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I
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4864
I
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lato
r
2
(
NS2
)
s
i
m
u
latio
n
s
,
ac
co
m
p
a
n
ied
b
y
s
tati
s
tical
a
n
a
l
y
s
e
s
a
n
d
a
s
e
n
s
it
iv
i
t
y
s
t
u
d
y
t
h
at
d
e
m
o
n
s
tr
ate
th
e
r
o
b
u
s
tn
e
s
s
an
d
s
u
p
er
io
r
it
y
o
f
th
is
ap
p
r
o
ac
h
o
v
er
tr
ad
itio
n
al
m
et
h
o
d
s
.
T
h
e
r
em
ain
d
er
o
f
th
is
p
ap
er
is
o
r
g
an
ized
as
f
o
llo
w
s
:
s
ec
tio
n
2
r
ev
ie
w
s
r
elate
d
w
o
r
k
.
Sectio
n
3
p
r
esen
ts
an
o
v
er
v
ie
w
o
f
t
h
e
p
r
o
p
o
s
ed
s
y
s
te
m
.
Sec
tio
n
4
d
etails
th
e
c
h
ar
ac
ter
is
tic
s
an
d
co
m
p
o
n
e
n
t
s
o
f
th
e
p
r
o
p
o
s
ed
p
r
o
to
co
l.
Sectio
n
5
d
escr
ib
es
its
s
i
m
u
la
tio
n
an
d
ev
alu
ates
it
s
ef
f
ec
ti
v
en
e
s
s
.
Fin
all
y
,
s
ec
tio
n
6
co
n
clu
d
es t
h
e
p
ap
er
.
2.
RE
L
AT
E
D
WO
RK
S
Ma
n
y
r
esear
ch
er
s
h
a
v
e
s
tu
d
ie
d
en
er
g
y
r
ed
u
ctio
n
i
n
W
SNs
,
lead
in
g
to
t
h
e
d
ev
elo
p
m
e
n
t
o
f
v
ar
io
u
s
r
o
u
tin
g
p
r
o
to
co
ls
.
T
h
ese
p
r
o
t
o
co
ls
ar
e
g
en
er
all
y
cla
s
s
i
f
ied
in
to
f
o
u
r
ca
te
g
o
r
ies:
h
ier
ar
ch
ical,
d
ata
-
ce
n
tr
ic,
lo
ca
tio
n
-
b
ased
,
a
n
d
n
et
w
o
r
k
f
lo
w
-
b
ased
[
1
1
]
,
[
1
2
]
.
T
h
is
p
ap
er
f
o
cu
s
es
o
n
h
ier
ar
ch
ical
p
r
o
to
co
ls
,
w
h
ich
ai
m
to
o
p
tim
ize
d
ata
r
o
u
tin
g
to
th
e
b
ase
s
tatio
n
(
B
S)
w
h
i
le
i
m
p
r
o
v
in
g
en
er
g
y
e
f
f
icie
n
c
y
.
Am
o
n
g
th
e
s
e
p
r
o
to
co
ls
,
L
E
AC
H
[
1
3
]
,
T
E
E
N
[
9
]
,
an
d
HE
E
D
[
1
4
]
ad
j
u
s
t
CH
s
elec
tio
n
b
ased
o
n
n
o
d
e
en
er
g
y
lev
els
a
n
d
n
et
w
o
r
k
ch
ar
ac
ter
is
tic
s
.
T
h
e
KNN
alg
o
r
ith
m
h
a
s
b
ee
n
in
teg
r
ated
in
to
s
o
m
e
p
r
o
to
co
ls
to
o
p
tim
ize
C
H
s
e
lectio
n
a
n
d
ex
ten
d
n
et
w
o
r
k
li
f
eti
m
e.
Fo
r
ex
a
m
p
l
e,
its
ap
p
licatio
n
to
th
e
T
E
E
N
p
r
o
t
o
co
l
h
as
en
ab
led
b
etter
e
n
er
g
y
m
a
n
ag
e
m
e
n
t
th
r
o
u
g
h
m
o
r
e
e
f
f
ic
ien
t
C
H
s
elec
tio
n
[
1
5
]
.
