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ta.
Re
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o
rm
s b
e
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K
ey
w
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d
s
:
C
lu
s
ter
lead
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C
lu
s
ter
in
g
Fu
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lo
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Mo
b
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elem
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t
Vir
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p
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ts
W
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etwo
r
k
T
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s
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c
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ss
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rticle
u
n
d
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r th
e
CC B
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SA
li
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C
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p
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A
uth
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:
Swap
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C
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Dep
ar
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atesh
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co
m
1.
I
NT
RO
D
UCT
I
O
N
L
ar
g
e
n
u
m
b
er
o
f
s
en
s
o
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s
ar
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d
ep
lo
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d
in
th
e
f
ield
,
ter
m
e
d
as
wir
eless
s
en
s
o
r
n
etwo
r
k
(
W
SN)
[
1
]
.
T
h
ese
s
en
s
o
r
s
h
elp
s
in
s
en
s
in
g
th
e
en
v
ir
o
n
m
en
t
an
d
co
m
m
u
n
icate
s
th
e
s
am
e
with
b
ase
s
tatio
n
an
d
f
r
o
m
b
ase
s
tatio
n
to
th
e
u
s
er
an
d
h
elp
s
t
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e
u
s
er
to
m
o
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ito
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an
d
co
n
tr
o
l
th
e
en
v
i
r
o
n
m
e
n
t
r
em
o
tely
.
T
h
u
s
,
W
SN
h
as
wid
e
r
an
g
e
o
f
a
p
p
licatio
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s
in
m
ilit
ar
y
s
u
r
v
eillan
ce
,
ag
r
ic
u
ltu
r
e,
m
ed
ical
d
o
m
ain
[
2
]
–
[
5
]
,
an
d
h
elp
s
to
m
o
n
ito
r
in
f
o
r
m
atio
n
s
u
ch
as
tem
p
er
at
u
r
e,
p
r
ess
u
r
e,
a
n
d
h
u
m
id
ity
.
W
h
ile
g
ath
er
in
g
th
e
i
n
f
o
r
m
atio
n
f
r
o
m
th
e
s
en
s
o
r
n
o
d
e
lo
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o
f
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wer
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co
n
s
u
m
e
d
to
tr
an
s
m
it
th
e
in
f
o
r
m
atio
n
f
r
o
m
ea
c
h
s
en
s
o
r
to
th
e
b
ase
s
tatio
n
[
6
]
.
T
h
e
l
o
w
en
er
g
y
ad
ap
tiv
e
clu
s
ter
in
g
h
i
er
ar
ch
y
(
L
E
AC
H)
[
7
]
is
o
n
e
o
f
th
e
h
ier
ar
c
h
ical
clu
s
ter
in
g
m
eth
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d
wh
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t
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n
etwo
r
k
is
p
a
r
titi
o
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r
clu
s
ter
ed
an
d
b
ased
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n
th
e
p
r
o
b
a
b
ilit
y
o
n
e
o
f
th
e
n
o
d
e
is
s
elec
ted
as
clu
s
ter
h
ea
d
(
C
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.
I
n
o
r
d
er
to
m
ak
e
th
e
n
e
two
r
k
last
lo
n
g
e
r
,
m
o
b
ile
ele
m
en
ts
ar
e
u
s
ed
.
T
h
ese
m
o
b
ile
elem
en
ts
[
8
]
,
[
9
]
go
to
th
e
C
H
an
d
r
ec
eiv
e
d
ata
f
r
o
m
th
e
n
etwo
r
k
.
Sev
er
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ar
tif
icial
in
tellig
en
ce
m
eth
o
d
s
,
wh
ich
ar
e
a
s
u
b
s
et
o
f
m
ac
h
in
e
lear
n
in
g
[
1
0
]
–
[
1
2
]
,
c
an
b
e
u
s
ed
t
o
b
o
o
s
t e
f
f
icien
cy
an
d
lo
wer
e
n
er
g
y
u
s
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell,
Vo
l.
1
3
,
No
.
4
,
Dec
em
b
er
2
0
2
4
:
3
8
2
7
-
3
8
3
6
3828
I
n
o
u
r
p
r
o
p
o
s
ed
wo
r
k
,
a
n
o
v
el
en
er
g
y
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f
icien
t
d
ata
g
ath
er
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g
alg
o
r
ith
m
f
o
r
wir
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ess
s
en
s
o
r
n
etwo
r
k
s
u
s
in
g
ar
tific
ial
in
tell
ig
en
ce
(
NDGA
I
)
th
e
b
ase
s
tatio
n
is
co
n
s
id
er
ed
to
b
e
at
th
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c
en
ter
.
T
h
e
n
etwo
r
k
co
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s
is
ts
o
f
h
u
n
d
r
ed
o
f
n
o
d
es
(
also
k
n
o
wn
as
m
o
tes)
an
d
th
e
en
tire
n
etwo
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is
s
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b
d
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m
b
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clu
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ter
s
b
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s
in
g
g
ap
s
tatis
tic
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alg
o
r
ith
m
alo
n
g
w
ith
am
en
d
ed
ex
p
ec
ted
m
a
x
im
izatio
n
(
AE
M)
.
T
h
e
clu
s
ter
lead
er
is
s
elec
ted
b
ase
d
o
n
th
e
f
u
zz
y
l
o
g
ic
n
ea
r
t
h
e
ce
n
tr
o
id
o
f
th
e
ea
c
h
cl
u
s
ter
.
T
h
e
m
o
b
ile
elem
en
t
h
as
to
r
ea
ch
all
t
h
e
clu
s
ter
s
an
d
g
ath
er
th
e
in
f
o
r
m
atio
n
.
T
h
e
s
to
p
p
o
in
ts
ar
e
th
e
v
ir
tu
al
p
o
in
ts
th
at
ar
e
co
n
s
id
er
ed
with
in
th
e
co
m
m
u
n
icatio
n
r
an
g
e
o
f
th
e
clu
s
ter
lead
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an
d
th
e
m
o
b
ile
elem
en
ts
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ch
es
th
es
e
v
ir
tu
al
p
o
in
ts
an
d
g
ath
er
th
e
d
ata.
