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25
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3
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term
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(I
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ar
tific
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tellig
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AI
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,
m
u
ltime
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ap
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licatio
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s
,
an
d
o
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in
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tech
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b
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All
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tech
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m
ay
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f
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lv
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atch
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5
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s
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wav
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d
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W
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atch
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ir
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wid
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[
1
]
.
W
DM
tech
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lo
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wid
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ed
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o
m
ee
t
th
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s
to
m
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d
to
f
ac
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ch
allen
g
es
[
2
]
.
Op
tical
f
ib
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co
u
ld
e
n
ab
le
th
e
d
ev
elo
p
m
en
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o
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b
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W
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r
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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I
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J
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&
C
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Sci
,
Vo
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25
,
No
.
3
,
Ma
r
ch
20
22
:
1
5
3
9
-
1
5
4
8
1540
ch
an
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3
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Op
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in
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witch
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C
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p
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PS
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,
a
n
d
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u
r
s
t
s
witch
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(
OB
S)
[
4
]
,
[
5
]
.
B
etwe
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all
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O
B
S
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tech
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d
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ically
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[
6
]
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I
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OC
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witch
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b
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b
y
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e
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OC
S
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m
eth
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d
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it m
ay
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t b
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f
u
lly
u
tili
ze
d
[
7
]
.
T
h
eir
d
is
ad
v
an
tag
es tak
e
tim
e
to
s
et
u
p
an
d
to
d
estro
y
,
a
n
d
th
o
s
e
r
eso
u
r
ce
s
ar
e
n
o
t
ef
f
icien
tly
em
p
lo
y
ed
wh
il
e
th
e
cir
cu
it
is
es
tab
lis
h
ed
[
8
]
as
well
a
s
th
e
u
tili
zin
g
r
eso
u
r
ce
s
b
ec
o
m
e
h
ar
d
u
p
an
d
th
e
tr
a
n
s
m
is
s
io
n
o
f
o
t
h
er
d
ata
b
ec
o
m
es
im
p
o
s
s
ib
le
alth
o
u
g
h
n
o
wastin
g
tim
e
in
waitin
g
d
u
r
i
n
g
s
witch
in
g
.
I
n
OP
s
witch
in
g
,
th
e
m
ess
ag
e
s
ar
e
r
o
u
ted
as
in
d
iv
id
u
al
p
ac
k
ets
in
a
co
n
n
ec
tio
n
less
n
etwo
r
k
an
d
th
er
e
is
n
o
r
eso
u
r
ce
r
eser
v
atio
n
,
n
o
b
an
d
wid
th
r
eser
v
atio
n
,
a
n
d
n
o
p
r
o
ce
s
s
in
g
tim
e
s
ch
ed
u
lin
g
f
o
r
ea
ch
p
ac
k
et.
OPS,
h
as
v
ar
ied
im
p
lem
en
tatio
n
is
s
u
es
f
o
r
ex
am
p
le,
c
o
n
n
ec
tio
n
is
s
u
es
th
at
ca
n
r
esu
lt
i
n
in
f
o
r
m
atio
n
lo
s
s
,
d
elay
s
in
in
f
o
r
m
atio
n
d
eliv
er
y
an
d
o
p
tical
-
elec
tr
o
n
ic
-
o
p
tical
co
n
v
e
r
s
atio
n
[
9
]
,
h
ig
h
co
s
t
an
d
h
ig
h
p
o
wer
co
n
s
u
m
p
tio
n
,
y
et
it c
an
en
ab
le
h
ig
h
b
an
d
wid
th
u
tili
za
tio
n
[
7
]
.
OB
S
i
s
a
d
ata
tr
an
s
m
is
s
io
n
tech
n
o
lo
g
y
,
wh
ich
c
o
m
b
in
es
o
p
tical
s
witch
in
g
an
d
tr
an
s
m
is
s
io
n
to
co
n
v
ey
d
ata
in
lar
g
e
b
u
r
s
ts
b
e
twee
n
ass
o
ciate
d
in
g
r
ess
n
o
d
e
s
.
I
t
is
cr
ea
ted
b
y
co
m
b
in
in
g
t
h
e
g
r
ea
t
est
asp
ec
ts
o
f
b
o
t
h
PS
an
d
o
p
tical
cir
cu
it
s
witch
in
g
(
C
S)
wh
ile
av
o
id
in
g
th
eir
d
r
awb
ac
k
s
[
1
0
]
.
OB
S
is
th
e
n
ex
t
ev
o
lu
tio
n
o
f
o
p
tical
I
n
ter
n
et
tech
n
o
lo
g
y
.
I
t
h
as
b
ee
n
ch
o
s
en
to
g
et
b
etter
b
an
d
wid
th
u
tili
za
tio
n
f
o
r
b
u
ild
in
g
a
f
lex
ib
le
n
etwo
r
k
th
at
is
ea
s
ily
f
o
r
h
an
d
lin
g
th
e
b
u
r
s
t
tr
af
f
ic
g
en
er
ated
b
y
m
u
lt
im
ed
ia
s
er
v
ic
es.
T
h
is
s
w
itch
in
g
im
p
r
o
v
es
tr
a
n
s
f
er
r
in
g
d
ata
in
o
p
tical
n
etwo
r
k
s
with
h
ig
h
-
s
p
ee
d
s
witch
in
g
tech
n
o
lo
g
y
[
1
1
]
.
OB
S
co
n
s
is
t
o
f
:
co
n
tr
o
l
b
u
r
s
t
(
C
B
)
an
d
d
ata
b
u
r
s
ts
(
DB
)
[
3
]
.
Data
b
u
r
s
t
an
d
co
n
tr
o
l
b
u
r
s
t
ar
e
r
ef
er
r
ed
to
b
u
r
s
t
p
a
y
lo
ad
a
n
d
b
u
r
s
t
h
ea
d
e
r
p
ac
k
et.
B
o
th
u
tili
ze
s
ep
ar
ate
wav
elen
g
th
s
f
o
r
tr
a
n
s
m
is
s
io
n
[
1
2
]
.
T
h
e
C
B
is
s
en
t
b
ef
o
r
e
tr
an
s
m
itti
n
g
DB
b
y
a
tim
e
ca
ll
ed
an
o
f
f
s
et
tim
e,
to
s
etu
p
a
r
o
u
te
f
o
r
th
e
d
ata
b
u
r
s
t in
th
e
s
w
itch
in
g
s
y
s
tem
[
3
]
.
T
ab
le
1
co
m
p
ar
es th
e
th
r
ee
s
witch
in
g
tech
n
iq
u
es.
T
ab
le
1
.
C
o
m
p
a
r
is
o
n
th
e
th
r
ee
tech
n
iq
u
es o
f
o
p
tical
s
witch
in
g
[
5
]
,
[
1
3
]
C
h
a
r
a
c
t
e
r
i
s
t
i
c
s/
P
r
o
p
e
r
t
i
e
s
C
i
r
c
u
i
t
P
a
c
k
e
t
B
u
r
s
t
B
a
n
d
w
i
d
t
h
Lo
w
H
i
g
h
H
i
g
h
S
e
t
-
up
H
i
g
h
Lo
w
Lo
w
O
p
t
i
c
a
l
b
u
f
f
e
r
U
n
w
a
n
t
e
d
W
a
n
t
e
d
U
n
w
a
n
t
e
d
O
v
e
r
h
e
a
d
P
r
o
c
e
s
si
n
g
Lo
w
H
i
g
h
Lo
w
Tr
a
f
f
i
c
A
d
a
p
t
a
b
i
l
i
t
y
Lo
w
H
i
g
h
H
i
g
h
S
p
e
e
d
's Sw
i
t
c
h
i
n
g
S
l
o
w
F
a
st
M
o
d
e
r
a
t
e
C
o
m
p
l
e
x
i
t
y
P
r
o
c
e
ssi
n
g
Lo
w
H
i
g
h
M
e
d
i
u
m
S
i
g
n
a
l
i
n
g
S
c
h
e
m
e
Tw
o
W
a
y
s
O
n
e
W
a
y
O
n
e
W
a
y
2.
ARCH
I
T
E
C
T
UR
E
O
F
O
B
S
Op
tical
b
u
r
s
t
s
wi
tch
in
g
n
etwo
r
k
is
b
u
f
f
er
less
in
n
atu
r
e
[
1
4
]
,
it
co
n
s
is
t
s
o
f
two
n
o
d
es;
ed
g
e
(
I
n
g
r
ess
)
n
o
d
e
a
n
d
c
o
r
e
(
E
g
r
ess
)
n
o
d
e
s
,
in
ter
n
et
p
r
o
to
co
l
(
IP
)
p
ac
k
ets
f
r
o
m
d
if
f
er
en
t
clien
ts
ar
e
ag
g
r
e
g
ated
at
th
e
in
g
r
ess
in
f
o
r
m
o
f
b
u
r
s
t
an
d
d
is
-
ag
g
r
eg
ated
to
I
P
p
ac
k
et
at
th
e
eg
r
ess
,
wh
er
e
th
ey
r
o
u
te
d
to
th
eir
d
is
ten
tio
n
[
1
5
]
u
s
in
g
o
n
e
way
s
ig
n
alin
g
r
eso
u
r
ce
r
eser
v
atio
n
p
r
o
to
c
o
l
[
1
6
]
to
p
ass
es
th
e
b
u
r
s
ts
th
r
o
u
g
h
th
e
n
etwo
r
k
with
o
u
t
waitin
g
an
ac
k
n
o
wle
d
g
m
en
t
f
r
o
m
d
esti
n
atio
n
[
1
4
]
.