Oth
er
ap
p
r
o
ac
h
es
h
a
v
e
co
m
b
i
n
ed
KNN
w
it
h
m
eta
h
e
u
r
is
tic
alg
o
r
ith
m
s
to
i
m
p
r
o
v
e
n
o
d
e
p
lace
m
e
n
t,
alth
o
u
g
h
th
i
s
lead
s
to
in
cr
ea
s
ed
co
m
p
u
ta
tio
n
al
co
m
p
lex
i
t
y
an
d
m
o
r
e
co
m
p
le
x
d
ea
d
n
o
d
e
m
an
a
g
e
m
en
t [
1
6
].
B
ey
o
n
d
en
er
g
y
o
p
ti
m
izatio
n
,
th
e
KNN
alg
o
r
ith
m
h
as
al
s
o
b
ee
n
ex
p
lo
ited
f
o
r
W
SN
s
ec
u
r
it
y
,
p
ar
ticu
lar
l
y
i
n
in
tr
u
s
io
n
d
etec
t
io
n
[
1
7
]
.
So
m
e
s
t
u
d
ies
h
a
v
e
i
m
p
le
m
e
n
ted
h
y
b
r
id
m
o
d
els
co
m
b
in
i
n
g
KNN
a
n
d
o
th
er
m
ac
h
in
e
lear
n
i
n
g
tec
h
n
i
q
u
es to
en
h
an
ce
c
y
b
er
s
ec
u
r
it
y
an
d
r
ed
u
ce
n
et
w
o
r
k
v
u
l
n
er
ab
il
ities
[
1
8
].
Fu
r
t
h
er
m
o
r
e,
ad
v
an
ce
d
ap
p
r
o
ac
h
es
h
a
v
e
b
ee
n
p
r
o
p
o
s
ed
to
s
i
m
u
lta
n
eo
u
s
l
y
i
m
p
r
o
v
e
th
e
s
ec
u
r
it
y
a
n
d
en
er
g
y
ef
f
icie
n
c
y
o
f
W
SNs
.
T
h
e
HM
R
P
-
I
W
SN,
w
h
ic
h
co
m
b
in
e
s
d
ee
p
n
eu
r
al
n
e
t
w
o
r
k
s
w
ith
a
n
en
er
g
y
-
ef
f
icien
t r
o
u
ti
n
g
p
r
o
to
co
l,
h
as d
em
o
n
s
tr
ated
a
s
i
g
n
if
ican
t i
m
p
r
o
v
e
m
en
t i
n
o
v
er
all
n
et
w
o
r
k
p
er
f
o
r
m
a
n
ce
[
19
].
Mu
lti
-
o
b
j
ec
tiv
e
o
p
tim
iza
tio
n
h
as
also
b
ee
n
s
tu
d
ied
to
b
al
an
ce
m
u
ltip
le
cr
i
ter
ia
s
u
ch
a
s
en
er
g
y
ef
f
icien
c
y
,
late
n
c
y
,
a
n
d
tr
an
s
m
is
s
io
n
r
eliab
ilit
y
[
2
0
]
,
[
1
2
]
.
Fin
a
ll
y
,
m
ac
h
i
n
e
lear
n
in
g
t
ec
h
n
iq
u
es
s
u
ch
a
s
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
e
s
(
S
VM
)
h
av
e
b
ee
n
ap
p
lied
to
i
m
p
r
o
v
e
C
H
s
e
lectio
n
a
n
d
o
p
tim
ize
e
n
er
g
y
m
an
a
g
e
m
e
n
t
o
f
W
SNs
[
2
1
]
.
T
h
ese
ad
v
an
ce
s
s
h
o
w
t
h
at
ar
t
if
icial
in
telli
g
en
ce
p
la
y
s
a
k
e
y
r
o
le
in
i
m
p
r
o
v
in
g
W
SNs
,
o
p
en
in
g
th
e
w
a
y
to
n
e
w
p
er
s
p
ec
tiv
e
s
i
n
o
p
ti
m
izatio
n
an
d
s
ec
u
r
it
y
.
3.
DE
SCR
I
P
T
I
O
N
O
F
T
H
E
S
YST
E
M
A
co
m
p
lete
d
escr
ip
tio
n
o
f
t
h
e
m
o
d
el
o
f
o
u
r
p
r
o
p
o
s
ed
s
y
s
te
m
w
ill
b
e
p
r
esen
ted
i
n
th
i
s
s
e
ctio
n
.