T
h
e
p
ath
o
f
th
e
m
o
b
ile
elem
en
ts
is
d
eter
m
in
ed
b
y
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
alg
o
r
ith
m
with
ar
tific
ial
b
ee
co
lo
n
y
(
AB
C
)
n
am
ed
as
PS
O
-
AB
C
alg
o
r
ith
m
is
u
s
ed
,
wh
ich
s
o
lv
es
th
e
tr
av
ellin
g
s
alesm
an
p
r
o
b
lem
.
T
h
e
r
esid
u
e
o
f
p
ap
e
r
is
ca
teg
o
r
ized
as
liter
atu
r
e
r
ev
iew
in
s
ec
tio
n
2
,
s
ec
tio
n
3
p
r
esen
ts
th
e
s
y
s
tem
m
o
d
el
an
d
ass
u
m
p
tio
n
s
,
s
ec
tio
n
4
c
o
n
s
is
ts
o
f
p
r
o
p
o
s
ed
wo
r
k
,
s
ec
tio
n
5
c
o
n
s
is
ts
o
f
s
im
u
latio
n
r
esu
lts
,
an
d
f
in
al
ly
s
ec
tio
n
6
d
ea
ls
with
th
e
c
o
n
clu
s
io
n
s
.
2.
L
I
T
E
R
T
AU
RE
R
E
VI
E
W
Hein
ze
lm
an
et
a
l
.
[
1
3
]
p
r
o
p
o
s
ed
an
h
ier
ar
c
h
ical
r
o
u
tin
g
alg
o
r
ith
m
k
n
o
wn
as
L
E
AC
H.
Her
e
t
h
e
n
etwo
r
k
is
d
iv
id
ed
in
to
clu
s
ter
s
an
d
C
H’
s
ar
e
s
elec
ted
b
ased
o
n
th
e
p
r
o
b
ab
ilit
y
f
u
n
ctio
n
,
t
h
at
s
elec
ts
th
e
n
o
d
e
with
h
ig
h
en
e
r
g
y
as C
H.
Ho
wev
er
,
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
n
etwo
r
k
d
eg
r
ad
es a
s
th
e
C
H
s
en
d
s
th
e
d
ata
d
ir
ec
tly
to
th
e
b
ase
s
tatio
n
.
Salem
an
d
Sh
u
d
if
at
[
1
4
]
h
as
p
r
o
p
o
s
ed
a
n
en
h
an
ce
d
v
er
s
io
n
o
f
L
E
AC
H
p
r
o
to
co
l.
T
h
e
C
H
is
s
elec
ted
b
ased
o
n
th
e
d
is
ta
n
ce
f
u
n
ctio
n
in
s
u
ch
a
way
th
at
th
e
d
is
tan
ce
is
lo
w
f
r
o
m
b
ase
s
tat
io
n
an
d
th
is
h
elp
s
to
r
ed
u
ce
th
e
en
er
g
y
c
o
n
s
u
m
p
tio
n
b
y
in
cr
ea
s
in
g
th
e
n
e
two
r
k
life
tim
e.
Acc
o
r
d
in
g
to
Yo
u
n
is
an
d
Fah
m
y
[
1
5
]
,
an
alg
o
r
ith
m
is
d
esig
n
ed
in
wh
ich
C
H’
s
ar
e
s
elec
ted
b
y
co
n
s
id
er
in
g
th
e
n
o
d
e
r
esid
u
al
en
er
g
y
a
n
d
d
eg
r
ee
o
f
th
e
n
o
d
e
to
its
n
eig
h
b
o
u
r
s
an
d
ac
h
ie
v
es
u
n
v
a
r
y
in
g
C
H
d
is
tr
ib
u
tio
n
in
th
e
en
tire
n
etwo
r
k
.
Ho
wev
e
r
m
o
r
e
en
er
g
y
is
u
tili
ze
d
wh
e
n
d
ata
is
tr
an
s
m
itted
d
ir
ec
tly
to
t
h
e
b
as
e
s
tatio
n
.
L
i
n
d
s
e
y
a
n
d
R
a
g
h
a
v
e
n
d
r
a
[
1
6
]
h
a
s
p
r
o
p
o
s
e
d
a
n
a
l
g
o
r
i
t
h
m
,
p
o
w
e
r
-
e
f
f
i
c
i
e
n
t
g
a
t
h
e
r
i
n
g
i
n
s
e
n
s
o
r
i
n
f
o
r
m
a
t
i
o
n
s
y
s
t
e
m
s
(
P
E
G
A
S
I
S
)
,
i
n
w
h
i
c
h
c
h
a
i
n
a
m
o
n
g
t
h
e
s
e
n
s
o
r
n
o
d
e
s
a
r
e
f
o
r
m
e
d
a
n
d
t
h
e
n
o
d
e
t
r
a
n
s
i
t
i
t
s
i
n
f
o
r
m
a
t
i
o
n
t
o
a
n
e
a
r
e
s
t
n
e
i
g
h
b
o
u
r
n
o
d
e
s
a
n
d
t
h
e
n
f
i
n
a
l
l
y
t
o
t
h
e
b
a
s
e
s
t
a
t
i
o
n
.
B
u
t
t
h
e
n
o
d
e
s
c
l
o
s
e
t
o
t
h
e
b
a
s
e
s
t
a
t
i
o
n
d
i
e
f
a
s
t
e
r
,
w
h
i
c
h
s
h
o
r
t
e
n
s
t
h
e
l
i
f
e
o
f
t
h
e
n
e
t
w
o
r
k
.
C
H
s
e
l
e
c
t
i
o
n
i
s
a
l
s
o
l
o
o
k
e
d
a
t
i
n
[
1
7
]
.
T
h
i
s
m
e
t
h
o
d
g
e
t
s
t
h
e
l
o
w
e
s
t
l
a
g
b
y
s
t
o
p
p
i
n
g
t
h
e
p
r
o
c
e
s
s
f
o
r
O
(
l
o
g
l
o
g
N
)
w
h
e
n
N
n
o
d
e
s
a
r
e
g
i
v
e
n
a
n
d
g
i
v
i
n
g
a
p
a
t
h
l
o
s
s
e
x
p
o
n
e
n
t
o
f
2
.
