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I
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W
ir
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Me
s
h
Ne
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w
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k
(
W
MN
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is
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ed
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s
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atic
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m
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f
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w
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s
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m
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ed
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s
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s
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c
h
as
[
1
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1
2
]
.
T
h
ese
w
ir
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s
ta
tio
n
s
in
(
W
MN
)
ar
e
k
n
o
w
n
to
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v
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m
i
ted
m
o
b
il
it
y
o
r
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m
o
b
ilit
y
at
al
l
[
1
3
]
.
B
y
u
s
i
n
g
a
m
e
s
h
n
et
w
o
r
k
p
r
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to
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l,
th
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s
tatio
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s
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e
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m
m
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l
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b
y
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atter
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m
m
u
n
i
ca
te
w
it
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ea
c
h
o
t
h
er
to
b
r
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ad
ca
s
t
m
es
s
ag
e
s
a
n
d
ex
ec
u
te
o
th
er
tas
k
s
.
T
h
er
e
ar
e
t
w
o
t
y
p
e
s
o
f
n
o
d
es
in
W
MN
;
m
es
h
r
o
u
ter
s
a
n
d
m
e
s
h
clie
n
ts
.
I
n
o
r
d
er
to
s
u
p
p
o
r
t
m
e
s
h
n
et
w
o
r
k
i
n
g
,
m
es
h
r
o
u
ter
s
h
a
v
e
ad
d
itio
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al
r
o
u
t
i
n
g
f
u
n
ctio
n
s
s
u
c
h
a
s
i
ts
m
u
l
tip
le
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u
ilt
-
n
o
w
ir
eles
s
i
n
ter
f
a
ce
to
i
m
p
r
o
v
e
t
h
e
f
le
x
ib
ilit
y
o
f
t
h
e
n
et
w
o
r
k
a
n
d
its
lo
w
tr
an
s
m
is
s
io
n
p
o
w
er
th
r
o
u
g
h
m
u
lt
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-
h
o
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co
m
m
u
n
icatio
n
.
A
W
MN
is
al
s
o
r
eliab
le
an
d
o
f
f
er
s
r
ed
u
n
d
a
n
c
y
.
I
f
o
n
e
n
o
d
e
f
ails
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o
p
er
ate,
th
e
r
e
s
t
o
f
t
h
e
n
o
d
es
i
n
n
et
w
o
r
k
ca
n
s
ti
ll
co
m
m
u
n
icate
w
i
th
o
n
e
a
n
o
th
e
r
as
its
n
ei
g
h
b
o
r
w
il
l
s
i
m
p
l
y
f
i
n
d
an
o
t
h
er
r
o
u
te.
D
u
e
to
d
y
n
a
m
ic
r
o
u
t
in
g
,
n
o
d
es
h
av
e
t
h
e
ca
p
ab
ilit
y
to
ch
o
o
s
e
th
e
q
u
ic
k
es
t
p
ath
to
s
e
n
d
in
f
o
r
m
atio
n
.
I
n
a
f
u
l
l
m
e
s
h
to
p
o
lo
g
y
,
ev
er
y
n
o
d
e
in
ter
ac
ts
a
n
d
co
m
m
u
n
icate
s
w
it
h
ea
c
h
o
th
er
n
o
t
j
u
s
t
b
ac
k
an
d
f
o
r
th
to
t
h
e
ce
n
tr
al
r
o
u
ter
an
d
t
h
is
h
elp
s
co
n
f
i
g
u
r
e
r
o
u
tes in
a
m
o
r
e
d
y
n
a
m
ic
m
a
n
n
er
.
I
t
is
e
v
id
en
t
th
at
W
MN
s
ar
e
s
elf
-
co
n
f
i
g
u
r
i
n
g
an
d
s
el
f
-
h
ea
li
n
g
.
Ho
w
e
v
er
,
t
h
er
e
a
r
e
i
m
m
i
n
en
t
is
s
u
e
s
th
at
t
h
e
s
e
n
et
w
o
r
k
s
f
ac
e.
A
lar
g
e
n
u
m
b
er
o
f
o
p
en
r
ese
ar
ch
es
d
is
c
u
s
s
W
MN
li
m
itat
io
n
s
s
u
c
h
a
s
lo
ad
b
alan
cin
g
,
en
er
g
y
o
p
ti
m
iza
ti
o
n
,
r
o
u
te
o
p
tim
izat
io
n
,
co
s
t
m
in
i
m
iza
tio
n
,
u
n
s
p
lit
tab
le
f
lo
w
,
an
d
li
m
ited
r
eso
u
r
ce
s
.
