f
Net
w
o
r
k
-
on
-
C
h
ip
(
No
C
)
[
1
]
.
T
h
e
p
er
f
o
r
m
an
ce
s
u
c
h
as
lo
w
p
o
w
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co
n
s
u
m
p
tio
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lo
w
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a,
lo
w
laten
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an
d
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ig
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t
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r
o
u
g
h
p
u
t
ar
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th
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m
ai
n
d
esira
b
le
ch
ar
ac
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is
tic
f
o
r
No
C
ar
ch
itect
u
r
e.
Ho
w
ev
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,
t
h
e
p
er
f
o
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m
a
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ce
i
s
d
r
o
p
as
th
e
n
u
m
b
er
o
f
co
r
es
i
s
in
cr
ea
s
in
g
[
2
]
.
T
h
is
is
b
ec
au
s
e
t
h
e
n
u
m
b
er
o
f
co
r
es
is
p
r
o
p
o
r
tio
n
al
to
th
e
a
v
er
ag
e
laten
c
y
a
n
d
to
tal
p
o
w
er
co
n
s
u
m
p
tio
n
.
T
h
e
c
h
o
ice
o
f
a
n
et
wo
r
k
to
p
o
lo
g
y
f
o
r
No
C
is
s
i
g
n
i
f
ica
n
tl
y
i
m
p
ac
ts
it
s
p
er
f
o
r
m
a
n
ce
[
3
]
[
4
]
.
T
h
e
ter
m
o
f
n
et
w
o
r
k
to
p
o
lo
g
y
ca
n
d
e
f
in
e
as
h
o
w
th
e
r
o
u
ter
is
i
n
ter
co
n
n
ec
t
to
ea
ch
o
t
h
er
[
5
]
.
T
h
e
n
et
w
o
r
k
to
p
o
lo
g
y
ca
n
b
e
d
esig
n
ed
as
ap
p
licatio
n
s
p
ec
if
ied
o
r
r
eg
u
lar
.
R
eg
u
lar
to
p
o
lo
g
y
h
av
e
b
ee
n
s
u
cc
e
s
s
f
u
ll
y
e
m
p
lo
y
ed
i
n
a
n
u
m
b
er
o
f
tile
-
b
ased
ch
ip
m
u
ltip
r
o
ce
s
s
o
r
p
r
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j
ec
t
b
ec
au
s
e
o
f
p
r
o
ce
s
s
o
r
h
o
m
o
g
en
eit
y
a
n
d
ap
p
licatio
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tr
af
f
ic
v
ar
iab
ilit
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.
T
h
er
e
ar
e
n
u
m
b
er
o
f
r
esear
ch
d
is
co
v
er
in
g
t
h
e
p
r
o
s
an
d
co
n
s
o
f
clu
s
ter
i
n
g
m
et
h
o
d
in
d
if
f
er
en
t
to
p
o
lo
g
ies
to
i
m
p
r
o
v
e
t
h
e
o
v
er
all
p
er
f
o
r
m
an
ce
.
C
l
u
s
ter
in
g
ca
n
d
e
f
in
e
as d
iv
id
i
n
g
t
h
e
n
o
d
es i
n
t
h
e
n
e
t
w
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k
s
i
n
to
d
i
f
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e
n
t
clu
s
ter
ac
co
r
d
in
g
to
ce
r
tain
p
r
in
cip
le.
A
n
o
d
e
is
s
elec
ted
as
a
clu
s
ter
h
ea
d
er
in
ea
ch
clu
s
te
r
.
A
clu
s
ter
h
ea
d
er
is
r
esp
o
n
s
ib
le
f
o
r
th
e
co
m
m
u
n
icatio
n
b
et
w
ee
n
cl
u
s
ter
s
a
n
d
m
an
a
g
e
m
e
n
t
w
it
h
i
n
its
cl
u
s
ter
.
T
h
e
h
ea
d
er
o
f
th
e
clu
s
ter
h
a
s
t
h
e
a
v
er
ag
e
m
in
i
m
u
m
d
is
ta
n
ce
to
all
i
ts
m
e
m
b
er
.
