Co
m
pu
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er
Science
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nfo
r
m
a
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n T
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Vo
l.
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,
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ar
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20
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2722
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2
74
J
o
ur
na
l ho
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ep
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:
h
ttp
:
//ia
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co
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ex
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An uneven
clust
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nfo
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ticle
his
to
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y:
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J
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ev
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an
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e
n
e
r
g
y
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c
o
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stra
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e
d
wire
les
s
se
n
so
r
n
e
two
r
k
s
(W
S
Ns
)
c
o
m
p
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se
d
o
f
se
n
so
r
n
o
d
e
s
(S
Ns
)
c
h
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ra
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teriz
e
d
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y
m
u
lt
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rit
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ria
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o
n
trad
icto
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y
wit
h
e
a
c
h
o
th
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r,
it
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ll
o
n
e
o
f
t
h
e
c
h
a
ll
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n
g
e
s to
b
e
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g
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re
o
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w t
o
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m
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rit
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ria
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se
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iza
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n
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lg
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m
fo
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g
a
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l
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lu
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se
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ro
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ti
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g
p
r
o
t
o
c
o
l.
In
t
h
is
a
rti
c
le,
we
o
v
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rtu
re
a
n
e
w
ro
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ti
n
g
p
r
o
to
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o
l
b
a
se
d
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n
c
lu
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th
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y
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rid
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S
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VT)
a
n
d
a
n
imp
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d
m
a
x
-
m
in
a
n
t
c
o
l
o
n
y
o
p
ti
m
iza
ti
o
n
(
ACO
)
.
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h
is
sc
h
e
m
e
u
se
s
th
e
h
y
b
ri
d
F
VT
to
p
e
rfo
rm
th
e
c
lu
ste
rin
g
,
a
n
d
u
se
s
a
n
im
p
ro
v
e
d
m
a
x
-
m
in
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to
c
o
n
fi
g
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re
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ro
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ti
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g
t
re
e
fo
r
th
e
re
lay
tran
sm
issio
n
o
f
se
n
se
d
d
a
ta.
Th
e
e
x
ten
si
v
e
sim
u
latio
n
e
x
p
e
rime
n
ts
h
a
v
e
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n
c
a
rried
o
u
t
t
o
s
h
o
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th
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t
th
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p
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se
d
sc
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m
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re
a
tl
y
p
ro
l
o
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g
s
th
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e
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c
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g
a
n
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r
g
y
c
o
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su
m
p
ti
o
n
b
a
lan
c
e
su
p
e
rio
r
to
th
e
p
re
v
i
o
u
s s
c
h
e
m
e
s.
K
ey
w
o
r
d
s
:
C
lu
s
ter
-
r
o
u
te
f
ix
atio
n
Hy
b
r
id
FC
NP
-
VW
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-
T
OP
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I
m
p
r
o
v
ed
m
a
x
-
m
in
AC
O
R
o
u
tin
g
tr
ee
f
o
r
m
atio
n
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ir
eles
s
s
en
s
o
r
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etwo
r
k
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
:
J
in
Sim
Kim
I
n
ter
n
atio
n
al
T
e
ch
n
o
l
o
g
y
C
o
r
p
o
r
atio
n
C
en
ter
,
Kim
C
h
ae
k
Un
iv
er
s
ity
o
f
T
ec
h
n
o
lo
g
y
6
0
Ky
o
g
u
,
Su
n
g
r
i
Stre
et,
Py
o
n
g
y
an
g
,
Dem
o
cr
atic
Peo
p
le
’
s
R
ep
u
b
lic
o
f
Ko
r
ea
E
m
ail: k
js
8
9
2
1
@
s
tar
-
co
.
n
et.
k
p
1.
I
NT
RO
D
UCT
I
O
N
A
m
o
n
g
t
h
e
v
a
r
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o
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s
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t
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p
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o
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o
f
w
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l
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o
r
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tw
o
r
k
s
(
W
S
Ns
)
,
t
h
e
m
o
s
t
at
t
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t
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y
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f
f
i
c
i
en
t
u
t
i
l
i
z
at
i
o
n
[
1
]
.
I
n
g
e
n
e
r
a
l
,
c
l
u
s
t
e
r
-
b
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d
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p
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m
u
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n
W
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s
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ci
f
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c
l
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h
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a
d
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H
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n
o
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f
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t
a
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as
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li
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m
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ti
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p
r
o
a
c
h
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s
,
i
n
c
l
u
d
i
n
g
m
u
l
t
i
-
c
r
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te
r
i
a
d
e
c
is
i
o
n
m
a
k
i
n
g
(
MC
D
M
)
o
r
f
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z
z
y
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g
i
c
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L
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f
o
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u
s
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r
o
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t
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.
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h
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r
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a
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c
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s
,
s
u
c
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F
L
-
b
a
s
e
d
[
2
]
,
u
s
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n
g
t
u
t
o
r
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a
l
MC
DM
m
e
t
h
o
d
s
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k
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n
a
l
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t
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c
h
i
e
r
a
r
c
h
y
p
r
o
c
e
s
s
(
A
HP
)
[
3
]
,
t
e
c
h
n
i
q
u
e
f
o
r
o
r
d
e
r
p
r
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f
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n
c
e
b
y
s
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m
il
ar
i
t
y
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o
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d
e
a
l s
o
l
u
ti
o
n
(
T
O
P
S
I
S
)
[
4
]
,
a
n
d
p
r
e
f
e
r
e
n
c
e
r
a
n
k
i
n
g
o
r
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a
n
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t
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d
f
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h
m
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t
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v
a
l
u
a
t
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o
n
(
P
R
O
M
E
T
H
E
E
)
[
5
]
a
n
d
c
o
m
b
i
n
i
n
g
a
f
e
w
I
O
a
l
g
o
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t
h
m
s
,
f
o
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x
a
m
p
l
e
,
a
n
t
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y
o
p
t
im
i
z
a
t
i
o
n
(
AC
O
)
a
n
d
F
L
[
6
]
.
T
h
e
o
b
j
e
c
t
i
v
e
o
f
t
h
e
c
l
u
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cl
u
s
ter
in
g
b
y
FL
w
h
ich
u
s
es
3
m
u
ltip
le
cr
iter
ia
an
d
b
y
s
elec
t
in
g
th
e
s
u
itab
le
n
e
x
t
r
elay
C
H
n
o
d
e
with
th
e
m
ax
-
m
in
A
C
O
is
s
u
g
g
ested
[
6
]
.