T
h
is
w
o
r
k
f
o
c
u
s
es
o
n
co
s
t
m
i
n
i
m
izatio
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f
o
r
estab
lis
h
in
g
a
n
et
w
o
r
k
b
y
u
s
i
n
g
h
e
u
r
is
tic
al
g
o
r
ith
m
s
.
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I
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310
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g
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r
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r
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Fig
u
r
e
1
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W
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in
f
r
astr
u
ct
u
r
e.
A
d
ap
ted
f
r
o
m
[
1
4
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I
n
Fig
u
r
e
1
,
th
e
d
as
h
ed
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d
s
o
lid
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es
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n
d
icate
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s
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d
w
ir
ed
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s
r
esp
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el
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r
m
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m
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s
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o
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in
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r
astr
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r
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ase,
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m
ed
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l
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eg
io
n
o
n
t
h
e
s
a
m
e
c
h
a
n
n
el.
T
h
is
is
ca
lled
d
en
s
e
m
e
s
h
n
et
w
o
r
k
d
ile
m
m
a.
Am
o
n
g
t
h
e
wa
y
s
to
r
eso
l
v
e
th
is
is
s
u
e
is
s
p
litt
i
n
g
n
et
w
o
r
k
r
eso
u
r
ce
s
i
n
th
eir
o
w
n
ch
a
n
n
el
s
u
c
h
as
s
p
lit
tin
g
ti
m
e
i
n
ti
m
e
ch
a
n
n
el
a
n
d
f
r
eq
u
e
n
c
y
in
f
r
eq
u
e
n
c
y
c
h
a
n
n
el
[
1
5
]
.
No
w
th
at
t
h
er
e
ar
e
r
eso
u
r
ce
s
n
ee
d
to
b
e
h
an
d
led
,
a
q
u
esti
o
n
o
f
h
o
w
to
allo
ca
te
th
ese
a
v
ailab
le
r
eso
u
r
ce
s
ar
i
s
e
s
w
h
ile
ta
k
i
n
g
o
th
er
f
ac
to
r
s
i
n
t
o
co
n
s
id
er
atio
n
as
w
ell.
I
n
w
ir
ele
s
s
n
et
w
o
r
k
r
o
u
te
p
la
n
n
i
n
g
,
r
eso
u
r
ce
allo
ca
tio
n
p
la
y
s
an
i
m
p
o
r
tan
t
r
o
le
to
g
iv
e
a
co
s
t
-
an
d
-
en
er
g
y
-
e
f
f
icie
n
t
s
o
l
u
tio
n
.
He
u
r
is
tic
ap
p
r
o
ac
h
to
s
o
lv
e
p
ath
p
lan
n
in
g
in
w
ir
ele
s
s
n
e
t
w
o
r
k
is
s
e
en
as
o
n
e
o
f
th
e
m
o
s
t p
o
p
u
lar
r
esear
ch
ar
ea
s
i
n
th
e
r
ec
en
t
y
ea
r
s
[
1
6
]
.
P
r
o
p
o
s
ed
a
h
eu
r
i
s
tic
al
g
o
r
ith
m
to
m
i
n
i
m
ize
th
e
n
u
m
b
er
o
f
tr
an
s
m
is
s
io
n
tr
ee
a
n
d
in
d
ir
ec
tl
y
co
n
s
er
v
e
b
an
d
w
id
t
h
.
T
h
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
h
o
w
ev
er
w
as
b
u
ilt
to
a
llo
w
m
u
lticas
t
p
r
o
to
co
l
in
s
tead
o
f
s
in
g
le
-
p
ath
.
I
n
an
o
th
er
p
ap
er
[
1
7
]
,
im
p
le
m
e
n
ted
an
t
co
lo
n
y
o
p
ti
m
izatio
n
i
n
t
o
th
eir
an
y
ca
s
t
r
o
u
t
in
g
p
r
o
to
co
l
in
th
e
ai
m
to
s
elec
t
p
r
o
p
er
ac
ce
s
s
g
ate
w
a
y
in
W
MN
.
C
o
m
b
in
in
g
d
is
tr
i
b
u
ted
co
m
p
u
ti
n
g
w
i
th
h
eu
r
i
s
t
ic
s
ea
r
ch
i
n
g
o
f
a
n
t
co
lo
n
y
al
g
o
r
it
h
m
,
th
e
g
ate
w
a
y
s
elec
tio
n
w
a
s
tr
ea
ted
a
s
a
n
an
y
ca
s
t
s
er
v
ice
[
1
8
.
