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tes
t
t
h
e
m
o
d
el
o
f
s
ec
o
n
d
ar
y
d
ata
o
b
tain
ed
f
r
o
m
o
n
e
o
f
th
e
lo
ca
l ser
v
er
i
n
P
ale
m
b
an
g
,
w
h
er
e
d
ata
u
s
ed
co
n
s
i
s
ted
o
f
m
ail,
f
ile
an
d
I
P
ca
m
er
a
tr
af
f
ic
d
ata.
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
T
h
is
s
ec
tio
n
ex
p
lai
n
s
ab
o
u
t
th
e
m
o
d
el
d
e
v
elo
p
b
y
ap
p
l
y
i
n
g
B
E
R
Qo
S
attr
ib
u
te,
alo
n
g
w
it
h
t
h
e
p
ar
am
eter
s
an
d
v
ar
iab
les d
e
f
in
ed
.
3
.
1
.
M
o
dified
M
o
dels
In
t
h
e
m
o
d
i
f
ied
m
o
d
el,
t
h
e
m
o
d
el
d
ev
elo
p
ed
b
y
co
m
b
i
n
i
n
g
w
ith
t
h
e
n
e
t
w
o
r
k
m
o
d
el
in
m
u
lti
s
er
v
ice
n
et
w
o
r
k
b
y
ad
d
in
g
p
ar
a
m
eter
s
,
v
ar
iab
le
d
ec
is
io
n
s
a
n
d
co
n
s
tr
ain
t
s
o
f
ea
ch
m
o
d
el
a
n
d
s
ettin
g
b
ase
p
r
ice
(
α
)
an
d
p
r
em
iu
m
q
u
ali
t
y
(
β
)
.
w
ir
e
less
i
n
ter
n
et
f
i
n
an
c
in
g
s
c
h
e
m
e
s
o
n
th
e
m
o
d
if
ied
m
o
d
el
f
o
r
Qo
S
attr
ib
u
te
B
E
R
is
d
iv
id
ed
in
to
f
o
u
r
(
4
)
ca
s
es b
ased
o
n
th
e
v
a
lu
e
o
f
t
h
e
m
o
d
el
m
o
d
if
icatio
n
,
d
an
.
P
ar
am
eter
s
u
s
ed
in
t
h
e
m
o
d
i
f
i
ed
m
o
d
els ar
e
as
f
o
llo
w
s
.
: Fu
n
ctio
n
o
f
r
ev
en
u
e
:
C
o
s
t to
co
n
n
ec
t
w
i
th
a
v
ailab
l
e
Qo
S
:
C
o
s
t c
h
a
n
g
es a
lo
n
g
w
it
h
Qo
S c
h
a
n
g
e
: A
n
i
n
cr
ea
s
e
o
r
d
ec
r
ea
s
e
o
n
Qo
S v
alu
e
: N
o
m
in
a
l v
al
u
e
o
f
Qo
S a
ttrib
u
tes i
n
o
p
er
ato
r
n
et
w
o
r
k
:
B
ase
v
alu
e
f
o
r
a
co
n
n
ec
tio
n
i
n
s
er
v
ice
i
an
d
lin
k
k
: L
i
n
ea
r
it
y
f
ac
to
r
:
L
i
n
ea
r
co
s
t f
ac
to
r
in
s
er
v
ice
i
an
d
lin
k
k
: T
r
af
f
ic
lo
ad
: P
r
ed
eter
m
in
ed
li
n
ea
r
p
ar
a
m
e
ter
: P
r
ed
eter
m
in
ed
li
n
ea
r
p
ar
a
m
e
ter
: M
in
i
m
u
m
v
al
u
e
s
et
b
y
s
er
v
ic
e
p
r
o
v
id
er
f
o
r
: M
ax
i
m
u
m
v
al
u
e
s
et
b
y
s
er
v
i
ce
p
r
o
v
id
er
f
o
r
:
Nu
m
b
er
o
f
m
i
n
i
m
u
m
tr
a
f
f
ic
l
o
ad
allo
w
ab
le
f
o
r
: N
u
m
b
er
o
f
m
a
x
i
m
u
m
tr
a
f
f
ic
lo
ad
allo
w
ab
le
f
o
r
:
Qu
alit
y
i
n
d
ex
f
o
r
s
er
v
ice
i
:
P
r
ice
f
o
r
u
s
er
o
f
s
er
v
ice
i
i
n
l
in
k
k
:
Nu
m
b
er
o
f
u
s
er
s
i
n
s
er
v
ice
i
in
li
n
k
k
:
C
ap
ac
it
y
n
ee
d
ed
f
o
r
s
er
v
ice
i
in
lin
k
k
:
T
o
tal
ca
p
ac
ity
i
n
li
n
k
k
:
T
o
tal
ca
p
ac
ity
o
f
i
in
li
n
k
k
:
Qo
S
m
i
n
i
m
u
m
f
o
r
s
er
v
ice
i
:
Nu
m
b
er
o
f
u
s
er
s
i
n
s
er
v
ice
i
:
Min
i
m
u
m
q
u
alit
y
p
r
e
m
i
u
m
f
o
r
s
er
v
ice
i
: M
ax
i
m
u
m
k
u
a
litas
p
r
e
m
iu
m
u
n
t
u
k
la
y
a
n
a
n
i
y
: M
in
i
m
u
m
b
ase
p
r
ice
f
o
r
s
er
v
ice
i
z
: M
ax
i
m
u
m
b
ase
p
r
ice
f
o
r
s
er
v
ice
i
T
h
er
e
ar
e
f
o
u
r
ca
s
es
w
h
ic
h
ar
e
th
e
ca
s
e
o
f
α
an
d
β
as
p
ar
am
eter
s
,
as
th
e
ca
s
e
α
an
d
β
p
ar
a
m
eter
an
d
v
ar
iab
les,
ca
s
e
α
an
d
β
as v
ar
iab
les a
n
d
ca
s
e
v
ar
iab
les
α
an
d
β
as p
ar
a
m
eter
.
3
.
1
.
1
.
M
o
dified
M
o
del f
o
r
a
nd
P
a
ra
m
et
er
o
f
B
E
R
Q
o
S At
t
rib
ute
W
ir
eless
p
r
icin
g
s
c
h
e
m
e
m
o
d
el
o
f
m
o
d
if
ied
ca
s
e
o
f
α
a
n
d
β
s
eb
ag
ai
p
ar
a
m
eter
,
t
h
e
n
t
h
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
w
ill b
e
as
:
∑
∑
(
(
)
)
(