Me
h
ta
an
d
Sax
en
a
[
9
]
p
r
o
p
o
s
ed
a
g
r
id
-
b
ased
clu
s
ter
in
g
m
eth
o
d
,
wh
ic
h
u
s
es
th
r
ee
b
r
o
ad
p
ar
am
eter
s
to
s
elec
t
th
e
C
H
n
o
d
e
b
y
f
u
zz
y
an
aly
ti
c
h
ier
ar
ch
ical
an
al
y
s
is
(
FAHP
)
-
T
OPSIS.
Af
ter
C
H
s
elec
tio
n
,
th
is
s
ch
em
e
u
s
ed
th
e
em
p
er
o
r
p
e
n
g
u
i
n
o
p
tim
izatio
n
(
E
PO)
f
o
r
r
o
u
te
f
i
x
atio
n
.
L
iter
atu
r
e
[
1
0
]
p
r
o
p
o
s
ed
a
m
et
h
o
d
wh
ic
h
ch
o
o
s
es
th
e
o
p
tim
u
m
C
H
ad
o
p
tin
g
th
e
g
en
er
alize
d
in
tu
itio
n
is
tic
f
u
zz
y
s
o
f
t
s
et
ap
p
r
o
ac
h
,
c
o
n
s
tr
u
cti
n
g
th
e
r
o
u
tin
g
tr
ee
with
s
h
ar
k
s
m
ell
o
p
tim
izatio
n
an
d
g
en
etic
alg
o
r
ith
m
(
GA)
.
Gam
al
et
a
l.
[
1
1
]
p
r
o
p
o
s
ed
a
FL
L
E
AC
H
-
b
ased
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
s
ch
em
e,
wh
ich
u
tili
ze
s
h
y
b
r
id
PS
O
an
d
a
K
-
m
ea
n
s
clu
s
ter
in
g
to
f
o
r
m
clu
s
ter
,
an
d
s
elec
ts
th
e
p
r
im
ar
y
C
H
an
d
s
ec
o
n
d
ar
y
C
H
n
o
d
es
u
s
in
g
FL.
I
n
[
1
2
]
,
a
r
o
u
tin
g
m
eth
o
d
b
ased
o
n
E
PO
an
d
Q
-
lear
n
in
g
m
eth
o
d
was
s
u
g
g
ested
f
o
r
u
n
d
er
wate
r
W
SN.
A
h
y
b
r
id
E
PO
m
eth
o
d
was
p
r
o
p
o
s
ed
to
d
ea
l
with
3
is
s
u
es:
lo
ad
b
alan
c
e,
s
ec
u
r
ity
e
n
h
an
ce
m
en
t,
an
d
r
ed
u
cin
g
th
e
e
n
er
g
y
e
x
p
en
d
itu
r
e
[
1
3
]
.
I
n
[
1
4
]
,
t
h
e
W
SN
ar
ch
itectu
r
e
wh
ich
co
n
s
is
ts
o
f
4
s
tag
es
wa
s
s
u
g
g
este
d
.
I
t
is
clea
r
th
at
th
e
r
o
u
tin
g
m
eth
o
d
s
m
en
tio
n
e
d
ab
o
v
e
ad
o
p
ts
eith
er
in
d
iv
id
u
a
l
MCDM
s
o
r
th
e
h
y
b
r
id
FAHP
-
T
OPSIS
f
o
r
C
H
s
elec
tio
n
o
r
en
lis
tin
g
C
Ms
to
C
H
f
o
r
clu
s
ter
in
g
,
an
d
u
s
e
I
O
s
ch
em
es f
o
r
th
e
s
elec
tio
n
o
f
n
ex
t r
elay
C
H
f
o
r
c
o
n
s
tr
u
ctio
n
o
f
th
e
r
o
u
tin
g
tr
ee
.
S
in
g
h
et
a
l.
[
1
5
]
is
p
r
o
p
o
s
ed
a
C
H
n
o
d
e
s
ele
cti
o
n
m
et
h
o
d
t
h
at
ap
p
l
ies
a
h
y
b
r
i
d
GA
u
s
in
g
m
u
ta
ti
o
n
o
p
e
r
at
o
r
b
ase
d
o
n
g
r
ee
d
y
s
t
r
a
t
eg
y
f
o
r
I
o
T
e
n
a
b
l
ed
h
ete
r
o
g
e
n
eo
u
s
W
SNs
.
C
h
a
u
r
asia
a
n
d
K
u
m
ar
[
1
6
]
s
u
g
g
ested
a
n
ew
m
eth
o
d
b
ased
o
n
th
e
a
d
ap
tiv
e
m
eta
-
h
eu
r
is
tic
b
ased
clu
s
ter
in
g
an
d
r
o
u
tin
g
alg
o
r
ith
m
f
o
r
I
o
T
-
ass
is
ted
W
SN
(
AC
R
A
)
to
a
d
d
r
ess
t
h
e
i
s
s
u
es
o
f
d
e
a
d
l
o
c
k
an
d
li
v
e
lo
ck
in
I
o
T
ass
is
te
d
W
SN.
A
b
r
ah
a
m
a
n
d
Va
d
i
v
el
[
1
7
]
p
r
o
p
o
s
ed
a
clu
s
ter
in
g
r
o
u
tin
g
s
ch
em
e,
wh
ich
em
p
lo
y
s
th
e
f
lam
in
g
o
s
ea
r
ch
alg
o
r
ith
m
(
FS
A)
to
p
r
o
ce
ed
s
C
H
n
o
d
e
s
elec
tio
n
an
d
u
s
es
Q
-
le
ar
n
in
g
to
s
elec
t
th
e
r
o
u
tes
f
r
o
m
C
Hs
to
B
S.
I
n
[
1
8
]
,
th
e
s
ea
h
o
r
s
e
o
p
tim
izer
(
SHO)
is
b
len
d
e
d
with
th
e
o
p
p
o
s
itio
n
-
b
ased
lear
n
in
g
(
OB
L
)
an
d
th
e
g
r
ee
d
y
s
elec
tio
n
(
GS)
s
tr
ateg
ies
to
b
e
u
s
ed
in
s
elec
tin
g
C
H
n
o
d
es.