T
h
e
h
i
e
r
a
r
c
h
i
c
a
l
g
r
o
u
p
i
n
g
m
e
t
h
o
d
i
s
u
s
e
d
i
n
[
1
8
]
.
E
a
c
h
c
l
u
s
t
e
r
h
a
s
a
C
H
t
h
a
t
g
a
t
h
e
r
s
d
a
t
a
f
r
o
m
t
h
e
o
t
h
e
r
c
l
u
s
t
e
r
m
e
m
b
e
r
s
,
a
d
d
s
i
t
a
l
l
t
o
g
e
t
h
e
r
,
a
n
d
s
e
n
d
s
i
t
t
o
t
h
e
b
a
s
e
s
t
a
t
i
o
n
b
y
t
h
e
c
l
o
s
e
s
t
C
H
.
E
a
c
h
C
H
i
n
a
c
l
u
s
t
e
r
t
a
k
e
s
a
t
u
r
n
b
a
s
e
d
o
n
t
h
e
t
i
m
e
.
A
s
t
i
m
e
g
o
e
s
o
n
,
t
h
o
u
g
h
,
t
h
e
l
e
f
t
o
v
e
r
e
n
e
r
g
y
m
a
y
b
e
l
e
s
s
t
h
a
n
t
h
e
c
u
t
o
f
f
e
n
e
r
g
y
,
w
h
i
c
h
b
r
e
a
k
s
t
h
e
t
r
a
n
s
m
i
s
s
i
o
n
l
i
n
k
.
A
s
t
h
e
u
t
i
l
i
z
a
t
i
o
n
o
f
w
i
r
e
l
e
s
s
s
e
n
s
o
r
n
e
t
w
o
r
k
s
i
s
i
n
c
r
e
a
s
i
n
g
d
r
a
s
t
i
c
a
l
l
y
t
h
e
r
e
i
s
l
o
t
o
f
r
e
s
e
a
r
c
h
h
a
p
p
e
n
i
n
g
a
n
d
t
h
e
a
u
t
h
o
r
s
h
a
v
e
d
e
s
i
g
n
e
d
a
l
g
o
r
i
t
h
m
s
b
a
s
e
d
o
n
m
o
b
i
l
e
n
o
d
e
[
1
9
]
.
I
n
o
t
h
e
r
w
o
r
d
s
,
a
m
o
b
i
l
e
n
o
d
e
w
a
s
u
s
e
d
.
T
h
i
s
n
o
d
e
s
e
n
d
s
d
a
t
a
t
o
t
h
e
b
a
s
e
s
t
a
t
i
o
n
f
r
o
m
t
h
e
C
H
o
r
t
h
e
c
l
u
s
t
e
r
.
O
n
e
i
d
e
a
f
r
o
m
C
h
o
e
t
a
l
.
[
2
0
]
i
s
t
o
u
s
e
m
o
b
i
l
e
s
i
n
k
s
t
o
c
o
l
l
e
c
t
d
a
t
a
a
s
p
a
r
t
o
f
a
p
r
o
g
r
a
m
m
e
.
I
n
t
h
e
P
-
L
E
A
C
H
a
l
g
o
r
i
t
h
m
t
h
a
t
w
a
s
c
r
e
a
t
e
d
,
t
h
e
g
r
o
u
p
s
a
r
e
s
h
a
p
e
d
l
i
k
e
c
i
r
c
l
e
s
a
n
d
a
r
e
s
p
l
i
t
i
n
t
o
f
o
u
r
s
e
p
a
r
a
t
e
a
r
e
a
s
.
E
a
c
h
o
f
t
h
e
s
e
a
r
e
a
s
c
a
n
e
f
f
e
c
t
i
v
e
l
y
t
r
a
c
k
m
o
b
i
l
e
s
i
n
k
s
a
n
d
s
a
v
e
e
n
e
r
g
y
.
O
n
t
h
e
o
t
h
e
r
h
a
n
d
,
t
h
e
s
u
g
g
e
s
t
e
d
m
e
t
h
o
d
h
a
s
m
o
r
e
d
a
t
a
t
h
a
t
i
s
d
u
p
l
i
c
a
t
e
d
.
G
a
o
e
t
a
l
.
[
2
1
]
h
a
v
e
u
s
e
d
i
n
t
e
g
e
r
-
l
i
n
e
a
r
-
p
r
o
g
r
a
m
m
i
n
g
p
r
o
b
l
e
m
a
n
d
p
r
o
p
o
s
e
d
m
a
x
i
m
u
m
a
m
o
u
n
t
s
h
o
r
t
e
s
t
p
a
t
h
a
n
d
r
e
d
u
c
e
d
e
n
e
r
g
y
c
o
n
s
u
m
p
t
i
o
n
,
b
y
f
i
n
d
i
n
g
o
p
t
i
m
a
l
m
a
p
p
i
n
g
b
e
t
w
e
e
n
i
t
s
m
e
m
b
e
r
s
a
n
d
s
u
b
-
s
i
n
k
.
S
i
e
t
a
l
.
[
2
2
]
h
a
s
e
m
p
l
o
y
e
d
a
d
a
t
a
g
a
t
h
e
r
i
n
g
m
e
t
h
o
d
b
a
s
e
d
o
n
f
u
z
z
y
r
u
l
e
-
b
a
s
e
d
C
H
s
e
l
e
c
t
i
o
n
b
y
c
o
n
s
i
d
e
r
i
n
g
r
e
s
i
d
u
a
l
e
n
e
r
g
y
o
f
n
o
d
e
s
,
d
e
g
r
e
e
o
f
c
e
n
t
r
a
l
i
t
y
,
s
i
n
k
d
i
s
t
a
n
c
e
a
n
d
n
u
m
b
e
r
o
f
n
e
i
g
h
b
o
u
r
n
o
d
e
s
.
T
h
i
s
e
n
s
u
r
e
s
u
n
i
f
o
r
m
C
H
d
i
s
t
r
i
b
u
t
i
o
n
.
A
l
o
n
g
w
i
t
h
C
H
e
l
e
c
t
i
o
n
,
i
n
t
r
a
c
l
u
s
t
e
r
d
a
t
a
a
g
g
r
e
g
a
t
i
o
n
u
s
i
n
g
c
o
r
r
e
l
a
t
i
o
n
f
u
n
c
t
i
o
n
i
n
f
u
z
z
y
t
h
e
o
r
y
i
s
a
d
o
p
t
e
d
[
2
3
]
.