T
h
e
n
et
w
o
r
k
m
o
d
el
w
ill
b
e
p
r
ese
n
ted
f
ir
s
t,
t
h
e
n
t
h
e
en
er
g
y
co
n
s
u
m
p
tio
n
m
o
d
el,
b
e
f
o
r
e
d
ef
in
i
n
g
th
e
k
e
y
co
n
ce
p
ts
an
d
ass
u
m
p
tio
n
s
u
n
d
er
l
y
i
n
g
t
h
is
s
t
u
d
y
.
3
.
1
.
Net
wo
rk
m
o
del
T
h
e
p
r
o
p
o
s
ed
p
r
o
to
c
o
l
tar
g
ets
n
o
n
-
d
y
n
a
m
ic
n
et
w
o
r
k
s
co
m
p
o
s
ed
o
f
a
B
S
an
d
n
s
tat
ic
s
en
s
o
r
n
o
d
es.
T
h
e
W
SN
is
d
e
p
lo
y
ed
o
n
an
x
an
d
y
p
lan
e.
S
tatic
B
S
co
llects
d
ata
f
r
o
m
n
r
an
d
o
m
l
y
d
is
tr
i
b
u
ted
s
en
s
o
r
n
o
d
es
th
at
ar
e
r
esp
o
n
s
ib
le
f
o
r
s
en
s
i
n
g
an
d
in
f
o
r
m
a
tio
n
co
llectio
n
.
Fo
r
n
et
w
o
r
k
s
i
m
u
latio
n
,
al
l
s
en
s
o
r
s
h
a
v
e
t
h
e
s
a
m
e
tec
h
n
i
ca
l
ch
ar
ac
ter
is
t
ics
(
s
a
m
e
e
n
er
g
y
lev
e
ls
,
s
a
m
e
p
r
o
ce
s
s
i
n
g
an
d
co
m
m
u
n
icatio
n
ca
p
ab
ilit
ies).
A
ll
n
o
d
es
k
n
o
w
t
h
eir
p
o
s
itio
n
an
d
ca
n
c
o
n
tr
o
l
th
eir
e
n
er
g
y
in
o
r
d
er
to
ag
g
r
e
g
ate
d
ata
as
m
u
ch
a
s
CH
.
T
h
e
B
S
is
a
s
s
u
m
ed
to
h
a
v
e
u
n
li
m
ited
co
m
p
u
ti
n
g
p
o
w
er
a
n
d
r
eso
u
r
ce
s
,
allo
w
in
g
d
ir
ec
t c
o
m
m
u
n
icat
io
n
w
it
h
all
n
o
d
es.
3
.
2
.
M
o
del o
f
ener
g
y
co
ns
um
p
t
io
n
T
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
u
s
e
s
a
s
i
m
ilar
en
er
g
y
co
n
s
u
m
p
t
io
n
ap
p
r
o
ac
h
t
o
L
E
A
C
H
[
2
2
]
-
[2
5
]
.
I
t
d
if
f
er
e
n
tiate
s
t
w
o
co
m
m
u
n
ica
tio
n
s
ce
n
ar
io
s
b
ased
o
n
t
h
e
d
is
tan
ce
b
et
w
ee
n
n
o
d
es.
W
h
en
t
h
e
d
i
s
ta
n
ce
to
b
e
tr
an
s
m
itted
i
s
b
e
y
o
n
d
t
h
e
t
h
r
e
s
h
o
ld
0
,
th
e
m
o
d
el
ta
k
es
in
to
a
cc
o
u
n
t
s
i
g
n
al
r
e
f
lectio
n
a
n
d
s
ca
tter
in
g
ef
f
ec
t
s
.
C
o
n
v
er
s
el
y
,
f
o
r
d
is
tan
ce
s
les
s
th
an
0
,
a
f
r
ee
-
s
p
ac
e,
o
b
s
tacle
-
f
r
ee
en
v
ir
o
n
m
e
n
t
is
as
s
u
m
ed
[
2
6
]
,
[
2
7
]
.