1)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
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8708
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239
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30
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B
y
m
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y
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ai
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3
2
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ased
o
n
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tiv
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u
n
c
tio
n
(
1
)
an
d
E
q
u
atio
n
(
2
)
to
E
q
u
ati
o
n
(
32
)
,
th
e
o
p
ti
m
al
s
o
lu
tio
n
f
o
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ch
ca
s
e
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ased
o
n
B
E
R
Qo
S
attr
ib
u
te
w
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l b
e
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g
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I
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1
1
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T
ab
le
1
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Op
tim
al
So
l
u
tio
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o
f
Mo
d
if
ied
Mo
d
el
o
f
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ir
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I
n
ter
n
et
P
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g
Sc
h
e
m
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o
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B
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S
A
ttrib
u
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f
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r
an
d
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eter
V
a
r
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a
b
l
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s
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c
r
e
a
se
i
n
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a
se
i
n
c
r
e
a
se
d
e
c
r
e
a
se
d
e
c
r
e
a
se
i
n
c
r
e
a
se
d
e
c
r
e
a
se
d
e
c
r
e
a
se
M
o
d
e
l
C
l
a
ss
I
N
L
P
I
N
L
P
I
N
L
P
I
N
L
P
S
t
a
t
e
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o
c
a
l
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p
t
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a
l
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c
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c
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b
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t
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5
.
6
4
1
9
2
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1
0
8
9
8
.
7
5
8
7
6
7
.
7
5
7
6
6
9
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2
3
3
8
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n
f
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b
i
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i
t
y
0
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5
.