]
A
n
al
y
z
ed
d
if
f
er
e
n
t
m
eta
-
h
eu
r
i
s
tic
m
et
h
o
d
s
to
co
n
s
id
er
th
e
p
lace
m
e
n
t
o
f
m
es
h
r
o
u
te
r
s
in
W
MN
s
.
T
ak
i
n
g
co
n
n
ec
t
iv
it
y
a
n
d
co
v
er
ag
e
p
r
o
b
lem
s
,
v
ar
io
u
s
s
ch
e
m
e
s
i
n
clu
d
in
g
g
e
n
etic
a
lg
o
r
it
h
m
,
s
i
m
u
lated
a
n
n
ea
l
in
g
,
tab
u
s
ea
r
c
h
,
a
n
d
h
ill
cl
i
m
b
i
n
g
w
er
e
u
s
ed
to
an
al
y
ze
t
h
eir
b
eh
av
io
r
s
.
T
h
e
au
t
h
o
r
s
th
e
n
u
s
e
d
Frie
d
m
a
n
test
to
co
m
p
ar
e
th
e
s
i
m
u
latio
n
r
esu
l
ts
.
Her
e,
it
h
as
b
ee
n
f
o
u
n
d
t
h
at
d
if
f
er
e
n
t
al
g
o
r
ith
m
s
w
o
r
k
b
et
ter
th
an
th
e
o
t
h
er
s
w
h
e
n
s
u
b
j
ec
ted
to
d
if
f
er
en
t
s
itu
a
tio
n
s
[
1
9
]
.
I
n
th
eir
e
f
f
o
r
t
to
m
ax
i
m
ize
t
h
e
s
er
v
iced
n
u
m
b
er
o
f
clie
n
t
s
o
r
s
u
b
s
cr
ib
er
s
in
W
MN
,
th
e
y
d
ev
elo
p
ed
lo
ad
-
b
ased
g
r
ee
d
y
al
g
o
r
ith
m
i
n
te
g
r
ated
w
ith
lo
ad
-
b
ased
MCM
al
g
o
r
ith
m
to
o
f
f
er
a
d
ela
y
-
co
n
tr
ain
ed
a
n
d
i
n
ter
f
er
e
n
ce
-
f
r
ee
s
o
lu
t
io
n
to
co
n
s
tr
u
ct
m
u
ltic
ast
tr
ee
s
f
o
r
t
h
e
n
et
w
o
r
k
[
2
0
]
.
P
r
o
p
o
s
ed
a
g
en
et
ic
alg
o
r
ith
m
to
s
o
l
v
e
n
o
d
e
p
lace
m
en
t p
r
o
b
lem
i
n
a
w
ir
eles
s
m
esh
n
et
w
o
r
k
.
B
y
e
m
p
lo
y
i
n
g
d
i
f
f
er
en
t
m
u
tatio
n
a
n
d
s
elec
tio
n
o
p
er
ato
r
s
as
w
el
l
as
s
ize
o
f
g
ia
n
t
co
m
p
o
n
e
n
t,
t
h
e
au
t
h
o
r
s
co
n
s
id
er
ed
W
eib
u
ll
d
is
tr
ib
u
tio
n
f
o
r
th
e
m
es
h
clien
ts
[
2
1
]
.
C
o
m
b
in
ed
m
u
lti
-
o
b
j
ec
tiv
e
P
ar
ticle
Sw
ar
m
Op
ti
m
izatio
n
an
d
Ge
n
etic
A
l
g
o
r
ith
m
to
d
ev
is
e
a
s
w
ar
m
-
b
ased
al
g
o
r
ith
m
to
s
o
l
v
e
W
MN
p
lan
n
i
n
g
p
r
o
b
le
m
s
o
f
th
r
ee
m
o
d
el
s
.
T
h
e
th
r
ee
m
u
lti
-
o
b
j
ec
tiv
e
m
o
d
el
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
1
,
Feb
r
u
ar
y
2
0
1
7
:
3
0
9
–
315
311
ar
e
lo
ad
-
b
alan
ce
d
,
in
ter
f
er
e
n
c
e
an
d
f
lo
w
-
ca
p
ac
it
y
m
o
d
els
[
2
2
]
.
A
d
ap
ted
a
n
e
w
ap
p
r
o
ac
h
o
f
p
laci
n
g
m
es
h
r
o
u
t
er
n
o
d
es
in
W
MN
t
h
r
o
u
g
h
h
e
u
r
is
t
ic
tab
u
s
ea
r
c
h
.