T
h
e
th
r
es
h
o
ld
is
ca
lcu
la
ted
u
s
i
n
g
(
1
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t
I
SS
N:
2089
-
4864
A k
-
n
ea
r
est n
eig
h
b
o
r
s
a
lg
o
r
ith
m
fo
r
en
h
a
n
ce
d
clu
s
teri
n
g
in
w
ir
ele
s
s
s
en
s
o
r
n
etw
o
r
k
…
(
A
d
il Hilma
n
i
)
607
0
=
√
ℇ
ℇ
(
1
)
w
h
er
e
ℇ
an
d
ℇ
d
en
o
te
th
e
a
m
p
li
f
i
ca
tio
n
f
ac
to
r
s
o
f
t
h
e
m
o
d
el
i
n
b
o
th
ca
s
es a
cc
o
r
d
in
g
to
t
h
r
esh
o
ld
0
.
is
th
e
e
n
er
g
y
co
n
s
u
m
ed
d
u
r
in
g
th
e
tr
an
s
m
i
s
s
io
n
o
f
m
b
its
i
n
a
p
ath
d
:
=
{
+
ℇ
2
,
<
0
+
ℇ
4
,
≥
0
(
2
)
w
h
er
e
is
t
h
e
en
er
g
y
co
n
s
u
m
e
d
to
s
en
d
o
r
r
ec
eiv
e
a
b
it.
In
(
3
)
r
ep
r
esen
ts
t
h
e
r
ec
ep
tio
n
en
er
g
y
o
f
m
b
it
s
it is
t
h
e
e
n
er
g
y
co
n
s
u
m
ed
.
=
(
3
)
4.
PR
O
P
O
SE
D
P
RO
T
O
CO
L
T
h
e
p
r
o
t
o
co
l
w
e
p
r
o
p
o
s
e
is
s
tr
u
ctu
r
ed
i
n
to
th
r
ee
p
r
i
m
ar
y
s
te
p
s
:
i)
clu
s
ter
in
g
p
r
o
ce
s
s
,
ii)
CH
elec
tio
n
,
an
d
iii)
d
ata
co
llectio
n
an
d
co
m
m
u
n
icatio
n
.
T
h
ese
s
tep
s
co
llectiv
el
y
i
m
p
r
o
v
e
t
h
e
n
e
t
w
o
r
k
tr
a
n
s
m
i
s
s
io
n
ef
f
icien
c
y
b
y
u
til
izin
g
cl
u
s
ter
i
n
g
,
r
ed
u
ci
n
g
en
er
g
y
d
is
s
ip
atio
n
an
d
co
n
s
o
lid
atin
g
d
ata
to
p
r
ep
ar
e
it f
o
r
s
en
d
in
g
.
T
h
e
co
llected
in
f
o
r
m
a
tio
n
i
s
f
i
n
all
y
tr
an
s
m
itted
to
t
h
e
B
S
v
ia
o
p
ti
m
ized
in
tr
a
-
cl
u
s
t
er
an
d
in
ter
-
cl
u
s
ter
co
m
m
u
n
icatio
n
p
at
h
s
.
4
.
1
.
Clus
t
er
ing
pro
ce
s
s
C
lu
s
ter
i
n
g
i
s
a
cr
itical
s
tep
f
o
r
o
p
ti
m
izi
n
g
e
n
er
g
y
co
n
s
u
m
p
tio
n
i
n
W
SNs
.
T
h
is
s
te
p
in
v
o
l
v
es
g
r
o
u
p
in
g
n
et
w
o
r
k
n
o
d
es
in
to
clu
s
ter
s
u
s
i
n
g
t
h
e
KN
N
al
g
o
r
ith
m
.
T
h
e
cl
u
s
ter
i
n
g
p
r
o
ce
s
s
i
n
v
o
l
v
es
s
e
v
er
al
k
e
y
s
tep
s
,
in
cl
u
d
in
g
d
is
tan
ce
ca
lc
u
latio
n
,
KNN
s
elec
t
io
n
,
clu
s
t
er
in
itializatio
n
,
an
d
n
o
d
e
ass
ig
n
m
e
n
t
to
clu
s
ter
s
,
w
h
ic
h
w
ill b
e
d
etailed
b
elo
w
.