8
2
x
1
0
11
I
t
e
r
a
t
i
o
n
s
14
21
12
13
G
M
U
32K
32K
32K
32K
ER
0s
0s
0s
0s
B
ased
o
n
T
ab
le
1
,
th
e
v
al
u
e
w
il
l
ac
h
iev
e
t
h
e
m
o
s
t
o
p
ti
m
al
r
esu
lt
s
i
n
th
e
f
ir
s
t
ca
s
e
w
h
ic
h
is
eq
u
al
to
5
.
6
4
1
9
2
x
1
0
8
.
T
h
ese
r
esu
l
ts
w
il
l
b
e
o
b
tain
ed
b
y
iter
ati
n
g
1
4
iter
atio
n
s
o
f
t
h
e
i
n
f
ea
s
ib
ili
t
y
o
f
0
.
Ge
n
er
ated
Me
m
o
r
y
Used
(
GM
U)
t
is
3
2
K
an
d
E
lap
s
ed
R
u
n
ti
m
e
(
E
R
)
i
s
0
s
ec
o
n
d
s
.
B
ased
o
n
T
ab
le
2
it
ca
n
b
e
s
ee
n
t
h
at
t
h
e
v
a
lu
e
s
o
f
v
ar
iab
les
f
o
r
ca
s
e
1
is
v
er
y
b
i
g
,
f
o
r
ca
s
e
2
an
d
3
is
q
u
ite
b
ig
,
w
h
i
le
in
f
o
u
r
ca
s
e
4
th
e
v
alu
es
o
f
v
ar
iab
les
is
0
.
I
n
ca
s
e
1
th
e
v
alu
e
o
f
x
is
1
,
w
h
er
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s
i
n
ca
s
es
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d
3
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e
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al
u
e
o
f
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ala
h
0
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in
ca
s
e
4
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h
e
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al
u
e
o
f
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i
s
10
-
7
o
r
clo
s
e
to
0
.
Valu
e
o
f
f
o
r
ca
s
e
1
an
d
2
is
d
if
f
er
e
n
t
b
u
t
n
o
t
m
u
c
h
d
if
f
er
e
n
t
w
h
er
ea
s
t
h
e
v
al
u
e
o
f
f
o
r
c
ases
3
a
n
d
4
ap
p
r
o
ac
h
es
0
an
d
q
u
ite
d
if
f
er
en
t
f
r
o
m
t
h
e
v
al
u
e
o
f
in
ca
s
e
1
an
d
2
.
Valu
es
o
f
in
ca
s
e
1
is
2
.
3
7
5
2
7
3
w
h
ile
i
n
ca
s
es
1
,
2
an
d
3
,
th
e
ca
s
es
h
av
e
v
ar
iab
le
th
e
s
a
m
e
v
al
u
es
o
f
.
Valu
e
o
f
ai
k
i
n
ca
s
e
1
an
d
3
is
th
e
s
a
m
e
o
n
e,
n
o
t
m
u
c
h
d
if
f
er
en
t
f
r
o
m
th
e
ca
s
e
2
an
d
ca
s
e
4
in
w
h
ic
h
ca
s
e
2
an
d
4
h
av
e
th
e
v
al
u
es
o
f
th
e
s
a
m
e
v
ar
iab
le
.
T
ab
le
2
.
Valu
e
o
f
Dec
is
io
n
Va
r
iab
les in
Mo
d
if
ied
Mo
d
el
f
o
r
B
E
R
Qo
S A
ttrib
u
te
f
o
r
an
d
Par
a
m
eter
V
a
r
i
a
b
l
e
s
i
n
c
r
e
a
se
i
n
c
r
e
a
se
i
n
c
r
e
a
se
d
e
c
r
e
a
se
d
e
c
r
e
a
se
i
n
c
r
e
a
se
d
e
c
r
e
a
se
d
e
c
r
e
a
se
PQ
11
2
.
9
0
5
7
3
8
2
.
9
0
2
8
3
3
0
.
0
7
5
4
0
7
0
.
0
7
5
4
0
7
PQ
21
0
.
6
0
0
0
0
0
7
.
8
9
4
7
4
3
0
.
