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Sep
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20
25
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41
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al
clu
s
ter
m
em
b
er
n
o
d
es,
cr
ea
tin
g
a
h
ie
r
ar
ch
ical
s
tr
u
ctu
r
e.
Sen
s
in
g
d
ata
f
r
o
m
th
e
g
ath
er
e
d
ad
jace
n
t
r
e
g
io
n
an
d
s
en
d
in
g
it
to
th
e
clu
s
ter
h
ea
d
n
o
d
e
is
th
e
r
esp
o
n
s
ib
ilit
y
o
f
th
e
cl
u
s
ter
m
em
b
er
n
o
d
e.
T
h
e
clu
s
ter
h
e
ad
n
o
d
e
is
in
ch
ar
g
e
o
f
g
ath
e
r
in
g
d
ata
f
r
o
m
th
e
m
em
b
er
n
o
d
es
an
d
f
u
s
in
g
it
to
g
eth
er
b
e
f
o
r
e
s
en
d
in
g
it to
th
e
b
ase
s
tatio
n
.
Fig
u
r
e
1
.
C
lu
s
ter
in
g
r
o
u
tin
g
alg
o
r
ith
m
to
p
o
lo
g
y
[
4
]
T
h
e
clu
s
ter
in
g
r
o
u
tin
g
alg
o
r
i
th
m
h
as
two
m
ain
p
h
ases
:
t
h
e
clu
s
ter
estab
lis
h
m
en
t
p
h
ase
an
d
th
e
s
tead
y
tr
an
s
m
is
s
io
n
p
h
ase.
I
n
th
e
clu
s
ter
estab
lis
h
m
en
t
p
h
as
e,
clu
s
ter
h
ea
d
s
ar
e
g
en
er
ated
,
wh
ich
d
eter
m
in
es
th
e
f
in
al
n
u
m
b
e
r
an
d
s
ize
o
f
cl
u
s
ter
s
,
as
well
as
th
e
o
v
er
all
e
n
er
g
y
co
n
s
u
m
p
tio
n
o
f
th
e
n
et
wo
r
k
.
C
lu
s
ter
h
ea
d
s
ar
e
ty
p
ically
s
elec
ted
th
r
o
u
g
h
a
clu
s
ter
in
g
alg
o
r
ith
m
th
at
em
p
lo
y
s
a
p
er
io
d
ic
r
o
tatio
n
m
eth
o
d
,
tak
in
g
in
to
co
n
s
id
er
atio
n
f
ac
to
r
s
lik
e
n
o
d
e
en
er
g
y
,
lo
ca
tio
n
,
an
d
in
tr
a
-
c
lu
s
ter
co
m
m
u
n
icatio
n
co
s
t.
Af
ter
th
e
clu
s
ter
h
ea
d
b
r
o
ad
ca
s
ts
in
f
o
r
m
atio
n
[
7
]
,
[
8
]
m
em
b
er
n
o
d
es
ar
e
ch
o
s
en
b
ased
o
n
v
ar
io
u
s
f
ac
to
r
s
s
u
ch
as
lo
ad
b
alan
cin
g
am
o
n
g
clu
s
ter
h
ea
d
s
,
s
h
o
r
te
s
t
d
is
tan
ce
,
o
r
lo
west
en
er
g
y
co
n
s
u
m
p
tio
n
with
in
th
e
c
lu
s
ter
.
I
n
th
e
d
ata
tr
an
s
m
is
s
io
n
p
h
ase,
m
em
b
er
n
o
d
es c
o
m
m
u
n
icate
with
th
e
clu
s
ter
h
ea
d
,
wh
ich
p
er
f
o
r
m
s
d
a
ta
f
u
s
io
n
with
in
th
e
clu
s
ter
.
Fro
m
t
h
er
e,
th
e
d
ata
c
an
b
e
s
en
t
d
ir
ec
tly
to
th
e
b
ase
s
tatio
n
o
r
r
elay
ed
th
r
o
u
g
h
o
th
er
clu
s
ter
h
ea
d
s
th
at
ac
t
as
in
ter
m
ed
iar
y
n
o
d
es.
T
h
e
clu
s
ter
in
g
r
o
u
tin
g
alg
o
r
ith
m
en
co
m
p
ass
es
a
r
an
g
e
o
f
clu
s
ter
in
g
ap
p
r
o
ac
h
es.
Op
tio
n
s
in
clu
d
e
d
is
tr
ib
u
te
d
o
r
ce
n
tr
alize
d
clu
s
ter
in
g
,
u
n
if
o
r
m
o
r
n
o
n
-
u
n
if
o
r
m
clu
s
ter
s
izes,
an
d
s
in
g
le
-
lay
er
o
r
m
u
lti
-
lay
e
r
clu
s
ter
s
tr
u
ctu
r
es.
Ad
d
itio
n
ally
,
co
m
m
u
n
icat
io
n
b
etwe
en
cl
u
s
ter
s
ca
n
b
e
e
ith
er
s
in
g
le
-
h
o
p
o
r
m
u
lti
-
h
o
p
.
R
eg
ar
d
less
o
f
th
e
clu
s
ter
in
g
m
eth
o
d
ch
o
s
en
,
th
e
k
ey
ch
allen
g
e
is
to
b
alan
ce
th
e
n
etwo
r
k
'
s
en
er
g
y
co
n
s
u
m
p
tio
n
an
d
m
ak
e
ef
f
icien
t u
s
e
o
f
n
o
d
e
e
n
er
g
y
to
ex
te
n
d
th
e
n
etwo
r
k
'
s
life
s
p
an
[
9
]
,
[
1
0
]
.
A
w
ir
eless
s
en
s
o
r
n
etwo
r
k
(
W
SN)
is
a
cu
ttin
g
-
ed
g
e
I
o
T
tech
n
o
lo
g
y
c
o
m
p
o
s
ed
o
f
m
u
l
tip
le
n
o
d
es
with
ca
p
ab
ilit
ies f
o
r
s
en
s
in
g
,
p
r
o
ce
s
s
in
g
,
co
m
p
u
tin
g
,
an
d
co
m
m
u
n
icatio
n
.
Ho
wev
e
r
,
ea
ch
s
en
s
o
r
h
as a
lim
ited
s
en
s
in
g
r
an
g
e
an
d
b
atter
y
life
,
lead
in
g
to
s
ev
e
r
al
cr
itical
ch
allen
g
es
in
I
o
T
,
s
u
c
h
as
s
elec
tin
g
clu
s
ter
h
ea
d
s
,
lo
ca
lizin
g
n
o
d
es,
an
d
d
esig
n
in
g
r
o
u
tin
g
p
r
o
to
c
o
ls
.
Op
tim
izatio
n
m
eth
o
d
s
in
s
p
ir
ed
b
y
in
s
ec
t
f
o
r
a
g
in
g
b
eh
av
i
o
r
o
f
f
er
e
f
f
icien
t
s
o
lu
tio
n
s
,
as
th
ese
m
eth
o
d
s
ar
e
f
lex
ib
le,
r
o
b
u
s
t,
d
is
tr
ib
u
ted
,
a
n
d
s
ca
lab
le,
alig
n
in
g
with
I
o
T
r
o
u
tin
g
p
r
o
t
o
co
l
r
e
q
u
ir
em
e
n
ts
.
C
o
n
s
eq
u
en
tly
,
m
an
y
o
p
tim
i
za
tio
n
tech
n
iq
u
es
h
av
e
b
ee
n
d
ev
elo
p
e
d
f
o
r
I
o
T
r
o
u
tin
g
p
r
o
to
co
ls
[
1
1
]
,
[
1
2
]
.
T
h
e
clu
s
ter
r
o
u
tin
g
p
r
o
to
c
o
l
is
a
co
m
m
o
n
ly
u
s
ed
ap
p
r
o
ac
h
in
I
o
T
,
wh
er
e
s
elec
tin
g
a
clu
s
ter
h
ea
d
(
C
H)
is
a
s
ig
n
if
ican
t
ch
allen
g
e.
Sp
e
cif
ically
,
ch
o
o
s
in
g
a
C
H
is
an
NP
-
h
ar
d
p
r
o
b
lem
,
m
ea
n
in
g
it
is
c
o
m
p
u
tatio
n
ally
co
m
p
lex
.
Swar
m
in
tellig
en
ce
(
SI)
,
k
n
o
wn
f
o
r
s
o
lv
in
g
NP
-
h
ar
d
p
r
o
b
lem
s
,
is
a
s
u
itab
le
ap
p
r
o
ac
h
d
u
e
to
its
a
b
ilit
y
to
wo
r
k
with
a
lim
ited
n
u
m
b
er
o
f
p
ar
am
ete
r
s
an
d
p
er
f
o
r
m
m
u
lti
-
o
b
jectiv
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
2
5
8
6
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
,
Vo
l
.
14
,
No
.
3
,
Sep
tem
b
er
20
25
:
41
8
-
42
8
420
o
p
tim
izatio
n
,
allo
win
g
it
t
o
s
e
lect
C
Hs
in
m
u
ltip
le
clu
s
ter
s
s
im
u
ltan
eo
u
s
ly
.
