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[
1
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A
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ty
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[
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Gm
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Ma
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as Saa
S
[
3
]
.
On
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Go
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tag
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to
clie
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to
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s
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4
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.
Ultim
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[
5
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,
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6
]
.
R
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tech
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[
7
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Acc
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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1243
p
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[
8
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[
9
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h
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n
b
e
p
ar
titi
o
n
ed
in
to
th
r
ee
class
es
in
lig
h
t
o
f
t
h
e
I
aa
S,
SaaS,
an
d
PaaS
class
if
icatio
n
s
[
1
0
]
.
A
wh
ile
later
,
th
e
h
o
m
o
g
en
o
u
s
u
n
d
e
r
tak
in
g
s
ca
n
b
e
s
h
i
p
p
ed
o
f
f
th
e
s
u
itab
le
h
elp
class
if
icatio
n
b
u
n
ch
es
in
th
e
ac
co
m
p
an
y
in
g
lay
er
.
T
h
e
clu
s
ter
s
ch
ed
u
lin
g
alg
o
r
ith
m
(
C
SA)
ca
n
allo
ca
te
h
o
m
o
g
e
n
o
u
s
r
esp
o
n
s
ib
ilit
ies
t
o
s
u
itab
le
b
u
n
ch
es
[
1
1
]
i
n
th
e
s
u
b
s
eq
u
e
n
t
lay
er
,
wh
ich
is
allu
d
ed
t
o
a
s
th
e
clu
s
ter
s
elec
tio
n
(
C
S)
la
y
er
,
t
o
wo
r
k
o
n
th
e
f
r
am
ewo
r
k
’
s
u
n
wa
v
er
in
g
q
u
a
lity
.
Als
o
,
th
is
lay
er
ca
n
b
r
in
g
d
o
wn
th
e
ex
p
en
s
e
an
d
c
u
l
m
in
atio
n
s
ea
s
o
n
o
f
er
r
an
d
b
o
o
k
in
g
.
T
h
e
th
ir
d
lay
er
,
clien
t
s
o
u
r
ce
n
o
d
e
s
am
p
lin
g
(
SNS),
is
liab
le
f
o
r
d
is
p
atch
in
g
r
e
s
p
o
n
s
ib
ilit
ies
to
s
u
p
p
o
r
t
h
u
b
s
.
Ad
v
an
ce
d
cl
u
s
ter
in
g
s
u
f
f
r
a
g
e
s
ch
ed
u
le
r
(
AC
SS
)
at
a
h
ig
h
lev
el
is
p
r
esen
ted
h
er
e
to
f
u
r
th
er
d
ev
elo
p
ass
et
u
tili
za
tio
n
an
d
a
cc
o
m
p
lis
h
lo
ad
a
d
ju
s
tin
g
.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
Fo
r
d
if
f
er
en
t
a
p
p
licatio
n
c
o
n
d
itio
n
s
,
n
u
m
er
o
u
s
b
o
o
k
i
n
g
s
tr
ateg
ies
h
av
e
b
ee
n
i
n
tr
o
d
u
ce
d
.
Sh
o
jaf
ar
et
a
l.
[
1
2
]
,
f
o
r
in
s
tan
ce
,
p
r
o
p
o
s
es
an
en
er
g
y
-
ef
f
ec
tiv
e
v
er
s
atile
ass
et
s
ch
ed
u
ler
d
esig
n
f
o
r
o
f
f
er
in
g
co
n
tin
u
o
u
s
clo
u
d
ad
m
in
is
tr
atio
n
s
to
v
eh
icu
lar
clien
ts
.
T
h
e
p
r
o
p
o
s
ed
co
n
v
e
n
tio
n
’
s
k
e
y
co
m
m
itm
en
t
is
to
am
p
lify
b
y
a
n
d
lar
g
e
co
r
r
esp
o
n
d
en
ce
in
a
d
d
itio
n
to
p
r
o
ce
s
s
in
g
en
er
g
y
p
r
o
d
u
ctiv
ity
wh
il
e
lik
ewise
m
ee
tin
g
ap
p
licatio
n
-
ac
tu
ated
r
i
g
id
q
u
ality
o
f
s
er
v
ices
(
Qo
S)
d
em
an
d
s
m
in
im
u
m
tr
an
s
f
er
r
ates
,
m
ax
im
u
m
d
elay
,
in
clu
d
in
g
d
elay
b
u
tter
f
lies
[
1
3
]
.
Sh
o
jaf
ar
et
a
l.
[
1
3
]
p
r
esen
t
a
jo
in
t
p
r
o
ce
s
s
in
g
in
ad
d
itio
n
to
co
r
r
esp
o
n
d
en
ce
s
tr
ea
m
lin
in
g
s
y
s
tem
th
at
u
tili
ze
s
v
ir
tu
aliza
tio
n
in
n
o
v
atio
n
s
to
g
iv
e
clien
ts
Qo
S,
b
o
o
s
t
en
er
g
y
r
eser
v
e
f
u
n
d
s
,
an
d
m
ee
t
g
r
ee
n
d
is
tr
ib
u
ted
co
m
p
u
tin
g
o
b
jectiv
es
in
a
to
tally
d
is
p
er
s
ed
way
.
As
a
g
en
er
al
r
u
le,
th
ese
p
r
o
p
o
s
ed
ca
lcu
latio
n
s
an
d
d
esig
n
s
ca
n
h
elp
with
th
e
ex
h
a
u
s
tiv
e
r
ec
o
n
s
id
er
in
g
o
f
b
o
o
k
in
g
ca
lcu
latio
n
p
lan
.
T
h
e
co
n
tin
u
o
u
s
k
i
n
d
an
d
th
e
clu
m
p
ty
p
e
ar
e
th
e
two
k
in
d
s
o
f
p
lan
n
in
g
ca
lc
u
latio
n
s
th
at
ca
n
b
e
p
r
o
v
id
e
d
in
lig
h
t
o
f
th
e
b
o
o
k
i
n
g
tim
e
.
Fu
n
d
am
en
tally
,
c
o
n
ti
n
u
o
u
s
er
r
a
n
d
s
ar
e
d
o
led
o
u
t
t
o
clo
u
d
s
er
v
er
h
u
b
s
wh
en
th
e
y
a
r
e
g
o
tten
.
I
n
th
e
b
u
n
ch
m
o
d
e,
th
en
ag
ain
,
g
o
t
er
r
an
d
s
a
r
e
c
o
llected
f
o
r
a
w
h
ile
p
r
io
r
to
b
ei
n
g
co
n
v
ey
e
d
to
clo
u
d
s
er
v
e
r
h
u
b
s
.
A
clu
s
ter
p
lan
n
in
g
ca
lcu
l
atio
n
ca
n
g
iv
e
im
p
r
o
v
ed
r
esu
lts
th
an
a
c
o
n
s
tan
t
b
o
o
k
in
g
a
p
p
r
o
ac
h
.
T
h
is
is
o
n
th
e
g
r
o
u
n
d
s
th
at
a
b
u
n
ch
-
b
ase
d
p
lan
n
in
g
ca
lcu
latio
n
ca
n
co
n
s
id
er
th
e
Miss
io
n
co
n
s
eq
u
en
ce
s
o
f
all
p
o
s
itio
n
s
[
1
3
]
,
[
1
4
]
.
T
o
s
en
d
th
e
p
r
o
ject
to
in
ter
n
et
s
er
v
er
s
’
h
u
b
in
s
id
e
th
e
d
is
tr
ib
u
ted
s
o
f
twar
e
clo
u
d
o
r
g
an
izatio
n
,
v
ar
io
u
s
b
o
o
k
in
g
ca
lcu
latio
n
s
[
1
5
]
,
[
1
6
]
h
av
e
b
ee
n
cr
ea
te
d
,
in
clu
d
in
g
th
e
m
i
n
im
u
m
,
m
ax
im
u
m
-
m
i
n
im
u
m
,
s
u
f
f
r
ag
e,
an
d
m
ax
im
u
m
s
u
f
f
r
a
g
e
ca
lcu
latio
n
s
[
1
5
]
,
[
1
7
]
,
[
1
8
]
.