A
ck
n
o
w
led
g
i
n
g
t
h
at
a
W
MN
o
p
tim
izatio
n
p
r
o
b
lem
i
s
o
f
ten
t
i
m
e
s
NP
-
co
m
p
lete,
t
h
e
au
th
o
r
s
e
x
p
lo
r
e
th
e
s
o
lu
t
io
n
s
p
ac
e
at
th
e
s
a
m
e
ti
m
e
a
v
o
id
g
ettin
g
s
t
u
ck
i
n
lo
ca
l
m
i
n
i
m
a
b
y
m
a
x
i
m
izi
n
g
th
e
s
iz
e
o
f
g
ia
n
t c
o
m
p
o
n
e
n
ts
.
2.
P
RE
VIOU
S AP
P
RO
ACH
C
r
itical
d
es
ig
n
f
ac
to
r
s
o
f
W
MN
s
b
r
in
g
f
o
r
th
d
i
f
f
er
e
n
t
c
h
alle
n
g
i
n
g
i
s
s
u
es
r
an
g
i
n
g
f
r
o
m
th
e
p
h
y
s
ica
l
la
y
er
to
th
e
ap
p
licatio
n
la
y
er
an
d
it
is
ap
p
ar
en
t
t
h
at
m
a
n
y
p
r
o
b
lem
s
s
till
r
e
m
ain
[
1
5
]
.
P
r
esen
ted
v
ar
io
u
s
h
eu
r
i
s
tic
m
e
th
o
d
s
to
estab
lis
h
a
w
ir
eless
m
es
h
n
e
t
w
o
r
k
in
I
E
E
E
8
0
2
.
1
6
j
in
an
ec
o
n
o
m
ic
al
w
a
y
.
T
h
e
w
o
r
k
p
r
o
p
o
s
ed
a
lo
w
co
s
t
R
S
a
n
d
B
S
in
o
r
d
er
t
o
co
m
p
en
s
ate
f
o
r
b
an
d
w
id
th
d
e
m
a
n
d
o
f
th
e
cl
ien
ts
.
A
lt
h
o
u
g
h
th
e
m
et
h
o
d
s
ap
p
ea
r
r
o
b
u
s
t,
th
e
y
s
u
f
f
er
f
r
o
m
s
ev
er
al
l
i
m
itatio
n
s
.
Af
ter
ca
r
e
f
u
l
o
b
s
er
v
a
tio
n
s
,
it
h
as
b
ee
n
f
o
u
n
d
t
h
at
[
1
5
]
f
ailed
to
r
ef
lect
th
e
s
i
g
n
i
f
ica
n
ce
o
f
d
is
ta
n
ce
b
et
w
ee
n
s
tatio
n
s
in
th
e
n
e
t
w
o
r
k
.
Fo
r
e
x
a
m
p
le,
i
f
a
n
o
d
e
is
d
ed
icate
d
to
b
e
a
r
o
u
tin
g
s
ta
ti
o
n
o
r
a
b
ase
s
tatio
n
to
s
er
v
e
o
n
e
s
u
b
s
cr
ib
er
,
ig
n
o
r
i
n
g
t
h
e
n
o
d
e'
s
d
is
ta
n
ce
f
r
o
m
th
e
s
u
b
s
cr
ib
er
m
i
g
h
t
i
m
p
ac
t
t
h
e
q
u
ali
t
y
o
f
co
m
m
u
n
ica
tio
n
i
f
t
h
e
s
u
b
s
cr
ib
er
’
s
d
i
s
tan
ce
f
r
o
m
t
h
e
n
o
d
e
is
s
m
all
ev
en
i
f
th
e
co
s
t
is
h
i
g
h
er
.
Fi
g
u
r
e
2
,
is
a
g
r
ap
h
s
h
o
w
i
n
g
p
o
s
s
ib
le
lin
k
s
b
et
w
ee
n
n
o
d
es
w
h
er
e
th
e
b
est
s
o
lu
tio
n
is
e
m
b
o
ld
en
ed
.
Fig
u
r
e
2
.
E
x
a
m
p
le
o
f
a
n
o
p
ti
m
al
s
o
lu
tio
n
.
A
d
o
p
ted
f
r
o
m
[
1
5
]
I
t
is
k
n
o
w
n
t
h
at
d
i
g
ital
s
ig
n
al
atten
u
ates
d
u
r
in
g
tr
an
s
m
is
s
io
n
.
I
n
i
n
s
ta
n
ce
s
w
h
er
e
t
h
e
d
is
tan
ce
b
et
w
ee
n
t
w
o
n
o
d
es
g
et
s
lar
g
er
,
th
e
atte
n
u
atio
n
also
g
r
o
ws
b
ig
g
er
.