C
l
u
s
ter
i
n
g
m
eth
o
d
m
a
y
ab
le
to
s
h
ar
e
co
m
m
o
n
in
ter
m
ed
iate
n
et
w
o
r
k
r
es
o
u
r
ce
s
.
Dis
ab
le
co
r
es
an
d
r
o
u
ter
s
b
ased
o
n
clu
s
ter
in
g
m
et
h
o
d
p
r
o
p
o
s
ed
h
er
e
is
b
ased
o
n
4
x
4
m
es
h
to
p
o
lo
g
y
.
Fi
g
u
r
e
1
s
h
o
w
a
2
-
d
i
m
e
s
io
n
al
4
x
4
m
e
s
h
to
p
o
lo
g
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
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n
esia
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J
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lec
E
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&
C
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p
Sci
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N:
2502
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4752
R
ed
u
cin
g
To
t
a
l P
o
w
er C
o
n
s
u
mp
tio
n
a
n
d
To
ta
l A
r
ea
Tech
n
i
q
u
es fo
r
N
etw
o
r
k
-
on
-
C
h
ip
…(
N
g
Yen
P
h
in
g
)
515
T
h
e
ef
f
icie
n
c
y
o
f
t
h
e
p
r
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p
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s
e
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ased
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h
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is
in
v
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ted
b
y
u
s
in
g
B
o
o
k
Si
m
2
.
0
s
i
m
u
lato
r
,
a
cy
cle
-
ac
cu
r
ate
s
i
m
u
lato
r
f
o
r
No
C
[
6
]
.
T
o
o
b
tain
th
e
to
tal
p
o
w
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co
n
s
u
m
p
tio
n
,
Or
io
n
2
.
0
p
o
w
er
lib
r
ar
y
[
7
]
w
a
s
i
n
te
g
r
ated
in
B
o
o
k
Si
m
2
.
0
.
T
h
e
m
ai
n
co
n
tr
ib
u
tio
n
o
f
th
i
s
p
ap
er
ar
e
in
v
esti
g
ate
th
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p
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f
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f
clu
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m
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ased
to
p
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ab
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ased
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ased
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all
y
,
s
ec
tio
n
5
co
n
clu
d
es t
h
is
p
ap
er
.
Fig
u
r
e
1
.
A
2
-
D
i
m
e
n
s
io
n
4
x
4
Me
s
h
T
o
p
o
lo
g
y
No
C
2.
RE
L
AT
E
D
WO
RK
T
h
er
e
ar
e
s
ev
er
al
r
esear
ch
h
av
e
b
ee
n
d
o
n
e
m
ai
n
l
y
to
m
i
n
i
m
i
ze
th
e
to
tal
p
o
w
er
co
n
s
u
m
p
tio
n
b
y
ap
p
ly
i
n
g
clu
s
ter
i
n
g
m
et
h
o
d
.
R
eg
ar
d
in
g
[
8
]
,
a
d
ec
o
m
p
o
s
e
an
d
cl
u
s
t
er
in
g
w
it
h
r
ef
i
n
e
m
e
n
t
alg
o
r
it
h
m
i
s
p
r
o
p
o
s
ed
to
r
ed
u
ce
th
e
to
tal
p
o
w
er
co
n
s
u
m
p
tio
n
w
it
h
co
n
s
id
er
in
g
o
f
C
en
tr
al
P
r
o
ce
s
s
in
g
Un
i
t
(
C
P
U)
ti
m
e.
T
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
r
ed
u
ce
d
th
e
to
tal
p
o
w
er
co
n
s
u
m
p
tio
n
b
y
u
s
in
g
t
w
o
-
s
ta
g
e
m
et
h
o
d
f
o
r
d
ec
o
m
p
o
s
e
an
d
clu
s
ter
.
I
n
ad
d
itio
n
,
a
f
au
lt
to
ler
an
t
r
o
u
ti
n
g
al
g
o
r
it
h
m
m
et
h
o
d
o
f
Net
wo
r
k
-
on
-
C
h
ip
s
y
s
te
m
b
ased
o
n
clu
s
ter
i
n
g
m
e
th
o
d
is
p
r
o
p
o
s
ed
b
y
[
9
]
.