No
twith
s
tan
d
in
g
,
s
u
ch
esti
m
ates
p
r
im
ar
ily
tak
e
in
to
ac
co
u
n
t
th
e
f
ac
to
r
o
f
es
tim
ated
co
n
s
u
m
p
tio
n
tim
e
(
E
C
T
)
an
d
d
is
r
eg
ar
d
th
e
s
er
v
er
h
u
b
’
s
h
ea
p
s
tate.
Acc
o
r
d
in
g
ly
,
th
e
e
x
h
ib
itio
n
m
is
s
es
th
e
m
ar
k
co
n
ce
r
n
i
n
g
ass
u
m
p
tio
n
s
,
a
n
d
th
e
i
n
s
ig
n
if
ican
t
f
r
u
itio
n
tim
e
ca
n
’
t
b
e
m
et.
T
h
e
ass
ig
n
m
en
t
h
as
t
h
e
lo
west
E
C
T
b
etwe
en
al
l
u
n
allo
ca
ted
d
u
ties
.
T
,
f
o
r
ex
am
p
le,
is
r
ef
er
r
ed
to
as
m
in
im
u
m
E
C
T
in
th
e
m
in
ca
lcu
latio
n
.
Fo
llo
win
g
th
at,
th
e
o
cc
u
p
atio
n
with
th
e
least
E
C
T
ca
n
b
e
p
ick
ed
an
d
d
is
p
atch
ed
to
th
e
s
u
itab
le
wai
ter
h
u
b
.
T
h
e
r
ec
e
n
tly
p
air
e
d
wo
r
k
is
th
e
n
r
e
m
o
v
ed
o
u
t
o
f
a
d
esig
n
ated
T
,
a
n
d
p
r
ac
tice
co
n
tin
u
es
till
all
th
e
u
n
d
er
tak
i
n
g
s
h
a
v
e
b
ee
n
s
en
t.
I
n
th
is
p
r
esen
t
cir
cu
m
s
tan
ce
,
t
h
e
r
esp
o
n
s
ib
ilit
y
is
p
r
o
b
a
b
ly
g
o
in
g
t
o
en
d
u
p
b
ei
n
g
u
n
eq
u
al
s
in
ce
th
e
r
e
ar
e
s
u
ch
a
lar
g
e
n
u
m
b
er
o
f
u
n
d
er
ta
k
in
g
s
th
at
s
h
o
u
l
d
b
e
p
lan
n
ed
.
T
h
e
E
C
T
is
lik
ewise
u
s
ed
f
o
r
wo
r
k
d
is
p
atch
in
g
in
t
h
e
m
a
x
im
u
m
-
m
in
im
u
m
ca
lcu
latio
n
.
I
n
t
h
e
m
ax
im
u
m
-
m
i
n
im
u
m
ca
lcu
lati
o
n
,
th
e
o
cc
u
p
atio
n
with
th
e
m
o
s
t
n
o
tewo
r
th
y
co
m
p
lete
E
C
T
is
co
n
s
tan
tly
r
eleg
ated
,
b
r
in
g
in
g
a
b
o
u
t
a
n
ex
ten
s
iv
e
ascen
t
in
g
en
er
ally
E
C
T
[
1
0
]
,
[
1
7
]
.
B
esid
es,
ea
c
h
o
f
th
e
p
r
ev
io
u
s
ly
m
en
tio
n
ed
m
eth
o
d
s
co
u
ld
wit
h
o
u
t
m
u
ch
o
f
a
s
tr
etch
o
u
tco
m
e
in
h
ig
h
e
r
-
lim
it
s
er
v
er
h
u
b
s
b
ein
g
d
o
led
o
u
t
ad
d
itio
n
al
p
o
s
itio
n
s
th
an
lo
we
r
-
lim
it
s
er
v
er
h
u
b
s
.
C
lo
u
d
s
er
v
er
h
u
b
r
esp
o
n
s
ib
ilit
ies
ar
e
l
o
p
s
id
ed
an
d
wastef
u
l.
T
h
u
s
,
th
e
S
u
f
f
er
a
g
e
ca
lcu
latio
n
[
1
5
]
,
[
1
7
]
was
p
r
o
p
o
s
ed
as
a
n
im
p
r
o
v
em
e
n
t
tech
n
iq
u
e
f
o
r
d
ec
r
ea
s
in
g
th
e
jo
b
s
o
f
clo
u
d
s
er
v
er
h
u
b
s
.
T
o
ass
ig
n
lab
o
r
,
o
v
e
r
all
s
u
f
f
r
ag
e
v
al
u
e
(
SV)
is
s
u
b
tr
ac
ted
f
r
o
m
th
e
p
r
im
ar
y
E
C
T
to
g
et
an
an
ticip
ated
v
alu
e
.
T
h
e
o
cc
u
p
atio
n
with
th
e
m
o
s
t
elev
ate
d
SV
wo
r
t
h
ca
n
th
e
n
b
e
p
ic
k
e
d
an
d
d
esp
atc
h
ed
to
th
e
clo
u
d
s
er
v
er
h
u
b
with
th
e
least
E
C
T
.
At
th
e
p
o
in
t
wh
en
t
h
e
q
u
an
tity
o
f
d
elay
i
n
g
ass
ig
n
m
en
ts
is
ex
tr
em
ely
p
er
f
ec
t,
b
e
th
at
as it m
ay
,
th
e
S
u
f
f
er
ag
e
ca
lcu
latio
n
ca
n
’
t a
c
co
m
p
lis
h
p
r
o
f
ic
ien
t e
x
ec
u
ti
o
n
.
Acc
o
r
d
in
g
ly
,
to
r
eso
lv
e
th
e
a
b
o
v
e
is
s
u
e,
th
e
Ma
x
Su
f
f
e
r
ag
e
tech
n
iq
u
e
[
3
]
,
[
1
8
]
,
[
1
9
]
,
w
h
ich
is
a
n
en
h
an
ce
m
e
n
t
f
o
r
th
e
Su
f
f
er
a
g
e
ca
lcu
latio
n
,
i
n
co
r
p
o
r
ates
t
h
r
ee
s
tag
es.
I
n
t
h
e
SVi
co
m
p
u
tatio
n
s
tag
e,
all
ass
ig
n
m
en
ts
’
SV
v
alu
es
s
h
o
u
ld
n
o
t
s
et
in
s
to
n
e.
I
n
th
e
MSV
i
ca
lcu
latio
n
s
tep
,
th
e
E
C
T
f
r
o
m
p
h
ase
I
th
at
h
as
th
e
s
ec
o
n
d
-
h
ig
h
est
SV
v
alu
e
will
b
e
ch
o
s
en
as
th
e
Ma
x
Su
f
f
er
an
ce
v
al
u
e
(
MSV)
esteem
.
I
n
th
e
f
in
al
p
h
ase,
ca
lled
th
e
m
is
s
io
n
d
is
p
atch
p
h
ase,
if
th
e
E
C
T
ij
o
f
s
er
v
e
r’s
h
u
b
j
is
n
o
t
p
r
ec
is
ely
MSVi,
th
e
h
ig
h
est
-
SV
jo
b
I
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
2
,
No
v
em
b
er
20
24
:
1
2
4
2
-
1
2
5
2
1244
m
ig
h
t
b
e
s
en
t
to
t
h
e
c
o
n
tr
asti
n
g
s
er
v
e
r
h
u
b
j.
Miss
io
n
I
with
th
e
m
o
s
t
n
o
tewo
r
th
y
E
C
T
ij
esteem
,
th
en
ag
ain
,
ca
n
b
e
s
h
ip
p
e
d
o
f
f
s
er
v
er
h
u
b
j.