3.
SYST
E
M
M
O
D
E
L
A
ND
AS
SUM
P
T
I
O
NS
T
h
e
m
ain
m
o
tiv
atio
n
f
o
r
o
u
r
p
r
o
p
o
s
ed
wo
r
k
NDGA
I
is
to
f
in
d
o
p
tim
al
n
u
m
b
er
o
f
clu
s
ter
,
clu
s
ter
lead
er
s
elec
tio
n
,
v
ir
tu
al
p
o
i
n
ts
s
elec
tio
n
an
d
p
ath
s
elec
tio
n
f
o
r
m
o
b
ile
elem
e
n
t
u
s
in
g
a
r
tific
ial
in
tellig
en
ce
to
th
e
ex
is
tin
g
alg
o
r
ith
m
s
.
I
n
o
u
r
p
r
o
p
o
s
ed
wo
r
k
,
S
n
u
m
b
er
o
f
s
en
s
o
r
n
o
d
es
ar
e
d
ep
lo
y
e
d
i
n
th
e
m
2
n
etwo
r
k
ar
ea
.
T
h
e
lo
ca
tio
n
o
f
t
h
e
s
en
s
o
r
n
o
d
es
in
k
n
o
wn
b
y
u
s
in
g
th
e
lo
ca
lizatio
n
tec
h
n
iq
u
e
.
T
h
e
n
etwo
r
k
is
b
ased
o
n
th
e
h
ier
ar
c
h
ical
n
etwo
r
k
[
2
4
]
,
i.e
.
,
it
c
o
n
s
is
ts
o
f
clu
s
ter
s
wi
th
k
cl
u
s
ter
ce
n
tr
o
id
s
d
en
o
ted
as
k
1
,k
2
,k
3
.
.
.
.
.
.
.
k
n
.
E
ac
h
clu
s
ter
co
n
s
is
ts
o
f
clu
s
t
er
lead
er
,
v
ir
tu
al
p
o
in
ts
p
o
in
t
s
b
etwe
en
clu
s
ter
lead
er
an
d
b
ase
s
tat
io
n
[
2
5
]
,
m
o
b
ile
elem
en
t to
g
ath
er
t
h
e
i
n
f
o
r
m
atio
n
f
r
o
m
clu
s
ter
lead
er
an
d
a
ce
n
ter
b
ase
s
tatio
n
.
3
.
1
.
Ass
um
ptio
n
s
T
h
e
f
o
llo
win
g
ar
e
s
o
m
e
o
f
t
h
e
ass
u
m
p
tio
n
s
th
at
a
r
e
co
n
s
id
er
ed
in
W
SN.
T
h
o
s
e
ass
u
m
p
tio
n
s
ar
e
lis
ted
as
f
o
llo
ws:
All
th
e
n
o
d
e
s
ar
e
d
e
p
lo
y
e
d
ac
c
o
r
d
in
g
t
o
G
au
s
s
ian
d
is
tr
ib
u
tio
n
f
u
n
ctio
n
.
T
h
e
co
m
m
u
n
icatio
n
r
an
g
e
o
f
all
th
e
s
en
s
o
r
n
o
d
es
in
clu
d
in
g
m
o
b
ile
elem
en
t
h
a
v
e
th
e
co
m
m
u
n
icatio
n
r
an
g
e
o
f
R
an
d
is
ab
le
to
co
m
m
u
n
icate
p
r
o
p
e
r
ly
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2
2
5
2
-
8
9
3
8
A
n
o
ve
l e
n
erg
y
efficien
t d
a
ta
g
a
th
erin
g
a
lg
o
r
ith
m
fo
r
w
ir
ele
s
s
s
en
s
o
r
n
etw
o
r
k
s
u
s
in
g
…
(
S
w
a
p
n
a
C
h
a
vv
a
)
3829
4.
P
RO
P
O
SE
D
WO
RK
T
h
e
p
r
o
p
o
s
ed
wo
r
k
NDGA
I
d
ea
ls
with
th
e
d
ata
g
at
h
er
in
g
f
r
o
m
th
e
s
en
s
o
r
n
o
d
es
in
th
e
W
SN.
W
h
ils
t
s
en
d
in
g
an
d
r
ec
eiv
in
g
th
e
d
ata
p
ac
k
ets,
lo
t o
f
en
er
g
y
is
co
n
s
u
m
ed
r
esp
ec
tiv
ely
as g
iv
en
b
y
(
1
)
an
d
(
2
)
.
=
{
+
2
d<
d
+
4
d
≥
(
1
)
=
(
2
)
W
h
er
e
en
er
g
y
r
eq
u
i
r
ed
f
o
r
t
r
an
s
m
is
s
io
n
is
g
iv
en
b
y
e
tr
;
en
er
g
y
r
e
q
u
ir
ed
f
o
r
r
ec
eiv
in
g
is
d
en
o
ted
as
e
rt
tr
an
s
m
itted
b
its
is
d
en
o
ted
b
y
l;
ea
ch
b
it
tr
an
s
it
en
er
g
y
is
E
ele
;
en
er
g
y
co
s
t
f
o
r
tr
a
n
s
m
is
s
i
o
n
an
d
r
ec
e
p
tio
n
o
f
s
ig
n
al
is
g
iv
en
b
y
ϵ
fs
d
2
a
n
d
ϵ
fs
d
4
;
tr
an
s
m
is
s
io
n
d
is
tan
ce
is
d
e
n
o
ted
as
d
,
d
0
is
th
e
e
r
r
o
r
f
r
ee
r
ec
eiv
in
g
d
is
tan
ce
.
T
h
u
s
f
r
o
m
(
1
)
it
is
clea
r
th
at
t
h
e
en
er
g
y
r
eq
u
ir
ed
f
o
r
tr
a
n
s
m
itti
n
g
th
e
d
ata
is
d
ir
ec
tly
p
r
o
p
o
r
tio
n
to
th
e
s
q
u
ar
e
o
f
th
e
co
m
m
u
n
icatio
n
d
is
tan
c
e.
4
.