T
h
e
ai
m
o
f
t
h
e
f
au
l
t
to
ler
an
t
r
o
u
ti
n
g
alg
o
r
i
th
m
i
n
t
h
is
p
ap
er
is
to
r
ed
u
ce
t
h
e
a
v
er
ag
e
late
n
c
y
.
T
h
e
f
au
lt
to
ler
an
t
r
o
u
ti
n
g
al
g
o
r
ith
m
is
b
ased
o
n
ex
i
s
ti
n
g
ad
ap
tiv
e,
d
eter
m
in
is
tic
a
n
d
r
o
u
ter
clu
s
ter
in
g
tech
n
o
lo
g
y
.
B
ased
o
n
[
1
0
]
,
r
ed
u
cin
g
t
h
e
to
tal
p
o
w
er
co
n
s
u
m
p
tio
n
b
y
u
s
i
n
g
cl
u
s
ter
ed
r
o
u
ter
d
r
o
u
tin
g
in
Net
w
o
r
k
-
on
-
C
h
ip
(
No
C
)
.
A
h
eter
o
g
e
n
eo
u
s
a
n
d
h
y
b
r
id
clu
s
ter
ed
to
p
o
lo
g
y
f
o
r
No
C
is
p
r
o
p
o
s
ed
b
y
[
1
1
]
to
o
p
tim
ized
th
e
av
er
a
g
e
late
n
c
y
an
d
r
esp
o
n
s
e
ti
m
e.
T
h
e
g
eo
m
etr
y
o
f
th
e
h
eter
o
g
en
eo
u
s
a
n
d
h
y
b
r
id
clu
s
ter
ed
to
p
o
lo
g
y
i
s
s
a
m
e
as t
h
at
o
f
m
e
s
h
to
p
o
lo
g
y
.
L
ast
l
y
,
a
No
C
ar
c
h
itect
u
r
e
b
ased
o
n
clu
s
ter
m
et
h
o
d
is
p
r
o
p
o
s
ed
b
y
[
12]
.
T
h
is
clu
s
ter
m
et
h
o
d
is
b
ased
o
n
to
p
o
lo
g
y
w
i
th
lo
n
g
r
a
n
g
e
lin
k
i
n
s
er
tio
n
alg
o
r
it
h
m
.
3.
CL
US
T
E
R
-
M
E
SH
M
E
T
H
O
D
T
h
e
clu
s
ter
in
g
m
e
th
o
d
an
d
d
is
ab
le
n
o
d
es
b
ased
o
n
clu
s
ter
in
g
m
et
h
o
d
is
d
is
cu
s
s
i
n
th
e
s
ec
t
io
n
.
C
lu
s
ter
i
n
g
i
s
t
h
e
ta
s
k
o
f
g
r
o
u
p
in
g
t
h
e
n
o
d
es
in
t
h
e
n
et
wo
r
k
s
in
to
d
if
f
er
en
t
cl
u
s
ter
ac
co
r
d
in
g
to
ce
r
tain
p
r
in
cip
le.
I
n
ea
ch
cl
u
s
ter
,
a
n
o
d
e
is
s
elec
ted
as
a
cl
u
s
ter
h
ea
d
er
.
A
cl
u
s
ter
h
ea
d
er
is
r
esp
o
n
s
ib
le
f
o
r
th
e
co
m
m
u
n
icatio
n
b
et
w
ee
n
c
lu
s
t
er
s
an
d
m
an
a
g
e
m
en
t
w
it
h
i
n
it
s
clu
s
ter
.
T
h
e
th
r
ee
m
ai
n
r
u
les
to
f
o
r
m
a
clu
s
ter
i
n
1
6
n
o
d
es m
e
s
h
to
p
o
lo
g
y
ar
e:
R
u
le
1
:
T
h
e
n
u
m
b
er
o
f
n
o
d
es
in
ea
ch
g
r
o
u
p
is
eq
u
al.
T
h
e
f
o
llo
w
in
g
f
o
r
m
u
la
is
u
s
ed
to
d
eter
m
in
e
t
h
e
n
u
m
b
er
o
f
cl
u
s
ter
.