Fig
u
r
e
1
is
an
illu
s
tr
ati
on
d
iag
r
am
o
f
OB
S
n
etwo
r
k
.
Fig
u
r
e
1
.
OB
S n
etwo
r
k
[
9
]
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
P
erfo
r
ma
n
ce
a
n
a
lysi
s
co
mp
a
r
is
o
n
o
f o
p
tica
l
b
u
r
s
t sw
itch
in
g
…
(
La
ila
A
.
Wa
h
a
b
A
b
d
u
lla
h
)
1541
T
h
e
m
ajo
r
f
u
n
ctio
n
s
o
f
in
g
r
e
s
s
n
o
d
es:
as
s
em
b
lin
g
o
f
b
u
r
s
t,
r
o
u
tin
g
,
an
d
wav
elen
g
th
as
s
ig
n
m
en
t,
s
ig
n
alin
g
,
g
en
er
atin
g
th
e
co
n
t
r
o
l
p
ac
k
et
an
d
d
eter
m
in
e
th
e
o
f
f
s
et
tim
e.
I
n
co
r
e
n
o
d
es,
d
at
a
b
u
r
s
ts
ar
e
s
h
if
ted
f
r
o
m
o
n
e
in
p
u
t
p
o
r
t
to
o
th
er
b
ased
o
n
t
h
e
in
f
o
r
m
atio
n
in
th
e
co
n
tr
o
l
p
ac
k
et
h
ea
d
er
.
C
o
r
e
n
o
d
e
d
ec
i
d
es
o
n
th
e
b
u
r
s
t'
s
r
o
u
te
to
r
eso
lv
e
th
e
co
n
ten
tio
n
b
etwe
en
t
h
e
n
u
m
b
er
s
o
f
b
u
r
s
ts
.
Als
o
,
th
e
m
ajo
r
f
u
n
c
tio
n
o
f
e
g
r
ess
n
o
d
e
is
:
d
is
ag
g
r
eg
ates
b
u
r
s
ts
to
I
P
p
ac
k
ets
an
d
d
ir
ec
te
d
th
e
p
ac
k
ets
to
th
e
ap
p
r
o
p
r
iate
ac
ce
s
s
n
etwo
r
k
[
1
5
]
.
I
n
s
id
e
OB
S,
th
e
o
p
tical
s
witch
es
g
iv
e
a
r
o
u
te
o
p
tically
o
v
er
ea
c
h
r
o
u
ter
wh
er
e
n
o
elec
tr
o
n
ic
d
at
a
p
r
ep
ar
atio
n
tak
es
p
lace
o
p
tically
.
E
lectr
o
n
ic
h
e
ad
er
p
r
o
ce
s
s
in
g
is
s
till
r
eq
u
ir
ed
in
ev
er
y
r
o
u
ter
to
o
b
tain
th
e
s
witch
in
g
d
ata
r
eq
u
ir
ed
to
p
lan
ac
tiv
ities
a
n
d
s
witch
in
g
.
C
o
n
tr
o
l
b
u
r
s
t
(
h
ea
d
er
)
is
s
ep
ar
ated
f
r
o
m
th
e
d
ata
b
u
r
s
t
an
d
tr
an
s
f
er
r
ed
in
a
d
v
an
ce
b
e
f
o
r
e
th
e
in
f
o
r
m
atio
n
t
o
en
s
u
r
e
s
u
cc
ess
f
u
l
p
r
ep
a
r
atio
n
o
f
th
e
s
witch
in
g
d
ata
a
n
d
h
ea
d
er
'
s
r
o
u
tin
g
o
n
a
s
ep
ar
ate
d
co
n
tr
o
l
ch
an
n
el
[
1
7
]
.
T
h
e
d
a
ta
b
u
r
s
t
s
witch
es
o
p
tically
with
o
u
t
d
ela
y
alo
n
g
its
p
ath
,
wh
e
r
ea
s
th
e
co
n
tr
o
l
p
ac
k
et
h
ea
d
e
r
u
n
d
er
g
o
es
Op
tical/E
lectr
o
n
ic/Op
tical
co
n
v
e
r
s
io
n
at
th
e
i
n
ter
m
ed
iate
n
o
d
es,
wh
ich
ta
k
es tim
e
f
o
r
p
r
o
ce
s
s
in
g
[
5
]
as sh
o
wn
i
n
Fig
u
r
e
2
.
Fig
u
r
e
2
.
Diag
r
a
m
o
f
b
u
r
s
t f
lo
w
[
9
]
W
h
en
two
b
u
r
s
ts
o
r
m
o
r
e
u
s
e
th
e
s
am
e
wav
elen
g
th
a
n
d
c
o
m
p
ete
at
th
e
s
am
e
tim
e
f
o
r
th
e
s
am
e
o
u
tp
u
t
p
o
r
t,
th
is
will
lead
to
co
n
ten
tio
n
at
a
co
r
e
n
o
d
e
wh
ic
h
ca
u
s
e
lo
s
in
g
o
f
d
ata
b
u
r
s
t.
R
ep
ea
ted
lo
s
in
g
o
f
d
ata
b
u
r
s
t
will
im
p
ac
t
o
n
n
et
wo
r
k
p
er
f
o
r
m
an
ce
in
ad
d
itio
n
to
th
e
q
u
ality
o
f
s
er
v
ice
(
Q
o
S
)
o
f
th
e
n
etwo
r
k
[
1
6
]
.
T
h
e
f
o
cu
s
o
f
o
u
r
d
is
cu
s
s
io
n
s
h
if
ts
to
a
co
m
p
ar
is
o
n
o
f
f
ib
er
d
elay
lin
es,
d
ef
le
ctio
n
r
o
u
tin
g
,
a
n
d
s
eg
m
en
tatio
n
d
r
o
p
p
in
g
tec
h
n
i
q
u
es.
Ap
p
r
o
p
r
iate
m
ath
em
atic
al
m
o
d
els
wer
e
c
o
n
s
tr
u
cted
a
n
d
s
im
u
lated
u
s
in
g
MA
T
L
AB
s
im
u
latio
n
to
ass
es
s
th
e
co
n
ten
tio
n
r
eso
lv
in
g
ca
p
ac
ity
o
f
b
o
th
co
n
ten
tio
n
r
eso
lu
tio
n
s
ch
em
es.
T
h
i
s
p
a
p
e
r
o
r
d
e
r
e
d
a
s
:
I
n
s
e
ct
io
n
2
c
o
n
t
e
n
t
i
o
n
r
e
s
o
l
u
t
i
o
n
t
e
c
h
n
i
q
u
e
s
.
I
n
s
e
ct
i
o
n
3
,
c
o
n
t
e
n
t
i
o
n
r
e
s
o
l
u
t
i
o
n
b
y
u
s
i
n
g
o
p
t
i
c
a
l
b
u
f
f
e
r
i
n
g
.
I
n
s
e
c
ti
o
n
4
c
o
n
t
e
n
t
i
o
n
r
e
s
o
l
u
t
i
o
n
b
y
u
s
i
n
g
s
e
g
m
e
n
t
a
t
i
o
n
.
I
n
s
e
c
t
i
o
n
5
c
o
n
t
e
n
t
i
o
n
r
e
s
o
l
u
t
i
o
n
b
y
u
s
i
n
g
d
e
f
l
ec
t
i
o
n
r
o
u
t
i
n
g
.
I
n
s
e
c
t
i
o
n
6
s
i
m
u
l
a
ti
o
n
s
a
n
d
r
e
s
u
l
ts
.
F
i
n
al
c
o
n
c
l
u
s
i
o
n
in
s
e
c
t
i
o
n
7
.
3.
CO
NT
E
NT
I
O
N
RE
SO
L
U
T
I
O
N
T
E
CH
N
I
Q
UE
S
C
o
n
ten
tio
n
is
th
e
m
ain
p
r
o
b
le
m
with
OB
S
tech
n
iq
u
e
an
d
h
as
a
n
eg
ativ
e
im
p
ac
t
o
n
OB
S
n
etwo
r
k
s
.
C
o
n
ten
t
io
n
o
cc
u
r
s
d
u
e
to
o
v
er
lap
p
in
g
in
s
er
v
ice
tim
e
[
1
8
]
,
wh
er
e
th
e
in
c
o
m
in
g
b
u
r
s
t
is
d
r
o
p
p
e
d
if
c
o
n
ten
tio
n
ca
n
n
o
t r
eso
lv
e.
I
t
is
im
p
o
r
tan
t
to
r
eso
lv
e
th
is
p
r
o
b
lem
b
ec
au
s
e
it
is
an
ess
en
tial
p
er
f
o
r
m
an
c
e
cr
iter
io
n
o
n
OB
S
n
etwo
r
k
s
s
in
ce
it im
p
r
o
v
es th
e
q
u
an
tity
o
f
s
er
v
ice
o
f
th
e
n
etwo
r
k
[
1
9
]
.
Var
io
u
s
ap
p
r
o
ac
h
es
f
o
r
b
u
r
s
t
co
n
ten
tio
n
r
eso
l
u
tio
n
h
a
v
e
b
ee
n
p
r
o
p
o
s
ed
.