Hu
g
e
u
n
d
er
tak
in
g
s
,
th
en
ag
ain
,
ar
e
ess
en
tially
s
h
ip
p
ed
o
f
f
lo
w
-
ab
ilit
y
s
er
v
e
r
h
u
b
s
in
h
ete
r
o
g
e
n
eo
u
s
s
ettin
g
s
u
tili
zin
g
th
is
m
eth
o
d
o
lo
g
y
.
T
h
e
a
d
v
an
ce
d
Ma
x
Su
f
f
er
an
c
e
(
AM
S)
co
m
p
u
tatio
n
[
1
9
]
i
s
p
r
esen
ted
to
ac
co
m
m
o
d
ate
th
e
is
s
u
e
ab
o
v
e
b
y
f
u
r
th
er
d
ev
elo
p
in
g
th
e
Ma
x
Su
f
f
e
r
ag
e
ca
lcu
latio
n
’
s
in
ad
eq
u
ac
y
.
No
twith
s
tan
d
in
g
,
a
u
to
n
o
m
o
u
s
o
f
th
e
b
u
n
ch
o
r
s
o
r
t
o
f
a
d
m
in
i
s
tr
atio
n
,
th
e
AM
S
ju
s
t
co
n
s
id
er
s
m
is
s
io
n
b
o
o
k
in
g
o
f
a
d
m
in
is
tr
atio
n
h
u
b
s
.
Acc
o
r
d
in
g
ly
,
a
s
tead
y
m
eth
o
d
o
lo
g
y
is
p
r
o
p
o
s
ed
f
o
r
at
th
e
s
am
e
tim
e
tack
lin
g
t
h
e
b
o
o
k
in
g
o
f
a
d
m
in
is
tr
atio
n
ty
p
es,
b
u
n
ch
es,
a
n
d
a
d
m
in
is
tr
atio
n
h
u
b
s
.
Mo
r
eo
v
er
,
r
e
g
ar
d
l
ess
o
f
wh
eth
er
th
e
s
er
v
er
h
u
b
s
ar
e
in
a
d
if
f
er
en
t
clim
ate,
all
p
o
s
itio
n
s
ca
n
b
e
c
o
n
v
ey
e
d
to
th
e
f
itti
n
g
s
er
v
er
h
u
b
s
in
th
e
d
is
tr
ib
u
te
d
co
m
p
u
ti
n
g
o
r
g
an
izatio
n
.
3.
RE
S
E
ARCH
M
E
T
H
O
D
An
o
r
d
in
ar
y
b
u
n
ch
d
esig
n
d
eliv
er
y
ca
lcu
latio
n
d
o
esn
’
t
d
i
s
p
a
tch
er
r
an
d
s
in
lig
h
t
o
f
g
r
o
u
p
lim
it,
wh
ich
m
ig
h
t
b
r
i
n
g
ab
o
u
t
Miss
io
n
id
len
ess
,
lo
w
d
ep
e
n
d
ab
ilit
y
,
an
d
a
lo
n
g
m
a
k
es
co
n
tain
e
r
.
Su
b
s
eq
u
e
n
tly
,
as
d
elin
ea
ted
in
Fig
u
r
e
1
,
a
T
L
C
D
d
esig
n
as
well
as
co
m
p
a
r
in
g
b
o
o
k
in
g
ca
lcu
latio
n
s
will
b
e
in
tr
o
d
u
ce
d
f
o
r
u
s
e
in
clu
s
ter
s
to
r
a
g
e
c
o
n
f
ig
u
r
atio
n
s
.
All
d
o
cu
m
en
tatio
n
a
n
d
th
eir
clar
if
icatio
n
s
as
u
tili
ze
d
i
n
th
e
c
alcu
latio
n
ar
e
co
o
r
d
in
ate
d
in
T
a
b
le
1
p
r
ec
ed
i
n
g
g
iv
i
n
g
th
e
s
u
b
tleties
o
f
th
e
p
r
o
p
o
s
ed
co
n
v
en
tio
n
.
Fig
u
r
e
1
.
T
L
C
D
to
p
o
lo
g
y
T
ab
le
1
.
T
r
a
n
s
cr
ip
tio
n
e
x
p
lan
a
tio
n
s
in
th
e
clu
s
ter
ed
s
elec
tin
g
p
h
ase
P
h
o
n
e
t
i
c
s
y
m
b
o
l
s
S
u
mm
a
r
y
N
O
v
e
r
a
l
l
n
u
m
b
e
r
o
f
o
b
l
i
g
a
t
i
o
n
s
L
M
a
x
i
m
u
m
a
m
o
u
n
t
o
f
c
l
u
s
t
e
r
s
K
C
l
u
st
e
r
s
Th
e
su
m
o
f
a
l
l
o
p
e
r
a
t
i
o
n
s i
n
t
h
e
k
-
c
l
u
st
e
r
Th
e
t
h
r
e
s
h
o
l
d
o
f
r
e
l
i
a
b
i
l
i
t
y
Th
e
c
u
t
o
f
f
p
o
i
n
t
o
f
t
h
e
t
o
t
a
l
p
r
i
c
e
W
o
r
k
o
r
d
e
r
:
i
W
e
i
g
h
i
n
g
t
h
e
c
l
u
st
e
r
's
d
e
p
e
n
d
a
b
i
l
i
t
y
k
D
i
me
n
si
o
n
s
o
f
t
h
e
c
l
u
s
t
e
r
's
l
i
f
e
t
i
m
e
k
W
o
r
k
in
g
o
n
th
e
ex
ac
tn
ess
o
f
clo
u
d
ad
m
in
is
tr
atio
n
s
ea
r
ch
in
th
e
d
is
tr
ib
u
ted
co
m
p
u
tin
g
clim
ate
i
s
tr
o
u
b
leso
m
e
[
1
4
]
.
Acc
o
r
d
in
g
l
y
,
th
e
i
n
itial
p
h
ase
in
th
e
r
e
co
m
m
en
d
e
d
co
n
v
en
tio
n
is
to
ch
ar
ac
ter
ize
cl
o
u
d
ad
m
in
is
tr
atio
n
class
if
icatio
n
s
to
im
p
r
o
v
e
b
y
an
d
lar
g
e
e
x
e
cu
tio
n
.
As
in
d
icate
d
b
y
Sh
o
j
af
ar
et
a
l.
[
1
3
]
,
th
e
f
r
am
ewo
r
k
will
p
ick
a
cl
o
u
d
ad
m
in
is
tr
atio
n
m
is
s
io
n
as
th
e
m
ain
b
u
n
c
h
’
s
ce
n
ter
wo
r
k
in
d
is
cr
im
in
ately
.
T
h
e
lik
en
ess
es
b
etwe
en
th
is
h
ap
h
az
ar
d
ly
p
ick
ed
clo
u
d
ad
m
i
n
i
s
tr
atio
n
m
is
s
io
n
an
d
o
th
e
r
cl
o
u
d
a
d
m
in
is
tr
atio
n
u
n
d
er
tak
i
n
g
s
will
b
e
d
eter
m
in
ed
af
ter
th
at.
All
clo
u
d
ad
m
in
is
tr
atio
n
o
cc
u
p
atio
n
s
with
lik
en
ess
s
co
r
es
m
o
r
e
n
o
tewo
r
th
y
th
a
n
o
r
eq
u
iv
alen
t
to
th
e
ed
g
es
h
av
e
s
p
ec
if
ied
will
b
e
in
co
r
p
o
r
ated
in
to
th
e
m
ain
s
et.
Af
ter
th
at,
th
e
lis
t
o
f
clo
u
d
lo
ca
tio
n
s
co
n
tain
in
g
th
ese
co
o
r
d
i
n
ates
wo
u
ld
b
e
r
em
o
v
ed
.
ad
m
in
is
tr
atio
n
m
is
s
io
n
co
m
p
etito
r
s
.