Nu
m
b
er
o
f
clu
s
ter
(
n
)
i
s
ac
ce
p
ted
a
s
a
n
u
m
b
er
o
f
clu
s
ter
w
h
e
n
n
o
r
e
m
a
in
d
er
f
r
o
m
t
h
e
f
o
llo
w
i
n
g
eq
u
atio
n
.
16
N
u
m
b
e
r
o
f
C
l
u
s
t
e
r
(
n
)
=
,
n
0
a
n
d
1
n
R
u
le
2
: M
i
n
i
m
u
m
o
n
e
o
r
m
o
r
e
n
o
d
es
is
co
n
n
ec
ted
to
th
e
h
ea
d
er
n
o
d
e
o
f
clu
s
ter
.
R
u
le
3
: E
ac
h
h
ea
d
er
o
f
clu
s
ter
w
ill co
n
n
ec
ted
to
g
e
th
er
f
o
r
m
a
m
es
h
to
p
o
lo
g
y
.
R
u
le
4
:
A
h
ier
ar
ch
ical
C
lu
s
t
er
in
g
to
p
o
lo
g
y
w
i
th
s
u
b
h
ea
d
er
w
ill
b
e
f
o
r
m
w
h
en
t
h
e
n
u
m
b
er
o
f
n
o
d
e
co
n
n
ec
ted
to
th
e
h
ea
d
er
is
eq
u
al
to
3
o
r
m
o
r
e
th
a
n
3
.
T
h
e
ex
p
lan
atio
n
o
f
ea
c
h
co
lo
u
r
n
o
d
e
is
ex
p
lain
ed
in
tab
le
1
.
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Re
s
ourc
e
s
Rout
e
r
/
S
w
i
t
c
h
L
i
nk
/
Cha
nne
l
Re
s
ourc
e
s
N
e
t
w
ork
Int
e
rfa
c
e
(
RN
I
)
IP
Cor
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.
10
,
No
.
2
,
Ma
y
2
0
1
8
:
5
1
4
–
5
2
0
516
T
ab
le
1
.
E
x
p
lan
atio
n
o
f
C
o
lo
u
r
in
Fig
u
r
e
1
C
o
l
o
u
r
Ex
p
l
a
n
a
t
i
o
n
N
o
d
e
(
C
o
r
e
a
n
d
R
o
u
t
e
r
)
C
l
u
st
e
r
H
e
a
d
e
r
C
l
u
st
e
r
S
u
b
H
e
a
d
e
r
Fig
u
r
e
2
s
h
o
w
s
t
h
e
1
6
n
o
d
es
m
es
h
to
p
o
lo
g
y
a
n
d
t
h
e
cl
u
s
ter
-
m
es
h
b
ased
to
p
o
lo
g
y
.
B
ased
o
n
t
h
e
p
r
o
p
o
s
ed
clu
s
ter
r
u
le,
1
6
n
o
d
es
m
e
s
h
to
p
o
lo
g
y
i
s
p
o
s
s
ib
le
to
f
o
r
m
a
to
tal
o
f
f
iv
e
t
y
p
e
o
f
clu
s
ter
-
m
es
h
to
p
o
lo
g
y
.
T
h
e
f
iv
e
t
y
p
e
o
f
cl
u
s
ter
-
m
es
h
b
ased
to
p
o
l
o
g
y
ar
e
m
e
s
h
cl
u
s
ter
h
ea
d
er
t
w
o
,
m
es
h
clu
s
ter
h
ea
d
er
f
o
u
r
,
m
es
h
c
lu
s
ter
h
ea
d
er
eig
h
t,
m
es
h
c
lu
s
ter
h
ea
d
er
t
w
o
w
it
h
s
u
b
h
ea
d
er
t
w
o
,
an
d
cl
u
s
ter
h
ea
d
er
f
o
u
r
w
it
h
s
u
b
h
ea
d
er
f
o
u
r
.