I
n
t
h
eir
ef
f
o
r
t
to
m
in
i
m
ize
t
h
e
co
s
t
o
f
estab
lis
h
in
g
th
e
n
et
w
o
r
k
,
t
h
e
y
o
v
er
lo
o
k
ed
th
e
a
f
f
ec
t
t
h
at
it
d
o
es
n
o
t
al
w
a
y
s
g
u
ar
an
tee
g
etti
n
g
b
est
p
er
f
o
r
m
a
n
ce
in
s
id
e
th
e
n
et
w
o
r
k
.
Su
c
h
tr
ad
e
-
o
f
f
is
co
m
m
o
n
i
n
o
p
ti
m
izatio
n
p
r
o
b
le
m
s
.
T
h
is
p
ap
er
p
r
o
p
o
s
es
an
i
m
p
r
o
v
e
m
en
t
f
o
r
t
h
e
m
et
h
o
d
i
n
n
et
w
o
r
k
p
la
n
n
in
g
u
s
i
n
g
h
eu
r
is
tic
al
g
o
r
ith
m
w
h
er
e
t
h
e
p
r
i
m
ar
y
p
u
r
p
o
s
e
is
to
m
i
n
i
m
ize
th
e
co
s
t b
y
tak
i
n
g
in
to
ac
co
u
n
t th
e
d
i
s
tan
ce
b
et
w
ee
n
n
o
d
es i
n
W
MN
.
3.
P
RO
P
O
SE
AP
P
RO
ACH
T
h
e
p
r
o
b
lem
at
h
a
n
d
is
a
b
i
n
ar
y
o
p
ti
m
iza
tio
n
p
r
o
b
le
m
.
W
e
h
a
v
e
d
ec
id
ed
to
ap
p
r
o
ac
h
t
h
e
p
r
o
b
le
m
u
s
i
n
g
Mo
d
if
ied
B
i
n
ar
y
P
ar
tic
le
S
w
ar
m
Op
ti
m
izatio
n
(
MB
P
SO)
.
MB
P
SO
w
as
ch
o
s
e
n
a
s
it
o
v
er
co
m
es
th
e
u
n
r
ea
s
o
n
ab
le
b
eh
a
v
io
r
o
f
it
s
p
r
ed
ec
ess
o
r
,
B
P
SO
[
2
3
]
.
Su
p
p
o
s
e
th
at
t
h
e
n
u
m
b
er
o
f
SS
s
i
s
,
th
e
n
u
m
b
er
o
f
R
Ss
i
s
,
an
d
th
e
n
u
m
b
er
o
f
B
S
s
is
.
T
h
e
s
u
m
o
f
co
m
p
o
n
e
n
t
s
i
n
ea
ch
p
ar
ticle
is
eq
u
a
l to
[
1
5
]
,
(
1
)
W
h
en
e
v
er
a
n
e
w
p
ar
ticle
is
g
en
er
ated
,
w
h
et
h
er
it
i
s
r
an
d
o
m
l
y
g
e
n
er
ated
(
in
i
tializatio
n
p
h
ase
o
r
d
u
e
to
m
u
tatio
n
)
o
r
d
u
e
to
th
e
alg
o
r
ith
m
’
s
p
r
o
g
r
ess
io
n
,
it
m
u
s
t
b
e
ch
ec
k
ed
f
o
r
v
alid
it
y
.
I
f
a
s
tatio
n
p
r
esen
ted
(
b
y
―
1
‖)
is
i
n
v
alid
i
n
r
ea
l li
f
e
d
u
e
to
it b
ein
g
o
u
t o
f
t
h
e
co
v
e
r
ag
e
ar
ea
,
it
m
u
s
t b
e
r
e
m
o
v
ed
f
r
o
m
t
h
e
m
a
tr
ix
t
h
at
r
ep
r
esen
ts
it (
b
y
t
u
r
n
i
n
g
i
t in
to
―
0
‖)
.
T
h
e
ai
m
o
f
s
o
lv
i
n
g
t
h
e
p
r
o
b
lem
i
s
to
m
in
i
m
ize
t
h
e
co
s
t
o
f
e
s
tab
lis
h
in
g
a
n
et
w
o
r
k
.
T
h
e
f
it
n
es
s
v
alu
e
o
f
a
n
et
w
o
r
k
i
s
as f
o
llo
w
s
,
(
2
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2
0
8
8
-
8708
I
mp
r
o
ve
men
t a
t Netw
o
r
k
P
la
n
n
in
g
u
s
in
g
Heu
r
is
t
ic
A
lg
o
r
ith
m
to
Min
imiz
e
C
o
s
t o
f D
is
ta
n
ce
…
(
S
h
iva
n
Q.
A
.