As
o
f
n
o
w,
t
h
e
f
r
am
ewo
r
k
will
co
n
s
tr
u
ct
a
s
u
b
s
eq
u
en
t
clo
u
d
g
r
o
u
p
b
y
h
a
p
h
az
ar
d
ly
ch
o
o
s
in
g
an
o
th
er
ce
n
ter
o
cc
u
p
atio
n
f
r
o
m
th
e
ex
ce
s
s
clo
u
d
ad
m
in
is
tr
atio
n
u
n
d
e
r
tak
in
g
s
.
T
o
ad
d
co
m
p
ar
ativ
e
clo
u
d
ad
m
in
is
tr
atio
n
ex
er
cises
to
th
is
g
r
o
u
p
,
th
e
f
r
a
m
ewo
r
k
will
u
tili
ze
a
co
m
p
ar
ab
le
c
h
o
ice
cy
cle.
T
h
e
d
eter
m
in
atio
n
m
eth
o
d
will
g
o
o
n
u
n
til
all
clo
u
d
ad
m
i
n
is
tr
atio
n
o
cc
u
p
atio
n
s
h
av
e
b
ee
n
a
s
s
em
b
led
to
g
eth
er
.
I
n
th
e
wak
e
o
f
d
is
tin
g
u
is
h
i
n
g
a
n
d
class
if
y
in
g
th
e
u
n
d
e
r
tak
in
g
s
,
th
e
p
r
o
p
o
s
ed
T
L
C
D
en
g
in
ee
r
i
n
g
will
co
n
tin
u
ally
e
x
ec
u
te
ev
e
r
y
o
r
d
er
ed
ass
ig
n
m
en
t.
C
o
m
in
g
u
p
n
ex
t a
r
e
th
e
p
a
r
ticu
lar
s
o
f
T
L
C
D.
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:
2
5
0
2
-
4
7
52
N
etw
o
r
k
r
o
u
tin
g
a
n
d
s
ch
ed
u
li
n
g
a
r
ch
itectu
r
e
in
a
fu
lly
d
is
tr
ib
u
ted
clo
u
d
…
(
V
ija
y
a
K
u
ma
r
S
)
1245
3
.
1
.
Clus
t
er
ing
f
o
r
a
llo
ca
t
in
g
cla
s
s
la
y
er
C
o
n
v
en
tio
n
al
b
u
n
ch
en
g
in
ee
r
i
n
g
u
tili
ze
s
clo
u
d
ass
et
ch
ief
s
to
g
ath
er
a
n
d
a
p
p
r
o
p
r
iate
r
esp
o
n
s
ib
ilit
ies
to
th
e
g
r
o
u
p
.
I
n
an
y
ca
s
e,
g
r
o
u
p
h
eter
o
g
en
eity
m
i
g
h
t
ch
an
g
e
th
e
p
o
r
tio
n
cy
cle,
m
ak
i
n
g
th
e
ass
ig
n
m
en
t
u
n
ess
en
tial
r
eg
ar
d
in
g
p
lan
n
in
g
.
T
h
is
is
b
ec
au
s
e
o
f
clo
u
d
ass
ets
th
e
ex
ec
u
tiv
es
ap
p
o
r
ti
o
n
th
e
jo
b
s
to
an
in
ac
tiv
e
g
r
o
u
p
.
T
h
u
s
,
th
e
b
o
o
k
in
g
r
esu
lt
is
n
o
t
g
r
ea
t.
T
h
e
d
is
tr
ib
u
ted
co
m
p
u
tin
g
f
r
am
ewo
r
k
will
tu
r
n
o
u
t
t
o
b
e
m
o
r
e
m
o
d
er
n
s
u
b
s
eq
u
en
tl
y.
B
esid
es
th
at,
th
e
ass
o
r
tm
en
t
o
f
o
b
lig
atio
n
s
ad
d
s
to
th
e
h
an
d
li
n
g
tim
e
d
elay
.
T
h
e
h
eter
o
g
en
e
o
u
s
er
r
a
n
d
ca
n
b
e
o
r
d
er
e
d
in
to
v
ar
i
o
u
s
class
es
i
n
lig
h
t
o
f
in
ter
est
ch
a
r
ac
ter
ized
in
th
e
C
AC
lay
er
[7
]
,
[
8
]
to
d
im
in
is
h
th
e
d
ef
e
r
r
al
an
d
in
t
r
icac
y
o
f
p
lan
n
i
n
g
.
T
h
er
e
a
r
e
ess
en
tially
th
r
e
e
d
if
f
e
r
en
t
wa
y
s
to
ca
teg
o
r
ize
g
r
o
u
p
in
g
s
o
f
clo
u
d
s
:
I
aa
S,
SaaS,
an
d
PaaS.
T
h
e
in
tr
icac
y
o
f
b
o
o
k
in
g
h
eter
o
g
en
eo
u
s
p
o
s
itio
n
s
an
d
p
lan
n
in
g
d
ef
er
r
als ca
n
b
e
d
im
in
is
h
ed
b
y
u
tili
zin
g
th
ese
th
r
ee
ch
ar
ac
ter
izatio
n
g
at
h
er
in
g
s
.
3
.
2
.
Clus
t
er
s
elec
t
io
n la
y
er
T
h
e
ar
r
a
n
g
ed
u
n
d
er
tak
in
g
s
ca
n
b
e
d
is
p
atch
ed
to
th
e
c
o
m
p
ar
in
g
class
if
icatio
n
g
r
o
u
p
af
ter
t
h
e
class
if
icatio
n
m
is
s
io
n
b
u
n
c
h
l
ay
er
h
as
b
ee
n
o
r
d
er
ed
.
Fo
llo
w
in
g
th
at,
m
a
k
in
g
u
s
e
o
f
d
e
p
en
d
ab
ilit
y
’
s
(
Di)
co
r
e
co
m
p
o
n
en
ts
,
p
r
ice
(
Pi),
an
d
M
ar
k
etSp
an
(
Mi)
,
a
clu
s
ter
s
elec
tio
n
alg
o
r
ith
m
(
C
SA)
is
cr
ea
ted
to
war
d
s
r
eleg
ate
r
esp
o
n
s
ib
ilit
ies
as
s
u
itab
le
b
u
n
ch
es
(
3
)
.
T
h
e
tim
ef
r
a
m
e
it
tak
es
to
f
o
llo
w
th
r
o
u
g
h
with
a
jo
b
is
ca
lled
Mi
.
As
a
g
en
er
al
r
u
le,
wh
en
th
e
Mi
esteem
ex
p
an
d
s
,
th
e
f
r
am
ewo
r
k
will
ca
ll
f
o
r
g
r
ea
ter
in
v
estme
n
t
to
wo
r
k
.
T
h
e
f
ig
u
r
in
g
p
o
wer
will
d
ev
el
o
p
as
th
e
r
eliab
ilit
y
ex
p
a
n
d
s
b
ec
au
s
e
o
f
th
e
co
m
p
ar
ab
ilit
y
o
f
g
r
o
u
p
a
d
ap
tatio
n
to
in
ter
n
al
f
ailu
r
e.
T
h
u
s
,
we
s
h
o
u
ld
f
o
c
u
s
o
n
th
e
co
m
p
u
tatio
n
al
ab
ilit
y
o
f
b
u
n
ch
es
[
2
0
]
.
At
last
,
th
e
ex
p
en
s
e
f
ac
to
r
i
s
c
h
ar
ac
ter
ized
as
th
e
ex
p
en
s
e
o
f
s
en
d
in
g
an
d
an
s
w
er
in
g
a
m
is
s
io
n
.
U
n
d
er
tak
i
n
g
s
ca
n
b
e
r
eleg
ated
to
p
r
o
p
er
g
r
o
u
p
s
an
d
f
r
am
ew
o
r
k
p
r
o
f
icien
cy
ca
n
b
e
im
p
r
o
v
ed
wh
en
th
ese
th
r
ee
m
o
d
e
ls
ar
e
th
o
u
g
h
t
o
f
.