T
an
g
an
d
Nie
[
1
9
]
e
x
p
lo
ited
t
h
e
s
war
m
in
tellig
en
ce
ap
p
r
o
a
ch
to
b
len
d
with
th
e
f
ea
tu
r
es
o
f
W
SN,
an
d
s
u
g
g
ested
a
clu
s
ter
in
g
s
ch
em
e
th
at
u
s
es
th
e
ch
ao
s
P
SO
to
ch
o
o
s
e
th
e
C
H
n
o
d
es.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
3
2
2
1
C
o
m
p
u
t Sci
I
n
f
T
ec
h
n
o
l
,
Vo
l.
7
,
No
.
1
,
M
ar
ch
20
26
:
7
4
-
8
2
76
C
h
au
r
asia
et
a
l
.
[
2
0
]
p
r
o
p
o
s
ed
a
clu
s
ter
in
g
r
o
u
tin
g
p
r
o
to
co
l
ca
lled
E
E
M
-
C
R
P,
wh
ich
em
p
lo
y
s
d
r
ag
o
n
f
ly
alg
o
r
ith
m
to
ch
o
o
s
e
th
e
o
p
ti
m
al
C
H
n
o
d
es
an
d
th
e
r
o
u
tes
f
r
o
m
th
e
s
elec
ted
C
H
s
to
B
S
.
I
n
[
2
1
]
,
in
o
r
d
er
to
ch
o
o
s
e
th
e
o
p
tim
al
C
H
n
o
d
es,
au
th
o
r
s
p
r
o
p
o
s
e
a
h
y
b
r
i
d
alg
o
r
ith
m
ca
lled
f
ir
e
f
l
y
r
e
p
lace
d
p
o
s
itio
n
u
p
d
ate
i
n
d
r
ag
o
n
f
ly
.
W
an
g
et
a
l.
[
2
2
]
s
u
g
g
est
an
en
h
a
n
ce
d
p
elica
n
o
p
tim
izatio
n
alg
o
r
ith
m
(
POA
)
wh
ich
b
le
n
d
s
th
e
L
ev
y
f
lig
h
t
with
t
h
e
o
r
ig
in
al
POA
to
im
p
r
o
v
e
th
e
C
H
n
o
d
e
s
elec
tio
n
p
er
f
o
r
m
a
n
ce
.
Pra
s
a
d
et
a
l.
[
2
3
]
em
p
lo
y
m
u
lti
-
o
b
jectiv
e
o
p
tim
izatio
n
u
s
in
g
r
atio
an
aly
s
is
to
ch
o
o
s
e
th
e
C
H
n
o
d
es,
an
d
u
s
e
th
e
m
in
im
u
m
s
p
an
n
in
g
tr
ee
f
o
r
m
atio
n
m
eth
o
d
b
ased
o
n
m
o
d
if
ied
Dijk
s
tr
a
to
d
ec
r
ea
s
e
in
tr
a
-
clu
s
ter
c
o
m
m
u
n
icatio
n
d
is
tan
ce
a
n
d
t
o
p
ar
titi
o
n
th
e
wo
r
k
lo
ad
o
n
C
M
n
o
d
es
e
v
en
ly
.
B
a
r
n
wa
l
et
a
l
.
[
2
4
]
u
s
es
wh
ale
m
o
t
h
f
l
a
m
e
o
p
ti
m
i
za
t
io
n
m
et
a
-
h
e
u
r
is
ti
c
al
g
o
r
it
h
m
to
ch
o
o
s
e
th
e
C
H
n
o
d
es
a
n
d
e
x
p
l
o
its
i
m
p
r
o
v
e
d
Af
r
i
ca
n
b
u
f
f
al
o
o
p
ti
m
iz
ati
o
n
(
I
AB
O
)
t
o
f
o
r
m
th
e
r
o
u
tes
f
r
o
m
C
H
n
o
d
e
s
t
o
B
S
.
I
n
th
is
ar
tic
le
,
w
e
o
v
e
r
t
u
r
e
a
n
u
n
e
q
u
al
c
lu
s
te
r
i
n
g
r
o
u
ti
n
g
p
r
o
t
o
c
o
l
.
T
h
e
p
r
o
t
o
co
l
a
d
o
p
ts
th
e
h
y
b
r
i
d
FV
T
t
o
c
h
o
o
s
e
a
C
H
n
o
d
e
a
n
d
t
o
e
n
l
is
t
C
Ms
t
o
a
C
H
.
I
t
a
ls
o
a
d
o
p
ts
a
n
im
p
r
o
v
e
d
m
a
x
-
m
i
n
AC
O
wh
ic
h
u
s
es t
h
e
m
u
lti
-
c
r
it
er
ia
’
wei
g
h
ts
al
lo
ca
t
e
d
wit
h
FC
NP
-
VW
A
t
o
est
a
b
lis
h
th
e
r
o
u
te
t
o
B
S
.
3.
S
YST
E
M
M
O
D
E
L
3
.
1
.
Net
w
o
rk
m
o
del
T
h
e
ass
u
m
p
tio
n
s
f
o
r
th
e
co
n
s
id
er
in
g
W
SN a
r
e
as b
elo
w:
i)
T
h
e
co
n
s
id
er
in
g
n
etwo
r
k
h
as N
s
tatio
n
ar
y
SNs
r
an
d
o
m
ly
lo
ca
ted
in
a
r
ec
tan
g
u
lar
d
o
m
ain
an
d
a
f
ix
ed
B
S
th
at
is
n
o
t e
n
er
g
y
-
lim
ited
an
d
a
lo
n
g
way
o
f
f
a
s
u
r
v
eillan
ce
r
eg
io
n
.
ii)
All
SNs
h
av
e
a
b
atter
y
with
th
e
lim
ited
ca
p
ac
itan
ce
wh
ic
h
is
n
o
t
ab
le
t
o
r
ec
h
a
r
g
e
a
n
d
a
u
n
iq
u
e
I
D
.