)
312
Ho
w
e
v
er
,
p
er
f
o
r
m
an
ce
is
n
o
t
g
u
ar
a
n
teed
j
u
s
t
b
y
m
in
i
m
izi
n
g
t
h
e
co
s
t
o
f
e
s
tab
lis
h
i
n
g
a
n
e
t
w
o
r
k
w
it
h
r
eg
ar
d
to
m
etr
ics
s
u
c
h
a
s
P
DR
an
d
E
2
E
d
ela
y
.
[
1
5
]
ap
p
r
o
a
ch
ed
th
e
p
r
o
b
le
m
f
r
o
m
t
h
e
p
e
r
s
p
ec
tiv
e
o
f
co
s
t
b
u
t
it
i
g
n
o
r
ed
a
cr
u
cial
f
ac
to
r
i
n
n
et
w
o
r
k
p
er
f
o
r
m
a
n
ce
,
i.e
.
,
t
h
e
d
is
tan
ce
b
et
w
ee
n
n
et
w
o
r
k
s
tat
io
n
s
.
D
ig
i
tal
s
ig
n
al
s
atten
u
ate
d
u
r
i
n
g
tr
a
n
s
m
is
s
io
n
w
it
h
r
esp
ec
t
to
d
i
s
tan
ce
.
T
h
e
g
r
ea
ter
t
h
e
d
is
tan
ce
,
th
e
g
r
ea
ter
th
e
a
tten
u
atio
n
.
T
h
u
s
,
ig
n
o
r
in
g
s
u
ch
a
co
n
s
id
e
r
atio
n
is
d
etr
i
m
e
n
tal
to
th
e
p
er
f
o
r
m
a
n
ce
o
f
a
n
et
w
o
r
k
.
T
h
e
m
at
h
e
m
atica
l
m
o
d
el,
―
M
o
d
el
B
ased
o
n
Flo
w
C
o
n
s
er
v
atio
n
an
d
C
ap
ac
it
y
‖
p
r
o
p
o
s
ed
b
y
[
1
5
]
is
g
o
o
d
an
d
w
e
h
a
v
e
ad
ap
ted
it
f
o
r
th
e
r
esear
ch
at
h
a
n
d
.
D
is
tan
ce
w
as
ta
k
e
n
i
n
to
ac
co
u
n
t
d
u
r
i
n
g
n
e
t
w
o
r
k
p
lan
n
i
n
g
b
y
u
p
d
ati
n
g
t
h
e
o
b
j
e
ctiv
e
f
u
n
ctio
n
2
as f
o
llo
w
s
,
(
3
)
Op
ti
m
izatio
n
w
i
ll
h
elp
m
i
n
i
m
ize
th
e
p
r
ev
io
u
s
f
u
n
c
tio
n
,
w
h
i
ch
w
o
u
ld
b
alan
ce
m
i
n
i
m
izin
g
co
s
t
a
n
d
th
e
to
tal
d
is
tan
ce
p
o
s
s
ib
le
b
et
w
ee
n
n
et
w
o
r
k
s
tatio
n
s
.
T
h
u
s
,
i
m
p
r
o
v
i
n
g
th
e
o
v
er
all
p
er
f
o
r
m
an
ce
o
f
t
h
e
n
et
w
o
r
k
.
4.
E
XP
E
R
I
M
E
NT
S AN
D
RE
S
UL
T
S
T
h
is
s
ec
tio
n
d
is
c
u
s
s
es
th
e
r
es
u
lts
f
r
o
m
t
h
e
co
n
d
u
cted
e
x
p
e
r
i
m
en
ts
in
d
etail.
A
tr
ip
ar
tite
g
r
ap
h
w
a
s
u
s
ed
as t
h
e
s
i
m
u
latio
n
m
o
d
el
i
n
M
A
T
L
A
B
an
d
is
s
h
o
w
n
i
n
F
ig
u
r
e
3
.
Fig
u
r
e
3
.
T
r
ip
ar
tite g
r
ap
h
r
ep
r
esen
tat
io
n
o
f
a
s
a
m
p
le
p
r
o
b
lem
.
A
d
o
p
ted
f
r
o
m
[
1
5
]
Firstl
y
,
MB
P
SO
h
ad
to
b
e
e
v
a
lu
ated
f
o
r
w
h
ic
h
t
h
e
M
A
T
L
A
B
en
v
ir
o
n
m
e
n
t
w
a
s
c
h
o
s
e
n
.
T
h
e
o
r
ig
i
n
al
o
b
j
ec
tiv
e
f
u
n
c
tio
n
w
as
u
s
ed
a
n
d
th
e
r
es
u
lt p
r
esen
ted
as a
m
atr
ix
,
T
h
e
r
esu
lt h
ad
th
e
f
o
llo
w
i
n
g
p
atter
n
:
,
w
h
er
e
ele
m
en
ts
:
1
an
d
2
r
ep
r
esen
t
.