W
h
ile
GPS
is
co
m
m
o
n
l
y
u
s
ed
f
o
r
p
o
s
itio
n
in
g
,
its
h
i
g
h
e
n
er
g
y
co
n
s
u
m
p
tio
n
an
d
lim
ited
co
v
er
ag
e
m
ak
e
it
im
p
r
ac
tic
al
f
o
r
I
o
T
s
.
No
d
e
lo
ca
lizatio
n
,
an
is
s
u
e
in
I
o
T
s
,
is
a
ty
p
e
o
f
er
r
o
r
o
p
tim
izatio
n
p
r
o
b
lem
th
at
b
elo
n
g
s
t
o
th
e
c
ateg
o
r
y
o
f
c
o
m
p
lex
o
p
tim
izatio
n
ch
allen
g
es.
Op
tim
izatio
n
alg
o
r
ith
m
s
ca
n
b
e
u
s
ed
to
s
o
lv
e
s
u
ch
p
r
o
b
lem
s
ef
f
e
ctiv
ely
[
1
3
]
,
[
1
4
]
.
T
h
e
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
alg
o
r
ith
m
,
cr
ea
ted
b
y
Ken
n
ed
y
an
d
E
b
er
h
ar
t,
is
a
g
lo
b
al
r
an
d
o
m
s
ea
r
ch
m
et
h
o
d
th
at
e
m
u
lates
th
e
b
eh
av
io
r
o
f
s
war
m
s
d
u
r
in
g
m
ig
r
atio
n
an
d
f
o
r
ag
in
g
.
I
n
th
e
f
l
o
ck
ag
g
r
eg
atio
n
m
o
d
el,
in
d
iv
i
d
u
a
ls
f
o
llo
w
ce
r
tain
r
u
les:
av
o
id
in
g
co
llis
io
n
s
with
n
ea
r
b
y
in
d
iv
id
u
als,
alig
n
in
g
th
eir
s
p
ee
d
with
o
t
h
er
s
in
th
e
v
icin
ity
,
f
ly
i
n
g
to
war
d
th
e
f
l
o
ck
'
s
ce
n
ter
,
an
d
c
o
llectiv
ely
h
ea
d
in
g
t
o
war
d
th
e
in
ten
d
ed
d
esti
n
atio
n
.
I
n
PS
O,
ea
ch
b
ir
d
in
th
e
s
ea
r
c
h
s
p
ac
e
ca
lled
a
p
ar
ticle
r
ep
r
esen
ts
a
p
o
ten
tial
s
o
lu
tio
n
to
an
o
p
tim
izatio
n
p
r
o
b
lem
.
E
v
e
r
y
p
ar
ticle
h
as
a
v
elo
city
th
at
d
ictates
it
s
d
ir
ec
tio
n
an
d
d
is
tan
ce
o
f
m
o
v
e
m
en
t,
an
d
it
also
h
as
a
f
itn
es
s
v
alu
e
b
ased
o
n
th
e
o
p
tim
al
f
u
n
ctio
n
.
T
h
e
p
ar
ticles
m
o
v
e
th
r
o
u
g
h
th
e
s
o
lu
tio
n
s
p
ac
e,
ad
ju
s
tin
g
th
eir
tr
ajec
to
r
y
to
w
ar
d
th
e
p
a
r
ticle
with
th
e
b
est
f
itn
ess
,
wh
ich
r
ep
r
esen
ts
th
e
cu
r
r
e
n
t
o
p
tim
al
s
o
lu
tio
n
.
An
t
co
lo
n
y
o
p
tim
i
za
tio
n
(
AC
O)
is
an
alg
o
r
ith
m
th
at
u
s
es
a
p
r
o
b
ab
ilis
tic
ap
p
r
o
ac
h
to
s
o
lv
e
co
m
p
u
tatio
n
al
p
r
o
b
lem
s
an
d
f
in
d
o
p
tim
al
p
ath
s
in
a
g
r
a
p
h
[
1
5
]
,
[
1
6
]
.
I
n
AC
O,
ea
ch
a
n
t
l
ea
v
es
p
h
er
o
m
o
n
es
alo
n
g
th
e
p
ath
it
tak
es.
T
h
e
en
tire
an
t
co
lo
n
y
ca
n
d
etec
t
th
ese
p
h
er
o
m
o
n
es.
An
ts
ten
d
to
ch
o
o
s
e
p
ath
s
with
h
ig
h
er
p
h
e
r
o
m
o
n
e
lev
els,
r
ein
f
o
r
cin
g
th
o
s
e
p
ath
s
b
y
d
ep
o
s
itin
g
m
o
r
e
p
h
e
r
o
m
o
n
es
as
th
ey
tr
av
el.
Ov
er
tim
e,
th
is
p
r
o
ce
s
s
g
u
id
es
th
e
an
t
co
lo
n
y
to
war
d
th
e
s
h
o
r
test
r
o
u
te
to
f
o
o
d
.
AC
O'
s
b
en
ef
its
in
cl
u
d
e
a
s
tr
o
n
g
g
l
o
b
al
o
p
tim
izatio
n
ca
p
ab
ilit
y
an
d
f
l
ex
ib
le
im
p
lem
e
n
tatio
n
,
m
a
k
in
g
it
s
u
itab
le
f
o
r
i
n
teg
r
atio
n
with
o
th
er
alg
o
r
ith
m
s
.
T
h
e
ar
tific
ial
b
ee
co
lo
n
y
(
AB
C
)
alg
o
r
ith
m
im
itates
th
e
b
eh
av
io
r
o
f
a
s
war
m
o
f
b
ee
s
co
llectin
g
h
o
n
ey
,
with
ea
ch
b
ee
ex
h
ib
itin
g
d
if
f
er
e
n
t
b
eh
av
io
r
s
b
ased
o
n
its
r
o
le
in
th
e
d
iv
is
io
n
o
f
lab
o
r
.
B
ee
s
co
m
m
u
n
icate
an
d
s
h
ar
e
in
f
o
r
m
atio
n
am
o
n
g
th
em
s
elv
es
to
ar
r
iv
e
at
th
e
o
p
tim
al
s
o
lu
tio
n
.
T
h
e
alg
o
r
ith
m
d
iv
id
es
th
e
ar
tific
ial
b
ee
s
war
m
in
to
th
r
ee
ca
teg
o
r
ies:
s
co
u
ts
,
o
n
lo
o
k
e
r
s
,
an
d
em
p
lo
y
ed
b
ee
s
[
1
7
]
,
[
1
8
]
.
I
n
ea
c
h
s
ea
r
ch
p
r
o
ce
s
s
,
b
ee
s
f
in
d
th
e
b
est
s
o
lu
tio
n
b
y
f
o
ll
o
win
g
th
e
lead
in
g
b
ee
to
a
f
o
o
d
s
o
u
r
ce
.
I
f
a
b
ee
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co
u
tin
g
f
o
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f
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d
s
u
s
p
ec
ts
is
s
tu
c
k
at
a
l
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al
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t
im
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m
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it
r
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n
d
o
m
l
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s
ea
r
c
h
es
f
o
r
o
th
e
r
f
o
o
d
s
o
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ce
s
.
E
a
c
h
f
o
o
d
s
o
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r
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e
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y
m
b
o
li
ze
s
a
p
o
s
s
i
b
l
e
s
o
lu
tio
n
to
th
e
p
r
o
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lem
,
an
d
th
e
q
u
an
tity
o
f
n
ec
tar
f
r
o
m
a
f
o
o
d
s
o
u
r
ce
in
d
icate
s
th
e
q
u
ality
o
f
th
at
s
o
lu
tio
n
.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
San
k
ar
et
a
l.
[
1
9
]
i
n
tr
o
d
u
ce
d
a
n
o
v
el
clu
s
ter
h
ea
d
(
C
H)
s
elec
tio
n
an
d
clu
s
ter
f
o
r
m
atio
n
alg
o
r
ith
m
aim
ed
at
ad
d
r
ess
in
g
ce
r
tain
l
im
itatio
n
s
.
T
h
e
ap
p
r
o
ac
h
in
cl
u
d
ed
two
m
ain
s
tag
es:
f
ir
s
t,
C
H
s
elec
tio
n
wa
s
co
n
d
u
cte
d
u
s
in
g
th
e
s
ailf
is
h
o
p
tim
izatio
n
alg
o
r
ith
m
(
SOA
)
,
a
ty
p
e
o
f
s
war
m
in
tellig
en
ce
alg
o
r
ith
m
.
Nex
t,
clu
s
ter
f
o
r
m
atio
n
was
b
ased
o
n
th
e
E
u
clid
ea
n
d
is
tan
ce
.
T
h
e
a
u
th
o
r
s
u
s
ed
t
h
e
NS2
s
im
u
lato
r
f
o
r
th
eir
ex
p
er
im
en
ts
.
T
h
e
SOA'
s
ef
f
ec
tiv
en
ess
was
co
m
p
ar
ed
with
th
r
ee
o
th
er
m
et
h
o
d
s
:
im
p
r
o
v
ed
an
t
b
ee
co
lo
n
y
o
p
tim
izatio
n
-
b
ased
clu
s
ter
in
g
(
I
AB
C
O
C
T
)
,
en
h
an
ce
d
p
ar
ticl
e
s
war
m
o
p
tim
izatio
n
tec
h
n
iq
u
e
(
E
PS
OC
T
)
,
an
d
h
ier
ar
ch
ical
clu
s
ter
in
g
-
b
ased
C
H
E
lectio
n
(
HC
C
HE
)
.