T
h
ese
n
o
d
es a
r
e
h
eter
o
g
e
n
eo
u
s
an
d
d
o
n
’
t k
n
o
w
th
e
in
f
o
r
m
at
io
n
o
f
t
h
eir
lo
ca
tio
n
s
.
iii)
S
N
s
c
a
n
c
o
n
t
r
o
l
t
h
e
i
r
t
r
a
n
s
m
i
s
s
i
o
n
p
o
w
e
r
i
n
a
c
c
o
r
d
a
n
c
e
w
it
h
th
e
d
i
s
t
a
n
c
e
f
r
o
m
t
h
e
r
ec
e
i
v
e
r
to
t
h
e
m
s
e
l
v
es
.
3
.
2
.
E
nerg
y
e
x
pend
it
ure
m
o
del
W
e
u
s
e
th
e
“f
ir
s
t
-
o
r
d
er
r
ad
i
o
m
o
d
el”
f
o
r
th
e
en
er
g
y
ex
p
en
d
itu
r
e
m
o
d
el.
T
h
e
en
er
g
y
s
p
en
t
f
o
r
tr
an
s
m
itti
n
g
th
e
-
b
it d
ata
is
esti
m
ated
as
in
(
1
)
.
(
,
)
=
{
×
+
×
×
2
<
0
×
+
×
×
4
≥
0
(
1
)
H
er
e,
an
d
ar
e
co
ef
f
icien
ts
o
f
t
h
e
p
r
o
p
ag
atio
n
lo
s
s
,
is
th
e
en
e
r
g
y
s
p
e
n
t
f
o
r
tr
a
n
s
m
itti
n
g
1
-
b
i
t
d
ata,
wh
ile
is
th
e
tr
an
s
m
is
s
io
n
d
is
tan
ce
.
T
h
e
p
o
wer
o
f
d
i
s
s
p
ec
if
ied
b
y
d
an
d
th
e
t
h
r
esh
o
ld
d
is
tan
ce
0
=
√
⁄
=8
7
.
7
m
.
T
h
e
e
n
er
g
y
co
n
s
u
m
e
d
f
o
r
t
h
e
d
ata
r
ec
e
p
tio
n
o
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1
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1
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Ass
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C
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h
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es
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ich
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ly
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o
it
b
y
s
en
d
in
g
J
o
in
_
Msg
(
·
)
.
I
f
th
e
n
o
d
es
r
ec
eiv
e
m
o
r
e
th
an
2
C
H_
Msg
(
·
)
,
th
e
y
jo
in
i
n
th
e
m
o
s
t
p
r
o
p
er
C
H
with
F
VT
as
in
C
H
s
elec
tio
n
.
Su
ch
a
C
H
h
as
th
e
lar
g
est
clo
s
en
ess
v
alu
e
to
t
h
e
p
o
s
itiv
e
id
ea
l
s
o
lu
tio
n
C
i
∗
.
T
h
e
n
o
d
e
w
h
ich
d
o
esn
’
t
r
ec
ei
v
e
ev
e
n
a
s
in
g
le
C
H_
Msg
(
·
)
f
o
r
a
ce
r
tain
p
er
io
d
m
ak
es a
d
ec
lar
atio
n
its
elf
as th
e
C
H.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
3
2
2
1
C
o
m
p
u
t Sci
I
n
f
T
ec
h
n
o
l
,
Vo
l.
7
,
No
.
1
,
M
ar
ch
20
26
:
7
4
-
8
2
78
T
ab
le
4
.
Prio
r
ities
o
f
s
en
s
o
r
n
o
d
e
s
S
e
n
s
o
r
n
o
d
e
∗
0
∗
P
r
e
f
e
r
e
n
c
e
S
N
1
0
.
5
9
6
9
0
.
8
8
1
3
0
.
5
9
6
2
1
S
N
2
0
.
6
1
6
0
0
.
8
5
0
3
0
.
5
7
9
9
2
S
N
3
0
.
8
0
7
8
0
.
7
7
9
1
0
.
4
9
1
0
3
S
N
4
0
.
5
5
8
3
0
.
8
1
5
0
0
.
5
9
3
4
4
S
N
5
0
.
6
6
1
1
0
.
5
7
1
7
0
.
4
6
3
8
5
S
N
6
0
.
0
7
6
6
0
.
4
6
6
6
0
.
3
0
2
4
6
4
.
1
.
3
.
Co
ns
t
ruct
ing
a
ro
uting
t
re
e
T
o
co
n
s
tr
u
ct
a
r
o
u
tin
g
tr
ee
,
C
H
n
o
d
e
s
b
r
o
ad
ca
s
t
Nex
t_
Ho
p
_
C
H_
Msg
(
i,
,
,
,
,
,
,
)
with
in
r
R
i
co
m
p
e
,
h
er
e
r
is
t
h
e
s
m
allest
in
teg
er
wh
ich
allo
ws
an
y
C
H
to
in
clu
d
e
at
least
o
n
e
n
eig
h
b
o
r
C
H
in
ac
co
r
d
an
ce
with
[
1
]
.
is
th
e
n
eig
h
b
o
r
in
g
d
eg
r
ee
o
f
n
o
d
e
i
.
Af
ter
b
r
o
ad
ca
s
tin
g
Nex
tHo
p
_
C
H_
Msg
(
•)
,
all
C
H
s
g
r
asp
f
o
r
war
d
n
eig
h
b
o
r
C
Hs
wh
o
s
e
Di
s
is
s
h
o
r
ter
th
an
o
n
e
o
f
its
elf
.
T
h
en
th
e
im
p
r
o
v
ed
m
a
x
-
m
in
AC
O
s
h
o
wn
b
elo
w
d
eter
m
in
es th
e
n
ex
t h
o
p
C
H
n
o
d
e.
At
th
e
b
eg
in
n
in
g
o
f
th
e
r
o
u
te
estab
lis
h
m
en
t,
ea
ch
an
t
is
p
lace
d
at
C
H
n
o
d
es
with
in
th
e
n
etwo
r
k
an
d
t
h
en
r
a
n
d
o
m
ly
ch
o
o
s
es
th
e
C
H
n
o
d
es
to
v
is
it.
First,
th
e
p
r
o
b
ab
ilit
y
th
at
an
a
n
t
k
p
lace
d
at
C
H
n
o
d
e
i
ch
o
o
s
es
C
H
n
o
d
e
j
is
ca
lcu
lated
.