Op
tical
b
u
f
f
e
r
in
g
,
wav
elen
g
th
co
n
v
er
s
io
n
,
d
ef
le
ctio
n
r
o
u
tin
g
,
an
d
b
u
r
s
t
s
eg
m
en
tatio
n
ar
e
th
e
m
o
s
t
co
m
m
o
n
s
y
s
tem
s
.
Fo
r
co
n
ten
tio
n
r
eso
lu
tio
n
b
etwe
en
th
e
b
u
r
s
ts
in
o
p
tical
b
u
f
f
er
m
eth
o
d
s
a
co
m
p
etin
g
b
u
r
s
t
is
d
elay
f
o
r
a
s
p
ec
if
ic
tim
e
b
y
f
ib
er
d
elay
lin
es,
th
is
d
elay
is
d
ep
en
d
i
ng
o
n
th
e
le
n
g
th
o
f
th
e
b
u
r
s
t.
I
n
t
h
e
wav
elen
g
th
co
n
v
er
s
io
n
tech
n
iq
u
es,
wh
e
n
two
o
r
m
o
r
e
b
u
r
s
ts
ar
e
co
n
ten
d
in
g
f
o
r
s
am
e
p
o
r
t,
o
n
e
o
f
t
h
em
will
d
ir
ec
t
ed
to
th
e
ad
eq
u
ate
p
o
r
t
wh
ile
th
e
o
th
er
will
d
ir
ec
ted
to
alter
n
ate
o
u
tp
u
t
p
o
r
t
b
y
ch
an
g
in
g
th
e
wa
v
elen
g
th
s
.
I
n
d
ef
lectio
n
r
o
u
tin
g
,
a
co
m
p
etin
g
b
u
r
s
t w
o
u
ld
g
iv
e
a
d
if
f
er
en
t p
ath
to
its
d
esti
n
atio
n
.
So
m
e
o
f
its
d
is
ad
v
an
tag
es th
at
th
e
b
u
r
s
ts
m
ay
r
ea
ch
th
eir
d
esti
n
atio
n
o
u
t
-
of
-
o
r
d
er
a
n
d
th
e
d
ef
lectin
g
b
u
r
s
t
s
m
ay
f
o
llo
w
a
lo
n
g
r
o
u
te
to
ar
r
iv
e
th
eir
tar
g
et.
B
u
r
s
ts
m
a
y
h
av
e
a
lo
n
g
d
elay
as
a
r
esu
lt
o
f
th
is
.
Fu
r
th
er
m
o
r
e,
ad
d
itio
n
al
tr
af
f
ic
is
g
en
er
a
ted
in
th
e
n
etwo
r
k
wh
en
co
m
p
etin
g
b
u
r
s
ts
tr
av
er
s
e
th
e
n
etwo
r
k
with
o
u
t n
ee
d
in
g
to
.
I
n
th
e
b
u
r
s
t
s
eg
m
en
tatio
n
d
r
o
p
p
in
g
s
ch
e
m
e
th
e
b
u
r
s
t
is
s
p
lit
in
to
s
m
all
p
ar
ts
ca
lled
s
e
g
m
en
ts
o
f
b
u
r
s
t.
All
o
f
th
e
s
eg
m
e
n
ted
b
u
r
s
ts
ar
e
co
m
b
in
e
d
in
to
o
n
e
b
u
r
s
t.
W
h
en
th
er
e
is
co
n
ten
tio
n
b
etwe
en
b
u
r
s
ts
,
th
e
o
n
ly
s
eg
m
e
n
t
b
u
r
s
t
th
o
s
e
co
n
f
licts
with
s
eg
m
en
ts
o
f
a
n
t
h
er
s
b
u
r
s
t
ar
e
d
r
o
p
p
e
d
[
2
0
]
.
T
h
e
b
en
e
f
it
o
f
th
is
tech
n
iq
u
e
is
th
at
it
r
ed
u
ce
s
th
e
p
r
o
b
a
b
ilit
y
o
f
b
u
r
s
t
lo
s
s
with
o
u
t
ad
d
in
g
a
n
y
ad
d
itio
n
a
l
h
ar
d
war
e
b
y
u
s
in
g
f
r
ag
m
en
te
d
b
u
r
s
ts
[
2
1
]
.
T
o
o
v
er
co
m
e
b
u
r
s
t
lo
s
s
es
d
u
e
to
co
n
ten
tio
n
in
th
e
n
etwo
r
k
,
two
way
s
ar
e
u
s
ed
:
r
ea
ctiv
e
an
d
p
r
o
ac
tiv
e.
T
h
e
r
ea
ctiv
e
co
n
te
n
tio
n
s
tr
ateg
y
ai
m
s
to
r
eso
lv
e
co
n
ten
tio
n
s
a
f
t
er
th
ey
ex
is
t
in
th
e
co
r
e
n
etwo
r
k
,
wh
er
ea
s
th
e
p
r
o
ac
tiv
e
co
n
g
esti
o
n
ap
p
r
o
ac
h
is
aim
ed
to
av
o
id
co
n
ten
tio
n
s
f
r
o
m
o
cc
u
r
r
in
g
in
th
e
n
etwo
r
k
ca
u
s
in
g
d
ata
b
u
r
s
t lo
s
s
es
[
1
6
]
,
[
2
2
]
.
Fig
u
r
e
3
d
ep
icts
th
e
d
is
ag
r
ee
m
en
t i
n
OB
S.
T
o
r
eso
lv
e
r
ea
ctiv
e
c
o
n
f
lict,
a
class
ic
s
o
lu
tio
n
ca
n
b
e
u
s
ed
s
u
ch
as:
o
p
tical
b
u
f
f
er
in
g
u
tili
z
in
g
a
f
ib
er
d
elay
lin
es,
wav
elen
g
th
co
n
v
er
t
er
,
d
ef
lectin
g
r
o
u
tin
g
a
n
d
b
u
r
s
t
s
eg
m
en
tatio
n
d
r
o
p
p
i
n
g
.
T
h
e
o
n
ly
f
ir
s
t
th
r
ee
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
3
,
Ma
r
ch
20
22
:
1
5
3
9
-
1
5
4
8
1542
ap
p
r
o
ac
h
es
ar
e
ef
f
ec
tiv
e
in
r
eso
lv
in
g
co
n
f
licts
,
b
u
t
t
h
ey
n
ec
e
s
s
itate
an
ex
tr
a
h
a
r
d
war
e
an
d
ad
d
itio
n
al
c
o
s
t
an
d
co
m
p
lex
ity
to
th
e
cir
cu
its
.
I
n
th
e
d
r
o
p
p
in
g
s
eg
m
en
tatio
n
s
tr
ateg
y
,
th
e
in
ter
lace
d
p
a
r
t
o
f
th
e
b
u
r
s
t
is
o
n
ly
d
is
ca
r
d
ed
wh
er
e
t
h
e
d
r
o
p
p
i
n
g
will b
e
in
th
e
tail o
r
in
th
e
h
ea
d
o
f
th
e
b
u
r
s
t
[
1
]
.
Fig
u
r
e
3
.
C
o
n
ten
ti
o
n
in
OB
S
[
1
6
]
,
[
2
2
]
4.
CO
NT
E
NT
I
O
N
RE
SO
L
U
T
I
O
N
B
Y
USI
NG
O
P
T
I
CA
L
B
UF
F
E
RING
I
N
O
B
S N
E
T
W
O
RK
I
n
o
p
tical
b
u
f
f
e
r
wh
er
e
r
is
k
ass
ess
m
en
t
m
eth
o
d
s
tatem
en
ts
(
R
AM
s
)
do
n
o
t
av
ailab
le,
t
h
e
f
ib
er
d
ela
y
lin
e
(
FDLs
)
ar
e
u
s
ed
as o
p
tica
l b
u
f
f
er
.
I
n
s
tead
o
f
b
ein
g
s
to
r
ed
in
th
e
b
u
f
f
e
r
s
,
th
e
co
m
p
etin
g
b
u
r
s
ts
ar
e
d
elay
e
d
f
o
r
a
s
et
am
o
u
n
t
o
f
tim
e.
T
h
is
d
o
n
e
b
y
r
eser
v
in
g
f
ir
s
t
t
h
e
wav
elen
g
t
h
,
th
e
n
FDL
r
e
s
er
v
atio
n
.
At
th
e
b
eg
in
n
in
g
,
ch
ec
k
th
e
av
ailab
ili
ty
o
f
th
e
wav
elen
g
th
wh
er
e
th
e
d
ata
m
u
s
t w
ait
f
o
r
a
m
in
im
al
am
o
u
n
t o
f
tim
e;
if
th
e
waitin
g
tim
e
is
less
th
an
th
e
FDL'
s
d
elay
,
th
en
d
ata
b
u
r
s
t
will
s
en
d
to
FDL;
o
th
er
wis
e,
it will d
r
o
p
.
B
ef
o
r
e
s
en
d
in
g
th
e
d
ata
b
u
r
s
t
to
FDLs
it
is
n
ec
ess
ar
y
to
k
n
o
w
th
e
FDLs's
len
g
th
,
th
is
len
g
th
d
ep
e
n
d
s
o
n
b
u
r
s
t
len
g
th
,
w
h
ich
is
v
ar
i
ab
le
in
OB
S
s
o
,
u
s
in
g
o
f
b
u
f
f
er
in
g
is
lim
ited
in
OB
S
[
9
]
.