T
h
e
s
im
u
latio
n
r
esu
lts
in
d
icate
d
t
h
at
th
e
in
tr
o
d
u
ce
d
SOA
ap
p
r
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ac
h
e
n
h
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ce
d
n
etw
o
r
k
lo
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g
ev
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a
n
d
r
ed
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ce
d
d
el
ay
s
in
n
o
d
e
-
to
-
s
in
k
c
o
m
m
u
n
ic
atio
n
.
Du
an
d
Gu
[
2
0
]
h
ig
h
lig
h
ted
im
p
o
r
tan
ce
o
f
l
o
w
-
p
o
wer
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tin
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p
r
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to
co
l
d
esig
n
in
I
o
T
.
T
o
ad
d
r
ess
th
e
ch
allen
g
es
r
elate
d
to
n
etwo
r
k
lo
ad
an
d
en
e
r
g
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co
n
s
u
m
p
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in
ex
is
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clu
s
ter
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g
m
eth
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d
s
,
th
e
y
p
r
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ted
a
n
o
v
el
clu
s
ter
in
g
r
o
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tin
g
s
c
h
em
e
u
s
in
g
th
e
q
u
a
n
tu
m
b
el
u
g
a
wh
ale
o
p
tim
izatio
n
(
QB
W
O)
alg
o
r
ith
m
.
T
h
is
alg
o
r
ith
m
was
d
esig
n
e
d
to
ef
f
ec
tiv
ely
an
d
ce
n
tr
ally
co
n
f
ig
u
r
e
clu
s
ter
s
,
f
o
c
u
s
in
g
o
n
asp
e
cts
s
u
ch
as
clu
s
ter
ce
n
tr
o
id
s
,
clu
s
ter
m
em
b
er
s
,
cl
u
s
ter
en
er
g
y
,
clu
s
ter
p
r
io
r
ity
,
an
d
th
e
v
alid
ity
p
er
io
d
o
f
clu
s
ter
s
.
B
y
d
o
in
g
s
o
,
it
s
h
if
ted
th
e
co
m
p
u
tatio
n
al
en
er
g
y
co
n
s
u
m
p
tio
n
f
r
o
m
in
d
iv
id
u
al
n
o
d
es
to
th
e
b
ase
s
tatio
n
,
th
u
s
o
p
tim
izin
g
th
e
o
v
er
all
n
etwo
r
k
o
p
e
r
atio
n
f
o
r
b
o
th
th
e
tr
a
n
s
itio
n
al
an
d
s
tab
le
s
tag
es.
Simu
latio
n
ex
p
er
i
m
en
ts
d
em
o
n
s
tr
ated
th
e
ef
f
ec
tiv
e
n
ess
o
f
QB
W
O,
s
h
o
win
g
its
p
o
ten
tial
to
d
el
iv
er
a
m
o
r
e
b
alan
ce
d
n
etwo
r
k
lo
ad
an
d
en
er
g
y
co
n
s
u
m
p
tio
n
c
o
m
p
ar
e
d
to
tr
a
d
itio
n
al
clu
s
ter
in
g
m
eth
o
d
s
.
T
h
is
ap
p
r
o
ac
h
im
p
r
o
v
e
d
en
er
g
y
ef
f
icien
cy
a
n
d
a
lo
n
g
er
n
etwo
r
k
life
s
p
a
n
.
Sh
ar
m
in
et
a
l.
[
2
1
]
i
n
tr
o
d
u
ce
d
an
d
e
x
am
in
ed
a
s
ec
u
r
e
b
io
-
i
n
s
p
ir
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W
SN
r
o
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tin
g
p
r
o
t
o
co
l
u
s
in
g
t
h
e
AC
O
alg
o
r
ith
m
f
o
r
th
e
I
o
T
.
T
h
is
p
r
o
to
co
l
was
d
esig
n
e
d
t
o
f
in
d
a
s
ec
u
r
e
an
d
en
er
g
y
-
s
av
in
g
o
p
tim
al
p
ath
,
aim
in
g
to
estab
lis
h
tr
u
s
t
in
th
e
I
o
T
en
v
i
r
o
n
m
e
n
t.
T
h
e
p
er
f
o
r
m
an
ce
o
f
th
is
p
r
o
p
o
s
ed
r
o
u
tin
g
alg
o
r
ith
m
was
test
ed
u
s
in
g
MA
T
L
AB
.
T
h
e
r
esu
lts
s
h
o
wed
th
at
it
c
o
u
ld
id
en
tify
a
f
o
r
wa
r
d
in
g
p
ath
with
r
elativ
ely
lo
w
co
s
t
wh
ile
en
s
u
r
in
g
s
ec
u
r
ity
.
Ad
d
i
tio
n
ally
,
it
s
ig
n
if
ican
tly
r
ed
u
c
ed
av
er
ag
e
en
er
g
y
co
n
s
u
m
p
ti
o
n
b
y
ab
o
u
t
5
0
%
ev
en
with
a
n
in
c
r
ea
s
e
in
th
e
n
u
m
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er
o
f
n
o
d
es,
wh
e
n
co
m
p
ar
ed
with
t
h
e
tr
ad
itio
n
al
AC
O
alg
o
r
ith
m
,
a
well
-
k
n
o
wn
a
n
t c
o
lo
n
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b
ased
r
o
u
ti
n
g
alg
o
r
ith
m
,
an
d
a
co
n
tem
p
o
r
ar
y
I
o
T
r
o
u
tin
g
p
r
o
to
c
o
l.
Fan
an
d
Xin
[
2
2
]
in
tr
o
d
u
ce
d
a
clu
s
ter
in
g
an
d
r
o
u
tin
g
al
g
o
r
ith
m
s
p
ec
if
ically
d
esig
n
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f
o
r
f
ast
-
ch
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g
in
g
(
FC
-
C
R
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lar
g
e
-
s
ca
le
I
OT
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in
th
e
I
o
T
.
T
h
e
FC
-
C
R
A
cr
ea
ted
clu
s
ter
s
u
s
in
g
a
clu
s
ter
r
ad
iu
s
th
at
ca
n
ad
ju
s
t
d
y
n
am
ically
to
s
h
if
ts
in
n
o
d
e
en
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r
g
y
lev
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d
d
is
p
er
s
io
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.
T
o
co
n
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v
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n
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s
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-
2
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E
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f
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m
a
n
ce
,
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d
e
n
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g
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cy
.
T
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p
r
o
p
o
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alg
o
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ith
m
was
ab
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ed
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tain
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s
en
v
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o
n
m
en
ts
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Z
h
an
g
et
a
l.
[
2
3
]
p
r
o
p
o
s
ed
an
en
er
g
y
-
e
f
f
icien
t
m
u
ltil
ev
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s
ec
u
r
e
r
o
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tin
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E
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MSR
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p
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to
c
o
l
f
o
r
I
o
T
n
etwo
r
k
s
.
Giv
en
th
at
clu
s
ter
in
g
is
an
ef
f
ec
tiv
e
way
to
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o
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v
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s
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ased
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ltih
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im
ize
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ig
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m
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o
T
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r
k
s
.
T
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im
p
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d
an
a
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aly
tic
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o
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ter
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n
s
u
r
in
g
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r
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to
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ld
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u
p
p
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o
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s
I
o
T
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d
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ices
.
Ad
d
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co
r
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s
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r
o
to
c
o
l
u
s
ed
m
u
ltip
le
tr
u
s
t
lev
els
s
u
ch
a
s
d
ata
p
er
ce
p
tio
n
tr
u
s
t,
d
at
a
f
u
s
io
n
tr
u
s
t,
an
d
co
m
m
u
n
icatio
n
tr
u
s
t
to
d
ef
en
d
ag
ain
s
t
v
ar
i
o
u
s
s
ec
u
r
ity
t
h
r
e
ats.
T
h
e
p
r
o
p
o
s
ed
a
p
p
r
o
ac
h
p
e
r
f
o
r
m
e
d
b
etter
th
an
m
an
y
ex
is
tin
g
al
g
o
r
ith
m
s
in
ter
m
s
o
f
n
etwo
r
k
s
er
v
ice
p
er
io
d
,
th
r
o
u
g
h
p
u
t,
p
ac
k
et
d
el
iv
er
y
r
atio
,
en
er
g
y
b
alan
ce
,
an
d
f
lex
ib
ilit
y
.
Go
r
ik
ap
u
d
i
an
d
Ko
n
d
av
ee
ti
[
2
4
]
in
tr
o
d
u
ce
d
a
n
o
v
ice
m
eth
o
d
f
o
r
clu
s
ter
in
g
in
I
o
T
n
etw
o
r
k
s
.
T
h
ese
n
etwo
r
k
s
f
ac
e
d
a
cr
u
cial
ch
all
en
g
e
o
f
e
n
er
g
y
-
ef
f
icien
t
r
o
u
tin
g
d
u
e
t
o
th
e
lim
itatio
n
s
o
f
s
m
ar
t
g
ad
g
ets.