3
an
d
4
r
ep
r
esen
t
.
5
to
1
0
r
ep
r
esen
t
.
1
1
to
1
6
r
e
p
r
esen
t
.
1
7
to
2
0
r
e
p
r
esen
t
.
See
T
ab
le
1
.
T
ab
le
1
.
P
ar
ticle
S
w
ar
m
Op
ti
m
izatio
n
p
ar
a
m
eter
s
an
d
c
h
o
s
en
v
al
u
es
N
o
.
o
f
El
e
me
n
t
s
20
N
o
.
o
f
R
e
su
l
t
M
a
t
r
i
c
e
s
50
V
e
l
o
c
i
t
y
R
a
n
g
e
[
]
N
o
.
o
f
I
t
e
r
a
t
i
o
n
s
6
0
0
C1
1
C2
0
.
5
0
.
3
0
.
9
M
u
t
a
t
i
o
n
R
a
t
e
0
.
1
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
1
,
Feb
r
u
ar
y
2
0
1
7
:
3
0
9
–
315
313
T
h
e
alg
o
r
ith
m
g
e
n
er
ated
a
s
o
lu
tio
n
w
i
th
a
n
estab
li
s
h
m
e
n
t c
o
s
t o
f
2
5
,
as f
o
llo
w
s
:
[
]
w
h
er
e
[
]
,
[
]
,
[
]
,
[
]
,
an
d
[
]
.
I
n
t
h
is
s
o
lu
tio
n
,
B
S 1
an
d
R
S 2
f
o
r
m
t
h
e
b
ac
k
b
o
n
e
o
f
t
h
e
n
et
w
o
r
k
,
w
h
er
e
B
S
1
s
er
v
es
R
S 2
,
w
h
ich
i
n
t
u
r
n
s
er
v
es S
Ss
1
,
2
,
an
d
3
.
Up
o
n
u
p
d
atin
g
t
h
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
,
MB
P
SO
w
as
p
e
r
f
o
r
m
ed
w
it
h
th
e
s
a
m
e
p
ar
am
eter
s
.
I
n
o
r
d
er
to
p
er
f
o
r
m
co
m
p
ar
is
o
n
b
et
w
ee
n
o
u
r
ap
p
r
o
ac
h
an
d
[
1
5
]
,
th
e
d
is
tan
ce
s
b
et
w
ee
n
t
h
e
d
i
f
f
er
e
n
t
n
et
w
o
r
k
s
tatio
n
s
h
av
e
to
b
e
k
n
o
w
n
.
T
h
ese
d
is
tan
ce
s
h
a
v
e
b
ee
n
as
s
u
m
ed
an
d
ar
e
p
r
esen
ted
in
T
ab
les
(
2
-
3
)
.
T
h
e
d
is
tan
ce
b
et
w
ee
n
R
S 1
an
d
S
S 2
(
3
0
)
is
less
t
h
an
t
h
at
b
et
w
ee
n
R
S 2
a
n
d
SS
2
(
8
0
)
.
T
ab
le
2
.
Dis
tan
ce
s
b
et
w
ee
n
B
Ss
an
d
R
Ss
a
n
d
SS
s
d
i
st
a
n
c
e
d
i
st
a
n
c
e
C
o
v
e
r
a
g
e
Z
o
n
e
R
a
d
i
u
s
B
S
1
[
]
[
]
1
75
1
5
0
B
S
2
[
]
[
]
3
75
1
5
0
T
ab
le
3
.
Dis
tan
ce
s
b
et
w
ee
n
R
Ss
an
d
SS
s
d
i
st
a
n
c
e
C
o
v
e
r
a
g
e
Z
o
n
e
R
a
d
i
u
s
R
S
1
[
]
[
]
1
0
0
R
S
2
[
]
[
]
1
0
0
T
h
e
ex
p
er
im
e
n
t
y
ield
s
t
h
e
f
o
ll
o
w
i
n
g
s
o
lu
tio
n
w
it
h
an
e
s
tab
li
s
h
m
e
n
t c
o
s
t o
f
3
5
,
[
]
w
h
er
e
[
]
,
[
]
,
[
]
,
[
]
an
d
[
]
.
T
h
e
b
ac
k
b
o
n
e
o
f
th
e
n
et
w
o
r
k
ac
co
r
d
in
g
to
th
is
s
o
lu
tio
n
i
s
f
o
r
m
ed
b
y
B
S
1
a
n
d
R
S
1
,
w
h
er
e
R
S
1
t
h
en
s
er
v
e
s
S
Ss
1
,
2
,
an
d
3
.