Mo
r
eo
v
er
,
clien
ts
an
d
s
p
ec
ial
is
t
co
-
o
p
s
ca
n
f
it
th
o
s
e
th
r
ee
elem
en
ts
to
th
eir
p
a
r
ticu
lar
n
ec
ess
itie
s
.
W
ith
th
e
g
u
id
an
ce
o
f
th
e
f
o
llo
win
g
m
o
d
els,
th
ey
Di
an
d
Pi
an
d
allo
t
t
h
e
p
o
s
itio
n
s
to
th
e
s
u
itab
le
b
u
n
ch
es
in
lig
h
t o
f
t
h
e
ab
o
v
e
p
o
r
tr
a
y
al.
Miss
io
n
I
’
s
tr
u
s
two
r
th
in
ess
an
d
co
s
t a
r
e
s
h
o
wn
b
y
(
1
)
-
(
3)
.
D
i
=
∑
CR
k
n
k
k
=
1
N
(
1
)
P
i
=
∑
C
k
n
k
k
=
1
(
2
)
M
i
=
∑
CM
k
n
k
k
=
1
N
(
3
)
Fro
m
th
at
p
o
i
n
t
f
o
r
war
d
,
we
’
ll
g
iv
e
a
g
u
id
e
to
e
x
h
ib
it
Alg
o
r
ith
m
1
.
W
e
co
o
r
d
in
ate
th
e
b
len
d
o
f
o
cc
u
p
atio
n
s
in
all
b
u
n
ch
es
in
l
in
e
(
4
)
o
f
Alg
o
r
ith
m
1
.
T
h
e
b
u
n
ch
will
ch
o
o
s
e
a
r
ea
s
o
n
a
b
le
er
r
an
d
m
ix
an
d
h
elp
th
e
h
u
b
with
m
is
s
io
n
ch
an
g
es.
L
in
es
(
5
)
to
(
8
)
ar
e
lik
ewise
p
r
o
p
o
s
ed
f
o
r
ch
ec
k
i
n
g
wh
eth
er
th
e
Di
an
d
Pi
o
f
ev
er
y
m
is
s
io
n
I
c
o
n
cu
r
with
Di
T
r
an
d
Pi
T
c.
Af
ter
th
at
co
m
es
th
e
m
is
s
io
n
in
v
o
lv
in
g
th
e
y
o
u
n
g
est
Mi
is
r
eser
v
ed
o
u
t
o
f
ev
e
r
y
o
n
e
o
f
th
em
.
I
n
th
e
ev
en
t
th
at
m
u
ltip
le
g
ath
er
in
g
s
ar
e
ac
ce
s
s
ib
le,
w
e
lo
o
k
at
Di,
Mi
,
an
d
p
ick
Ai
as th
e
m
o
s
t d
ep
e
n
d
ab
l
e
g
r
o
u
p
in
th
e
s
h
o
r
test
am
o
u
n
t
o
f
tim
e.
C
lien
ts
ca
n
ch
an
g
e
th
e
n
atu
r
e
o
f
ad
m
in
is
tr
atio
n
s
in
C
SA
in
v
iew
o
f
b
o
u
n
d
ar
ies
lik
e
d
ep
e
n
d
ab
ilit
y
,
ev
alu
atin
g
,
an
d
Mi
.
Su
b
s
eq
u
en
tly
,
ca
lcu
latio
n
s
ca
n
tak
e
ca
r
e
o
f
th
e
r
e
q
u
ir
em
en
ts
o
f
a
wid
e
s
co
p
e
o
f
cu
s
to
m
er
s
wh
ile
lik
ewise
ex
p
an
d
in
g
th
e
p
r
o
f
icien
c
y
o
f
wo
r
k
p
lan
n
in
g
.
T
h
e
C
SA
ca
lcu
latio
n
is
th
en
m
ad
e
s
en
s
e
o
f
with
a
m
o
d
el,
an
d
t
h
e
co
n
n
ec
ted
p
r
esu
m
p
tio
n
s
ar
e
r
ec
o
r
d
ed
.
Alg
o
r
ith
m
1
.
Selectio
n
o
f
cl
u
s
ter
in
g
alg
o
r
ith
m
1: for number of amount
N
2:
for number
of cluster
L
3:
give
,
, and
of each cluster
k
4:
Cluster all jobs, and give each one a number of
5:
for finding up
,
, and
concerning the
m
ission
6:
if
≥
and
<
in
m
ission
then
is member
m
ission
7:
End
8:
select the youngest
in member
m
ission
9:
End
10: End
11. End
Fo
r
th
is
ex
am
p
le,
let
’
s
s
ay
we
h
av
e
1
0
jo
b
s
th
at
n
ee
d
to
b
e
d
is
tr
ib
u
ted
am
o
n
g
th
r
ee
d
if
f
er
en
t
clo
u
d
s
er
v
ice
p
r
o
v
i
d
er
s
;
1
.
T
h
e
v
al
u
es
f
o
r
T
r
a
n
d
T
c
m
ay
b
e
m
o
d
if
ied
b
y
th
e
u
s
er
.
Her
e,
we
s
ee
th
at
T
r
as
well
as
T
c
ar
e
eq
u
al
to
2
2
an
d
2
6
0
,
ac
c
o
r
d
in
g
ly
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
2
,
No
v
em
b
er
20
24
:
1
2
4
2
-
1
2
5
2
1246
2
.
Fin
d
th
e
R
i
,
C
i
,
a
n
d
M
i
f
o
r
ea
ch
p
o
s
s
ib
le
allo
ca
tio
n
.
I
n
ac
co
r
d
an
ce
with
t
h
e
b
r
ea
k
d
o
wn
s
h
o
wn
in
T
ab
le
2
,
f
iv
e
jo
b
s
ar
e
p
lace
d
in
c
lu
s
ter
1
,
two
in
c
lu
s
ter
2
,
a
n
d
th
r
ee
i
n
c
lu
s
ter
3
.
Her
e,
we
a
v
er
ag
ed
R
i,
C
i,
an
d
Mi
with
th
e
h
elp
o
f
(
1
)
-
(
3
)
.
T
h
e
s
am
e
m
eth
o
d
is
u
s
ed
f
o
r
all
o
f
t
h
e
ass
ig
n
m
en
ts
.
3
.
I
n
t
h
is
ca
s
e,
we
ch
o
o
s
e
s
ch
e
d
u
les A1
,
A2
,
a
n
d
A6
s
in
ce
th
ey
s
atis
f
y
th
e
co
n
s
tr
ain
ts
R
i
2
2
an
d
C
i
2
6
0
.
4
.
C
o
n
s
id
er
in
g
th
e
cr
iter
ia
o
f
s
tep
3
,
th
ey
ch
o
o
s
e
am
o
n
g
A1
b
ec
au
s
e
to
its
h
i
g
h
d
eg
r
ee
o
f
d
ep
en
d
a
b
ilit
y
an
d
lo
w
Mi
.
B
ec
au
s
e
a
s
s
ig
n
m
en
t
A1
y
ield
s
a
s
u
p
er
io
r
o
u
tco
m
e,
it
h
as
b
ee
n
ch
o
s
en
as
th
e
ac
ti
v
e
co
m
b
in
atio
n
f
o
r
th
is
ca
s
e.
5
.
T
h
e
a
f
o
r
em
e
n
tio
n
ed
m
eth
o
d
is
id
ea
l w
h
en
ev
er
th
e
Mi
is
r
ea
lly
th
e
d
r
iv
in
g
f
o
r
ce
.
6
.
Mi
an
d
c
o
s
t
b
ec
o
m
es
d
is
g
u
is
in
g
co
n
s
id
er
atio
n
s
wh
en
r
eliab
ilit
y
is
th
e
m
ajo
r
co
n
ce
r
n
,
r
ev
ea
lin
g
th
e
b
est
-
r
eliab
ilit
y
s
ch
ed
u
le.