T
h
eir
tech
n
iq
u
e
e
m
p
lo
y
ed
th
e
s
an
d
p
ip
er
o
p
tim
izatio
n
with
cy
c
le
cr
o
s
s
o
v
er
p
r
o
ce
s
s
(
SOC
C
P)
m
o
d
el
t
o
s
elec
t
clu
s
ter
h
ea
d
s
,
tak
in
g
in
to
ac
co
u
n
t c
o
n
s
tr
ain
ts
lik
e
d
is
tan
ce
,
en
er
g
y
,
s
ec
u
r
ity
,
an
d
clu
s
ter
r
a
d
iu
s
.
T
h
e
clu
s
ter
in
g
p
r
o
ce
s
s
u
tili
ze
d
a
n
o
p
tim
iz
ed
f
u
z
zy
c
-
m
ea
n
s
(
FC
M)
alg
o
r
ith
m
,
wh
ile
th
e
clu
s
ter
h
ea
d
an
d
r
a
d
iu
s
d
eter
m
in
atio
n
was
o
p
tim
ized
th
r
o
u
g
h
th
e
SOC
C
P
m
o
d
el.
T
h
e
p
r
esen
ted
ap
p
r
o
ac
h
was
ev
alu
ated
u
s
in
g
m
etr
ics
lik
e
aliv
e
n
o
d
e
an
aly
s
is
,
r
is
k
an
aly
s
is
,
an
d
d
is
tan
ce
a
n
aly
s
is
.
T
h
e
f
in
d
in
g
s
in
d
icate
d
th
at
th
e
p
r
esen
ted
s
o
lu
tio
n
s
u
r
p
ass
ed
b
aselin
e
clu
s
ter
in
g
a
p
p
r
o
ac
h
es,
d
e
m
o
n
s
tr
atin
g
r
ed
u
ce
d
r
is
k
a
n
d
e
n
h
an
ce
d
en
e
r
g
y
ef
f
icien
cy
.
T
h
e
d
is
tan
ce
a
n
aly
s
is
r
ev
ea
led
th
at
th
is
m
eth
o
d
ac
h
iev
es
th
e
lo
west
d
is
tan
ce
a
t
th
e
1
5
0
0
th
r
o
u
n
d
,
wh
er
ea
s
class
ic
ap
p
r
o
ac
h
es
s
h
o
wed
h
ig
h
er
d
is
tan
ce
s
at
th
e
s
am
e
p
o
in
t.
T
h
is
n
ew
a
p
p
r
o
ac
h
s
ee
m
s
p
r
o
m
is
in
g
f
o
r
ad
v
an
cin
g
clu
s
ter
in
g
in
I
o
T
n
etwo
r
k
s
.
Su
n
et
a
l.
[
2
5
]
d
e
v
elo
p
e
d
a
n
etwo
r
k
clu
s
ter
in
g
a
p
p
r
o
ac
h
u
s
in
g
th
e
K
-
m
ea
n
s
tech
n
iq
u
e.
T
o
ad
d
r
ess
th
e
K
-
m
ea
n
s
alg
o
r
ith
m
'
s
s
en
s
i
tiv
ity
to
th
e
in
itial
ce
n
ter
(
I
C
)
an
d
its
ten
d
en
cy
to
g
et
s
tu
ck
i
n
a
lo
ca
l
o
p
tim
u
m
,
th
ey
em
p
lo
y
ed
th
e
PS
O
tech
n
i
q
u
e
to
en
h
an
ce
th
e
in
itial
clu
s
ter
in
g
ce
n
ter
,
a
ch
iev
in
g
o
p
tim
al
clu
s
ter
in
g
.
Af
ter
clu
s
ter
in
g
th
e
n
etwo
r
k
,
th
ey
c
o
n
s
id
er
ed
t
h
e
lo
ca
tio
n
an
d
en
er
g
y
o
f
s
en
s
o
r
n
o
d
es
(
SNs
)
wh
en
s
elec
tin
g
a
C
H.
T
h
e
weig
h
ts
f
o
r
th
ese
f
ac
to
r
s
wer
e
d
y
n
am
ically
ad
ju
s
ted
b
a
s
ed
o
n
th
e
SNs
'
r
em
ain
in
g
en
er
g
y
.
T
h
e
p
r
o
p
o
s
ed
p
r
o
to
co
l e
f
f
ec
tiv
ely
b
alan
ce
d
en
er
g
y
u
s
ag
e
ac
r
o
s
s
th
e
n
etwo
r
k
an
d
ex
ten
d
e
d
its
life
s
p
an
in
test
f
in
d
in
g
s
.
W
an
g
et
a
l.
[
2
6
]
i
n
tr
o
d
u
ce
d
a
d
ata
-
o
r
ien
te
d
R
PL
m
eth
o
d
th
at
r
o
u
te
d
d
ata
b
ased
o
n
co
n
t
en
t,
u
s
in
g
b
in
ar
y
g
r
ay
wo
lf
o
p
tim
izatio
n
to
f
in
d
th
e
o
p
tim
al
p
at
h
.
T
h
is
tech
n
iq
u
e
en
h
an
c
ed
th
e
e
f
f
ec
tiv
en
ess
o
f
th
e
r
o
u
tin
g
p
r
o
t
o
co
l
f
o
r
lo
w
-
p
o
wer
an
d
l
o
s
s
y
n
etwo
r
k
s
(
R
PL)
.
I
n
th
e
tr
ee
co
n
s
tr
u
ctio
n
p
h
ase,
th
ey
u
s
ed
an
o
b
jectiv
e
f
u
n
ctio
n
to
s
elec
t
th
e
b
est
p
ar
e
n
t
n
o
d
e
f
o
r
r
o
u
tin
g
,
cr
ea
ted
with
f
u
zz
y
l
o
g
ic
a
n
d
b
in
a
r
y
g
r
ay
wo
lf
o
p
tim
izatio
n
.
T
h
e
m
eth
o
d
was
test
ed
in
th
e
MA
T
L
A
B
2
0
2
2
a
an
d
OM
NE
T
en
v
ir
o
n
m
en
ts
,
s
h
o
win
g
im
p
r
o
v
ed
en
er
g
y
ef
f
icien
cy
wh
ile
r
e
d
u
c
in
g
en
d
-
to
-
en
d
d
elay
an
d
in
s
tab
ilit
y
p
er
io
d
s
.
T
h
e
in
s
tab
ilit
y
p
er
io
d
r
atio
o
f
th
e
p
r
o
p
o
s
ed
tech
n
iq
u
e
was
s
ig
n
if
ican
tly
lo
wer
th
an
th
o
s
e
o
f
o
th
er
m
eth
o
d
s
.
Sp
ec
if
ically
,
i
t
was
5
7
%
f
o
r
th
e
p
r
o
p
o
s
ed
m
eth
o
d
,
wh
ile
it
was
8
0
%
f
o
r
OR
PL
an
d
Qo
S
R
PL,
an
d
8
9
%
f
o
r
th
e
s
tan
d
ar
d
R
PL
m
eth
o
d
.
T
h
is
lo
wer
in
s
tab
ilit
y
p
er
io
d
r
atio
in
d
icate
d
th
at
th
e
p
r
esen
ted
tech
n
iq
u
e
m
ain
tain
e
d
lo
n
g
er
s
tab
ilit
y
,
o
p
er
atin
g
with
th
e
m
ax
im
u
m
n
u
m
b
er
o
f
n
o
d
es f
o
r
an
e
x
ten
d
ed
p
er
io
d
.
B
ajp
ai
et
a
l.
[
2
7
]
p
r
esen
ted
a
m
eth
o
d
o
l
o
g
y
th
at
c
o
m
b
in
e
d
a
d
v
an
ce
d
m
ac
h
i
n
e
lear
n
i
n
g
tec
h
n
iq
u
es
to
ac
h
iev
e
ef
f
ec
tiv
e
clu
s
ter
in
g
a
n
d
d
ata
r
ed
u
ctio
n
.
T
h
e
s
tu
d
y
u
s
ed
a
n
o
v
el
ap
p
r
o
ac
h
b
y
i
n
teg
r
atin
g
an
im
p
r
o
v
ed
v
er
s
io
n
o
f
p
r
in
ci
p
al
co
m
p
o
n
e
n
t
an
aly
s
is
(
P
C
A)
with
a
r
ein
f
o
r
ce
m
en
t
lear
n
in
g
alg
o
r
ith
m
.
T
h
e
m
ain
o
b
jectiv
es
wer
e
to
ex
ten
d
a
n
etwo
r
k
'
s
s
er
v
ice
life
,
r
e
d
u
ce
e
n
er
g
y
co
n
s
u
m
p
tio
n
,
a
n
d
im
p
r
o
v
e
d
ata
ag
g
r
eg
atio
n
e
f
f
icien
cy
.
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
was
ev
alu
ated
u
s
in
g
d
ata
f
r
o
m
s
en
s
o
r
s
in
s
talled
in
ag
r
ic
u
ltu
r
al
f
ield
s
f
o
r
cr
o
p
m
o
n
ito
r
in
g
.