2
0
6
6
7
4
0
.
2
0
6
6
7
4
PQ
31
4
5
.
6
3
9
0
6
4
9
.
5
9
3
4
5
1
.
1
9
4
1
6
4
1
.
1
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
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m
p
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,
Vo
l.
8
,
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1
,
Feb
r
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2
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8
:
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6
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N:
2
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4
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
1
,
Feb
r
u
ar
y
2
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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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2
0
1
6
.
RE
F
E
R
E
NC
E
S
[1
]
E.
R.
W
a
ll
e
n
iu
s
,
“
Co
n
tro
l
a
n
d
M
a
n
a
g
e
m
e
n
t
o
f
M
u
lt
i
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A
c
c
e
ss
W
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re
les
s
Ne
t
w
o
rk
,
”
in
M
a
th
e
ma
ti
c
a
l
In
f
o
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
.
2
0
0
5
,
Un
iv
e
rsit
y
o
f
J
y
v
a
s
k
y
l
a
:
J
y
v
a
sk
y
la.
[2
]
J.
Re
z
a
z
a
d
e
h
,
e
t
a
l
.
,
“
F
u
n
d
a
me
n
t
a
l
M
e
trics
fo
r
W
ire
les
s
S
e
n
s
o
r
N
e
two
rk
s
lo
c
a
li
z
a
ti
o
n
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
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e
rin
g
(
IJ
ECE
)
2
0
1
2
,
2
(4
):
p
.
4
5
2
-
4
5
5
.
[3
]
S.
Su
a
n
d
S
.
W
a
n
g
,
“
A
si
m
p
le
m
o
n
it
o
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g
n
e
tw
o
rk
s
y
ste
m
o
f
W
irele
ss
S
e
n
so
r
Ne
t
w
o
rk
”,
Bu
let
in
T
e
k
n
ik
El
e
k
tr
o
d
a
n
In
f
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rm
a
ti
k
a
(
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ll
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ti
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o
f
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e
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trica
l
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g
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e
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g
a
n
d
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f
o
rm
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ti
c
s)
2
0
1
2
,
1
(
4
):
p
.
2
5
1
-
2
5
4
.
[4
]
X
.
Ya
n
,
e
t
a
l.
,
“
A
W
irele
s
s
S
e
n
so
r
Ne
tw
o
rk
in
P
re
c
isio
n
A
g
ricu
lt
u
re
,”
T
EL
KOM
NIKA
(
T
e
lec
o
mm
u
n
ica
t
io
n
Co
mp
u
t
in
g
El
e
c
tro
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ics
a
n
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o
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l
)
,
2
0
1
2
,
1
0
(4
):
p
.
7
8
8
-
7
9
7
.
[5
]
W
.
Ya
n
g
,
e
t
a
l.
,
“
De
ter
min
in
g
Diff
e
re
n
ti
a
ted
S
e
rv
ice
s
Ne
two
rk
Pricin
g
T
h
ro
u
g
h
A
u
c
ti
o
n
s
,”
in
Ne
tw
o
rk
in
g
-
ICN
2
0
0
5
,
4
th
I
n
tern
a
ti
o
n
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l
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e
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g
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2
0
0
5
P
r
o
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e
d
in
g
s,
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a
rt
I
.
2
0
0
5
.
Re
u
n
io
n
Isla
n
d
,
F
ra
n
c
e
:
S
p
rin
g
e
r
-
V
e
rlag
Be
rli
n
He
id
e
lb
e
r
g
.
[6
]
F
.
M
.
P
u
sp
it
a
,
e
t
a
l.
,
“
Im
p
ro
v
e
d
M
o
d
e
ls
o
f
In
tern
e
t
C
h
a
rg
in
g
S
c
h
e
m
e
o
f
S
in
g
le
Bo
tt
len
e
c
k
L
in
k
in
M
u
lt
i
Qo
S
Ne
tw
o
rk
s
,”
J
o
u
rn
a
l
o
f
Ap
p
li
e
d
S
c
ien
c
e
s
,
2
0
1
3
.
1
3
(4
):
p
.
5
7
2
-
5
7
9
.