Af
ter
th
e
clo
u
d
s
er
v
ice
ab
s
tr
ac
tio
n
(
C
SA)
lay
er
is
f
in
is
h
ed
,
th
e
jo
b
s
co
u
ld
b
e
tr
an
s
f
er
r
ed
to
th
e
m
o
d
el
’
s
clu
s
ter
s
clu
s
ter
in
g
lay
er
.
Nex
t,
o
n
th
e
u
n
d
er
ly
i
n
g
lay
er
,
th
e
ap
p
r
o
p
r
iate
s
er
v
er
n
o
d
es m
u
s
t b
e
s
elec
ted
to
ca
r
r
y
o
u
t th
e
m
is
s
io
n
.
3
.
3
.
L
a
y
er
f
o
r
s
elec
t
ing
s
er
v
er
no
des
Ho
m
o
g
en
e
o
u
s
p
o
s
itio
n
s
ca
n
b
e
allo
tted
to
h
o
m
o
g
e
n
eo
u
s
clo
u
d
b
u
n
ch
es
af
ter
th
e
in
itial
two
lev
els
ar
e
f
in
is
h
ed
.
No
twith
s
tan
d
in
g
,
wh
en
co
u
n
tles
s
p
o
s
itio
n
s
f
al
l
f
lat
attr
ib
u
tab
le
to
m
is
tak
en
m
is
s
io
n
,
th
e
clo
u
d
r
esp
o
n
s
ib
ilit
y
ca
n
b
ec
o
m
e
lo
p
s
id
ed
.
I
n
v
iew
o
f
t
h
e
p
r
e
v
io
u
s
,
th
is
wo
r
k
r
ec
o
m
m
en
d
ed
t
h
e
ad
v
a
n
ce
d
clu
s
ter
s
u
f
f
r
ag
e
s
ch
ed
u
lin
g
(
AC
SS
)
,
a
n
o
r
ig
in
al
m
eth
o
d
o
lo
g
y
th
at
te
n
d
s
to
th
e
d
o
wn
s
id
es
o
f
th
e
m
ax
im
u
m
S
u
f
f
er
a
g
e
ca
lcu
latio
n
[
1
2
]
,
[
1
3
]
,
p
ar
ticu
l
ar
ly
in
a
lo
ca
tio
n
with
a
lo
t
o
f
d
if
f
er
en
t
t
y
p
es
o
f
wea
th
e
r
.
T
o
r
estrict
th
e
ef
f
ec
t
o
f
m
is
tak
en
m
is
s
io
n
,
ea
c
h
u
n
d
er
tak
in
g
in
AC
SS
ca
n
in
d
ee
d
b
e
ass
ig
n
ed
t
o
th
e
a
p
p
r
o
p
r
ia
te
n
o
d
es
in
th
e
d
ata
ce
n
ter
b
y
Sj,
n
o
t
en
tire
ly
s
ettled
f
r
o
m
t
h
e
ty
p
ical
E
C
T
o
f
th
e
s
er
v
er
h
u
b
.
T
ab
le
4
a
n
d
Alg
o
r
ith
m
2
s
h
o
w
th
e
ter
m
in
o
lo
g
y
an
d
p
o
in
ts
o
f
in
te
r
est o
f
th
e
AC
SS
ca
lcu
latio
n
.
T
y
p
ically
,
th
er
e
ar
e
t
h
r
ee
s
ec
tio
n
s
to
th
e
AC
SS
alg
o
r
ith
m
.
T
h
e
SVj
ca
lcu
latio
n
s
tag
e,
th
e
E
E
C
T
i
(
ea
r
lies
t
an
ticip
ated
tim
in
g
o
f
co
m
p
letio
n
)
an
d
SEE
C
T
i
p
r
ed
icted
ar
r
iv
al
tim
e
af
ter
th
e
s
o
o
n
est
p
o
s
s
ib
le
ar
r
iv
al
tim
e,
b
u
t
b
ef
o
r
e
th
e
Sj
ar
e
f
ir
s
t
d
eter
m
in
ed
s
e
ctio
n
s
(
8
)
an
d
(
9
)
o
f
th
e
AC
SS
tech
n
iq
u
e
p
r
o
v
id
e
a
f
u
ll
ex
p
lan
atio
n
o
f
h
o
w
to
d
eter
m
in
e
th
e
SV
v
alu
e.
I
n
th
e
s
ec
o
n
d
p
h
ase,
k
n
o
wn
as
th
e
MSVi
ca
lcu
latio
n
p
h
ase,
wh
en
ev
er
wo
r
k
I
h
as
th
e
g
r
e
atest
SV
v
alu
e
ac
r
o
s
s
all
m
is
s
io
n
s
,
th
e
MSV
n
u
m
b
er
wo
u
ld
b
e
a
d
ju
s
ted
in
m
is
s
io
n
I
,
to
th
e
v
e
r
y
f
i
r
s
t E
C
T
v
alu
e
th
at
co
m
es a
f
ter
.
Ass
ig
n
m
en
t
s
in
ce
E
E
C
T
i
is
s
u
p
er
io
r
t
o
MSVi
an
d
E
C
T
ij,
an
d
s
u
p
er
io
r
to
AE
C
T
j
o
f
Sj,
i
n
th
e
f
in
al
s
tep
,
jo
b
s
en
d
in
g
,
I
will
b
e
tr
an
s
f
er
r
ed
to
Sj.
I
n
ca
s
es
wh
e
n
E
C
T
i
is
clo
s
e
t
o
AE
C
T
j
an
d
E
C
T
i
s
h
o
u
ld
b
e
b
ig
g
er
th
an
AE
C
T
j,
allo
ca
tio
n
I
m
ay
b
e
p
ass
ed
to
clien
t
n
o
d
e
j,
wh
e
r
e
its
E
C
T
i
is
s
m
aller
th
an
AE
C
T
j.
As
a
r
esu
lt,
th
e
f
u
n
d
am
e
n
tal
id
ea
i
s
d
is
tin
ct
f
r
o
m
ea
r
lier
m
eth
o
d
s
;
th
e
s
p
ec
if
ics
o
f
th
e
tec
h
n
iq
u
e
ar
e
p
r
esen
ted
in
s
ec
tio
n
s
1
1
an
d
1
2
o
f
Alg
o
r
ith
m
2
.
Alg
o
r
ith
m
2
.
Sch
ed
u
lin
g
f
o
r
c
lu
s
ter
s
u
f
f
r
ag
e
with
a
d
v
an
ce
d
tech
n
o
lo
g
y
1: for all unallocated duties
i
2:
for all network elements
3:
=
+
4:
do schedule every Mission.