1
.
Clus
t
er
ing
p
ha
s
e
C
lu
s
ter
in
g
th
e
s
en
s
o
r
n
etwo
r
k
m
ea
n
s
d
iv
id
in
g
th
e
e
n
tire
n
et
wo
r
k
in
to
s
u
b
n
etwo
r
k
s
.
T
h
e
b
en
ef
its
o
f
clu
s
ter
in
g
in
clu
d
e
tactica
l
r
eso
u
r
ce
u
s
ag
e,
s
ca
lab
ilit
y
o
f
n
et
wo
r
k
,
elev
ated
p
er
f
o
r
m
a
n
ce
a
n
d
to
av
o
id
lo
n
g
er
d
is
tan
ce
m
u
lti
h
o
p
co
m
m
u
n
ic
atio
n
.
B
ec
au
s
e
o
f
th
ese
ad
v
a
n
tag
es
clu
s
ter
in
g
is
co
n
s
id
er
e
d
to
b
e
o
n
e
o
f
th
e
m
ajo
r
s
tep
in
d
ata
g
ath
er
in
g
in
W
SN.
a.
Gap
s
tatis
tic
s
m
eth
o
d
to
d
eter
m
in
e
o
p
tim
al
n
u
m
b
e
r
o
f
clu
s
ter
s
:
I
n
g
ap
s
tatis
tics
m
eth
o
d
th
e
m
ax
im
u
m
n
u
m
b
er
o
f
clu
s
ter
k
max
h
as
to
b
e
d
ef
in
ed
i
n
itially
.
L
et
th
e
n
u
m
b
er
o
f
n
o
d
es
to
b
e
1
,
2
,
3
,
.
.
.
.
.
.
.
.
.
.
,
N
an
d
th
e
n
u
m
b
er
o
f
clu
s
ter
s
b
e
k
1
, k
2
, ......, k
max
.
T
h
e
o
p
tim
al
n
u
m
b
er
o
f
clu
s
ter
s
ca
n
b
e
ev
alu
ate
d
b
y
u
s
in
g
th
e
f
o
llo
win
g
s
tep
s
.
Step
.
1
: c
alcu
late
s
q
u
ar
ed
E
u
cl
id
ea
n
d
is
tan
ce
2
b
etwe
en
p
th
n
o
d
e
with
th
e
q
th
n
o
d
e
u
s
in
g
(
3
)
.
2
=
∑
(
−
)
2
=
1
(
3
)
L
et
k
r
d
en
o
te
th
e
in
d
ices o
f
o
b
s
er
v
atio
n
s
in
clu
s
ter
r
an
d
=
|
|
Step
.
2
:
ca
lcu
late
th
e
s
u
m
m
atio
n
b
etwe
en
th
e
p
air
s
o
f
d
is
tan
ce
s
o
f
all
th
e
n
o
d
es
th
at
b
el
o
n
g
to
th
e
clu
s
ter
r
,
u
s
in
g
(
4
)
.
=
∑
,
∈
(
4
)
Step
.
3
:
m
ea
s
u
r
e
d
is
p
er
s
io
n
with
in
in
tr
a
-
clu
s
ter
,
d
e
n
o
ted
b
y
,
wh
ich
g
iv
es
t
h
e
p
o
o
le
d
s
u
m
m
atio
n
o
f
s
q
u
ar
es with
in
clu
s
ter
m
ea
n
s
a
n
d
is
g
iv
en
b
y
(
5
)
.
=
∑
1
2
=
1
D
(
5
)
Step
.
4
:
g
en
er
ate
D
r
ef
er
en
ce
p
o
in
ts
u
s
in
g
u
n
if
o
r
m
r
an
d
o
m
d
is
tr
ib
u
tio
n
.
C
lu
s
ter
ea
ch
o
f
th
ese
d
ata
p
o
in
ts
b
y
co
n
s
id
er
in
g
k
1
,
k
2
…….
k
max
.
B
y
co
n
s
id
er
in
g
all
th
ese
d
ata
p
o
in
ts
ca
lcu
late
th
e
d
if
f
er
en
t
s
izes
o
f
clu
s
ter
s
,
en
u
m
er
ate
d
is
p
er
s
io
n
with
in
i
n
tr
a
-
clu
s
ter
g
iv
e
n
b
y
.
S
t
e
p
.
5
:
c
o
m
p
u
t
e
t
h
e
d
e
v
i
a
t
i
o
n
b
e
t
w
e
e
n
a
n
d
u
s
i
n
g
(
6
)
a
n
d
s
t
a
n
d
a
r
d
d
e
v
i
a
t
i
o
n
c
a
n
b
e
c
a
l
c
u
l
a
t
e
d
u
s
i
n
g
(
7
)
.
(
)
=
1
∑
(
(
)
−
=
1
(
)
)
(
6
)
=
[
1
∑
(
(
)
−
=
1
(
)
)
]
[
√
1
+
1
]
(
7
)
Step
.
6
:
f
in
ally
,
th
e
o
p
tim
al
n
u
m
b
er
o
f
cl
u
s
ter
v
alu
e
is
ca
lcu
lated
in
s
u
ch
a
way
th
at
th
e
s
m
allest
v
alu
e
o
f
k
p
r
o
v
id
e
d
th
e
c
o
n
d
itio
n
s
tated
in
(
8
)
is
s
atis
f
ied
.
(
)
≥
(
+
1
)
−
+
1
(
8
)
T
h
u
s
,
u
s
in
g
g
a
p
s
tatis
tics
,
th
e
o
p
tim
al
n
u
m
b
er
o
f
clu
s
ter
s
ar
e
d
eter
m
in
e
d
.
W
h
en
th
e
o
p
tim
al
n
u
m
b
er
o
f
clu
s
ter
s
ar
e
id
en
tifie
d
,
cl
u
s
ter
s
ar
e
f
o
r
m
ed
b
y
u
s
in
g
a
m
en
d
e
d
ex
p
ec
tatio
n
m
ax
im
izatio
n
al
g
o
r
ith
m
wh
ich
is
a
s
tatis
t
ical
m
eth
o
d
to
d
eter
m
in
e
m
ax
im
u
m
lik
elih
o
o
d
f
u
n
ctio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell,
Vo
l.