[7
]
F
.
M
.
P
u
sp
it
a
,
e
t
a
l.
,
“
T
h
e
I
m
p
ro
v
e
d
M
o
d
e
ls
o
f
In
tern
e
t
P
ricin
g
S
c
h
e
m
e
o
f
M
u
lt
i
S
e
rv
ice
M
u
lt
i
L
in
k
Ne
tw
o
rk
s
w
it
h
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a
rio
u
s Ca
p
a
c
it
y
L
in
k
s,
”
in
Ad
v
a
n
c
e
d
Co
mp
u
ter
a
n
d
Co
mm
u
n
ica
ti
o
n
E
n
g
in
e
e
rin
g
T
e
c
h
n
o
l
o
g
y
.
[8
]
H.A
.
S
u
laim
a
n
,
e
t
a
l.
,
Ed
it
o
rs.
2
0
1
5
,
S
p
ri
n
g
e
r
In
tern
a
ti
o
n
a
l
P
u
b
li
sh
in
g
:
S
w
it
z
e
lan
d
.
[9
]
E.
S
a
f
a
ri,
e
t
a
l.
,
“
De
ter
m
in
in
g
stra
teg
y
o
f
p
ricin
g
f
o
r
a
w
e
b
s
e
rv
ic
e
w
it
h
d
iff
e
re
n
t
Qo
S
lev
e
l
s
a
n
d
re
se
rv
a
ti
o
n
lev
e
l
c
o
n
stra
in
t
,”
Ap
p
li
e
d
M
a
th
e
ma
ti
c
a
l
M
o
d
e
ll
i
n
g
,
2
0
1
4
.
[1
0
]
N.M
.
A
d
rian
sy
a
h
,
e
t
a
l.
,
“
M
o
d
if
ied
G
re
e
d
y
P
h
y
sic
a
l
L
in
k
S
c
h
e
d
u
li
n
g
A
lg
o
rit
h
m
f
o
r
I
m
p
ro
v
in
g
W
irele
ss
M
e
sh
Ne
tw
o
rk
P
e
rf
o
rm
a
n
c
e
,”
T
EL
KOM
NIKA
(
T
e
le
c
o
mm
u
n
ica
ti
o
n
Co
mp
u
ti
n
g
El
e
c
tro
n
ics
a
n
d
Co
n
tro
l
)
,
2
0
1
5
.
1
3
(
1
):
p
.
202
-
2
1
0
.
[1
1
]
J.
L
i,
a
n
d
X.
T
ian
,
“
A
p
p
li
c
a
ti
o
n
o
f
A
n
t
Co
lo
n
y
A
l
g
o
rit
h
m
in
M
u
lt
i
-
o
b
jec
ti
v
e
Op
ti
m
iza
ti
o
n
P
r
o
b
lem
s
,”
T
EL
KOM
NIKA
(
T
e
lec
o
mm
u
n
ica
t
io
n
C
o
mp
u
ti
n
g
E
lec
tro
n
ics
a
n
d
C
o
n
tro
l
)
,
2
0
1
5
.
1
3
(3
):
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.
1
0
2
9
-
1
0
3
6
.
[1
2
]
Irm
e
il
y
a
n
a
,
e
t
a
l.
,
“
Op
ti
m
iza
ti
o
n
o
f
W
irele
ss
In
tern
e
t
P
rici
n
g
S
c
h
e
m
e
in
S
e
rv
in
g
M
u
lt
i
Qo
S
Ne
tw
o
rk
U
sin
g
V
a
rio
u
s Qo
S
A
tt
rib
u
tes
,”
T
E
L
KOM
NIKA
(
T
e
lec
o
mm
u
n
ica
ti
o
n
,
Co
mp
u
ti
n
g
,
El
e
c
tro
n
ics
a
n
d
C
o
n
tro
l
)
,
2
0
1
6
.
1
4
(
1
).
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
B
it E
r
r
o
r
R
a
te
(
B
E
R
)
Qo
S
A
ttr
ib
u
te
in
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o
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g
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ir
e
less
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r
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g
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ch
eme
o
n
S
in
g
le
Lin
k
…
(
I
r
meilya
n
a
)
245
[1
3
]
S
.