T
h
e
r
esear
c
h
er
s
co
m
p
ar
ed
t
h
eir
s
u
g
g
ested
m
e
th
o
d
,
n
a
m
ed
PC
A
-
b
ased
Q
-
lear
n
in
g
(
PQL)
,
wit
h
p
r
ev
io
u
s
ap
p
r
o
ac
h
es
lik
e
r
eg
i
o
n
al
en
er
g
y
-
awa
r
e
cl
u
s
ter
in
g
(
R
E
AC
)
an
d
ad
ap
tiv
e
Q
-
lear
n
in
g
(
AQL
)
.
T
h
eir
f
in
d
in
g
s
in
d
icate
d
th
at
th
e
p
r
e
s
en
ted
m
eth
o
d
cr
ea
ted
a
f
au
lt
-
to
ler
an
t
n
etwo
r
k
a
n
d
s
u
r
p
ass
ed
th
e
o
th
er
m
eth
o
d
s
in
ter
m
s
o
f
en
e
r
g
y
ef
f
icien
cy
a
n
d
n
etwo
r
k
life
s
p
an
.
3.
RE
S
E
ARCH
M
E
T
H
O
DO
L
O
G
Y
T
h
is
r
esear
ch
is
b
ased
o
n
n
et
wo
r
k
d
ep
lo
y
m
en
t,
clu
s
ter
f
o
r
m
atio
n
an
d
d
ata
r
o
u
tin
g
f
r
o
m
clu
s
ter
h
ea
d
to
b
ase
s
tatio
n
.
T
h
e
clu
s
ter
f
o
r
m
atio
n
is
d
o
n
e
u
s
in
g
f
r
u
it
f
ly
alg
o
r
ith
m
a
n
d
p
at
h
will
b
e
estab
lis
h
ed
u
s
in
g
AC
O
.
T
h
e
d
etails ar
e
g
iv
en
as
f
o
llo
ws.
3
.
1
.
Net
w
o
rk
deplo
y
m
ent
T
h
e
r
an
d
o
m
d
is
tr
ib
u
tio
n
o
f
n
o
d
es
is
o
n
e
o
f
th
e
b
asic
r
eq
u
i
r
em
en
ts
o
f
th
e
clu
s
ter
ed
wir
eless
s
en
s
o
r
n
etwo
r
k
’
s
ap
p
licatio
n
.
T
h
e
cl
u
s
ter
h
ea
d
s
ar
e
cr
ea
ted
d
u
e
to
th
is
r
an
d
o
m
d
is
tr
ib
u
tio
n
o
f
s
en
s
o
r
n
o
d
es
wh
ich
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
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2
7
2
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2
5
8
6
I
AE
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I
n
t
J
R
o
b
&
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u
to
m
,
Vo
l
.
14
,
No
.
3
,
Sep
tem
b
er
20
25
:
41
8
-
42
8
422
f
u
r
th
er
c
r
ea
tes
s
ev
er
al
is
s
u
es.
Du
e
to
en
er
g
y
co
n
s
u
m
p
tio
n
,
th
er
e
is
a
n
ee
d
to
a
v
o
id
d
is
p
o
s
ab
ilit
y
f
o
r
th
e
clu
s
ter
h
ea
d
.
Als
o
,
th
e
lo
n
g
-
d
is
tan
ce
co
m
m
u
n
icatio
n
in
t
h
e
clu
s
ter
h
ea
d
is
p
r
e
v
en
ted
an
d
th
e
ad
d
itio
n
o
f
n
o
d
es
b
elo
w
t
h
em
is
also
d
o
n
e
h
er
e.
T
h
e
n
o
d
es
wh
ich
will
n
o
t
m
ee
t
s
tan
d
ar
d
s
ar
e
n
o
t
s
elec
ted
as
th
e
clu
s
ter
h
ea
d
.
T
h
e
c
o
n
d
itio
n
s
o
f
n
o
d
es
m
ad
e
th
e
n
o
d
es
d
if
f
icu
lt
to
a
v
ailab
le
in
th
e
n
etwo
r
k
a
n
d
al
m
o
s
t
im
p
o
s
s
ib
le
f
o
r
th
em
to
b
e
av
ailab
le
at
r
em
o
te
an
a
r
ea
wh
ic
h
f
u
r
th
er
ca
u
s
es
in
ap
p
r
o
p
r
iate
n
o
d
es.
W
h
en
th
e
in
tr
a
-
clu
s
ter
en
er
g
y
is
in
cr
ea
s
ed
th
en
th
ese
n
o
d
es
ar
e
u
s
ed
as
clu
s
ter
h
ea
d
s
.
T
h
e
g
e
n
u
in
e
n
o
d
e
co
n
s
u
m
es
less
am
o
u
n
t
o
f
en
er
g
y
in
co
m
p
ar
is
o
n
s
to
th
e
r
ec
eiv
er
an
d
th
e
s
en
d
er
n
o
d
es.
W
h
en
th
e
ex
te
n
s
iv
e
s
p
ec
tr
u
m
is
p
r
o
v
id
e
d
to
th
e
s
y
s
tem
in
a
s
y
n
ch
r
o
n
ized
m
a
n
n
er
th
e
n
th
e
b
atter
y
p
o
wer
co
n
s
u
m
p
tio
n
is
v
er
y
less
th
an
co
n
s
u
m
e
d
b
y
th
e
n
o
d
es.
T
h
e
p
ar
e
n
t
n
o
d
e
is
s
elec
ted
f
o
r
e
v
er
clu
s
ter
h
ea
d
s
o
th
at
th
e
ac
tio
n
s
ca
n
b
e
s
ep
ar
ated
an
d
th
e
r
e
is
an
in
cr
ea
s
e
in
p
r
o
d
u
ctiv
ity
.
T
wo
v
alu
e
f
u
n
ctio
n
s
ar
e
p
r
o
p
o
s
ed
f
o
r
th
e
co
m
p
eten
ce
o
f
ea
c
h
s
en
s
o
r
y
n
o
d
e
wh
ich
f
u
r
th
er
h
elp
s
th
e
n
o
d
e
to
b
e
c
h
o
s
en
as
t
h
e
clu
s
ter
h
ea
d
.
De
g
r
ee
o
f
n
o
d
es
g
en
e
r
ates
f
u
n
ctio
n
s
an
d
th
e
av
e
r
ag
e
p
o
wer
o
f
th
e
n
eig
h
b
o
r
i
n
g
n
o
d
es
is
ca
lcu
lated
b
y
t
h
eir
d
is
tan
ce
to
th
e
b
ase
s
tatio
n
.
I
t
is
n
ec
ess
ar
y
to
g
en
e
r
ate
a
h
ig
h
er
d
eg
r
ee
o
f
n
o
d
es
s
o
th
a
t
th
e
clu
s
ter
h
ea
d
ca
n
b
e
f
o
r
m
ed
.
I
f
th
e
clu
s
ter
h
ea
d
h
as
a
h
ig
h
e
r
d
e
g
r
ee
ca
n
co
v
er
a
lar
g
e
n
u
m
b
er
o
f
n
o
d
es
wh
ich
av
o
i
d
s
th
e
ex
p
e
n
s
iv
e
c
o
m
m
u
n
icatio
n
s
.
3
.
2
.
Clus
t
er
f
o
r
m
a
t
i
o
n
T
h
e
n
etwo
r
k
is
d
ep
l
o
y
ed
a
n
d
th
e
wh
o
le
n
etwo
r
k
will
b
e
d
i
v
id
ed
in
to
clu
s
ter
s
.
T
h
e
clu
s
t
er
s
will
b
e
f
o
r
m
ed
b
ased
o
n
th
e
d
is
tan
ce
.
T
h
is
wo
r
k
em
p
lo
y
s
a
d
a
p
tiv
e
clu
s
ter
in
g
f
o
r
clu
s
ter
f
o
r
m
atio
n
.
Ad
ap
tiv
e
clu
s
ter
in
g
in
W
SNs
is
an
a
p
p
r
o
ac
h
to
in
cr
ea
s
e
th
e
l
o
n
g
ev
ity
o
f
th
e
n
etwo
r
k
b
y
m
in
im
izin
g
en
er
g
y
co
n
s
u
m
p
tio
n
.
W
ir
eless
Sen
s
o
r
Netwo
r
k
s
c
o
n
s
is
t
o
f
s
p
atially
d
is
tr
ib
u
ted
s
en
s
o
r
n
o
d
es
th
at
a
r
e
u
s
ed
to
m
o
n
it
o
r
th
e
p
h
y
s
ical
o
r
e
n
v
ir
o
n
m
en
ta
l
co
n
d
itio
n
s
.
E
f
f
icien
t
d
ata
tr
an
s
m
is
s
io
n
an
d
en
e
r
g
y
m
an
a
g
em
en
t
ar
e
th
e
two
k
ey
ar
ea
s
th
at
n
ee
d
t
o
b
e
f
o
cu
s
ed
o
n
f
o
r
en
h
a
n
cin
g
t
h
e
l
if
esp
an
an
d
ef
f
icien
c
y
o
f
th
e
n
etwo
r
k
.
Ad
ap
tiv
e
clu
s
ter
in
g
is
o
n
e
o
f
th
e
s
tr
ate
g
ies
am
o
n
g
th
e
ef
f
icien
t
o
n
es
u
s
ed
to
cr
ea
te
clu
s
ter
s
o
f
s
en
s
o
r
n
o
d
es
b
ased
o
n
d
y
n
am
ic
cr
iter
ia.