1
3
,
No
.
4
,
Dec
em
b
er
2
0
2
4
:
3
8
2
7
-
3
8
3
6
3830
b.
AE
M
alg
o
r
ith
m
:
ex
p
ec
tatio
n
m
ax
im
izatio
n
alg
o
r
it
h
m
is
a
s
ta
tis
tica
l
ap
p
r
o
ac
h
an
d
b
elo
n
g
s
to
u
n
s
u
p
er
v
is
ed
lear
n
in
g
m
eth
o
d
an
d
is
u
s
ed
in
th
e
f
o
r
m
a
tio
n
o
f
clu
s
ter
s
in
th
e
W
S
N.
ex
p
ec
tatio
n
m
ax
im
izatio
n
alg
o
r
ith
m
is
o
n
e
o
f
th
e
s
o
f
t
clu
s
ter
in
g
alg
o
r
ith
m
s
,
wh
ich
m
ea
n
s
th
at
th
e
clu
s
ter
s
m
ay
o
v
er
lap
,
i.e
.
,
th
e
n
o
d
e
m
a
y
b
e
lo
n
g
to
m
o
r
e
th
an
o
n
e
clu
s
ter
an
d
th
e
am
o
u
n
t
o
f
r
elatio
n
s
h
i
p
o
f
th
e
n
o
d
e
with
ea
ch
clu
s
ter
is
id
en
tifie
d
b
y
ca
lcu
latin
g
th
e
d
eg
r
ee
o
f
r
esp
o
n
s
ib
ilit
y
o
f
th
e
n
o
d
e
to
th
e
clu
s
ter
.
Hen
ce
to
ca
lcu
late
th
e
E
u
clid
e
an
d
is
tan
ce
th
e
g
e
n
er
alize
d
f
o
r
m
u
la
ad
o
p
ted
is
g
iv
en
i
n
(
9
)
.
=
√
(
−
)
2
−
(
−
)
2
(
9
)
T
h
e
n
o
d
e
in
a
W
SN
b
elo
n
g
s
to
a
p
ar
ticu
lar
clu
s
ter
if
its
d
is
t
an
ce
to
th
e
ce
n
tr
o
id
p
o
in
ts
is
less
wh
en
co
m
p
ar
ed
with
t
h
e
d
is
tan
ce
f
r
o
m
o
th
er
ce
n
tr
o
i
d
s
.
Af
ter
in
i
tial
clu
s
ter
s
ar
e
f
o
r
m
ed
th
e
m
ea
n
v
alu
e
f
o
r
ea
c
h
clu
s
ter
d
en
o
ted
b
y
µ
k
is
ca
lc
u
lated
b
y
co
n
s
id
er
i
n
g
th
e
av
e
r
ag
e
o
f
all
th
e
n
o
d
es
th
at
b
el
o
n
g
t
o
a
p
ar
ticu
lar
clu
s
ter
.
C
o
v
ar
ian
ce
,
ξ
k
is
ca
lcu
lated
u
s
in
g
(
1
0
)
.
=
1
∑
(
=
1
−
)
(
−
)
(
1
0
)
T
h
u
s
th
e
in
itial
clu
s
ter
p
ar
am
e
ter
s
µ
k
an
d
ξ
k
ar
e
o
b
tain
ed
an
d
th
ese
ar
e
th
e
p
o
s
itio
n
v
ec
to
r
s
o
f
clu
s
ter
ce
n
tr
o
id
s
.
Du
r
in
g
in
itializatio
n
s
tep
,
n
o
d
es
in
W
SN
ar
e
d
ep
lo
y
ed
ac
co
r
d
in
g
to
th
e
Ga
u
s
s
ian
d
is
tr
ib
u
tio
n
f
u
n
ctio
n
with
p
r
o
b
ab
ilit
y
f
u
n
c
tio
n
,
g
iv
e
n
b
y
(
1
1
)
.
(
)
=
∑
(
,
)
(
1
1
)
W
h
er
e
x
n
is
th
e
n
th
n
o
d
e
p
o
s
itio
n
v
ec
to
r
,
k
ar
e
th
e
n
u
m
b
er
o
f
clu
s
ter
s
,
µ
k
is
th
e
m
ix
in
g
co
ef
f
icien
t
an
d
th
e
v
alu
e
o
f
π
k
d
e
p
en
d
s
o
n
th
e
n
u
m
b
er
o
f
clu
s
ter
s
an
d
th
e
c
o
n
d
itio
n
o
n
π
k
ca
lcu
lated
b
ased
o
n
µ
k
an
d
it
is
a
2
2
d
iag
o
n
al
m
atr
i
x
.
(
,
)
is
th
e
Gau
s
s
i
an
d
is
tr
ib
u
tio
n
f
u
n
ctio
n
g
iv
e
n
b
y
(
1
2
)
.
(
,
)
=
1
(
2
)
|
|
[
−
1
2
(
−
)
−
1
(
−
)
]
(
1
2
)
Du
r
in
g
ex
p
ec
tatio
n
s
tep
,
th
e
d
eg
r
ee
o
f
r
esp
o
n
s
ib
ilit
y
,
o
f
ea
c
h
n
o
d
e
to
th
e
cl
u
s
ter
h
as
to
b
e
ca
lcu
lated
.
Deg
r
ee
o
f
r
esp
o
n
s
ib
ilit
y
,
d
en
o
te
d
as Γ
kn
ca
n
b
e
o
b
tain
ed
u
s
in
g
(
1
3
)
.
Γ
=
(
,
)
∑
=
1
(
,
)
(
1
3
)
As
a
n
ex
t
s
tep
,
m
ax
im
izatio
n
s
tep
h
as
to
b
e
ex
ec
u
te
d
.
I
n
th
i
s
s
tep
u
s
in
g
th
e
d
eg
r
ee
o
f
r
esp
o
n
s
ib
ilit
y
f
u
n
ctio
n
,
wh
ich
is
o
b
tain
ed
i
n
th
e
ex
p
ec
tatio
n
s
tep
h
as
to
b
e
u
s
ed
to
f
in
d
t
h
e
n
ew
p
ar
am
eter
s
o
f
th
e
cl
u
s
ter
ce
n
tr
o
id
s
.