S
a
in
a
n
d
S
.
He
rp
e
rs,
“
Pro
fi
t
M
a
x
imisa
ti
o
n
in
M
u
lt
i
S
e
rv
ice
Ne
two
rk
s
-
An
Op
ti
misa
ti
o
n
M
o
d
e
l,
”
in
P
ro
c
e
e
d
in
g
s
o
f
th
e
1
1
th
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u
ro
p
e
a
n
C
o
n
f
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n
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e
o
n
I
n
f
o
rm
a
ti
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n
S
y
ste
m
s E
CIS
2
0
0
3
.
2
0
0
3
.
Na
p
les
,
Italy
[1
4
]
J.
By
u
n
a
n
d
S
.
C
h
a
tt
e
rjee
,
“
A
str
a
teg
ic
p
ric
i
n
g
fo
r
q
u
a
li
ty
o
f
se
rv
ice
(
Qo
S
)
n
e
two
rk
b
u
si
n
e
ss
,”
in
P
r
o
c
e
e
d
in
g
s
o
f
th
e
T
e
n
th
Am
e
rica
s Co
n
fe
re
n
c
e
o
n
In
f
o
rm
a
ti
o
n
S
y
ste
m
s
.
2
0
0
4
.
Ne
w
Yo
rk
.
[1
5
]
E.
W
a
ll
e
n
iu
s
a
n
d
T
.
Hä
m
ä
läin
e
n
,
“
Pricin
g
M
o
d
e
l
fo
r
3
G/4
G
Ne
two
rk
s
”
,
in
T
h
e
1
3
th
IEE
E
In
tern
a
ti
o
n
a
l
S
y
m
p
o
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m
o
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P
e
rso
n
a
l,
I
n
d
o
o
r
,
a
n
d
M
o
b
i
le Ra
d
io
Co
m
m
u
n
ica
ti
o
n
s
.
2
0
0
2
:
L
isb
o
n
,
P
o
rt
u
g
a
l.
B
I
O
G
RAP
H
I
E
S
O
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AUTH
O
RS
Ir
m
e
il
y
a
n
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i
(Un
d
e
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ra
d
u
a
te
De
g
re
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in
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c
ien
c
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)
in
M
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m
a
ti
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s
f
ro
m
Bo
g
o
r
Ag
ricu
lt
u
re
In
st
it
u
te
(I
P
B)
In
d
o
n
e
sia
in
1
9
9
7
.
T
h
e
n
sh
e
re
c
e
iv
e
d
h
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r
M
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ste
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D
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g
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th
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m
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f
ro
m
Ba
n
d
u
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g
T
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n
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lo
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s
t
it
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te
(IT
B)
In
d
o
n
e
sia
in
1
9
9
9
.
S
h
e
h
a
s
b
e
e
n
a
M
a
th
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m
a
ti
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s
De
p
a
rtme
n
t
m
e
m
b
e
r
a
t
F
a
c
u
lt
y
M
a
th
e
m
a
ti
c
s
a
n
d
Na
tu
ra
l
S
c
ien
c
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s
S
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a
y
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Un
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rsit
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S
o
u
th
S
u
m
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tera
In
d
o
n
e
sia
sin
c
e
1
9
9
9
.
He
r
re
se
a
r
c
h
in
tere
sts
in
c
lu
d
e
S
tatisti
c
s,
o
p
t
im
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ti
o
n
a
n
d
it
s
a
p
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c
a
ti
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s.
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tr
i
M
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sp
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d
h
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r
S
.
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i
d
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g
re
e
in
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fro
m
S
ri
w
ij
a
y
a
Un
iv
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rsit
y
,
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o
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th
S
u
m
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tera
,
In
d
o
n
e
sia
in
1
9
9
7
.
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h
e
n
sh
e
re
c
e
iv
e
d
h
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r
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S
c
in
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t
h
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s
f
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m
Cu
rti
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Un
iv
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rsity
o
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T
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h
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lo
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T
)
Wes
tern
Au
stra
li
a
in
2
0
0
4
.