T
h
e
f
ir
s
t
s
tep
is
to
m
ea
s
u
r
e
th
e
d
is
tan
ce
b
et
w
ee
n
ea
ch
n
o
d
e
an
d
th
e
o
th
er
n
o
d
es
in
th
e
n
et
w
o
r
k
.
T
h
e
d
is
tan
ce
b
et
w
ee
n
t
w
o
n
o
d
es
an
d
,
w
it
h
t
h
eir
r
esp
ec
ti
v
e
p
o
s
itio
n
s
=
(
,
)
an
d
=
(
,
)
.
T
h
e
d
is
tan
ce
b
et
w
ee
n
t
w
o
n
o
d
es
an
d
is
g
i
v
e
n
b
y
(
4
)
:
(
,
)
=
√
(
−
)
2
+
(
−
)
2
(
4
)
On
ce
th
e
d
is
ta
n
ce
s
b
et
w
ee
n
a
ll
n
o
d
es
ar
e
ca
lcu
lated
,
ea
ch
n
o
d
e
s
elec
ts
its
KNN
.
E
ac
h
n
o
d
e
m
u
s
t
f
ir
s
t
ca
lc
u
late
th
e
co
s
t
f
u
n
ctio
n
(
,
)
f
o
r
ea
ch
o
t
h
er
n
o
d
e
in
th
e
n
et
w
o
r
k
,
w
h
er
e
≠
.
T
h
is
co
s
t
f
u
n
ctio
n
ta
k
es
in
to
ac
co
u
n
t
as
cr
iter
i
a
th
e
d
i
s
ta
n
ce
b
et
w
ee
n
n
o
d
es
an
d
t
h
e
r
e
m
ai
n
i
n
g
e
n
er
g
y
.
On
ce
th
e
co
s
ts
ar
e
ca
lcu
lated
,
th
e
n
o
d
e
s
o
r
ts
th
ese
v
a
lu
e
s
in
asce
n
d
in
g
o
r
d
er
.
T
h
en
,
it
s
elec
ts
t
h
e
K
n
o
d
es
h
av
i
n
g
th
e
K
-
lo
w
es
t c
o
s
ts
.
=
{
,
≠
,
(
,
)
ℎ
}
(
5
)
(
,
)
=
e
xp
(
(
,
)
)
+
e
xp
(
|
−
|
)
(
6
)
w
h
er
e
r
ep
r
esen
ts
t
h
e
s
et
o
f
KN
N
o
f
,
(
,
)
is
t
h
e
d
is
ta
n
ce
b
et
w
ee
n
n
o
d
es
an
d
,
an
d
ar
e
th
e
en
er
g
ie
s
o
f
t
h
e
n
o
d
es
an
d
.
On
ce
ea
ch
n
o
d
e
h
as
ca
lcu
late
d
its
KNN
,
th
e
n
ex
t
p
h
ase
is
to
in
itialize
th
e
clu
s
ter
s
.
T
h
e
id
ea
is
to
r
an
d
o
m
l
y
ch
o
o
s
e
K
n
o
d
es
as
clu
s
ter
ce
n
ter
s
.
T
h
ese
n
o
d
es
w
i
ll
b
e
t
h
e
r
ep
r
esen
tati
v
e
n
o
d
es
o
r
ce
n
tr
o
id
s
o
f
th
eir
r
esp
ec
tiv
e
cl
u
s
ter
s
.
T
h
e
ch
o
ice
o
f
clu
s
ter
ce
n
ter
s
is
es
s
e
n
tial
f
o
r
th
e
p
r
o
p
er
f
u
n
ctio
n
i
n
g
o
f
t
h
e
alg
o
r
it
h
m
.
On
ce
th
e
clu
s
ter
ce
n
ter
s
ar
e
in
itialized
,
it
is
n
ec
es
s
ar
y
to
ass
i
g
n
ea
c
h
n
o
d
e
to
th
e
clu
s
te
r
w
h
o
s
e
ce
n
ter
is
clo
s
est.
T
h
is
ass
ig
n
m
en
t
is
d
o
n
e
u
s
in
g
th
e
d
is
ta
n
ce
b
et
w
ee
n
ea
ch
n
o
d
e
an
d
th
e
cl
u
s
ter
ce
n
ter
s
.