5:
make every network node unallocated;
6:
for ever
y Mission
i
in
;
7:
locate host nodes
this results in the quickest delivery time;
8:
determine out the Suited to the Mission Index. (
=
−
);
9:
If
th
e
hi
gh
es
t
pr
i
or
it
y
of
pi
ck
th
e
Mi
ss
io
n
if
th
er
e
ar
e
se
ve
ra
l
or
mo
re
th
at
are the same
to
with greatest;
Else, the Mission will have the most
is
c
om
p
ar
ab
le
t
o
ce
rt
ai
n
ot
he
r
;
10:
end if
;
11:
If
(
<
)
th
er
ef
or
e,
th
e
jo
b
i
wi
th
gr
ea
te
st
ECT
ab
le
to
co
mm
un
ic
at
e
with host node
;
12:
el
se
if
(
>
)
&&
(
>
)
th
er
ef
or
e,
th
e
jo
b
i
ab
le
to
communicate with host node
;
13:
el
se
if
(
>
)
&
&
(
<
)
su
bs
eq
ue
nt
Mi
ss
io
n
al
lo
ca
ti
on
i
>
_
&&
≈
able to be s
ent to host node
;
14:
end if;
15:
end for
16:
end do
17: end for
18:
=
+
19:
=
+
20: end for
21:
End
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:
2
5
0
2
-
4
7
52
N
etw
o
r
k
r
o
u
tin
g
a
n
d
s
ch
ed
u
li
n
g
a
r
ch
itectu
r
e
in
a
fu
lly
d
is
tr
ib
u
ted
clo
u
d
…
(
V
ija
y
a
K
u
ma
r
S
)
1247
T
h
e
er
r
an
d
cu
lm
i
n
atio
n
tim
e
an
d
lo
ad
ad
ju
s
tin
g
ca
n
b
e
ef
f
ec
tiv
ely
b
r
o
u
g
h
t
d
o
wn
am
o
n
g
th
e
d
iv
er
s
e
n
etwo
r
k
in
g
f
o
r
clo
u
d
ap
p
li
ca
tio
n
s
u
tili
zin
g
th
e
m
eth
o
d
o
lo
g
y
p
o
r
tr
ay
ed
p
r
e
v
io
u
s
ly
.
T
h
e
asy
m
m
etr
ic
cr
y
p
to
g
r
ap
h
ic
m
eth
o
d
ap
p
r
o
a
ch
m
ay
b
e
u
s
ed
to
allev
iate
t
h
e
s
ec
u
r
ity
c
o
n
ce
r
n
[
2
1
]
,
[
2
2
]
.
I
t
is
r
elate
d
to
a
cr
u
cial
s
ess
io
n
to
en
s
u
r
e
th
at
p
er
h
ap
s
th
e
m
ess
ag
e
is
d
eliv
er
ed
v
er
itab
le
an
d
h
as
n
o
t
b
ee
n
alter
ed
.
Fo
llo
win
g
th
at,
a
m
o
d
el
is
g
iv
e
n
to
h
elp
t
h
e
p
er
ce
p
tio
n
o
u
t o
f
h
o
s
t h
u
b
s
id
en
tific
atio
n
g
r
ad
ien
t A
C
SS
co
m
p
u
ta
tio
n
.
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
I
n
th
is
s
ec
tio
n
,
it
is
ex
p
lain
ed
th
e
r
esu
lts
o
f
r
esear
c
h
an
d
at
t
h
e
s
am
e
tim
e
is
g
iv
en
th
e
co
m
p
r
eh
e
n
s
iv
e
d
is
cu
s
s
io
n
.
Hu
b
f
o
r
h
i
g
h
ly
d
i
v
er
s
e
s
er
v
er
s
(
HiHi)
,
lo
w
-
laten
cy
r
in
g
(
L
o
L
o
)
,
h
ig
h
-
laten
cy
r
i
n
g
(
HiHi)
,
an
d
L
o
L
o
[
1
8
]
,
[
2
3
]
ar
e
f
o
u
r
h
eter
o
g
en
e
o
u
s
co
n
d
itio
n
s
th
at
ca
n
b
e
co
n
ce
n
tr
ated
o
n
ar
o
u
n
d
h
er
e.
HiHi
is
,
b
y
a
lo
n
g
s
h
o
t,
th
e
m
o
s
t
co
n
v
o
lu
ted
o
f
th
e
m
u
ltit
u
d
e
o
f
ter
r
ito
r
ies.
Acc
o
r
d
in
g
ly
,
in
th
e
HiHi
h
eter
o
g
en
e
o
u
s
clim
ate,
an
illu
s
tr
atio
n
o
f
u
n
d
er
tak
in
g
m
is
s
io
n
with
f
o
u
r
s
er
v
er
h
u
b
s
an
d
twelv
e
er
r
an
d
s
is
talk
ed
ab
o
u
t.
First,
th
e
SVj
esti
m
ate
g
en
e
r
atio
n
a
n
d
th
e
MSVi
ca
lcu
latio
n
s
tag
e
m
ay
r
eso
lv
e
b
o
t
h
SV
r
en
o
wn
an
d
MSV
wo
r
t
h
in
d
ep
en
d
en
tly
.
Fo
llo
win
g
th
at,
d
u
r
in
g
th
e
u
n
d
er
ta
k
in
g
d
is
p
atch
in
g
s
tag
e,
th
e
AE
C
T
j o
f
n
o
t
s
et
in
s
to
n
e.
4
.
1
.
T
he
SVi
ca
lcula
t
io
n pha
se
Stag
e
1
:
a
s
d
em
o
n
s
tr
ated
in
T
ab
le
2
,
a
lis
t o
f
all
ex
p
ec
ted
r
u
n
n
in
g
tim
e
u
n
d
e
r
tak
in
g
s
I
o
n
Sj.
Stag
e
2
:
f
o
r
ea
c
h
er
r
an
d
,
asce
r
tain
th
e
SV
esteem
.
Fo
r
ex
a
m
p
le,
J
o
b
a
’
s
SV
v
alu
e
is
co
m
p
ar
ab
le
to
SEE
C
T
i
less
E
E
C
T
i,
wh
ich
is
2
3
5
2
6
-
2
2
3
4
5
=
1
1
8
1
,
s
im
ilar
ly
co
m
p
ar
ab
le
p
er
io
d
s
ar
e
u
s
ed
t
o
d
ec
i
d
e
th
e
SV
v
alu
es f
o
r
u
n
d
er
ta
k
in
g
s
b
t
h
r
o
u
g
h
l.
T
h
e
ca
lcu
lated
o
u
tco
m
e
s
ar
e
s
h
o
wn
in
T
ab
le
3
.
4
.
2
.
St
a
g
e
o
f
M
SVi
c
o
m
pu
t
a
t
io
n
Stag
e
1
.
m
ea
n
wh
ile
wo
r
k
I
h
a
v
e
m
o
s
t
n
o
tewo
r
th
y
SVi
wo
r
th
o
f
all
SV
v
alu
es,
th
e
MSV
wo
r
th
ca
n
b
e
p
ick
ed
as
th
e
n
ex
t
-
o
ld
est
E
C
T
wo
r
th
o
f
e
r
r
an
d
I
.
J
o
b
g
h
a
v
e
th
e
m
o
s
t
elev
ated
SVi
esteem
,
as
ex
p
r
ess
ed
in
T
ab
le
3
,
s
in
ce
4
4
7
4
6
is
th
e
n
e
x
t e
ar
lies
t E
C
T
in
E
C
T
aB
,
it i
s
u
s
ed
as th
e
MSV.
T
ab
le
2
.
T
h
e
p
r
o
b
lem
o
f
ca
lcu
latin
g
th
e
SV le
v
els
N
o
d
e
A
N
o
d
e
A
SV
M
i
ss
i
o
n
a
2
2
3
4
5
2
3
5
0
0
1
1
8
1
M
i
ss
i
o
n
b
1
6
6
6
7
1
7
9
0
1
1
2
6
3
M
i
ss
i
o
n
c
3
1
0
8
3
3
1
8
2
5
8
1
4
M
i
ss
i
o
n
d
2
4
7
1
2
2
5
1
2
3
4
4
4
M
i
ss
i
o
n
e
1
7
0
1
8
1
8
0
0
8
1
0
5
1
M
i
ss
i
o
n
f
1
2
0
5
0
1
3
2
1
8
1
2
3
9
M
i
ss
i
o
n
g
1
9
0
3
5
2
1
4
7
6
2
4
5
1
M
i
ss
i
o
n
h
1
3
9
1
1
1
4
6
7
8
6
9
1
M
i
ss
i
o
n
i
8
0
1
6
0
8
5
4
9
0
5
2
0
M
i
ss
i
o
n
j
1
3
6
1
8
1
4
5
1
7
9
7
8
M
i
ss
i
o
n
k
2
7
8
6
1
2
8
1
4
9
2
9
5
M
i
ss
i
o
n
l
4
0
0
0
0
4
4
7
4
6
1
3
9
5
T
ab
le
3
.