T
h
is
ca
n
b
e
u
p
d
at
ed
with
th
e
n
ew
v
alu
es
as
s
h
o
wn
f
r
o
m
(
1
4
)
-
(
1
7
)
.
T
h
e
n
ew
m
ea
n
v
alu
e
is
ca
lcu
lated
as in
(
1
4
)
.
=
1
∑
=
1
(
1
4
)
T
h
e
to
tal
n
u
m
b
er
o
f
n
o
d
es th
a
t b
elo
n
g
t
o
clu
s
ter
K
is
g
iv
en
b
y
(
1
5
)
.
=
∑
=
1
(
1
5
)
T
h
e
m
ix
in
g
co
ef
f
icie
n
t π
k
ca
n
b
e
u
p
d
ated
u
s
in
g
(
1
6
)
.
=
(
1
6
)
C
o
v
ar
ian
ce
ca
n
b
e
u
p
d
ated
b
y
u
s
in
g
(
1
7
)
.
=
1
∑
=
1
(
−
)
(
−
)
(
1
7
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2
2
5
2
-
8
9
3
8
A
n
o
ve
l e
n
erg
y
efficien
t d
a
ta
g
a
th
erin
g
a
lg
o
r
ith
m
fo
r
w
ir
ele
s
s
s
en
s
o
r
n
etw
o
r
k
s
u
s
in
g
…
(
S
w
a
p
n
a
C
h
a
vv
a
)
3831
Af
ter
u
p
d
atin
g
th
e
p
a
r
am
eter
s
o
f
th
e
ce
n
tr
o
id
o
f
th
e
clu
s
ter
,
as
a
last
s
tep
,
th
e
ex
p
ec
tatio
n
m
ax
im
izatio
n
alg
o
r
ith
m
is
ev
alu
ated
b
y
e
v
al
u
atin
g
co
n
v
er
g
e
n
ce
o
f
lo
g
lik
e
lih
o
o
d
f
u
n
ctio
n
as g
iv
en
i
n
(
1
8
)
.
=
(
,
,
)
=
∑
(
∑
(
,
)
=
1
)
=
1
(
1
8
)
4
.
2
.
Clus
t
er
lea
der
a
nd
v
irt
ua
l p
o
int
s
elec
t
io
n
C
lu
s
ter
lead
er
elec
tio
n
p
h
as
e:
f
o
llo
win
g
th
e
clu
s
ter
s
f
o
r
m
atio
n
,
th
e
clu
s
ter
lead
er
h
as
to
b
e
d
eter
m
in
ed
n
ea
r
th
e
ce
n
tr
o
i
d
,
s
o
th
at
all
th
e
n
o
d
es
with
in
t
h
e
clu
s
ter
ca
n
s
en
d
th
eir
g
ath
er
ed
in
f
o
r
m
atio
n
to
th
e
clu
s
ter
lead
er
.
I
t
m
ain
ly
co
n
s
is
ts
o
f
f
o
u
r
p
ar
ts
.
T
h
e
y
ar
e
i)
Fu
zz
if
ier
,
ii)
Fu
zz
y
r
u
le
b
ase
s
y
s
tem
,
iii)
in
tellig
en
t f
u
zz
y
in
f
er
en
ce
s
y
s
tem
(
I
I
S),
an
d
i
v
)
Def
u
zz
i
f
ier
,
as sh
o
wn
in
Fig
u
r
e
1
.
Fig
u
r
e
1
.
Fu
zz
y
lo
g
ic
c
o
n
tr
o
ll
er
s
y
s
tem
a)
Fu
zz
if
ier
:
f
u
zz
i
f
ier
co
n
v
er
ts
c
r
is
p
n
u
m
b
er
s
f
r
o
m
t
h
e
in
p
u
ts
to
th
e
f
u
zz
y
s
et
o
f
v
alu
es.
T
h
e
in
p
u
ts
to
th
is
Fu
zz
if
ier
ar
e:
−
C
lo
s
en
ess
o
f
n
o
d
e
to
th
e
clu
s
ter
ce
n
tr
o
id
(
C
C
C
)
: n
o
d
e
ce
n
tr
ality
co
n
v
ey
s
th
e
in
f
o
r
m
atio
n
t
h
at
h
o
w
m
u
c
h
n
ea
r
th
e
n
o
d
e
is
to
th
e
ce
n
tr
o
i
d
in
ea
ch
cl
u
s
ter
.
T
h
u
s
C
C
ca
n
b
e
ca
lcu
lated
b
y
u
s
in
g
(
1
9
)
.
=
√
,
(
1
9
)
−
Neig
h
b
o
u
r
n
o
d
es:
it
tells
u
s
h
o
w
m
a
n
y
n
o
d
es
ar
e
s
u
r
r
o
u
n
d
ed
b
y
th
e
elec
ted
clu
s
ter
lead
er
a
n
d
t
h
e
eq
u
atio
n
to
ca
lcu
late
n
eig
h
b
o
u
r
n
o
d
es is
g
iv
e
n
in
(
2
0
)
.
=
(
2
0
)
wh
er
e
L
is
th
e
n
u
m
b
er
o
f
n
ei
g
h
b
o
u
r
s
an
d
M
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
m
o
r
e
t
h
e
v
alu
e
o
f
n
eig
h
b
o
u
r
n
o
d
es th
e
m
o
r
e
th
e
c
h
an
ce
s
to
b
e
th
e
clu
s
ter
lead
er
.
−
Dir
ec
tio
n
o
f
n
o
d
e
to
war
d
s
b
a
s
e
s
tatio
n
(
D
B
S):
it
tells
u
s
t
h
at
h
o
w
m
u
ch
th
e
n
o
d
e
is
n
ea
r
to
th
e
b
ase
s
tatio
n
.
I
t c
an
b
e
ca
lc
u
lated
u
s
in
g
(
2
1
)
.
=
√
,
(
2
1
)
wh
er
e
n
k
is
th
e
n
th
n
o
d
e
i
n
k
th
clu
s
ter
an
d
b
is
th
e
l
o
ca
tio
n
o
f
b
ase
s
tatio
n
.
T
h
e
less
th
e
DB
S
v
alu
e,
th
e
m
o
r
e
th
e
c
h
an
ce
s
to
b
ec
o
m
e
c
lu
s
ter
lead
er
.