F
ig
u
r
e
4
illu
s
tr
ates
a
Nx
N
OB
S
n
o
d
e
an
d
with
an
in
p
u
t
p
o
r
t
N.
Ass
u
m
e
th
at,
th
e
b
u
r
s
t
ar
r
iv
al
is
co
n
s
id
er
ed
a
Po
is
s
o
n
p
r
o
ce
s
s
,
th
e
len
g
th
o
f
b
u
r
s
ts
is
ex
p
o
n
e
n
tially
d
is
tr
ib
u
ted
,
th
e
m
ea
n
o
f
tr
a
n
s
m
is
s
io
n
tim
e
(
m
ea
n
b
u
r
s
t
le
n
g
th
)
is
1
/μ
an
d
λ
is
th
e
d
ata
r
ate
in
b
u
r
s
t p
er
tim
e.
B
u
r
s
ts
f
r
o
m
in
p
u
t
p
o
r
ts
ar
e
m
u
ltip
lex
ed
to
o
u
tp
u
t
p
o
r
ts
wh
e
r
e
th
e
r
ec
ei
v
ed
d
ata
r
ate
at
e
v
er
y
o
u
tp
u
t
is
λ
.
Ass
u
m
e
th
at
th
e
in
ter
v
al
tim
e
b
etwe
en
b
u
r
s
ts
ar
r
iv
als
is
r
ep
r
esen
ted
b
y
a
r
an
d
o
m
v
ar
iab
le
t,
wh
ich
is
d
is
tr
ib
u
ted
ex
p
o
n
e
n
tially
with
r
ate
λ
a
n
d
d
en
s
ity
o
f
p
r
o
b
ab
i
lity
f
T
=
λ
−
λ
.
A
tech
n
iq
u
e
is
p
r
es
en
te
d
in
th
e
n
o
d
e
b
y
ass
u
m
in
g
e
v
er
y
o
u
tp
u
t w
ith
a
f
o
r
war
d
f
ix
ed
len
g
th
F
DL
b
u
f
f
er
i
n
g
.
At
o
u
t
p
o
r
t
A,
b
e
f
o
r
e
th
e
b
u
r
s
t
r
ea
ch
es
f
o
r
it,
it
m
u
s
t
s
p
ec
if
y
wh
eth
e
r
th
e
r
e
ar
e
an
y
b
u
r
s
ts
u
n
d
er
p
r
o
ce
s
s
in
g
o
r
n
o
t
an
d
also
if
th
er
e
an
y
b
u
r
s
ts
in
th
e
f
ib
er
d
elay
lin
e
.
T
h
e
ar
r
iv
in
g
b
u
r
s
t
ca
n
o
n
ly
ex
p
o
r
t
d
ir
ec
tly
f
r
o
m
p
o
r
t
A
if
b
o
th
F
DL
an
d
p
o
r
t
A
ar
e
u
n
u
s
ed
.
I
f
two
b
u
r
s
ts
ar
e
c
o
n
ten
d
in
g
o
n
th
e
s
am
e
o
u
tp
u
t
lin
e,
o
n
e
will
tr
a
n
s
f
er
v
ia
p
o
r
t
A,
wh
ile
th
e
o
th
er
will
b
e
d
elay
ed
f
o
r
a
wh
ile
v
ia
p
o
r
t
B
.
T
o
av
o
id
co
m
p
etitio
n
b
etwe
e
n
th
e
ar
r
iv
in
g
b
u
r
s
t
at
p
o
r
t
A
an
d
th
e
d
elay
i
n
g
b
u
r
s
t
o
v
er
FDL,
u
s
e
D=
3
/μ
.
T
h
e
s
u
b
s
eq
u
en
t
b
u
r
s
t
p
ac
k
ets
ar
e
o
n
ly
d
is
ca
r
d
ed
w
h
en
th
er
e
is
a
co
n
f
lict
in
p
o
r
t
B
.
As
a
r
esu
lt,
p
o
r
t
A'
s
co
n
f
li
ct
alr
ea
d
y
m
o
v
es
to
p
o
r
t B,
an
d
t
h
e
f
ib
e
r
d
elay
lin
e
s
d
elay
s
a
n
u
m
er
o
u
s
b
u
r
s
t b
ef
o
r
e
d
eliv
er
i
n
g
th
em
to
th
e
o
u
t
p
u
t p
o
r
t
[
2
3
]
.
Fig
u
r
e
4
.
T
h
e
ar
r
i
v
al
r
ates to
t
h
e
o
u
tp
u
t
FDLs f
r
o
m
v
a
r
io
u
s
i
n
p
u
ts
[
2
3
]
L
o
ad
(
ρ
)
is
th
e
p
r
o
p
o
r
tio
n
o
f
r
ate
o
f
ar
r
iv
al
to
th
e
p
ac
k
et
s
er
v
ice
r
ate.
Ass
u
m
e
p
to
b
e
th
e
p
ar
am
eter
th
at
d
en
o
ted
to
th
e
p
r
o
b
ab
ilit
y
o
f
a
d
ata
b
u
r
s
t
b
ein
g
tr
a
v
e
llin
g
to
t
h
e
p
o
r
t
B
.
As
s
h
o
wn
in
Fig
u
r
e
4
,
p
λ
r
ep
r
esen
ts
th
e
ar
r
iv
al
r
ate
o
f
d
ata
b
u
r
s
t
t
o
p
o
r
t
B
,
wh
ile
λ
(
1
-
p
)
is
th
e
ar
r
i
v
al
r
ate
o
f
th
e
b
u
r
s
t
to
p
o
r
t
A.
A
b
u
r
s
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
P
erfo
r
ma
n
ce
a
n
a
lysi
s
co
mp
a
r
is
o
n
o
f o
p
tica
l
b
u
r
s
t sw
itch
in
g
…
(
La
ila
A
.
Wa
h
a
b
A
b
d
u
lla
h
)
1543
is
d
ir
ec
tly
d
eliv
er
ed
to
p
o
r
t A
wh
en
t
h
er
e
is
n
o
d
elay
,
b
u
t w
h
en
th
e
b
u
r
s
t is d
eliv
er
ed
to
p
o
r
t B,
m
ea
n
s
th
er
e
is
a
d
elay
o
f
D,
w
h
er
e
D
is
th
e
FDL'
s
p
r
o
p
ag
atio
n
d
elay
.
I
n
ca
s
e,
p
o
r
t
B
is
o
cc
u
p
ied
,
th
e
ar
r
iv
in
g
b
u
r
s
t
f
r
o
m
an
o
th
er
in
p
u
t
p
o
r
t
(
N
-
1
)
will
b
e
d
r
o
p
p
ed
.
E
v
er
y
in
p
u
t
p
o
r
t
t
o
th
e
o
p
tical
s
witch
was
d
esig
n
ed
as
an
M/M
/1
/∞
q
u
eu
e,
i
n
th
e
s
im
u
latio
n
m
o
d
e
l
[
2
4
]
,
[
2
5
]
.
N
is
in
p
u
t
p
o
r
ts
f
o
r
a
N
x
N
s
witch
in
g
n
o
d
e,
Π
r
ep
r
esen
t
th
e
p
r
o
b
ab
ilit
y
o
f
p
o
r
t
B
wh
en
it
is
b
u
s
y
.
T
h
e
iter
ativ
e
in
(
1
)
-
(
6
)
wer
e
u
s
ed
to
s
im
u
late
th
e
v
alu
es o
f
v
ar
io
u
s
n
etwo
r
k
lo
a
d
s
f
o
r
N=
2
,
4
,
8
,
1
6
.
T
h
e
n
,
th
e
p
r
o
b
a
b
ilit
y
o
f
b
u
r
s
t lo
s
s
in
th
is
o
u
tp
u
t
p
o
r
t w
as c
alcu
lated
b
y
(
7
)
is
:
=
p
λ
p
λ
+
μ
+
(
1
−
p
)
λ
(
1
−
p
)
λ
+
μ
(
1
)
∏
=
p
λ
p
λ
+
μ
(
2
)
=
(
1
−
μ
μ
+
p
λ
(
1
−
)
e
−
p
λ
(
1
−
)
D
)
(
3
)
=
(
1
−
μ
μ
+
p
λ
(
1
−
)
e
−
p
λ
(
1
−
)
D
)
x
p
λ
p
λ
+
μ
+
(
1
−
p
)
λ
(
1
−
p
)
λ
+
μ
(
4
)
=
λ
λ
+
(
5
)
p
=
+
−
(
6
)
=
N
N
−
1
(
7
)
5.
O
B
S NE
T
WO
RK
CO
N
T
E
N
T
I
O
N
R
E
SO
L
UT
I
O
N
USI
N
G
SE
G
M
E
NT
AT
I
O
N
DRO
P
P
I
NG
S
e
g
m
e
n
t
a
ti
o
n
d
r
o
p
p
i
n
g
t
e
c
h
n
i
q
u
e
r
e
s
o
l
v
e
d
t
h
e
c
o
n
f
l
i
c
t
b
y
d
is
c
a
r
d
i
n
g
t
h
e
o
v
e
r
l
a
p
p
e
d
p
a
r
t
o
f
t
h
e
b
u
r
s
t
.