B
ased
o
n
r
u
l
e
4
,
a
h
ier
ar
ch
ica
l
C
lu
s
ter
in
g
to
p
o
lo
g
y
w
it
h
s
u
b
h
ea
d
er
w
ill
b
e
f
o
r
m
w
h
e
n
t
h
e
n
u
m
b
er
o
f
n
o
d
e
co
n
n
ec
ted
to
th
e
h
ea
d
er
is
≥
3.
T
h
er
ef
o
r
e,
a
clu
s
ter
h
ea
d
er
2
w
ith
s
u
b
h
ea
d
er
2
an
d
a
clu
s
ter
h
ea
d
er
4
w
it
h
s
u
b
h
ea
d
er
4
h
ier
ar
ch
ical
cl
u
s
ter
i
s
f
o
r
m
b
ased
o
n
1
6
m
es
h
clu
s
ter
h
ea
d
er
2
an
d
4
.
A
h
ier
a
r
ch
ical
cl
u
s
ter
i
s
a
co
m
b
i
n
atio
n
o
f
m
e
s
h
a
n
d
tr
ee
to
p
o
lo
g
ies.
Fig
u
r
e
2
.
1
6
No
d
es M
esh
an
d
C
lu
s
ter
-
Me
s
h
B
ased
T
o
p
o
lo
g
y
3
.
1
DIS
AB
L
E
RO
U
T
E
R
S AN
D
CO
RE
S B
AS
E
D
O
N
CL
U
S
T
E
R
-
M
E
SH
T
O
P
O
L
O
G
Y
T
h
is
p
ap
er
p
r
o
p
o
s
ed
a
d
is
ab
le
n
o
d
es b
ased
o
n
clu
s
ter
i
n
g
m
et
h
o
d
.
T
h
e
m
ai
n
r
u
le
to
d
is
ab
le
n
o
d
e
ar
e
:
R
u
le
1
: N
u
m
b
er
o
f
cl
u
s
ter
ed
h
ea
d
er
>
2
R
u
le
2
: D
i
s
ab
le
n
o
d
es b
ased
o
n
clu
s
ter
in
g
m
et
h
o
d
s
.
Dis
ab
le
m
i
n
i
m
u
m
1
g
r
o
u
p
o
f
cl
u
s
ter
.
R
u
le
3
: M
a
x
i
m
u
m
N
u
m
b
er
o
f
Dis
ab
le
C
l
u
s
ter
=
N
u
m
b
er
o
f
C
lu
s
ter
Hea
d
er
–
2
Fig
u
r
e
3
s
h
o
w
s
th
e
clu
s
te
r
ed
h
ea
d
er
4
m
e
s
h
to
p
o
lo
g
y
a
n
d
d
is
ab
le
m
o
d
e
b
ased
o
n
c
lu
s
ter
in
g
m
eth
o
d
i
n
clu
s
ter
ed
h
ea
d
er
4
m
e
s
h
to
p
o
lo
g
y
.
B
ased
o
n
r
u
le
3
,
th
e
m
ax
i
m
u
m
n
u
m
b
er
o
f
d
is
ab
le
clu
s
ter
ed
in
cl
u
s
ter
ed
h
ea
d
er
4
to
p
o
l
o
g
y
is
:
Ma
x
i
m
u
m
N
u
m
b
er
o
f
D
is
ab
le
C
lu
s
ter
ed
=
4
–
2
=
2
Gr
o
u
p
Fig
u
r
e
3
.
C
lu
s
ter
ed
Hea
d
er
4
Me
s
h
T
o
p
o
lo
g
y
a
n
d
Dis
ab
le
Mo
d
e
B
ased
o
n
C
lu
s
ter
i
n
g
Me
th
o
d
in
C
l
u
s
ter
ed
Hea
d
er
4
Me
s
h
T
o
p
o
lo
g
y
Fig
u
r
e
4
s
h
o
w
s
t
h
e
cl
u
s
ter
ed
h
ea
d
er
w
ith
s
u
b
h
ea
d
er
4
m
es
h
to
p
o
lo
g
y
a
n
d
d
is
ab
le
m
o
d
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u
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ased
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ased
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3
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8
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9
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d
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Fig
u
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3
.