I
n
g
e
n
er
al,
t
h
e
o
p
er
atio
n
s
in
ad
ap
tiv
e
clu
s
t
er
in
g
alg
o
r
ith
m
s
ar
e
d
iv
id
e
d
i
n
to
f
o
u
r
s
tep
s
:
n
o
d
e
in
itializatio
n
,
C
H
s
elec
tio
n
,
cl
u
s
ter
f
o
r
m
atio
n
an
d
d
ata
tr
an
s
m
is
s
io
n
an
d
ad
ap
tiv
e
ad
ju
s
tm
en
ts
.
−
No
d
e
in
itializatio
n
:
E
ac
h
n
o
d
e
in
itializes
its
en
er
g
y
lev
el
an
d
r
ec
o
g
n
izes
a
lis
t
o
f
n
ei
g
h
b
o
r
in
g
n
o
d
es
with
in
th
e
d
is
tan
ce
o
f
th
e
g
i
v
en
tr
a
n
s
m
is
s
io
n
r
an
g
e
.
T
h
e
tr
an
s
m
is
s
io
n
r
an
g
e
in
d
icate
s
th
e
m
a
x
im
u
m
co
m
m
u
n
icatio
n
d
is
tan
ce
a
n
o
d
e
ca
n
co
v
e
r
−
C
lu
s
ter
h
ea
d
s
elec
t
io
n
:
No
d
es
d
ec
id
e
th
eir
ch
an
ce
s
o
f
b
ein
g
clu
s
ter
h
ea
d
s
ac
co
r
d
in
g
to
th
eir
en
er
g
y
s
tatu
s
an
d
d
is
tan
ce
s
to
th
e
b
ase
s
tati
o
n
.
T
h
e
f
o
r
m
u
la
u
s
ed
f
o
r
t
h
is
is
:
=
∑
=
1
(
1
)
wh
er
e
is
th
e
p
r
o
b
ab
ilit
y
o
f
n
o
d
e
b
ein
g
a
C
H,
an
d
is
th
e
r
em
ain
in
g
en
e
r
g
y
o
f
n
o
d
e
.
−
C
lu
s
ter
f
o
r
m
atio
n
:
No
d
es
b
r
o
ad
ca
s
t
th
eir
I
Ds
to
n
ea
r
b
y
n
o
d
es.
No
d
es
with
th
e
h
ig
h
e
s
t
p
r
o
b
ab
ilit
ies
b
ec
o
m
e
clu
s
ter
h
ea
d
s
.
Oth
er
n
o
d
es jo
in
th
e
clo
s
est clu
s
ter
h
e
ad
b
ased
o
n
th
e
f
o
llo
win
g
cr
it
er
ia:
=
√
(
−
)
2
+
(
−
)
2
(
2
)
w
h
er
e
is
th
e
d
is
tan
ce
b
etwe
en
n
o
d
es
an
d
,
an
d
(
,
)
an
d
(
,
)
ar
e
th
eir
co
o
r
d
in
ates.
−
Data
tr
an
s
m
is
s
io
n
:
T
h
e
m
em
b
er
n
o
d
es
tr
an
s
m
it
th
eir
d
ata
to
a
s
elec
ted
clu
s
ter
h
ea
d
,
wh
ich
g
ath
er
s
th
e
d
ata
an
d
tr
a
n
s
m
its
it to
th
e
b
ase
s
tatio
n
.
−
Ad
ap
tiv
e
ad
j
u
s
tm
en
ts
:
Af
ter
ev
er
y
t
r
an
s
m
is
s
io
n
r
o
u
n
d
,
th
e
n
o
d
es
r
ea
s
s
ess
th
eir
en
er
g
y
l
ev
els
as
well
as
th
eir
co
m
m
u
n
icatio
n
m
etr
ics.
I
f
th
e
en
er
g
y
o
f
th
e
n
o
d
e
g
o
es
d
o
wn
lo
wer
th
an
th
e
s
et
t
h
r
esh
o
ld
,
it
ca
n
ch
o
o
s
e
to
b
e
a
n
o
n
-
clu
s
ter
h
ea
d
in
th
e
n
ex
t r
o
u
n
d
.
Ad
ap
tiv
e
clu
s
ter
in
g
in
W
SNs
p
r
o
v
id
es
a
m
ea
n
s
o
f
f
o
r
m
in
g
clu
s
ter
s
ef
f
icien
tly
b
y
r
e
g
r
o
u
p
in
g
th
e
s
en
s
o
r
s
d
y
n
am
ically
ac
co
r
d
i
n
g
to
s
o
m
e
m
etr
ics
lik
e
th
e
en
er
g
y
lev
el
o
f
th
e
n
o
d
e
an
d
th
e
d
is
tan
ce
to
th
e
n
eig
h
b
o
r
n
o
d
e.
Fu
r
th
e
r
,
t
h
is
wo
r
k
u
s
es
th
e
f
r
u
it
f
ly
alg
o
r
i
th
m
to
o
p
tim
ize
th
is
clu
s
ter
in
g
p
r
o
ce
s
s
,
s
o
as
to
en
h
an
ce
th
e
s
elec
tio
n
o
f
clu
s
ter
h
ea
d
s
,
h
en
ce
,
r
ed
u
cin
g
en
e
r
g
y
co
n
s
u
m
p
tio
n
.
I
n
th
is
way
,
W
SN
h
a
s
b
etter
n
etwo
r
k
life
tim
e
an
d
p
er
f
o
r
m
an
ce
d
u
e
to
m
o
r
e
o
p
tim
al
d
ata
ag
g
r
eg
atio
n
an
d
tr
an
s
m
is
s
io
n
.
Fru
it
f
lies
r
ely
o
n
th
eir
k
ee
n
s
en
s
e
o
f
s
m
ell
a
n
d
v
is
io
n
to
lo
ca
te
f
o
o
d
,
w
h
ich
is
s
u
p
er
io
r
co
m
p
ar
ed
t
o
o
th
er
f
ly
s
p
ec
ies.
L
ev
er
ag
in
g
s
war
m
in
tellig
en
c
e
o
p
tim
izatio
n
,
f
r
u
it
f
ly
is
a
d
e
p
t
at
ad
ju
s
tin
g
f
itn
ess
f
u
n
ctio
n
p
ar
am
eter
s
q
u
ick
ly
an
d
ef
f
ec
tiv
el
y
d
u
e
to
its
o
p
ti
m
izatio
n
s
p
ee
d
an
d
p
ar
a
m
eter
f
lex
ib
ilit
y
.
Gu
id
e
d
b
y
th
e
f
itn
ess
f
u
n
ctio
n
,
wh
ich
ac
ts
as
an
o
d
o
r
co
n
ce
n
tr
atio
n
d
ec
is
io
n
f
u
n
ctio
n
,
f
ly
o
p
tim
iz
atio
n
alg
o
r
ith
m
(
FOA)
aim
s
t
o
iter
ativ
ely
ad
ju
s
t
th
e
f
r
u
it
f
ly
p
o
p
u
latio
n
with
in
th
e
s
o
lu
tio
n
s
p
ac
e.
Fig
u
r
e
2
d
is
p
lay
s
th
e
clu
s
ter
f
o
r
m
atio
n
p
r
o
ce
s
s
u
s
in
g
f
r
u
it
f
ly
alg
o
r
ith
m
.
T
h
is
p
r
o
ce
s
s
ty
p
ically
in
v
o
lv
es f
o
u
r
s
tep
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
o
b
&
A
u
to
m
I
SS
N:
2722
-
2
5
8
6
E
n
erg
y
efficien
t c
lu
s
teri
n
g
a
n
d
r
o
u
tin
g
meth
o
d
fo
r
I
n
tern
et
o
f Th
in
g
s
(
B
h
a
w
n
a
A
h
la
w
a
t
)
423
−
I
n
itializatio
n
:
I
n
itializatio
n
en
t
ails
d
eter
m
in
in
g
th
e
s
tar
tin
g
p
ar
am
eter
s
f
o
r
th
e
f
r
u
it
f
ly
p
o
p
u
latio
n
,
s
u
ch
as
p
o
p
u
latio
n
s
ize,
m
ax
im
u
m
ite
r
atio
n
s
,
in
itial
p
o
s
itio
n
s
,
an
d
s
tep
len
g
th
.
T
h
is
en
ab
les
f
r
u
it
f
lies
to
n
av
ig
ate
to
war
d
s
th
eir
tar
g
et
u
s
in
g
r
an
d
o
m
f
lig
h
t
d
ir
ec
tio
n
s
an
d
r
an
g
e
s
.
(
)
=
0
+
(
3
)
(
)
=
0
+
(
4
)
T
h
e
in
itial p
o
s
itio
n
o
f
th
e
f
r
u
it
f
ly
is
d
en
o
te
d
b
y
0
an
d
0
.