T
h
en
th
e
v
is
ib
ilit
y
v
alu
e
is
ca
lcu
lated
with
th
e
cr
iter
ia’
weig
h
ts
wh
ich
ar
e
ass
ig
n
ed
b
y
FC
NP
-
VW
A
a
s
in
(
5
)
:
,
=
1
+
2
1
,
+
3
1
(
5
)
I
n
th
e
ab
o
v
e
eq
u
atio
n
,
1
,
2
an
d
3
ar
e
t
h
e
weig
h
ts
o
f
th
e
c
r
iter
i
a
s
u
ch
as
R
E
,
Dis
an
d
E
C
R
allo
ca
ted
b
y
th
e
FC
NP
-
V
W
A,
wh
ile
,
,
an
d
ar
e
th
e
n
o
r
m
alize
d
cr
iter
ia’
v
alu
es
o
f
R
E
,
Dis
an
d
E
C
R
o
f
C
H
n
o
d
e
j
,
r
esp
ec
tiv
el
y
.
Nex
t,
wh
en
th
e
an
ts
s
tar
tin
g
f
r
o
m
ea
ch
C
H
n
o
d
e
ar
r
iv
e
at
th
e
B
S,
we
u
s
e
th
e
ev
alu
atio
n
f
u
n
ctio
n
o
f
(
6
)
to
s
elec
t
m
s
o
lu
tio
n
s
,
i.e
.
,
r
o
u
tes
with
th
e
lar
g
est
ev
alu
atio
n
f
u
n
ctio
n
v
alu
e
in
th
e
cu
r
r
en
t
iter
atio
n
.
T
h
en
,
,
th
e
v
alu
e
o
f
ev
alu
atio
n
f
u
n
ctio
n
f
o
r
th
e
r
o
u
te
with
s
h
o
p
s
wh
ich
an
t
k
f
o
llo
ws,
is
ca
lcu
lated
as
in
(
6
)
t
o
(
8
)
:
=
1
+
δ
1
(
6
)
=
∑
=
1
=
∑
(
1
+
2
1
,
+
3
1
+
4
1
+
5
+
6
1
)
=
1
(
7
)
=
√
1
∑
(
−
1
∑
)
=
1
2
=
1
(
8
)
I
n
th
e
ab
o
v
e
ex
p
r
ess
io
n
s
,
is
t
h
e
weig
h
t
o
f
cr
iter
ia
i
ass
ig
n
e
d
b
y
FC
NP
-
VW
A,
is
th
e
f
o
r
war
d
in
g
co
s
t
o
f
th
e
i
th
h
o
p
.
an
d
ar
e
th
e
f
o
r
war
d
in
g
c
o
s
t
an
d
v
a
r
ian
ce
f
o
r
th
e
r
o
u
te
o
f
an
t
k
,
r
esp
ec
tiv
ely
.
an
d
δ
ar
e
co
n
s
tan
t
co
ef
f
icien
ts
b
etwe
en
0
an
d
1
an
d
+
=
1
.
As
a
r
esu
lt,
th
e
r
o
u
te
with
a
lo
wer
f
o
r
war
d
in
g
co
s
t a
n
d
a
lo
wer
v
ar
ian
ce
h
as a
lar
g
er
ev
al
u
atio
n
f
u
n
ctio
n
v
a
lu
e.
T
h
e
B
S
b
r
o
ad
ca
s
ts
Ph
er
o
m
o
n
e_
Up
d
ate_
Msg
(
)
to
th
e
e
n
tire
n
etwo
r
k
s
o
th
at
th
e
an
ts
f
r
o
m
ea
ch
C
H
n
o
d
e
u
p
d
ate
t
h
e
p
h
er
o
m
o
n
e
o
f
th
e
ed
g
es
o
f
th
e
C
H
n
o
d
es
in
m
r
o
u
tes
with
th
e
lar
g
est
v
alu
e
o
f
th
e
ev
alu
atio
n
f
u
n
ctio
n
am
o
n
g
th
e
t
h
eir
r
o
u
t
es.
T
h
e
C
H
n
o
d
es
th
at
r
ec
eiv
ed
th
is
m
ess
ag
e
ch
an
g
e
th
e
p
h
er
o
m
o
n
e
tr
ail
v
al
u
e
in
[
,
]
to
im
p
r
o
v
e
th
e
co
n
v
e
r
g
en
c
e
r
ate.
At
th
is
tim
e,
we
u
s
e
th
e
ad
ap
tiv
e
ch
an
g
e
r
u
le
o
f
ev
ap
o
r
atio
n
co
ef
f
icien
t
an
d
th
e
r
ewa
r
d
a
n
d
p
u
n
is
h
m
en
t
m
ec
h
an
is
m
f
o
r
en
h
a
n
cin
g
th
e
co
n
v
er
g
e
n
ce
as
in
[
6
]
.
T
h
is
p
r
o
ce
d
u
r
e
is
r
e
p
ea
ted
f
o
r
g
iv
en
s
ev
er
al
iter
atio
n
s
t
o
f
in
d
t
h
e
b
est
n
e
x
t
r
elay
C
H
wh
ich
ev
er
y
C
H
ad
o
p
ts
to
r
elay
d
ata
to
B
S.
I
n
th
is
way
,
all
th
e
C
H
n
o
d
es
d
eter
m
in
e
t
h
e
n
ex
t
h
o
p
C
H
n
o
d
e,
an
d
f
i
n
ally
a
r
o
u
tin
g
tr
ee
f
r
o
m
a
n
y
C
H
n
o
d
e
to
th
e
r
o
o
t
n
o
d
e
B
S is
co
n
s
tr
u
cted
.
4
.
2
.
Da
t
a
g
a
t
hering
ph
a
s
e
I
n
th
e
in
t
r
a
-
clu
s
ter
co
m
m
u
n
ic
atio
n
,
f
o
r
av
o
id
in
g
t
h
e
co
llis
io
n
g
en
e
r
atio
n
if
s
ev
e
r
al
C
Ms
in
a
clu
s
ter
tr
an
s
m
it
th
e
s
en
s
ed
d
ata
to
a
C
H
s
im
u
ltan
eo
u
s
ly
,
th
e
C
H
b
r
o
ad
ca
s
ts
s
ch
ed
u
le_
Msg
(
·
)
m
ess
ag
e
to
its
C
Ms
a
t
th
e
s
tar
t
o
f
th
e
d
ata
g
ath
e
r
i
n
g
s
tag
e
a
n
d
allo
ca
tes
tim
e
s
lo
ts
f
o
r
tr
an
s
m
is
s
io
n
.