T
h
e
r
o
u
tes
b
et
w
ee
n
s
tatio
n
s
f
o
r
r
esu
lt
s
o
b
tain
ed
u
s
in
g
t
h
e
o
r
ig
i
n
al
an
d
u
p
d
ated
o
b
j
ec
tiv
e
f
u
n
ctio
n
s
ar
e
p
r
esen
ted
in
T
ab
les (
4
-
5
)
.
T
ab
le
4
.
R
o
u
tes u
s
i
n
g
o
r
ig
i
n
al
o
b
j
ec
tiv
e
f
u
n
ct
io
n
S
u
b
s
c
r
i
b
e
r
S
t
a
t
i
o
n
R
o
u
t
e
S
S
1
RS
1
—
B
S
1
S
S
2
R
S
1
—
B
S
1
S
S
3
R
S
1
—
B
S
1
T
ab
le
5
.
R
o
u
tes u
s
i
n
g
th
e
u
p
d
ated
o
b
j
ec
tiv
e
f
u
n
ctio
n
S
u
b
s
c
r
i
b
e
r
S
t
a
t
i
o
n
R
o
u
t
e
S
S
1
R
S
2
—
B
S
1
S
S
2
R
S
2
—
B
S
1
S
S
3
R
S
2
—
B
S
1
Seco
n
d
l
y
,
r
ea
l
-
w
o
r
ld
p
er
f
o
r
m
an
ce
h
ad
to
b
e
e
v
al
u
ated
u
s
i
n
g
th
e
P
DR
an
d
E
2
E
d
ela
y
m
etr
ics.
A
s
i
m
u
lat
io
n
o
f
a
r
ea
l
n
et
w
o
r
k
w
a
s
ca
r
r
ied
o
u
t
i
n
M
A
T
L
A
B
.
E
v
er
y
SS
w
o
u
ld
g
e
n
er
ate
d
at
a
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I
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r
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F
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NC
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S
[1
]
J.
Co
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Co
rre
ia.
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[2
]
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En
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.
[3
]
F
.
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2
0
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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315
[4
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In
ter
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[6
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[8
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o
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[9
]
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b
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G
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1
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2
]
M
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n
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g
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[1
3
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Y.
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jera
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o
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.
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7
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p
p
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4
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I.
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mm
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p
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.
[1
5
]
S.
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.
Kh
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u
risti
c
a
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h
m
s
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:
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e
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c
2
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2
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.
[1
6
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R.
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tam
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p
p
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8
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7
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[1
7
]
S
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a
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8
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9
]
W.
L
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re
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w
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T
IIS
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v
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l.
5
,
p
p
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2
6
9
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6
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1
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0
]
A
.
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ro
ll
i,
T
.
Od
a
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h
a
f
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a
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a
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m
f
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lac
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m
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W
M
Ns
:
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rf
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a
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Ev
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f
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e
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n
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:
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p
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r
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2
0
1
3
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p
p
.
2
2
3
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3
1
.
[2
1
]
D.
Be
n
y
a
m
in
a
,
A
.
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f
id
,
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Ha
ll
a
m
,
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n
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re
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u
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M
a
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A
h
y
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tu
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in
sp
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d
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p
ti
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ize
r
f
o
r
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m
e
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n
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tw
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rk
s d
e
sig
n
,
Co
mp
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ter
Co
mm
u
n
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ti
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n
s
,
v
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l
.
3
5
,
p
p
.
1
2
3
1
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2
4
6
,
2
0
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2
.
[2
2
]
F
.
Xh
a
f
a
,
A
.
B
a
ro
ll
i,
a
n
d
M
.
T
a
k
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w
a
.
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tab
u
s
e
a
rc
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a
l
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h
m
f
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ff
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lac
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e
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t
in
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m
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in
In
telli
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tw
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ll
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s
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0
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In
ter
n
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ti
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fer
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e
o
n
,
2
0
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1
,
p
p
.
5
3
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5
9
.
[2
3
]
J.
Ya
n
g
,
H.
Zh
a
n
g
,
Y.
L
in
g
,
C.
P
a
n
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a
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d
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.
S
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T
a
sk
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ll
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w
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s se
n
so
r
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t
w
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sin
g
m
o
d
if
ied
b
in
a
r
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p
a
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le sw
a
r
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o
p
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iz
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ti
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,
IEE
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so
rs
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o
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l
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v
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1
4
,
p
p
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8
8
2
-
8
9
2
,
2
0
1
4
.
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