No
d
e
is
ass
i
g
n
ed
to
clu
s
ter
k
f
o
r
w
h
ich
th
e
d
i
s
tan
ce
i
s
m
in
i
m
a
l (
7
)
.
(
)
=
a
r
g
(
,
)
(
7
)
w
h
er
e
(
)
is
t
h
e
clu
s
ter
to
w
h
ic
h
n
o
d
e
is
ass
i
g
n
ed
an
d
is
t
h
e
ce
n
ter
o
f
th
e
clu
s
ter
k
.
Af
ter
th
e
i
n
itia
l
ass
i
g
n
m
e
n
t
o
f
n
o
d
es
to
clu
s
ter
s
b
ased
o
n
th
e
p
r
o
x
i
m
it
y
o
f
t
h
e
ce
n
ter
s
,
t
h
e
clu
s
ter
s
m
a
y
n
o
t
b
e
o
p
ti
m
al.
T
o
ad
d
r
e
s
s
t
h
i
s
is
s
u
e,
t
h
e
p
r
o
ce
s
s
o
f
as
s
ig
n
i
n
g
n
o
d
es
a
n
d
u
p
d
atin
g
ce
n
ter
s
i
s
iter
ated
.
At
ea
ch
iter
atio
n
,
th
e
ce
n
ter
s
o
f
t
h
e
cl
u
s
ter
s
ar
e
r
ec
alcu
lated
b
y
tak
i
n
g
th
e
av
er
a
g
e
o
f
t
h
e
p
o
s
itio
n
s
o
f
t
h
e
n
o
d
es
ass
i
g
n
ed
to
th
e
m
(
8
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4864
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
d
ed
Sy
s
t
,
Vo
l.
14
,
No
.
3
,
No
v
e
m
b
er
2
0
2
5
:
605
-
613
608
=
(
1
|
|
∑
,
1
|
|
∑
∈
∈
)
(
8
)
w
h
er
e
is
th
e
ce
n
ter
o
f
th
e
cl
u
s
ter
k
,
|
|
in
d
icate
s
h
o
w
m
a
n
y
n
o
d
es
ar
e
in
th
e
cl
u
s
ter
k
,
a
n
d
(
,
)
ar
e
p
o
s
itio
n
o
f
t
h
e
n
o
d
e
d
e
in
th
e
clu
s
ter
.
T
h
e
clu
s
ter
u
p
d
ate
p
r
o
ce
s
s
(
r
ea
s
s
ig
n
in
g
n
o
d
es
an
d
r
ec
alcu
latin
g
ce
n
ter
s
)
is
r
ep
ea
ted
u
n
til
th
e
clu
s
ter
s
n
o
lo
n
g
er
ch
a
n
g
e,
i.e
.
,
n
o
d
es
n
o
l
o
n
g
er
ch
an
g
e
clu
s
ter
s
in
th
e
n
e
x
t
it
er
atio
n
.
T
h
is
s
tab
ilizatio
n
cr
iter
io
n
en
s
u
r
es t
h
at
t
h
e
clu
s
ter
i
n
g
i
s
o
p
ti
m
al.
4
.
2
.
T
he
clus
t
er
hea
d
elec
t
io
n
T
o
o
p
tim
ize
p
o
w
er
co
n
s
u
m
p
t
io
n
in
W
SNs
,
o
u
r
p
ap
er
p
r
o
p
o
s
es
an
e
f
f
icie
n
t
m
eth
o
d
f
o
r
s
elec
tin
g
C
Hs.
T
h
e
s
elec
tio
n
p
r
o
ce
s
s
is
b
ased
o
n
th
r
ee
k
ey
cr
it
er
ia:
th
e
n
o
d
e’
s
en
er
g
y
r
eser
v
e
,
it
s
s
p
atial
ce
n
tr
alit
y
w
it
h
i
n
t
h
e
cl
u
s
ter
,
an
d
it
s
co
m
m
u
n
icatio
n
lo
ad
.