Po
s
=
[
Ver
y
Hig
h
,
Hig
h
,
Me
d
i
u
m
Hig
h
,
Me
d
i
u
m
L
o
w,
L
o
w,
Ver
y
L
o
w]
b)
Def
u
zz
if
ier
:
d
ef
u
zz
if
ier
h
elp
s
in
d
ef
u
zz
if
icatio
n
.
Def
f
u
zif
ie
r
tak
es
th
e
f
u
zz
y
o
u
tp
u
t
s
et
f
r
o
m
th
e
I
I
S
an
d
p
r
o
v
id
es
cr
is
p
o
u
tp
u
t,
th
at
h
e
lp
s
in
d
eter
m
in
in
g
th
e
clu
s
ter
lead
er
ac
cu
r
ately
.
T
h
u
s
to
o
b
tain
th
e
cr
is
p
o
u
tp
u
t
f
r
o
m
d
ef
u
zz
if
ier
,
th
e
c
en
tr
o
id
m
eth
o
d
,
w
h
ich
is
also
k
n
o
wn
as
th
e
ce
n
ter
o
f
ar
ea
is
u
s
ed
.
I
n
th
is
m
eth
o
d
t
h
e
ce
n
ter
p
o
in
t
is
d
et
er
m
in
ed
,
w
h
er
e
th
e
ar
ea
u
n
d
e
r
th
e
cu
r
v
e
o
n
b
o
th
s
id
es
o
f
th
i
s
p
o
in
t
is
eq
u
al
an
d
th
e
s
am
e
is
o
b
tain
e
d
b
y
u
s
in
g
(
2
2
)
.
∫
(
)
=
∫
(
)
∗
∗
(
2
2
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell,
Vo
l.
1
3
,
No
.
4
,
Dec
em
b
er
2
0
2
4
:
3
8
2
7
-
3
8
3
6
3832
Vir
tu
al
p
o
in
ts
elec
tio
n
p
h
ase:
th
e
s
elec
tio
n
o
f
v
i
r
tu
al
p
o
in
t
is
v
er
y
im
p
o
r
tan
t
to
r
e
d
u
ce
th
e
p
ath
len
g
th
o
f
th
e
m
o
b
ile
elem
en
t.
Selectin
g
th
e
o
p
tim
al
n
u
m
b
e
r
o
f
v
ir
tu
al
p
o
in
ts
h
as
to
b
e
a
ch
iev
ed
,
s
o
th
at
th
e
d
ata
is
co
llected
ef
f
ec
tiv
ely
.
T
h
e
d
is
tan
ce
f
r
o
m
th
e
clu
s
ter
lead
er
an
d
th
e
b
ase
s
tatio
n
c
an
b
e
ca
lcu
lated
b
y
u
s
in
g
E
u
clid
ea
n
d
is
tan
ce
an
d
t
h
en
b
y
s
u
b
tr
ac
tin
g
th
e
r
an
g
e
o
f
co
m
m
u
n
icatio
n
as sh
o
wn
i
n
(
2
3
)
.
,
=
√
(
−
1
)
2
−
(
−
2
)
2
(
2
3
)
wh
er
e
i
is
th
e
i
th
clu
s
ter
lea
d
er
,
(
c
i
,
c
j
)
ar
e
th
e
clu
s
ter
le
ad
er
o
r
d
i
n
ates
an
d
(
b
1
,
b
2
)
a
r
e
th
e
b
ase
s
tatio
n
co
o
r
d
in
ates.
T
h
u
s
b
y
u
s
in
g
(
2
3
)
th
e
ex
ac
t
p
o
in
t
o
f
v
ir
t
u
al
p
o
in
ts
ca
n
b
e
o
b
tain
e
d
.
4
.
3
.
P
a
t
h det
er
m
ina
t
io
n pha
s
e
T
h
e
s
ea
r
ch
is
m
ad
e
i
n
s
u
ch
a
way
th
at
th
e
o
b
jectiv
e
f
u
n
ctio
n
v
alu
e
is
m
in
im
ized
.
T
h
e
o
b
jectiv
e
f
u
n
ctio
n
is
f
ix
e
d
b
y
co
n
s
id
er
i
n
g
th
e
p
ar
a
m
eter
s
s
u
ch
as in
(
2
4
)
.
=
(
)
,
(
)
,
(
)
(
2
4
)
wh
er
e
is
th
e
d
is
tan
ce
b
etwe
en
th
e
n
o
d
es,
e
CL
is
th
e
en
er
g
y
in
clu
s
ter
lead
er
,
tm
is
th
e
tim
e
tak
en
b
y
t
h
e
m
o
b
ile
elem
en
t to
r
ea
ch
th
e
v
i
r
tu
al
p
o
in
ts
.
T
h
u
s
th
e
o
b
jectiv
e
f
u
n
ctio
n
is
g
iv
en
as in
(
2
5
)
.
=
(
1
+
2
+
3
(
2
5
)
On
ce
th
e
o
b
jectiv
e
f
u
n
ctio
n
is
f
ix
ed
th
e
ar
tific
ial
b
ee
s
th
at
a
r
e
p
r
esen
t
in
th
e
s
ea
r
ch
s
p
ac
e
r
an
d
o
m
l
y
s
elec
ts
an
in
itial
v
ec
to
r
an
d
la
ter
th
e
b
est
r
o
u
te
is
f
o
u
n
d
f
r
o
m
th
e
in
itial
p
o
p
u
latio
n
b
y
u
s
in
g
g
r
ee
d
y
s
o
lu
tio
n
.
T
h
is
is
ac
h
iev
ed
b
y
iter
ativ
e
m
eth
o
d
an
d
em
p
lo
y
in
g
th
e
s
tr
ateg
y
b
y
m
o
v
in
g
to
war
d
s
th
e
b
etter
s
o
lu
tio
n
an
d
b
y
ab
an
d
o
n
in
g
th
e
p
o
o
r
s
o
lu
ti
o
n
.
T
o
d
eter
m
in
e
wh
eth
e
r
th
e
s
o
lu
tio
n
is
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Evaluation Warning : The document was created with Spire.PDF for Python.