T
h
e
C
Ms
wh
ich
o
b
tain
s
ch
ed
u
le
-
Msg
(
·
)
s
en
d
th
e
d
ata
to
th
ei
r
C
H
n
o
d
es
o
n
ly
d
u
r
i
n
g
th
e
tim
e
s
lo
t
allo
ca
ted
to
th
e
m
an
d
th
en
g
et
in
to
th
e
s
leep
m
o
d
e
to
s
av
e
e
n
er
g
y
.
Af
ter
th
e
in
tr
a
-
cl
u
s
ter
c
o
m
m
u
n
icatio
n
,
th
e
i
n
ter
-
clu
s
ter
co
m
m
u
n
icatio
n
b
etwe
en
C
H
n
o
d
es is
p
er
f
o
r
m
ed
th
r
o
u
g
h
t
h
e
co
n
s
tr
u
cte
d
r
o
u
tin
g
tr
ee
.
T
h
e
co
m
p
lex
ity
o
f
th
e
p
r
o
p
o
s
ed
s
ch
em
e
is
th
e
co
m
b
in
atio
n
o
f
th
at
o
f
FVT
an
d
im
p
r
o
v
ed
m
ax
-
m
in
AC
O
i.e
.
,
FC
N
P
-
VW
A
-
m
ax
-
m
in
AC
O.
Sin
ce
th
e
B
S
o
r
SN
s
k
n
o
w
th
e
m
u
lti
-
cr
iter
ia
’
w
eig
h
ts
d
eter
m
in
ed
b
y
Evaluation Warning : The document was created with Spire.PDF for Python.
C
o
m
p
u
t Sci
I
n
f
T
ec
h
n
o
l
I
SS
N:
2722
-
3
2
2
1
A
n
u
n
ev
e
n
clu
s
ter
-
b
a
s
ed
r
o
u
ti
n
g
p
r
o
to
c
o
l fo
r
WS
N
s
u
s
in
g
a
h
yb
r
id
MC
DM a
n
d
…
(
Ma
n
G
u
n
R
i)
79
an
ad
v
a
n
ce
esti
m
ate,
th
e
co
m
p
lex
ity
o
f
FC
NP
-
VW
A
is
n
o
t
in
clu
d
ed
with
in
th
e
to
tal
co
m
p
u
tatio
n
al
o
v
er
h
ea
d
.
T
h
u
s
,
th
e
co
m
b
in
atio
n
o
f
T
O
PS
I
S
an
d
m
a
x
-
m
in
AC
O
d
ete
r
m
in
es
th
e
to
tal
tim
e
c
o
m
p
le
x
ity
o
f
th
e
p
r
o
p
o
s
ed
s
ch
em
e.
T
h
e
p
s
eu
d
o
c
o
d
e
o
f
an
u
n
e
v
en
clu
s
ter
in
g
r
o
u
t
in
g
p
r
o
to
co
l
u
s
in
g
a
h
y
b
r
id
FVT
an
d
im
p
r
o
v
ed
m
ax
-
m
in
AC
O
is
s
h
o
wn
in
Alg
o
r
ith
m
1.
Alg
o
r
ith
m
1
.
A
d
ec
e
n
tr
alize
d
u
n
ev
en
clu
s
ter
-
b
ased
r
o
u
tin
g
p
r
o
to
co
l
u
s
in
g
a
h
y
b
r
id
FVT
an
d
im
p
r
o
v
e
d
m
ax
-
m
in
AC
O
I
n
p
u
t:
Set
o
f
aliv
e
SN
s
,
weig
h
ts
o
f
s
ix
cr
iter
ia
d
eter
m
in
ed
with
FC
NP
-
VW
A,
i
n
itializat
io
n
p
a
r
am
eter
s
f
o
r
m
ax
-
m
in
AC
O
Ou
tp
u
t: A
n
o
p
tim
al
r
o
u
tin
g
tr
e
e
1
:
p
r
o
ce
d
u
r
e
FVE
-
AC
O
-
UC
R
2
:
B
S
b
r
o
ad
ca
s
t
s
B
S_
s
tar
t_
M
s
g
(
·
)
an
d
in
f
o
r
m
s
6
cr
iter
ia’
weig
h
ts
allo
ca
ted
with
FC
NP
-
V
W
A
to
all
SN
s
in
th
e
n
etwo
r
k
;
3
:
Giv
e
an
d
ta
k
e
Hello
_
Msg
(
·
)
b
etwe
en
SN
s
an
d
ac
h
iev
e
cr
i
ter
ia
v
alu
es o
f
n
ei
g
h
b
o
r
in
g
n
o
d
es;
4
: Sele
ct
C
H
n
o
d
es b
y
FVT
an
d
b
r
o
a
d
ca
s
t
C
H_
Msg
(
·
)
wth
in
co
n
test
r
ad
iu
s
;
5
:
J
o
in
s
u
itab
le
C
H
n
o
d
e
b
y
F
VT
an
d
re
p
l
y
to
J
o
in
_
Msg
(
·
)
;
6
:
C
H
n
o
d
es
b
r
o
ad
ca
s
t
Nex
t_
Ho
p
_
C
H
_
Msg
(·)
with
in
r
c
o
m
p
e
i
R
to
k
n
o
w
an
ts
lo
ca
tio
n
co
r
r
esp
o
n
d
in
g
to
th
e
f
o
r
war
d
n
eig
h
b
o
r
in
g
C
H
n
o
d
e
s
;
7
:
wh
ile
t
≤
Ma
x_
I
ter
Do
;
8:
C
alcu
late
v
is
ib
ilit
y
v
alu
e
u
s
in
g
(
5
)
with
t
h
e
cr
iter
ia’
weig
h
ts
ass
ig
n
ed
b
y
FC
NP
-
VW
A
;
9:
C
alcu
late
ev
alu
atio
n
f
u
n
ctio
n
v
alu
es u
s
in
g
(
6
)
-
(
8
)
f
o
r
m
r
o
u
t
es th
at
ea
ch
an
t a
r
r
iv
es to
B
S;
10:
Select
th
e
r
o
u
te
with
th
e
lar
g
e
s
t e
v
alu
atio
n
f
u
n
ctio
n
v
al
u
e;
11:
B
S b
r
o
ad
ca
s
ts
Ph
er
o
m
o
n
e_
U
p
d
ate_
Msg
(
)
to
u
p
d
ate
p
h
er
o
m
o
n
e
o
f
ed
g
es o
f
C
H
n
o
d
es
in
m
r
o
u
te
s
;
1
2
: e
n
d
wh
ile
1
3
: Fo
r
m
th
e
r
o
u
ti
n
g
tr
ee
f
r
o
m
ea
ch
C
H
n
o
d
e
to
B
S;
1
4
: e
n
d
p
r
o
ce
d
u
r
e
5.