T
h
ese
f
ac
to
r
s
ar
e
co
m
b
i
n
ed
in
to
a
f
it
n
ess
f
u
n
ctio
n
,
w
h
ic
h
co
m
p
u
tes a
s
co
r
e
f
o
r
ea
ch
n
o
d
e,
as d
ef
in
ed
in
(
9
)
:
(
)
=
+
−
(
9)
w
h
er
e
is
th
e
en
er
g
y
r
eser
v
e
o
f
n
o
d
e
i
an
d
is
th
e
s
tar
ti
n
g
en
er
g
y
(
u
s
ed
f
o
r
n
o
r
m
a
liz
atio
n
)
.
r
ep
r
esen
ts
th
e
s
p
atial
ce
n
tr
alit
y
o
f
n
o
d
e
iii
w
it
h
i
n
its
cl
u
s
ter
an
d
is
ca
lcu
lated
as
(
1
0
)
:
=
−
1
|
|
∑
(
,
)
∈
(
10)
w
h
er
e
is
t
h
e
s
et
o
f
n
o
d
es
in
c
lu
s
ter
K,
(
,
)
is
t
h
e
d
is
tan
ce
b
et
wee
n
n
o
d
e
i
an
d
n
o
d
e
j
,
an
d
|
|
is
th
e
to
tal
n
u
m
b
er
o
f
n
o
d
es
in
t
h
e
clu
s
ter
.
T
h
e
co
m
m
u
n
icatio
n
lo
ad
is
d
ef
in
ed
as
th
e
n
u
m
b
e
r
o
f
n
o
d
es
w
i
th
w
h
ic
h
i c
o
m
m
u
n
icate
s
,
g
i
v
e
n
b
y
(
1
1
)
:
=
∑
(
(
,
)
≤
)
∈
,
≠
(
1
1
)
w
h
er
e
is
th
e
co
m
m
u
n
icatio
n
r
an
g
e
t
h
r
esh
o
ld
,
an
d
(
)
is
an
i
n
d
icato
r
f
u
n
ctio
n
t
h
at
eq
u
al
s
1
if
j
is
w
it
h
i
n
t
h
e
co
m
m
u
n
icat
io
n
r
an
g
e
o
f
i,
an
d
0
o
th
er
w
is
e.
Af
ter
ca
lc
u
lati
n
g
th
e
f
i
tn
e
s
s
s
co
r
es
f
o
r
all
n
o
d
es
w
i
th
i
n
a
cl
u
s
ter
,
t
h
e
n
o
d
e
w
it
h
t
h
e
h
i
g
h
e
s
t
s
co
r
e
i
s
ch
o
s
en
a
s
th
e
CH
:
=
a
r
g
∈
_
(
)
(
1
2
)
T
h
is
ap
p
r
o
ac
h
en
ab
les
d
y
n
a
m
ic
s
elec
tio
n
o
f
C
Hs
b
ased
p
r
im
ar
il
y
o
n
e
n
er
g
y
r
eser
v
e
,
w
h
i
ch
en
h
a
n
ce
s
e
n
er
g
y
m
an
a
g
e
m
e
n
t a
n
d
p
r
o
lo
n
g
s
t
h
e
n
et
w
o
r
k
’
s
o
p
er
atio
n
al
li
f
eti
m
e
.
4
.
3
.
Da
t
a
c
o
llect
io
n a
nd
co
m
m
u
nica
t
io
n
Ou
r
p
ap
er
p
r
esen
ts
an
o
p
ti
m
iz
ed
m
e
th
o
d
f
o
r
d
ata
ag
g
r
eg
atio
n
an
d
tr
an
s
m
is
s
io
n
i
n
cl
u
s
ter
e
d
W
SNs
to
en
h
a
n
ce
en
er
g
y
e
f
f
icie
n
c
y
an
d
n
et
w
o
r
k
lo
n
g
ev
it
y
.
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
e
m
p
lo
y
s
a
m
u
lti
-
h
o
p
co
m
m
u
n
icatio
n
s
tr
ate
g
y
w
h
er
e
C
Hs
r
ela
y
d
ata
to
th
e
B
S
w
h
ile
co
n
s
id
er
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,
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(
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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f
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609
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
9
-
4864
I
n
t J
R
ec
o
n
f
i
g
u
r
ab
le
&
E
m
b
ed
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Sy
s
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,
Vo
l.
14
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[
1
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A
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d
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p
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:
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[
5
]
R
.
B
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i
,
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K
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.
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6
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P
.
M
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w
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D
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