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h
e
g
ra
d
u
a
te
d
f
ro
m
F
a
c
u
lt
y
o
f
S
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c
e
a
n
d
T
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c
h
n
o
lo
g
y
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m
i
c
S
c
ien
c
e
Un
i
v
e
rsit
y
o
f
M
a
la
y
si
a
(USIM
),
Nila
i,
Ne
g
e
ri
S
e
m
b
il
a
n
Da
ru
l
Kh
u
su
s
,
M
a
la
y
sia
in
2
0
1
5
.
S
h
e
h
a
s
b
e
e
n
a
M
a
th
e
m
a
ti
c
s
De
p
a
rt
m
e
n
t
m
e
m
b
e
r
a
t
F
a
c
u
lt
y
m
a
th
e
m
a
ti
c
s
a
n
d
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tu
ra
l
S
c
ien
c
e
s
S
riw
ij
a
y
a
Un
iv
e
rsit
y
S
o
u
th
S
u
m
a
tera
In
d
o
n
e
sia
sin
c
e
1
9
9
8
.
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r
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
o
p
ti
m
iza
ti
o
n
a
n
d
it
s
a
p
p
li
c
a
ti
o
n
s
su
c
h
a
s
v
e
h
icle
ro
u
ti
n
g
p
ro
b
lem
s
a
n
d
Qo
S
p
rici
n
g
a
n
d
c
h
a
rg
i
n
g
in
th
ird
g
e
n
e
ra
ti
o
n
i
n
ter
n
e
t
.
Ind
r
a
w
a
ti
re
c
e
iv
e
d
h
e
r
re
c
e
iv
e
d
h
e
r
S
.
S
i
d
e
g
re
e
in
M
a
th
e
m
a
ti
c
s
fro
m
S
ri
w
ij
a
y
a
Un
iv
e
rsit
y
,
S
o
u
th
S
u
m
a
tera
,
In
d
o
n
e
sia
in
1
9
9
6
.
T
h
e
n
sh
e
re
c
e
iv
e
d
M
.
S
i
in
M
a
th
e
m
a
ti
c
s
Ac
tu
a
rial
f
ro
m
Ba
n
d
u
n
g
In
stit
u
te
o
f
T
e
c
h
n
o
l
o
g
y
,
In
d
o
n
e
s
ia
in
2
0
0
4
.
S
h
e
h
a
s
b
e
e
n
a
M
a
th
e
m
a
ti
c
s
De
p
a
rt
m
e
n
t
m
e
m
b
e
r
a
t
F
a
c
u
lt
y
m
a
th
e
m
a
ti
c
s
a
n
d
Na
tu
ra
l
S
c
ien
c
e
s
S
ri
w
ij
a
y
a
Un
iv
e
rsit
y
S
o
u
t
h
S
u
m
a
tera
In
d
o
n
e
sia
sin
c
e
1
9
9
8
.
He
r
re
se
a
rc
h
in
tere
st
in
c
l
u
d
e
s
a
c
tu
a
rial
sc
ien
c
e
a
n
d
it
s
a
p
p
li
c
a
ti
o
n
s
in
i
n
su
ra
n
c
e
a
n
d
ris
k
th
e
o
ry
.
Ra
h
a
y
u
T
a
m
y
Ag
u
sti
n
re
c
e
i
v
e
d
h
e
r
S
.
S
i
d
e
g
re
e
(Ba
c
h
e
lo
r
De
g
re
e
in
S
c
ien
c
e
)
in
M
a
th
e
m
a
ti
c
s
f
ro
m
S
riw
ij
a
y
a
Un
iv
e
rsit
y
,
S
o
u
th
S
u
m
a
ter
a
,
In
d
o
n
e
sia
in
2
0
1
6
.
He
r
re
s
e
a
rc
h
in
tere
st
in
c
lu
d
e
s
Op
ti
m
iza
ti
o
n
,
a
n
d
it
s ap
p
li
c
a
ti
o
n
o
n
i
n
tern
e
t
c
h
a
rg
in
g
sc
h
e
m
e
in
w
i
re
les
s n
e
tw
o
rk
.
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