W
h
e
n
c
o
n
f
l
i
c
t
o
c
c
u
r
s
,
t
h
e
c
o
m
p
e
t
i
n
g
b
u
r
s
t
s
a
r
e
d
i
v
i
d
e
d
i
n
t
o
s
e
g
m
e
n
t
s
a
n
d
t
h
e
o
v
e
r
l
a
p
p
i
n
g
o
n
e
s
w
i
ll
b
e
d
r
o
p
p
e
d
f
r
o
m
t
h
e
s
y
s
t
e
m
[
9
]
.
T
h
es
e
d
r
o
p
p
e
d
s
e
g
m
e
n
t
s
c
a
n
t
h
e
n
b
e
r
e
t
r
a
n
s
m
it
t
e
d
a
g
ai
n
.
T
h
is
t
e
c
h
n
i
q
u
e
i
m
p
r
o
v
e
d
t
h
e
t
h
r
o
u
g
h
p
u
t
o
f
t
h
e
n
e
tw
o
r
k
,
b
u
t
s
ti
l
l
s
u
f
f
e
r
f
r
o
m
c
o
n
t
r
o
l
li
n
g
t
h
e
d
r
o
p
p
i
n
g
s
e
g
m
e
n
t
,
an
d
d
r
o
p
s
e
g
m
e
n
ts
r
e
g
e
n
e
r
a
t
i
o
n
[
2
6
]
,
r
e
-
t
r
a
n
s
m
i
s
s
i
o
n
a
n
d
s
y
n
c
h
r
o
n
i
z
a
t
i
o
n
o
f
d
a
t
a
b
u
r
s
t
s
as
s
h
o
w
n
i
n
F
i
g
u
r
e
5
[
5
]
.
S
e
g
m
e
n
t
a
t
i
o
n
c
a
n
b
e
e
i
t
h
e
r
s
e
g
m
e
n
t
i
n
g
t
h
e
tai
l
o
r
a
s
i
n
F
i
g
u
r
e
6
(
a
)
o
r
s
e
g
m
en
t
i
n
g
t
h
e
h
e
a
d
e
r
a
s
i
n
F
i
g
u
r
e
6
(
b
)
[
2
6
]
.
Hea
d
d
r
o
p
p
in
g
h
as
an
ef
f
ec
t
o
n
tr
an
s
m
itti
n
g
th
e
p
ac
k
ets
in
s
eq
u
en
ce
,
a
n
d
d
r
o
p
p
i
n
g
o
f
t
h
e
tail
lead
to
g
iv
e
in
co
r
r
ec
t
in
f
o
r
m
atio
n
a
b
o
u
t
b
u
r
s
t
len
g
th
also
th
e
h
ea
d
er
d
o
esn
’
t
h
av
e
a
n
y
in
f
o
r
m
a
tio
n
ab
o
u
t
th
e
n
ew
len
g
th
b
ec
a
u
s
e
it
s
till
s
av
es
th
e
o
r
ig
in
al
b
u
r
s
t
len
g
th
s
o
th
is
in
d
icate
s
to
in
e
f
f
ec
tiv
e
u
tili
za
tio
n
o
f
th
e
b
an
d
wid
th
[
2
7
]
.
T
h
e
m
ain
d
i
f
f
icu
lty
in
s
eg
m
en
tatio
n
d
r
o
p
p
i
n
g
tech
n
iq
u
e
is
co
m
p
lex
co
n
tr
o
llin
g
an
d
m
an
ag
es
o
f
d
r
o
p
s
eg
m
e
n
t
an
d
th
e
r
eg
en
er
atio
n
s
eg
m
en
ts
.
C
o
r
e
n
o
d
es
in
s
eg
m
e
n
tatio
n
-
b
as
ed
-
d
r
o
p
p
in
g
ca
n
b
e
r
ep
r
esen
ted
as
M
/G/N
E
W
E
s
tan
d
ar
d
s
y
s
tem
[
1
]
,
with
th
e
p
r
o
b
ab
ilit
y
o
f
b
u
r
s
t lo
s
s
d
en
o
ted
as
:
=
∑
=
−
1
(
−
!
!
(
−
)
!
(
)
(
1
+
)
)
(
8
)
T
h
e
b
u
r
s
ts
ar
r
iv
al
is
tr
ea
te
d
as
a
Po
is
s
o
n
Pro
ce
s
s
;
λ
is
th
e
m
ea
n
ar
r
i
v
al
r
ate
o
f
th
e
b
u
r
s
t
an
d
1
is
th
e
m
ea
n
o
f
th
e
b
u
r
s
t
len
g
th
.
N
0
r
ep
r
esen
ts
th
e
n
u
m
b
er
o
f
t
h
e
o
u
tp
u
t
ch
an
n
els
av
ailab
le,
W
0
is
th
e
n
u
m
b
e
r
o
f
av
ailab
le
o
u
tp
u
t
wav
ele
n
g
th
s
an
d
n
is
th
e
en
tire
o
f
b
an
d
wid
th
r
eso
u
r
ce
s
,
th
en
n
=
N
0
W
0
.
Similar
ly
,
if
N
E
d
en
o
tes
to
th
e
av
ailab
le
n
u
m
b
er
o
f
i
n
p
u
t
c
h
an
n
els
an
d
W
E
d
en
o
te
th
e
n
u
m
b
e
r
o
f
av
ailab
le
in
p
u
t
wav
elen
g
th
s
,
th
e
to
tal
av
ailab
le
o
n
i
n
p
u
t
r
e
s
o
u
r
ce
is
N
E
W
E
,
wh
er
e
N
E
W
E
is
th
e
n
u
m
b
er
o
f
a
v
ailab
le
in
p
u
t
ch
a
n
n
els
wh
er
e
N
E
W
E
≥
n
[
1
]
.
Fig
u
r
e
5
.
Seg
m
e
n
tatio
n
d
r
o
p
p
i
n
g
[
9
]
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
3
,
Ma
r
ch
20
22
:
1
5
3
9
-
1
5
4
8
1544
(
a)
(
b
)
Fig
u
r
e
6
.
Seg
m
e
n
tatio
n
d
r
o
p
p
i
n
g
of
(
a)
th
e
tail a
n
d
(
b
)
th
e
h
e
ad
[
2
5
]
6.
CO
NT
E
NT
I
O
N
RE
SO
L
U
T
I
O
N
B
Y
USI
NG
DE
F
L
E
C
T
I
O
N
RO
UT
I
NG
I
N
O
B
S N
E
T
WO
RK
C
o
n
ten
tio
n
ca
n
b
e
r
eso
lv
ed
b
y
d
ef
lectio
n
r
o
u
tin
g
tech
n
iq
u
e
b
y
d
ir
ec
tin
g
th
e
co
m
p
etin
g
b
u
r
s
t
to
an
o
u
tp
u
t
r
o
u
te
o
th
er
th
a
n
th
e
o
r
ig
in
al
p
o
r
t.
I
f
two
d
ata
b
u
r
s
ts
ar
e
in
th
e
n
o
d
e
A
an
d
wan
t
to
ar
r
iv
e
n
o
d
e
B
a
s
am
e
p
er
io
d
o
f
tim
e,
th
e
s
h
o
r
test
p
ath
f
r
o
m
A
to
B
will
r
eser
v
e
f
o
r
th
e
b
u
r
s
t
th
at
f
i
r
s
t
ar
r
iv
e
o
r
th
e
b
u
r
s
t
p
r
io
r
ity
h
ig
h
er
.
T
h
e
n
,
th
e
d
ata
b
u
r
s
t
wh
ich
is
u
n
p
r
o
ce
s
s
ed
will
cr
ea
te
a
v
ir
tu
al
r
o
u
te
f
r
o
m
A
n
o
d
e
to
B
o
v
er
C
to
r
ea
ch
t
h
e
n
ea
r
est
p
at
h
to
n
o
d
e
B
with
o
u
t
wav
elen
g
th
co
n
v
er
s
io
n
[
1
]
as
s
h
o
wn
in
F
ig
u
r
e
7
.
So
,
in
d
ef
lectio
n
r
o
u
tin
g
,
th
e
p
r
o
b
a
b
ilit
y
o
f
b
u
r
s
t lo
s
s
i
s
d
ec
r
ea
s
in
g
,
an
d
u
tili
za
tio
n
o
f
th
e
lin
k
will in
cr
ea
s
e.
C
o
n
g
esti
o
n
an
d
r
e
-
r
o
u
tin
g
o
f
t
h
e
d
ata
b
u
r
s
ts
ar
e
th
e
m
ain
d
r
awb
ac
k
in
th
e
OB
S
n
etwo
r
k
s
wh
er
e
th
e
d
ef
lecte
d
b
u
r
s
t
in
cr
ea
s
es
co
n
g
esti
o
n
an
d
it
also
s
p
ee
d
-
u
p
co
n
ten
tio
n
a
n
d
c
o
n
g
esti
o
n
o
n
t
h
e
d
ef
lectio
n
p
ath
s
.
W
h
en
th
e
tr
af
f
ic
lo
ad
is
h
ig
h
er
,
th
e
d
ata
b
u
r
s
t
k
ee
p
-
o
n
in
d
ev
iatin
g
f
r
o
m
o
n
e
r
o
u
te
to
a
n
o
th
er
a
f
ew
m
o
r
e
tim
es
b
ef
o
r
e
r
ea
ch
in
g
th
e
r
eq
u
ir
ed
d
esti
n
atio
n
.