−
J
u
d
g
m
en
t: C
o
m
p
u
te
th
e
s
ce
n
t
co
n
ce
n
tr
atio
n
(
s
ce
n
t)
o
f
th
e
f
r
u
it f
ly
p
o
s
itio
n
u
s
in
g
th
e
f
itn
ess
f
u
n
ctio
n
(
)
=
(
(
)
)
(
5
)
(
)
=
1
(
(
)
2
+
(
)
∧
2
)
(
6
)
−
Mo
v
em
en
t:
Mo
v
e
m
en
t
in
v
o
lv
es
s
elec
tin
g
th
e
f
r
u
it
f
ly
in
d
i
v
id
u
al
with
th
e
h
ig
h
est
co
n
ce
n
tr
atio
n
with
in
th
e
p
o
p
u
latio
n
,
d
esig
n
atin
g
its
lo
c
atio
n
as
th
e
id
ea
l p
o
s
itio
n
.
Su
b
s
eq
u
en
tly
,
in
s
tr
u
ct
th
e
r
em
ai
n
in
g
f
r
u
it f
lies
to
m
o
v
e
in
t
h
at
d
ir
ec
tio
n
b
ased
o
n
th
eir
in
itial st
ep
len
g
th
.
−
I
ter
atio
n
:
R
ep
ea
t
s
tep
s
(
2
)
an
d
(
3
)
u
n
til
th
e
s
ce
n
t
co
n
ce
n
tr
atio
n
eith
er
m
ee
ts
th
e
p
r
ed
ef
in
ed
th
r
esh
o
ld
o
r
r
ea
ch
es
th
e
m
ax
im
u
m
n
u
m
b
er
o
f
iter
atio
n
s
.
T
h
e
f
itn
ess
f
u
n
ctio
n
s
elec
ts
th
e
r
o
o
t
m
e
an
s
q
u
ar
e
e
r
r
o
r
(
R
MSE
)
,
d
escr
ib
ed
as f
o
llo
ws:
=
√
∑
(
−
̂
)
2
⁄
=
1
(
7
)
T
h
is
in
d
icate
s
th
e
p
r
o
jecte
d
p
o
s
itio
n
v
alu
e
as
̂
,
th
e
d
is
cr
ete
p
o
s
itio
n
d
ata
u
tili
ze
d
f
o
r
p
r
o
c
ess
in
g
d
en
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,
th
e
co
u
n
t o
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ata
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ep
r
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n
,
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th
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t m
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Fig
u
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424
3
.
3
.
P
a
t
h
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s
t
a
bli
s
hm
ent
AC
O
is
a
m
etah
eu
r
is
tic
alg
o
r
ith
m
in
s
p
ir
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b
y
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e
h
av
io
r
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a
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I
n
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atu
r
e,
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n
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f
in
d
th
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o
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test
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ath
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o
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tim
izatio
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p
r
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b
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T
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p
r
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b
lem
s
ar
e
o
f
te
n
m
o
d
ele
d
as
g
r
ap
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s
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if
ic
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d
lin
k
s
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At
th
e
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tar
t,
ea
ch
n
o
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e
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ce
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tain
n
u
m
b
er
o
f
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t
s
,
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d
ea
ch
lin
k
h
as
an
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o
ciate
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weig
h
t.
T
h
is
weig
h
t is g
en
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ally
d
eter
m
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e
d
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ased
o
n
th
e
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h
y
s
ical
d
is
tan
ce
b
etwe
en
n
o
d
es,
a
g
e
n
er
ated
r
an
d
o
m
n
u
m
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er
,
o
r
a
v
alu
e
d
er
iv
ed
f
r
o
m
a
m
ath
em
atica
l
f
o
r
m
u
la.
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o
im
p
r
o
v
e
AC
O
's
u
n
ce
r
tain
co
n
v
er
g
en
ce
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it
ca
n
b
e
o
p
tim
ized
b
y
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n
s
id
er
i
n
g
f
ac
to
r
s
lik
e
r
esid
u
al
en
er
g
y
,
d
is
tan
ce
to
th
e
b
ase
s
tatio
n
,
an
d
n
o
d
e
d
eg
r
ee
.
T
h
e
p
r
o
ce
s
s
f
o
r
cr
ea
ti
n
g
r
o
u
tes u
s
in
g
AC
O
is
d
etailed
in
th
is
s
ec
tio
n
.
−
T
o
cr
ea
te
a
r
o
u
te
f
r
o
m
th
e
clu
s
ter
h
ea
d
(
C
H)
to
th
e
b
ase
s
tatio
n
(
B
S),
an
an
t
is
p
lace
d
at
ea
ch
C
H.
T
h
e
s
o
u
r
ce
C
H
th
en
g
en
er
ates
s
p
ec
if
ic
p
ac
k
ets
to
in
itiate
th
e
r
o
u
tin
g
p
r
o
ce
s
s
;
th
ese
p
ac
k
ets
ar
e
k
n
o
wn
as
f
o
r
war
d
a
n
t p
ac
k
ets
.
−
T
h
e
f
o
r
war
d
an
t
p
ac
k
ets
ar
e
r
an
d
o
m
l
y
s
en
t
to
th
e
n
ex
t
C
H
ac
co
r
d
in
g
to
a
p
r
o
b
ab
ilit
y
m
atr
ix
.
T
h
is
p
r
o
ce
s
s
o
f
f
o
r
war
d
in
g
th
e
p
ac
k
ets co
n
tin
u
es f
r
o
m
C
H
to
C
H
u
n
til th
ey
r
ea
c
h
th
e
B
S.
−
As
th
e
f
o
r
war
d
an
t
p
ac
k
ets
ar
e
tr
an
s
m
itted
,
ea
ch
p
ac
k
et
cr
e
ates
a
lo
ca
l
d
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ase
co
n
tain
i
n
g
in
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o
r
m
atio
n
ab
o
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t
th
e
C
Hs
it
v
is
its
.
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h
is
d
ata
in
clu
d
es
th
e
n
o
d
e
I
D,
r
esid
u
al
en
er
g
y
(
E
r
)
,
d
is
tan
ce
f
r
o
m
th
e
C
H
to
th
e
b
ase
s
tatio
n
(
.
)
,
an
d
th
e
n
o
d
e'
s
d
eg
r
ee
(
N
D
)
.
T
h
e
r
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u
al
en
er
g
y
in
ea
c
h
C
H
is
lar
g
ely
in
f
lu
en
ce
d
b
y
th
e
n
u
m
b
e
r
o
f
p
ac
k
ets (
l)
t
h
at
ar
e
tr
an
s
m
itted
th
r
o
u
g
h
th
e
n
etwo
r
k
.
−
On
ce
th
e
p
ath
is
estab
lis
h
ed
with
th
e
f
o
r
war
d
a
n
t
p
ac
k
ets
,
th
is
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ase
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u
s
ed
to
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ea
te
a
b
ac
k
war
d
a
n
t
p
ac
k
et
.
As
th
e
f
o
r
war
d
an
t
p
a
ck
et
p
r
o
g
r
ess
es
to
th
e
B
S,
th
e
b
ac
k
war
d
a
n
t
p
ac
k
et
f
o
llo
ws
th
e
s
am
e
r
o
u
te
in
r
ev
er
s
e.
I
t
u
s
es
th
e
in
f
o
r
m
a
tio
n
f
r
o
m
th
e
d
atab
ase
to
tr
ac
e
th
e
ex
ac
t
p
ath
th
at
th
e
f
o
r
w
ar
d
an
t
p
ac
k
et
to
o
k
to
r
ea
ch
th
e
B
S.
−
T
h
e
p
h
er
o
m
o
n
e
lev
els
f
o
r
ea
c
h
p
ath
ar
e
u
p
d
ate
d
b
ased
o
n
f
ac
to
r
s
lik
e
th
e
r
esid
u
al
en
er
g
y
,
th
e
d
is
tan
ce
f
r
o
m
th
e
n
o
d
e
to
th
e
b
ase
s
tatio
n
,
an
d
th
e
n
o
d
e'
s
d
eg
r
ee
.
−
T
h
e
an
t
ch
o
o
s
es
its
n
ex
t
h
o
p
ac
co
r
d
in
g
to
a
n
o
d
e
tr
an
s
itio
n
r
u
le
o
u
tlin
ed
in
(
8
)
,
wh
ich
ca
lcu
lates
th
e
p
r
o
b
a
b
ilit
y
o
f
a
n
an
t k
s
elec
tin
g
n
o
d
e
as th
e
n
e
x
t n
o
d
e
f
r
o
m
n
o
d
e
.
(
)
=
{
[
(
)
]
[
]
∑
[
(
)
]
[
]
∈
∈
0
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(
8
)
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e,
th
e
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r
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ten
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ated
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ased
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m
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ab
o
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t
th
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to
r
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th
e
r
o
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le.
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h
e
h
e
u
r
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tic
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o
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m
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ased
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th
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d
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u
p
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ated
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e,
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h
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r
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le
f
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r
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atin
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e
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e
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(
1
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1
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e
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m
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d
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th
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ep
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I
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Fig
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6
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r
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o
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s
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d
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e
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g
est
th
at
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p
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ap
p
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th
e
h
eter
o
g
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s
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n
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t
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er
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o
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th
e
o
th
e
r
ap
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ter
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u
r
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4
.
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Fig
u
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5
.
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e
o
f
d
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d
n
o
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es
Fig
u
r
e
6
.
Netwo
r
k
life
tim
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an
aly
s
is
5.