P
E
RF
O
RM
A
NCE
E
VA
L
U
AT
I
O
N
5
.
1
.
Sim
ula
t
i
o
n set
up
W
e
p
er
f
o
r
m
e
x
te
n
s
i
v
e
s
i
m
u
lat
i
o
n
s
o
n
Ma
tla
b
t
o
o
l
t
o
ass
ess
th
e
p
e
r
f
o
r
m
an
ce
o
f
t
h
e
s
u
g
g
est
e
d
s
ch
em
e.
I
n
th
e
e
x
t
e
n
s
i
v
e
s
i
m
u
la
ti
o
n
,
t
h
e
p
er
f
o
r
m
a
n
ce
o
f
th
e
s
u
g
g
este
d
s
c
h
e
m
e
n
am
ed
F
VT
-
AC
O
-
UC
R
is
co
m
p
a
r
e
d
t
o
UC
R
[
1
]
.
FV
E
-
UC
R
[
7
]
a
n
d
UC
FIA
[
6
]
.
T
h
e
s
i
m
u
lat
io
n
p
ar
am
ete
r
s
a
r
e
s
et
as
i
n
T
a
b
l
e
5
.
T
h
e
p
a
r
am
ete
r
s
r
el
ate
d
to
t
h
e
im
p
r
o
v
e
d
m
a
x
-
m
i
n
AC
O
ar
e
t
h
e
s
a
m
e
as
t
h
o
s
e
i
n
[
6
]
.
Fi
g
u
r
e
1
s
h
o
ws
t
h
e
e
x
p
e
r
im
e
n
ta
l
n
etw
o
r
k
ar
ea
w
it
h
r
e
d
p
o
in
ts
r
e
p
r
ese
n
t
in
g
h
i
g
h
im
p
o
r
ta
n
c
e
l
o
ca
ti
o
n
s
lik
e
w
ay
s
a
n
d
b
att
le
p
l
ac
es.
I
n
t
h
is
f
i
g
u
r
e,
th
e
ap
p
e
ar
in
g
f
r
eq
u
e
n
cy
o
f
t
h
e
t
ar
g
ets
wi
t
h
i
n
t
h
e
r
e
d
a
r
ea
is
2
t
i
m
es
h
ig
h
er
t
h
a
n
t
h
at
i
n
th
e
o
t
h
er
p
o
s
i
ti
o
n
s
.
T
ab
le
5
.
Simu
latio
n
p
ar
am
eter
s
P
a
r
a
me
t
e
r
V
a
l
u
e
N
e
t
w
o
r
k
s
i
z
e
200
×
200
m
2
N
u
m
o
f
S
N
s
4
0
0
P
o
si
t
i
o
n
o
f
B
S
(
2
5
0
m.
1
0
0
m)
I
n
c
i
p
i
e
n
t
e
n
e
r
g
y
0
.
5
J
D
a
t
a
p
a
c
k
e
t
l
e
n
g
t
h
4
0
0
0
b
i
t
C
o
n
t
r
o
l
p
a
c
k
e
t
l
e
n
g
t
h
2
0
0
b
i
t
5
0
n
J
/
b
i
t
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
a
l
5
.
2
.
Sim
ula
t
i
o
n r
esu
lt
s
a
nd
a
na
ly
s
is
Frist,
th
e
s
im
u
latio
n
in
ter
m
s
o
f
R
E
v
a
r
ian
ce
(
R
E
V)
m
etr
ic
is
co
n
d
u
cted
.
T
h
e
R
E
V
is
u
s
ed
f
o
r
ev
alu
atin
g
th
e
v
a
r
ian
ce
o
f
t
h
e
re
m
ain
in
g
en
e
r
g
y
o
f
all
SN
s
in
th
e
n
etwo
r
k
.
At
th
is
tim
e
,
th
e
d
ea
d
SN
s
ar
e
elim
in
at
ed
f
r
o
m
th
e
R
E
V
c
o
m
p
u
tatio
n
.
Simu
latio
n
r
esu
lts
o
f
R
E
V
ac
co
r
d
in
g
to
th
e
m
a
x
im
u
m
co
m
p
etitio
n
r
ad
iu
s
(
)
in
Fig
u
r
e
2
s
h
o
w
t
h
at
FVT
-
AC
O
-
UC
R
p
r
o
to
co
l
h
as
th
e
s
m
allest
R
E
V
co
m
p
ar
e
d
to
th
e
o
th
er
p
r
o
to
co
ls
.
T
h
e
s
u
g
g
ested
p
r
o
t
o
co
l
f
ir
s
t
d
eter
m
in
es
m
u
lti
-
c
r
iter
ia’
weig
h
ts
with
FC
NP
-
V
W
A,
an
d
th
en
b
ased
o
n
th
ese
ass
ig
n
ed
weig
h
ts
,
co
m
p
letes
th
e
clu
s
ter
in
g
s
tep
with
T
OPSIS,
th
u
s
n
o
t
m
a
g
n
if
y
in
g
th
e
p
er
ce
p
tio
n
o
f
th
e
p
air
wis
e
d
if
f
e
r
en
ce
,
also
s
elec
tin
g
C
H
m
o
r
e
s
u
itab
ly
th
an
FVE
-
UC
R
an
d
UC
FIA
.
I
n
ad
d
itio
n
,
I
n
FVT
-
AC
O
-
UC
R
,
th
e
r
o
u
tin
g
tr
ee
f
r
o
m
C
Hs to
b
ase
s
tatio
n
is
f
o
r
m
ed
b
ased
o
n
th
e
im
p
r
o
v
ed
m
ax
-
m
in
AC
O.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
3
2
2
1
C
o
m
p
u
t Sci
I
n
f
T
ec
h
n
o
l
,
Vo
l.