T
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A
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m
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r
1
6
No
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T
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p
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1
T
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(
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Fig
u
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4
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ased
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
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ased
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ased
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4
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ig
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Fig
u
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6
s
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ased
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ased
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8
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ased
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m
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u
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ch
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lu
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s
h
T
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p
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I
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ased
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ased
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ased
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y
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to
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m
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ar
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m
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Fu
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R
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Gr
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e
(
FR
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[
F
R
GS
n
u
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er
:
9
0
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]
u
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d
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tio
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(
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.
RE
F
E
R
E
NC
E
S
[1
]
N.
Y.
P
h
in
g
,
M
.
N.
M
.
W
a
rip
,
P
.
Eh
k
a
n
,
R.
B.
A
h
m
a
d
,
F
.
F
.
Zak
a
ria,
a
n
d
F
.
W
a
h
id
a
,
“
T
o
w
a
rd
s
Hig
h
P
e
rf
o
rm
a
n
c
e
Ne
t
w
o
rk
-
on
-
Ch
ip
:
A
S
u
rv
e
y
o
n
En
a
b
li
n
g
T
e
c
h
n
o
lo
g
ies
,
Op
e
n
Iss
u
e
s
a
n
d
Ch
a
ll
e
n
g
e
s,”
p
p
.
2
5
9
–
2
6
3
,
2
0
1
6
.
[2
]
N.
Y.
P
h
i
n
g
,
M
.
N.
M
o
h
d
W
a
rip
,
P
.
Eh
k
a
n
,
F
.
W
.
Zu
lk
e
f
li
,
a
n
d
R.
B.
A
h
m
a
d
,
“
Per
fo
rm
a
n
c
e
An
a
lys
is
o
f
th
e
Imp
a
c
t
o
f
De
sig
n
Pa
r
a
me
ter
s
to
Ne
two
rk
-
on
-
Ch
i
p
(
No
C)
Arc
h
it
e
c
tu
re
,
”
in
Re
c
e
n
t
T
re
n
d
s
in
In
f
o
rm
a
ti
o
n
a
n
d
Co
m
m
u
n
ica
ti
o
n
T
e
c
h
n
o
lo
g
y
:
P
ro
c
e
e
d
in
g
s
o
f
th
e
2
n
d
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
f
Re
li
a
b
le
In
fo
rm
a
ti
o
n
a
n
d
Co
m
m
u
n
ica
ti
o
n
T
e
c
h
n
o
l
o
g
y
(I
RICT
2
0
17
)
,
F
.
S
a
e
e
d
,
N.
G
a
z
e
m
,
S
.
P
a
tn
a
ik
,
A
.
S
.
S
a
e
d
Ba
laid
,
a
n
d
F
.
M
o
h
a
m
m
e
d
,
Ed
s.
Ch
a
m
:
S
p
ri
n
g
e
r
In
tern
a
ti
o
n
a
l
P
u
b
li
sh
i
n
g
,
2
0
1
8
,
p
p
.
2
3
7
–
2
4
6
.
[3
]
S
.
Ya
n
a
n
d
B.
L
in
,
“
A
p
p
li
c
a
ti
o
n
-
S
p
e
c
if
ic
Ne
t
w
o
rk
-
on
-
Ch
ip
A
rc
h
it
e
c
tu
re
S
y
n
th
e
sis
b
a
se
d
o
n
S
e
t
P
a
rti
t
io
n
s
a
n
d
S
tein
e
r
T
re
e
s,”
p
p
.
2
7
7
–
2
8
2
.
[4
]
S
.
S
.
Bh
o
p
le
a
n
d
M
.
A
.
Ga
ik
wa
d
,
“
De
sig
n
o
f
M
e
sh
a
n
d
T
o
ru
s
To
p
o
lo
g
ies
f
o
r
Ne
t
w
o
rk
-
On
-
Ch
ip
A
p
p
li
c
a
ti
o
n
,
”
v
o
l.
2
,
n
o
.
2
,
p
p
.
7
6
–
8
2
,
2
0
1
3
.
[5
]
N.
Y.
P
h
i
n
g
,
M
.