T
h
is
d
ata
b
u
r
s
ts
ar
r
iv
es
o
u
t
-
of
-
or
d
er
,
a
n
d
it
s
ef
f
ec
t
is
r
ef
lecte
d
o
n
th
e
d
ata
b
u
r
s
t
at
th
e
d
esti
n
atio
n
b
ec
a
u
s
e
th
e
s
eq
u
en
cin
g
o
f
d
ata
b
u
r
s
ts
at
th
e
eg
r
ess
n
o
d
e
is
im
p
o
r
tan
t
an
d
r
eq
u
ir
ed
[
9
]
,
[
1
9
]
.
T
h
e
m
ain
lim
itatio
n
s
o
f
d
ef
lectio
n
r
o
u
tin
g
ar
e
th
e
co
m
p
le
x
ity
in
m
a
n
a
g
in
g
th
e
d
ef
lecte
d
b
u
r
s
t o
n
th
e
r
ef
lecte
d
r
o
u
te
[
2
6
]
.
Fig
u
r
e
7
.
Prin
cip
al
o
p
er
atio
n
o
f
d
ef
lectio
n
r
o
u
tin
g
[
2
3
]
I
n
a
d
ef
lectio
n
r
o
u
tin
g
p
r
o
ce
s
s
,
th
e
p
r
o
b
ab
ilit
y
o
f
lo
s
s
is
e
x
p
r
ess
ed
as
[
1
]
,
wh
er
e
k
i
s
th
e
n
u
m
b
e
r
o
f
in
p
u
t
lin
k
s
to
th
e
n
o
d
e
an
d
n
th
e
n
u
m
b
er
o
f
alter
n
ate
p
at
h
s
f
r
o
m
t
h
e
s
o
u
r
ce
to
th
e
d
esti
n
atio
n
n
o
d
e.
=
[
]
∗
1
!
1
+
∑
[
]
∗
=
1
1
!
(
9
)
7.
SI
M
UL
A
T
I
O
N
A
ND
RE
SU
L
T
S
T
h
e
ca
p
ac
ity
o
f
th
e
f
ib
e
r
d
e
lay
lin
es,
s
eg
m
e
n
tatio
n
d
r
o
p
p
in
g
a
n
d
d
ef
lectio
n
r
o
u
tin
g
s
y
s
tem
s
to
r
eso
lv
e
co
n
ten
tio
n
is
ev
alu
ate
d
th
r
o
u
g
h
s
im
u
latio
n
s
.
Simu
l
atio
n
s
wer
e
d
o
n
e
f
o
r
v
ar
io
u
s
o
f
in
co
m
in
g
tr
af
f
ic
(
lo
ad
)
(
ρ
=
λ
μ
)
to
o
b
s
er
v
e
th
e
i
m
p
ac
t
o
f
N
(
th
e
n
u
m
b
er
o
f
w
av
elen
g
th
s
av
ailab
le
d
ed
icate
d
to
b
u
r
s
ts
o
n
th
e
o
u
tp
u
t
f
ib
er
lin
k
s
)
o
n
th
e
b
u
r
s
t
lo
s
s
p
r
o
b
ab
ilit
y
.
Fo
r
d
if
f
er
e
n
t
v
alu
es
o
f
N,
we
also
lo
o
k
ed
at
h
o
w
th
e
b
u
r
s
t
lo
s
s
p
r
o
b
ab
ilit
y
ch
a
n
g
ed
with
th
e
lo
ad
.
T
h
e
m
ajo
r
is
s
u
e
o
f
th
is
p
ap
e
r
i
s
to
p
r
o
v
e
th
at
,
th
e
p
er
f
o
r
m
an
ce
o
f
FDL
is
b
etter
to
r
eso
lv
e
co
n
ten
tio
n
in
co
m
p
ar
is
o
n
with
o
th
er
te
ch
n
iq
u
es.
T
h
is
p
a
p
er
co
m
p
ar
es
th
e
in
co
m
in
g
tr
a
f
f
ics
ag
a
in
s
t
th
e
b
u
r
s
t
lo
s
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
P
erfo
r
ma
n
ce
a
n
a
lysi
s
co
mp
a
r
is
o
n
o
f o
p
tica
l
b
u
r
s
t sw
itch
in
g
…
(
La
ila
A
.
Wa
h
a
b
A
b
d
u
lla
h
)
1545
p
r
o
b
a
b
ilit
y
(
B
L
P),
wh
er
eb
y
in
cr
ea
s
in
g
th
e
in
co
m
in
g
tr
af
f
ic
s
th
e
B
L
P
will
d
ec
r
ea
s
e
as
s
e
en
in
F
ig
u
r
es
8
-
1
0
.
Fro
m
th
ese
f
ig
u
r
es,
th
e
d
e
f
l
ec
tio
n
r
o
u
tin
g
tech
n
iq
u
e
g
o
t
less
B
L
P
th
an
o
th
er
tech
n
i
q
u
es,
b
u
t
its
m
ain
d
r
awb
ac
k
,
d
u
r
in
g
co
n
ten
tio
n
,
th
e
b
u
r
s
t
will
d
ef
lect
f
r
o
m
o
n
e
r
o
u
te
to
an
th
e
r
u
n
til
r
ea
c
h
t
o
th
eir
d
esti
n
atio
n
,
th
is
will
ca
u
s
e
d
elay
th
e
b
u
r
s
t
o
r
m
ay
lo
s
t,
wh
ile
in
ca
s
e
o
f
FDL
th
e
d
elay
is
lim
ited
d
ep
en
d
in
g
o
n
th
e
len
g
th
o
f
th
e
b
u
r
s
t,
r
esu
ltin
g
in
f
ib
e
r
d
elay
lin
es
b
ei
n
g
co
n
s
id
er
e
d
th
e
b
est
f
o
r
r
ed
u
cin
g
B
L
P.
T
h
e
s
im
u
latio
n
s
wer
e
ca
r
r
ied
o
u
t
u
s
in
g
MA
T
L
AB
t
o
o
ls
to
esti
m
ate
th
e
b
u
r
s
t
lo
s
s
p
r
o
b
a
b
ilit
y
o
f
ea
ch
f
ib
er
d
elay
lin
e,
s
eg
m
en
tatio
n
b
ase
d
r
o
p
p
in
g
,
an
d
d
ef
lectio
n
r
o
u
tin
g
s
tr
ateg
ies
f
o
r
v
ar
ie
d
n
etwo
r
k
ch
ar
ac
te
r
is
tics
u
n
d
er
p
r
o
p
er
n
o
d
e
an
d
tr
af
f
ic
ass
u
m
p
tio
n
s
u
s
in
g
(
2
)
,
(
7
)
,
(
8
)
,
a
n
d
(
9
)
.
I
n
th
is
s
im
u
latio
n
,
we
u
s
ed
th
e
to
tal
en
tire
o
f
b
a
n
d
wid
th
r
eso
u
r
ce
s
n
=
2
,
4
,
8
,
1
6
.
Als
o
,
th
e
av
ailab
le
n
u
m
b
er
o
f
in
p
u
t
ch
an
n
els
N
E
=
4
,
th
e
n
u
m
b
er
o
f
av
ailab
le
i
n
p
u
t
wav
elen
g
th
s
W
E
=
1
0
(
N
E
W
E
=
4
0
)
,
th
e
to
tal
av
ailab
ilit
y
o
f
in
p
u
t
r
eso
u
r
ce
N
E
W
E
n
.
Me
a
n
b
u
r
s
t
ar
r
iv
al
r
ate
λ
f
r
o
m
0
to
5
p
ac
k
ets/
s
ec
,
m
ea
n
b
u
r
s
t
len
g
th
1
μ
=1
s
ec
/p
ac
k
et,
lo
ad
r
an
g
e
f
r
o
m
0
to
5
(
=
λ
μ
)
,
tr
an
s
m
is
s
io
n
r
ate
1
0
Gb
p
s
an
d
D
=
3
/
μ
,
wh
er
e
D
is
th
e
FDL'
s
p
r
o
p
a
g
atio
n
d
ela
y
.
F
i
g
u
r
e
8
r
e
p
r
es
e
n
ts
t
h
e
p
r
o
b
a
b
i
l
i
t
y
o
f
b
u
r
s
t
l
o
s
s
v
e
r
s
u
s
l
o
ad
f
o
r
v
a
r
i
o
u
s
v
a
l
u
es
o
f
o
u
t
p
u
t
c
h
a
n
n
e
ls
a
v
a
i
l
a
b
l
e
b
y
f
i
x
i
n
g
t
h
e
n
u
m
b
e
r
o
f
i
n
p
u
t
c
h
a
n
n
e
l
a
v
a
i
l
a
b
l
e
i
n
th
e
s
e
g
m
e
n
t
a
ti
o
n
d
r
o
p
p
i
n
g
s
c
h
e
m
e
.
A
l
s
o
,
i
t
s
h
o
ws
t
h
a
t
,
w
h
e
n
t
h
e
n
u
m
b
e
r
o
f
o
u
t
p
u
t
c
h
a
n
n
e
l
s
i
s
i
n
c
r
e
as
e
d
,
t
h
e
p
r
o
b
a
b
i
l
i
t
y
o
f
d
r
o
p
p
i
n
g
a
b
u
r
s
t
i
s
d
e
c
r
e
a
s
i
n
g
a
n
d
t
h
e
re
s
u
l
t
v
a
l
i
d
at
e
s
r
e
al
i
t
y
.