7
,
No
.
1
,
M
ar
ch
20
26
:
7
4
-
8
2
80
Or
d
er
in
g
th
e
c
o
m
p
ar
e
d
f
o
u
r
p
r
o
to
co
ls
in
ter
m
s
o
f
t
h
e
R
E
V,
FVE
-
UC
R
f
o
llo
ws
th
e
p
r
o
p
o
s
ed
p
r
o
to
co
l,
UC
FIA
th
e
th
ir
d
,
an
d
UC
R
th
e
last
.
Alth
o
u
g
h
UC
FIA
u
s
es
th
e
m
ax
-
m
in
AC
O
f
o
r
th
e
r
o
u
tin
g
tr
ee
co
n
s
tr
u
ctio
n
,
it
c
o
n
d
u
cts
th
e
clu
s
ter
in
g
b
y
FL
a
d
o
p
tin
g
o
n
l
y
3
cr
iter
ia
lik
e
R
E
,
Dis
an
d
n
eig
h
b
o
r
d
eg
r
ee
,
s
o
n
o
t
ch
o
o
s
in
g
th
e
C
H
m
o
r
e
r
ea
s
o
n
ab
ly
th
a
n
FVT
-
AC
O
-
UC
R
an
d
n
o
t
b
alan
cin
g
th
e
e
n
er
g
y
ex
p
en
d
it
u
r
e
as
m
u
ch
as
FVT
-
AC
O
-
UC
R
ca
n
ac
h
iev
e.
Ne
x
t,
th
e
s
im
u
latio
n
in
ter
m
s
o
f
n
etwo
r
k
life
tim
e
(
NL
)
m
etr
ic
wh
ic
h
is
d
en
o
ted
as
th
e
tim
e
till
th
e
f
ir
s
t
SN
d
ies
ac
co
r
d
in
g
to
v
ar
y
in
g
R
max
is
p
er
f
o
r
m
ed
.
F
ig
u
r
e
3
s
h
o
ws
th
e
s
im
u
latio
n
r
esu
lts
o
f
NL
.
Fro
m
th
ese
r
esu
lts
,
we
ca
n
s
e
e
th
at
n
etwo
r
k
life
s
p
an
o
f
FVT
-
AC
O
-
UC
R
is
th
e
lo
n
g
est
f
o
r
all
R
m
ax
.
If
R
m
ax
is
6
0
,
NL
o
f
FVT
-
AC
O
-
U
C
R
is
2
1
3
.
4
4
%,
1
4
5
.
7
4
%
an
d
1
0
5
.
4
4
%
lo
n
g
er
co
m
p
ar
ed
to
UC
R
,
UC
FIA
an
d
FVE
-
UC
R
,
r
esp
ec
tiv
ely
.
FVE
-
UC
R
is
n
ex
t
o
r
d
er
a
n
d
i
s
s
u
p
er
io
r
o
v
er
th
e
c
o
m
p
ar
e
d
p
r
o
to
co
ls
u
n
d
e
r
all
R
m
ax
.
T
h
is
in
d
u
b
itab
ly
in
d
ic
ates
th
at
wh
en
th
e
h
y
b
r
id
MC
DM
is
u
s
ed
f
o
r
th
e
clu
s
ter
-
r
o
u
te
f
ix
atio
n
s
tag
e
o
f
th
e
clu
s
ter
in
g
r
o
u
tin
g
p
r
o
t
o
co
l,
it
is
f
ar
s
u
p
er
io
r
to
th
e
o
th
er
p
r
o
to
c
o
ls
.
T
h
e
f
o
llo
win
g
p
r
o
to
co
l
is
UC
FIA
.
UC
R
h
as
th
e
lo
west
NL
b
ec
au
s
e
th
is
p
r
o
to
c
o
l
u
s
es
th
e
R
E
f
o
r
th
e
C
H
s
elec
tio
n
,
an
d
also
u
s
es
2
cr
iter
ia
o
f
R
E
an
d
Dis
f
o
r
th
e
co
n
s
tr
u
ctio
n
o
f
th
e
r
o
u
tin
g
tr
ee
.
Fig
u
r
e
1
.
E
x
p
er
im
e
n
tal
en
v
ir
o
n
m
en
t f
o
r
s
im
u
latio
n
Fig
u
r
e
2
.
C
o
m
p
a
r
is
o
n
o
f
r
esid
u
al
en
er
g
y
v
ar
ia
n
ce
b
y
v
ar
y
in
g
th
e
m
ax
im
u
m
co
m
p
et
itio
n
r
ad
iu
s
R
m
ax
Fig
u
r
e
3
.
C
o
m
p
a
r
is
o
n
o
f
n
etw
o
r
k
life
tim
e
b
y
v
ar
y
in
g
R
max
6.
CO
NCLU
SI
O
N
T
h
e
in
ten
tio
n
o
f
o
p
tim
um
d
es
ig
n
co
m
b
i
n
in
g
th
e
h
y
b
r
id
MCDM
with
m
eta
-
h
eu
r
is
tic
alg
o
r
ith
m
s
ca
n
b
e
ef
f
ec
t
u
all
y
a
d
o
p
te
d
ev
en
wh
en
f
r
ee
ly
ch
o
o
s
in
g
o
th
er
m
u
lti
-
cr
iter
ia.
I
n
t
h
is
p
ap
er
,
an
en
er
g
y
-
ef
f
icien
t
clu
s
ter
in
g
r
o
u
tin
g
p
r
o
to
co
l is su
g
g
ested
,
in
wh
ich
it e
m
p
lo
y
s
a
h
y
b
r
id
FVT
to
c
h
o
o
s
e
th
e
C
H
n
o
d
es a
n
d
f
o
r
m
s
th
e
r
o
u
tes
to
B
S
b
y
ap
p
ly
in
g
th
e
im
p
r
o
v
ed
m
a
x
-
m
in
AC
O.
T
h
e
p
r
o
p
o
s
ed
p
r
o
t
o
co
l
p
r
o
l
o
n
g
s
th
e
NL
u
p
to
2
1
3
.
4
4
%,
1
4
5
.
7
4
%
an
d
1
0
5
.
4
4
%
in
co
m
p
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[
1
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