N.
M
.
W
a
rip
,
P
.
Eh
k
a
n
,
F
.
W
a
h
id
a
,
a
n
d
R.
B.
A
h
m
a
d
,
“
T
o
p
o
lo
g
y
De
sig
n
o
f
Ex
ten
d
e
d
T
o
ru
s
a
n
d
Rin
g
f
o
r
L
o
w
L
a
ten
c
y
Ne
t
w
o
rk
-
on
-
Ch
i
p
A
rc
h
it
e
c
tu
re
,
”
v
o
l.
1
3
,
n
o
.
2
,
2
0
1
5
.
[6
]
N.
Jia
n
g
,
D.
U.
Be
c
k
e
r,
G
.
M
ich
e
lo
g
ian
n
a
k
is,
J.
Ba
lf
o
u
r,
B.
T
o
wle
s,
D.
E.
S
h
a
w
,
J.
Ki
m
,
a
n
d
W
.
J.
Da
ll
y
,
“
A
De
tailed
a
n
d
F
lex
ib
le Cy
c
le
-
Ac
c
u
ra
te Ne
t
w
o
rk
-
on
-
Ch
i
p
S
im
u
lato
r.
”
[7
]
A
.
B.
K
a
h
n
g
,
B.
L
i,
L
.
P
e
h
,
K.
S
a
m
a
d
i,
S
.
Die
g
o
,
a
n
d
L
.
Jo
ll
a
,
“
O
RION
2
.
0
:
A
F
a
st
a
n
d
A
c
c
u
ra
te
No
C
P
o
w
e
r
a
n
d
A
re
a
M
o
d
e
l
f
o
r
Early
-
S
tag
e
De
sig
n
S
p
a
c
e
Ex
p
lo
ra
ti
o
n
,
”
p
p
.
1
–
6.
[8
]
J.
M
a
,
C.
Ha
o
,
W
.
Zh
a
n
g
,
a
n
d
T
.
Yo
sh
im
u
ra
,
“
P
o
w
e
r
-
e
ff
i
c
i
e
n
t
P
a
rti
t
io
n
in
g
a
n
d
Cl
u
ste
r
Ge
n
e
ra
ti
o
n
De
sig
n
f
o
r
A
p
p
li
c
a
ti
o
n
-
S
p
e
c
if
ic Ne
t
w
o
rk
-
on
-
Ch
ip
,
”
p
p
.
8
3
–
8
4
,
2
0
1
6
.
[9
]
J.
M
in
z
h
e
n
g
,
“
F
a
u
lt
-
T
o
lera
n
t
R
o
u
ti
n
g
M
e
th
o
d
o
f
No
C
S
y
ste
m
Ba
s
e
d
o
n
Cl
u
ste
rin
g
,
”
p
p
.
5
4
3
–
5
4
7
,
2
0
1
6
.
[1
0
]
P
.
B.
T
,
“
P
o
w
e
r
M
in
im
iza
ti
o
n
f
o
r
Clu
ste
re
d
R
o
u
ti
n
g
in
Ne
tw
o
rk
o
n
Ch
ip
,
”
n
o
.
Ic
e
c
s,
p
p
.
1
5
8
4
–
1
5
8
8
,
2
0
1
5
.
[1
1
]
S
.
Jo
h
a
ri,
A
.
Ku
m
a
r,
a
n
d
V
.
K.
S
e
h
g
a
l,
“
He
tero
g
e
n
e
o
u
s
a
n
d
Hy
b
rid
Cl
u
ste
re
d
T
o
p
o
lo
g
y
f
o
r
Ne
t
w
o
rk
s
-
on
-
Ch
ip
,
”
p
p
.
1
8
3
–
1
8
7
,
2
0
1
5
.
[1
2
]
R.
K.
S
,
“
Ne
tw
o
rk
-
on
-
Ch
ip
A
rc
h
it
e
c
tu
re
Ba
se
d
o
n
C
lu
ste
r
M
e
t
h
o
d
,
”
v
o
l.
3
,
n
o
.
3
,
p
p
.
6
1
–
6
5
,
2
0
1
5
.
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