Fi
g
u
r
e
9
d
e
p
i
c
t
s
t
h
e
b
u
r
s
t
l
o
s
s
p
r
o
b
a
b
i
l
i
t
y
i
n
d
e
f
l
e
c
ti
n
g
r
o
u
t
i
n
g
s
c
h
e
m
e
s
f
o
r
v
a
r
i
o
u
s
o
u
t
p
u
t
c
h
a
n
n
e
l
s
v
a
l
u
e
s
.
O
n
ea
ch
o
u
t
p
u
t
l
i
n
k
i
n
D
e
f
l
ec
t
i
o
n
r
o
u
ti
n
g
,
t
h
e
r
e
a
r
e
W
w
a
v
el
e
n
g
t
h
s
av
a
i
l
a
b
l
e
.
O
n
l
y
N
o
f
t
h
e
W
o
u
t
p
u
t
li
n
e
s
a
r
e
d
e
d
i
c
a
t
ed
t
o
d
e
f
l
e
c
t
e
d
b
u
r
s
ts
.
M
o
r
e
o
v
e
r
,
w
h
e
n
t
h
e
n
u
m
b
e
r
o
f
i
n
p
u
t
c
h
a
n
n
e
l
k
e
e
p
i
n
g
f
i
x
e
d
s
o
i
n
c
r
e
as
i
n
g
i
n
t
h
e
n
u
m
b
e
r
o
f
o
u
t
p
u
t
c
h
a
n
n
e
l
s
l
ea
d
s
t
o
d
e
c
r
e
as
e
s
t
h
e
b
u
r
s
t
l
o
s
s
p
r
o
b
a
b
i
l
i
t
y
.
Fig
u
r
e
1
0
r
e
p
r
esen
ts
th
e
b
u
r
s
t
lo
s
s
p
r
o
b
a
b
ilit
y
o
f
f
ib
e
r
d
elay
lin
es
s
ch
em
es
f
o
r
v
ar
i
o
u
s
v
alu
es
o
f
av
ailab
le
o
u
tp
u
t
ch
an
n
els.
Ob
v
io
u
s
ly
f
r
o
m
th
e
f
ig
u
r
e
th
at
in
cr
ea
s
in
g
in
th
e
o
u
tp
u
t
c
h
an
n
el
s
ca
u
s
in
g
in
c
r
ea
s
es
in
th
e
b
u
r
s
t
l
o
s
s
p
r
o
b
a
b
ilit
y
.
F
r
o
m
F
ig
u
r
es
8
-
1
0
we
ca
n
co
n
c
lu
d
e
th
at:
i
)
Def
lectio
n
r
o
u
tin
g
an
d
s
eg
m
e
n
tatio
n
d
r
o
p
p
in
g
h
av
e
th
e
s
am
e
p
r
in
ci
p
le
th
at,
r
ed
u
cin
g
b
u
r
s
ts
lo
s
in
g
p
r
o
b
a
b
ilit
y
as
th
e
n
u
m
b
er
o
f
o
u
tp
u
t
ch
an
n
els
is
in
cr
ea
s
in
g
,
b
u
t
f
o
r
f
i
b
er
d
elay
lin
es
th
e
in
cr
ea
s
in
g
in
n
u
m
b
er
o
f
o
u
tp
u
t
ch
an
n
els
ca
u
s
e
in
cr
ea
s
in
g
in
th
e
b
u
r
s
t
lo
s
s
p
r
o
b
ab
ilit
y
.
ii)
Fo
r
ex
a
m
p
le,
wh
en
n
=4
,
th
e
b
u
r
s
t
l
o
s
s
p
r
o
b
ab
ilit
y
in
s
eg
m
en
ta
tio
n
d
r
o
p
p
in
g
an
d
d
ef
lectio
n
r
o
u
tin
g
is
0
.
8
5
8
5
,
0
.
1
3
7
3
r
esp
ec
tiv
ely
,
an
d
in
f
i
b
er
d
elay
lin
es
is
0
.
5
3
2
7
.
W
e
ca
n
co
n
clu
d
e
th
at
co
n
ten
tio
n
r
eso
lu
tio
n
u
s
in
g
d
e
f
lectio
n
r
o
u
tin
g
is
b
etter
th
an
th
e
o
th
e
r
tech
n
iq
u
es.
iii)
I
t
is
e
asy
to
r
e
d
u
ce
b
u
r
s
t
l
o
s
s
p
r
o
b
a
b
i
l
it
y
i
f
t
h
e
n
e
t
w
o
r
k
l
o
a
d
i
s
l
o
w
,
o
n
t
h
e
o
t
h
e
r
h
a
n
d
,
c
o
n
t
e
n
t
i
o
n
c
a
n
b
e
i
n
c
r
e
a
s
e
d
w
h
e
n
t
h
e
n
e
t
w
o
r
k
l
o
a
d
i
n
c
r
e
a
s
i
n
g
.
F
o
r
t
h
is
,
i
n
c
r
e
as
i
n
g
i
n
b
u
r
s
t
l
o
s
s
p
r
o
b
a
b
i
l
i
t
y
lea
d
s
t
o
d
r
o
p
t
h
e
OB
S
n
e
tw
o
r
k
s
e
f
f
i
c
i
e
n
c
y
.
Fin
ally
,
F
ig
u
r
e
1
1
s
h
o
ws
th
e
co
m
p
ar
ativ
e
p
er
f
o
r
m
an
ce
an
aly
s
is
o
f
f
ib
er
d
elay
lin
es,
d
ef
lectio
n
r
o
u
tin
g
an
d
s
eg
m
en
tatio
n
d
r
o
p
p
in
g
,
f
o
r
v
ar
io
u
s
in
p
u
ts
an
d
o
u
tp
u
t
p
ar
am
eter
s
.
it
also
s
h
o
ws,
th
e
d
ef
lectio
n
r
o
u
tin
g
s
ch
em
e
o
u
tp
er
f
o
r
m
s
t
h
e
f
ib
er
d
elay
lin
e
a
n
d
s
eg
m
e
n
tatio
n
d
r
o
p
p
in
g
s
ch
em
es
in
ter
m
s
o
f
b
u
r
s
t
lo
s
s
p
r
o
b
a
b
ilit
y
o
f
v
ar
i
o
u
s
in
p
u
ts
a
n
d
o
u
tp
u
t
p
ar
am
eter
s
.
B
ec
au
s
e
th
e
d
ef
lectio
n
r
o
u
tin
g
s
ch
em
e
d
o
es
n
o
t
d
elay
o
r
d
r
o
p
t
h
e
b
u
r
s
t lik
e
th
e
f
ib
er
d
e
lay
lin
e
an
d
s
eg
m
e
n
tatio
n
s
ch
e
m
es d
o
.
Fig
u
r
e
1
1
f
u
r
th
er
s
h
o
ws
th
at
th
e
f
ib
er
d
ela
y
lin
e
is
b
etter
th
an
d
ef
lectio
n
r
o
u
tin
g
b
ec
au
s
e
wh
en
th
er
e
is
co
n
f
lict
at
a
n
y
n
o
d
e,
t
h
e
b
u
r
s
t
m
ay
d
ef
lect
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alter
n
ate
r
o
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wh
ich
m
a
y
r
esu
lt
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e
b
u
r
s
t
tak
in
g
a
l
o
n
g
e
r
r
o
u
te
to
its
d
esti
n
atio
n
.
As a
r
e
s
u
lt,
th
e
d
elay
f
o
r
a
b
u
r
s
t m
ay
b
e
u
n
ac
ce
p
t
a
b
le,
b
u
t i
n
ca
s
e
o
f
a
f
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er
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y
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e,
th
e
co
m
p
etin
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b
u
r
s
ts
ar
e
d
el
ay
ed
b
y
a
p
r
e
d
eter
m
in
e
d
am
o
u
n
t
o
f
tim
e
p
r
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p
o
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tio
n
ate
t
o
th
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len
g
th
o
f
th
e
o
cc
u
p
ied
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y
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T
h
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co
n
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lu
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io
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is
q
u
ite
in
ter
esti
n
g
an
d
u
s
ef
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l in
ter
m
s
o
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esig
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a
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o
d
n
etwo
r
k
with
a
lo
w
b
lo
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in
g
p
r
o
b
ab
ilit
y
.
Fig
u
r
e
8
.
B
u
r
s
t lo
s
s
p
r
o
b
ab
ilit
y
v
er
s
u
s
in
co
m
i
n
g
tr
af
f
ic
in
s
e
g
m
en
tatio
n
p
r
o
b
a
b
ilit
y
b
y
f
ix
i
n
g
in
p
u
t c
h
an
n
el
wh
ile
v
ar
y
in
g
o
u
tp
u
t c
h
an
n
el
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
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4
7
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2
I
n
d
o
n
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J
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&
C
o
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Sci
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25
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3
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22
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1546
Fig
u
r
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.
B
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ilit
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ar
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Fig
u
r
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0
.
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p
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er
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in
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er
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ar
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Fig
u
r
e
1
1
.
C
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o
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th
e
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eg
m
en
tatio
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p
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d
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ib
e
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o
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4
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u
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4
,
r
esp
ec
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ely
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
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-
4
7
5
2
P
erfo
r
ma
n
ce
a
n
a
lysi
s
co
mp
a
r
is
o
n
o
f o
p
tica
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b
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r
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t sw
itch
in
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La
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b
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1547
8.