CO
NCLU
SI
O
N
T
h
is
wo
r
k
p
r
esen
ts
a
n
o
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f
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T
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FF
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ter
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m
atio
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.
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ly
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ased
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o
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o
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.
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h
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f
o
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m
a
n
ce
o
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th
e
p
r
o
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o
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ed
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o
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ith
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is
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h
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m
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in
g
th
e
MA
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AB
to
o
l.
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h
e
p
r
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p
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s
ed
m
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d
is
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m
p
ar
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to
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co
m
m
o
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al
g
o
r
ith
m
s
:
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e
b
io
g
e
o
g
r
a
p
h
y
-
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OA
an
d
th
e
L
E
AC
H.
I
n
th
e
co
n
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t
o
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g
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n
d
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ea
,
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e
p
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ed
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g
o
r
ith
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s
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r
p
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b
o
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OA
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d
L
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C
H,
esp
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ially
in
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.
T
h
is
d
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o
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s
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ates
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e
ef
f
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o
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s
,
esp
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n
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es
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v
i
r
o
n
m
en
tal
m
o
n
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r
in
g
is
n
ee
d
ed
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
AE
S
I
n
t
J
R
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b
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A
u
to
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I
SS
N:
2722
-
2
5
8
6
E
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F
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ax
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h
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wan
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:
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:
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:
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:
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Au
th
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r
s
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o
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f
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est.
DATA AV
AI
L
AB
I
L
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Y
I
n
th
is
r
esear
ch
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r
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ataset
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o
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.
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h
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en
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r
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ated
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ar
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d
b
ased
o
n
p
er
s
o
n
al
r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
J.
C
.
R
.
K
u
mar,
D
.
V
.
K
u
mar
,
B
.
M
.
A
r
u
n
si
,
D
.
B
a
s
k
a
r
,
a
n
d
M
.
A
.
M
a
j
i
d
,
“
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e
r
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e
f
f
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t
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k
,
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i
n
Pr
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d
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g
s
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6
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2
0
2
2
.
9
7
5
3
8
0
9
.
[
2
]
S
.
U
mar,
N
.
L.
R
e
d
d
y
,
T
.
B
.
Y
a
d
e
sa
,
T.
D
.
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e
ss
a
,
a
n
d
E.
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i
k
a
d
u
,
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l
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g
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f
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o
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m
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t
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o
n
a
p
p
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o
a
c
h
,
”
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n
2
0
2
2
I
n
t
e
r
n
a
t
i
o
n
a
l
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f
e
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n
c
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o
n
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p
p
l
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d
Art
i
f
i
c
i
a
l
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n
t
e
l
l
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g
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n
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a
n
d
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o
m
p
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g
(
I
C
AAIC)
,
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p
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C
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C
5
3
9
2
9
.
2
0
2
2
.
9
7
9
2
9
4
5
.
[
3
]
B
.
A
h
l
a
w
a
t
a
n
d
A
.
S
a
n
g
w
a
n
,
“
M
u
l
t
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l
e
v
e
l
r
o
u
t
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n
g
f
o
r
d
a
t
a
t
r
a
n
smis
si
o
n
i
n
i
n
t
e
r
n
e
t
o
f
t
h
i
n
g
s
,
”
I
n
d
o
n
e
si
a
n
J
o
u
r
n
a
l
o
f
El
e
c
t
ri
c
a
l
En
g
i
n
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ri
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g
a
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d
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p
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o
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,
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p
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2
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7
,
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s.
v
3
4
.
i
3
.
p
p
2
0
6
5
-
2
0
7
7
.
[
4
]
B
.
A
h
l
a
w
a
t
a
n
d
A
.
S
a
n
g
w
a
n
,
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e
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f
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c
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g
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l
s
f
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r
W
S
N
i
n
I
o
T:
a
s
u
r
v
e
y
,
”
2
0
2
2
I
n
t
e
r
n
a
t
i
o
n
a
l
C
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f
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r
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n
c
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o
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Ma
c
h
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n
e
L
e
a
r
n
i
n
g
,
B
i
g
D
a
t
a
,
C
l
o
u
d
a
n
d
P
a
ra
l
l
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l
C
o
m
p
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t
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n
g
,
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O
M
-
IT
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O
N
2
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2
,
n
o
.
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y
,
p
p
.
3
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5
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,
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:
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/
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N
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4
6
0
1
.
2
0
2
2
.
9
8
5
0
6
4
9
.
[
5
]
A
.
S
h
a
h
r
a
k
i
,
A
.
Ta
h
e
r
k
o
r
d
i
,
O
.
H
a
u
g
e
n
,
a
n
d
F
.
El
i
a
sse
n
,
“
A
su
r
v
e
y
a
n
d
f
u
t
u
r
e
d
i
r
e
c
t
i
o
n
s
o
n
c
l
u
st
e
r
i
n
g
:
f
r
o
m
W
S
N
s
t
o
I
o
T
a
n
d
mo
d
e
r
n
n
e
t
w
o
r
k
i
n
g
p
a
r
a
d
i
g
m
s,”
I
EE
E
T
ra
n
s
a
c
t
i
o
n
s
o
n
N
e
t
w
o
rk
a
n
d
S
e
rv
i
c
e
M
a
n
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g
e
m
e
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t
,
v
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l
.
1
8
,
n
o
.
2
,
p
p
.
2
2
4
2
–
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2
7
4
,
Ju
n
.
2
0
2
1
,
d
o
i
:
1
0
.
1
1
0
9
/
TN
S
M
.
2
0
2
0
.
3
0
3
5
3
1
5
.
[
6
]
V
.
V
i
ma
l
e
t
a
l
.
,
“
C
l
u
st
e
r
i
n
g
i
s
o
l
a
t
e
d
n
o
d
e
s
t
o
e
n
h
a
n
c
e
n
e
t
w
o
r
k
’
s
l
i
f
e
t
i
me
o
f
W
S
N
s
f
o
r
I
o
T
a
p
p
l
i
c
a
t
i
o
n
s,
”
I
EE
E
S
y
st
e
m
s
J
o
u
r
n
a
l
,
v
o
l
.
1
5
,
n
o
.
4
,
p
p
.
5
6
5
4
–
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6
6
3
,
D
e
c
.
2
0
2
1
,
d
o
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:
1
0
.
1
1
0
9
/
JS
Y
S
T.
2
0
2
1
.
3
1
0
3
6
9
6
.
[
7
]
G
.
K
a
u
r
,
P
.
C
h
a
n
a
k
,
a
n
d
M
.
B
h
a
t
t
a
c
h
a
r
y
a
,
“
E
n
e
r
g
y
-
e
f
f
i
c
i
e
n
t
i
n
t
e
l
l
i
g
e
n
t
r
o
u
t
i
n
g
sc
h
e
me
f
o
r
I
o
T
-
e
n
a
b
l
e
d
W
S
N
s,
”
I
EEE
I
n
t
e
rn
e
t
o
f
T
h
i
n
g
s
J
o
u
rn
a
l
,
v
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l
.
8
,
n
o
.
1
4
,
p
p
.
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1
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4
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4
4
9
,
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l
.
2
0
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1
,
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:
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0
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1
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0
9
/
JI
O
T.
2
0
2
1
.
3
0
5
1
7
6
8
.
[
8
]
A
.
R
o
d
r
í
g
u
e
z
,
C
.
D
e
l
-
V
a
l
l
e
-
S
o
t
o
,
a
n
d
R
.
V
e
l
á
z
q
u
e
z
,
“
En
e
r
g
y
-
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f
f
i
c
i
e
n
t
c
l
u
st
e
r
i
n
g
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t
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n
g
p
r
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t
o
c
o
l
f
o
r
w
i
r
e
l
e
ss
se
n
so
r
n
e
t
w
o
r
k
s
b
a
s
e
d
o
n
y
e
l
l
o
w
s
a
d
d
l
e
g
o
a
t
f
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sh
a
l
g
o
r
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t
h
m,”
M
a
t
h
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m
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t
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c
s
,
v
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l
.
8
,
n
o
.
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p
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,
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2
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:
1
0
.
3
3
9
0
/
m
a
t
h
8
0
9
1
5
1
5
.
[
9
]
O
.
O
.
O
g
u
n
d
i
l
e
,
M
.
B
.
B
a
l
o
g
u
n
,
O
.
E
.
I
j
i
g
a
,
a
n
d
E
.
O
.
F
a
l
a
y
i
,
“
E
n
e
r
g
y
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b
a
l
a
n
c
e
d
a
n
d
e
n
e
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g
y
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e
f
f
i
c
i
e
n
t
c
l
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s
t
e
r
i
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g
r
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t
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g
p
r
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t
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c
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f
o
r
w
i
r
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l
e
ss
se
n
so
r
n
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t
w
o
r
k
s,
”
I
ET
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o
m
m
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n
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c
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n
s
,
v
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,
J
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n
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4
9
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t
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m
.
2
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6
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3
.
[
1
0
]
T.
M
.
B
e
h
e
r
a
,
S
.
K
.
M
o
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a
p
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,
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.
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k
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e
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e
,
a
n
d
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.
K
.
S
a
h
o
o
,
“
W
o
r
k
-
in
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p
r
o
g
r
e
ss:
D
E
EC
-
V
D
:
A
h
y
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r
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n
2
0
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