CO
NCLU
SI
O
N
Op
tical
b
u
r
s
t
s
wi
tch
in
g
(
OB
S)
b
ein
g
co
n
s
id
er
ed
as
a
p
o
ten
tial
s
o
lu
tio
n
f
o
r
th
e
n
ex
t
g
en
er
a
tio
n
o
f
th
e
o
p
tical
I
n
ter
n
et.
OB
S
was
ch
o
s
en
to
im
p
r
o
v
e
b
an
d
wid
th
u
s
ag
e
in
o
r
d
er
to
b
u
ild
a
f
lex
i
b
le
n
etwo
r
k
,
wh
ich
ac
co
m
m
o
d
ate
th
e
tr
af
f
ic
b
u
r
s
ts
g
en
er
ated
b
y
m
u
ltime
d
ia
s
er
v
ices.
Ov
er
co
m
i
n
g
p
er
f
o
r
m
a
n
ce
d
eter
io
r
atio
n
d
u
e
to
co
n
ten
tio
n
is
o
n
e
o
f
th
e
m
o
s
t
ch
allen
g
in
g
asp
ec
ts
o
f
u
s
in
g
an
OB
S
n
etwo
r
k
.
C
o
n
f
lict
r
eso
lu
tio
n
is
o
n
e
o
f
th
e
m
o
s
t
r
esear
ch
ed
is
s
u
es
in
th
e
OB
S
n
etwo
r
k
.
Dif
f
e
r
en
t
s
tr
ateg
ies,
s
u
ch
as
d
ef
lectio
n
r
o
u
tin
g
,
s
eg
m
en
tatio
n
b
ase
d
r
o
p
p
in
g
f
ib
er
d
elay
lin
e,
an
d
wa
v
elen
g
th
co
n
v
er
ter
s
s
ch
em
es,
ca
n
b
e
u
s
ed
to
s
o
lv
e
th
is
p
r
o
b
lem
.
A
co
m
p
ar
is
o
n
o
f
th
e
p
er
f
o
r
m
an
ce
o
f
f
ib
e
r
d
elay
lin
es,
d
ef
le
ctio
n
r
o
u
ti
n
g
,
a
n
d
s
eg
m
e
n
tatio
n
-
b
ased
d
r
o
p
p
in
g
s
ch
em
es
ar
e
d
escr
ib
ed
in
th
is
s
tu
d
y
.
All
in
p
u
t
an
d
o
u
tp
u
t
n
etwo
r
k
p
ar
a
m
eter
v
alu
es
ar
e
an
aly
ze
d
f
o
r
p
er
f
o
r
m
an
ce
.
T
h
e
r
esu
lts
s
u
g
g
est th
at
f
ib
er
d
elay
lin
es a
r
e
m
o
r
e
ef
f
ec
tiv
e
at
r
eso
lv
in
g
co
n
t
en
tio
n
.
RE
F
E
R
E
NC
E
S
[
1
]
M
.
K
.
D
u
t
t
a
,
“
P
e
r
f
o
r
m
a
n
c
e
A
n
a
l
y
s
i
s
o
f
D
e
f
l
e
c
t
i
o
n
R
o
u
t
i
n
g
a
n
d
S
e
g
m
e
n
t
a
t
i
o
n
D
r
o
p
p
i
n
g
S
c
h
e
m
e
i
n
O
p
t
i
c
a
l
B
u
r
s
t
S
w
i
t
c
h
i
n
g
(
O
B
S
)
N
e
t
w
o
r
k
:
A
S
i
m
u
l
a
t
i
o
n
S
t
u
d
y
,
”
i
n
A
d
v
a
n
c
e
s
i
n
I
n
t
e
l
l
i
g
e
n
t
S
y
st
e
m
s
a
n
d
C
o
m
p
u
t
i
n
g
,
v
o
l
.
9
8
8
,
p
p
.
1
1
9
–
128
,
2
0
2
0
,
.
[
2
]
G.
R
.
K
a
v
i
t
h
a
n
d
T.
S
.
I
n
d
u
m
a
t
h
i
,
“
N
o
v
e
l
R
O
A
D
M
m
o
d
e
l
l
i
n
g
w
i
t
h
W
S
S
a
n
d
O
B
S
t
o
I
mp
r
o
v
e
R
o
u
t
i
n
g
P
e
r
f
o
r
man
c
e
i
n
O
p
t
i
c
a
l
N
e
t
w
o
r
k
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
t
ri
c
a
l
a
n
d
C
o
m
p
u
t
e
r
En
g
i
n
e
e
r
i
n
g
(
I
J
EC
E)
,
v
o
l
.
6
,
n
o
.
2
,
p
.
6
6
6
,
A
p
r
.
2
0
1
6
,
d
o
i
:
1
0
.
1
1
5
9
1
/
i
j
e
c
e
.
v
6
i
2
.
p
p
6
6
6
-
6
7
3
.
[
3
]
H
.
A
.
M
.
H
a
r
b
,
W
.
M
.
G
a
b
a
l
l
a
h
,
A
.
S
.
S
a
mr
a
,
A
.
A
b
o
-
T
a
l
e
b
,
a
n
d
A
.
M
a
r
w
a
n
t
o
,
“
A
st
u
d
y
o
f
t
h
e
n
u
m
b
e
r
o
f
w
a
v
e
l
e
n
g
t
h
s
i
m
p
a
c
t
i
n
t
h
e
o
p
t
i
c
a
l
b
u
r
st
sw
i
t
c
h
i
n
g
c
o
r
e
n
o
d
e
,
”
i
n
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
El
e
c
t
ri
c
a
l
En
g
i
n
e
e
ri
n
g
,
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
a
n
d
I
n
f
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g
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e
e
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rn
e
d
with
first
c
las
s
h
o
n
o
u
rs
a
t
S
u
d
a
n
Un
iv
e
rsity
o
f
S
c
ien
c
e
a
n
d
Tec
h
n
o
l
o
g
y
.
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h
a
s
o
v
e
r
a
d
e
c
a
d
e
o
f
h
i
g
h
e
r
e
d
u
c
a
ti
o
n
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h
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g
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f
ield
o
f
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m
m
u
n
ica
ti
o
n
E
n
g
i
n
e
e
rin
g
.
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is
a
n
a
ss
o
c
iate
p
ro
fe
ss
o
r
a
t
th
e
F
u
tu
re
Un
iv
e
rsity
,
F
a
c
u
lt
y
o
f
Tele
c
o
m
m
u
n
ica
ti
o
n
a
n
d
S
p
a
c
e
.
His
re
se
a
rc
h
in
tere
st
fo
c
u
se
s
o
n
W
irele
ss
a
n
d
M
o
b
il
e
Co
m
m
u
n
ica
ti
o
n
,
Visib
le
Li
g
h
t
Co
m
m
u
n
ica
ti
o
n
a
n
d
S
o
ftwa
re
De
fin
e
Ne
two
rk
.
H
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
Ib
ra
h
im_
k
h
i
d
e
r@h
o
tma
il
.
c
o
m
.
Dr
.
Mo
h
a
m
m
e
d
Al
-
S
h
a
r
g
a
b
i
re
c
e
iv
e
d
h
is
P
h
D
i
n
C
o
m
p
u
ter
Ne
two
rk
s
fro
m
Un
iv
e
rsity
Tec
h
n
o
l
o
g
y
M
a
lay
sia
,
M
a
lay
sia
.
His
M
a
ste
r’s
d
e
g
re
e
e
a
rn
e
d
fr
o
m
M
u
lt
ime
d
ia
Un
iv
e
rsity
,
M
a
lay
sia
.
He
h
a
s
o
v
e
r
a
d
e
c
a
d
e
o
f
h
ig
h
e
r
e
d
u
c
a
ti
o
n
tea
c
h
in
g
e
x
p
e
rien
c
e
i
n
t
h
e
field
o
f
Co
m
p
u
ter
Ne
two
rk
s.
Hi
s
re
se
a
r
c
h
in
tere
st
fo
c
u
se
s
o
n
Qu
a
li
ty
o
f
S
e
rv
ice
,
Ne
two
r
k
S
e
c
u
rit
y
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
o
h
a
m
m
e
d
2
1
8
@
y
a
h
o
o
.
c
o
m
.
Dr
.
Adel
S
a
ll
a
m
M
o
h
a
m
e
d
H
a
i
d
e
r
re
c
e
iv
e
d
h
is
B.
S
c
.
a
n
d
M
.
S
c
.
in
C
o
m
p
u
ter
En
g
i
n
e
e
rin
g
Kh
a
rk
o
v
P
o
l
y
tec
h
n
i
c
In
stit
u
te,
Uk
ra
in
e
.
His
P
h
D
in
Tec
h
n
ica
l
S
c
ien
c
e
s,
S
a
i
n
t
P
e
ters
b
u
rg
S
tate
El
e
c
tro
Tec
h
n
ica
l
Un
iv
e
rsity
(L
ET
I),
R
u
ss
ia.
F
ield
o
f
S
p
e
c
ializa
ti
o
n
:
In
fo
rm
a
ti
o
n
Tec
h
n
o
l
o
g
y
-
Artifi
c
ia
l
in
te
ll
i
g
e
n
c
e
.
P
r
o
fe
ss
o
r
in
I
n
f
o
r
m
a
ti
o
n
Tec
h
n
o
l
o
g
y
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
h
a
id
e
r.
a
d
e
l
@g
m
a
il
.
c
o
m
.
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