E
s
tab
lis
h
in
g
wh
at
t
h
e
MSV
lev
els s
h
o
u
ld
b
e
r
eq
u
ir
e
s
s
o
m
e
ca
lcu
latio
n
N
o
d
e
A
N
o
d
e
B
SV
M
S
V
M
i
ss
i
o
n
a
2
2
3
4
5
2
3
5
2
6
1
1
8
1
-
M
i
ss
i
o
n
b
1
6
6
6
7
1
7
9
3
0
1
2
6
3
-
M
i
ss
i
o
n
c
3
1
0
8
3
3
1
8
9
7
8
1
4
-
M
i
ss
i
o
n
d
2
4
7
1
2
2
5
1
5
6
4
4
4
-
M
i
ss
i
o
n
e
1
7
0
1
8
1
8
0
6
9
1
0
5
1
-
M
i
ss
i
o
n
f
1
2
0
5
0
1
3
2
8
9
1
2
3
9
-
M
i
ss
i
o
n
g
1
9
0
3
5
2
1
4
8
6
2
4
5
1
-
M
i
ss
i
o
n
h
1
3
9
0
0
1
3
5
0
2
8
9
1
0
-
M
i
ss
i
o
n
i
7
0
1
6
2
9
5
3
6
8
5
5
8
-
M
i
ss
i
o
n
j
1
7
8
1
8
1
8
5
6
6
9
9
8
-
M
i
ss
i
o
n
k
2
7
1
8
1
2
7
8
9
6
6
9
5
-
M
i
ss
i
o
n
l
4
3
2
2
6
4
4
5
6
1
2
0
9
5
-
4
.
3
.
J
o
b
dis
t
ributio
n sta
g
e
B
y
an
d
lar
g
e,
th
r
ee
cir
cu
m
s
ta
n
ce
s
in
d
if
f
er
en
t
h
eter
o
g
en
eo
u
s
s
ettin
g
s
s
h
o
u
ld
b
e
an
aly
ze
d
,
an
d
th
u
s
th
e
in
s
tan
ce
s
ar
e
d
escr
ib
ed
a
n
d
p
r
esen
ted
i
n
th
e
f
o
llo
win
g
o
r
d
er
.
4
.
3
.
1
.
Ca
s
e
1
.
E
E
CT
i > A
E
C
T
j
o
f
Sj
a
nd
M
SVi >
E
CT
ij
o
f
Sj
I
n
th
e
MSVi
co
m
p
u
tatio
n
s
tep
,
co
m
p
ar
i
n
g
th
e
MSV
v
alu
e
to
th
e
ea
r
lies
t a
n
ticip
ated
f
in
is
h
in
g
tim
e
o
f
ot
h
er
jo
b
s
.
W
h
ile
MSVi
is
r
u
n
n
in
g
,
Miss
io
n
I
m
a
y
b
e
s
en
t to
an
y
estab
lis
h
ed
n
o
r
m
s
n
o
d
e
j.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
2
,
No
v
em
b
er
20
24
:
1
2
4
2
-
1
2
5
2
1248
>
E
E
C
T
i
>
AE
C
T
i
o
f
S,
an
d
E
C
T
ij
o
f
Sj
>
E
E
C
T
i.
Sin
ce
No
d
e
D
h
as
t
h
e
h
i
g
h
est
MSVi
an
d
l
o
west
E
C
T
d
D
in
T
ab
les 4
an
d
5
,
r
esp
ec
tiv
ely
,
T
ab
le
4
.
A
ctiv
ities
’
MSV
r
esu
lts
ar
e
ca
lcu
lated
N
o
d
e
C
N
o
d
e
D
SV
M
S
V
M
i
ss
i
o
n
a
5
2
9
7
8
2
5
3
2
8
2
7
6
5
0
-
M
i
ss
i
o
n
b
4
7
3
5
1
2
0
1
8
7
2
7
1
6
4
-
M
i
ss
i
o
n
d
5
4
4
2
9
2
6
3
3
0
2
8
0
9
9
5
4
4
2
9
M
i
ss
i
o
n
e
4
7
3
1
9
2
0
3
4
8
2
6
9
7
1
-
M
i
ss
i
o
n
f
4
3
5
6
6
1
5
9
1
8
2
7
6
4
8
-
M
i
ss
i
o
n
g
5
1
0
2
6
2
4
0
3
1
2
6
9
9
5
-
M
i
ss
i
o
n
h
4
4
3
1
0
1
7
6
7
8
2
6
6
3
2
-
M
i
ss
i
o
n
j
3
7
6
0
3
9
6
8
5
2
7
9
1
8
-
M
i
ss
i
o
n
l
4
3
9
8
6
1
6
5
5
8
2
7
4
2
8
-
A
v
e
r
a
g
e
-
1
9
5
5
6
-
-
T
ab
le
5
.
An
aly
s
is
o
f
t
h
e
n
o
d
e
D
jo
b
s
’
m
ed
ian
E
C
T
lev
els f
o
r
i
n
s
tan
ce
1
N
o
d
e
C
N
o
d
e
D
SV
M
S
V
M
i
ss
i
o
n
a
5
2
9
7
8
2
5
3
2
8
2
7
6
5
0
-
M
i
ss
i
o
n
b
4
7
3
5
1
2
0
1
8
7
2
7
1
6
4
-
M
i
ss
i
o
n
d
5
4
4
2
9
2
6
3
3
0
2
8
0
9
9
5
4
4
2
9
M
i
ss
i
o
n
e
4
7
3
1
9
2
0
3
4
8
2
6
9
7
1
-
M
i
ss
i
o
n
f
4
3
5
6
6
1
5
9
1
8
2
7
6
4
8
-
M
i
ss
i
o
n
g
5
1
0
2
6
2
4
0
3
1
2
6
9
9
5
-
M
i
ss
i
o
n
h
4
4
3
1
0
1
7
6
7
8
2
6
6
3
2
-
M
i
ss
i
o
n
j
3
7
6
0
3
9
6
8
5
2
7
9
1
8
-
M
i
ss
i
o
n
l
4
3
9
8
6
1
6
5
5
8
2
7
4
2
8
-
A
v
e
r
a
g
e
-
1
9
5
5
6
-
-
4
.
3
.
2
.
Ca
s
e
2
.
M
SVi > E
C
T
ij
o
f
Sj
Yo
u
m
ay
s
ee
h
o
w
ea
r
ly
o
th
er
m
is
s
io
n
s
ar
e
lik
ely
to
b
e
f
in
is
h
ed
b
y
co
m
p
ar
in
g
th
e
MSV
v
alu
e
d
eter
m
in
ed
d
u
r
in
g
th
e
MSVi
ca
lcu
latio
n
s
tep
.
I
f
MSVi
>
E
C
T
ij,
th
en
m
is
s
io
n
I
with
th
e
h
ig
h
est
E
C
T
m
ay
b
e
s
en
t
to
s
er
v
er
n
o
d
e
j.
Sin
ce
n
o
d
e
A
’
s
E
C
T
lA
is
h
ig
h
er
th
an
th
at
o
f
th
e
MSV
v
alu
e
in
T
ab
le
6
(
4
3
3
3
6
>
2
1
4
8
6
)
,
A
is
g
i
v
en
t
h
e
ass
ig
n
m
en
t o
f
m
is
s
io
n
l.
T
ab
le
6
.
No
d
e
A
’
s
m
ed
ian
E
C
T
in
c
ase
2
N
o
d
e
A
N
o
d
e
B
SV
M
S
V
M
i
ss
i
o
n
a
2
2
3
4
5
2
3
5
2
6
1
1
8
1
-
M
i
ss
i
o
n
b
1
6
6
6
7
1
7
9
3
0
1
2
6
3
-
M
i
ss
i
o
n
c
3
1
0
8
3
3
1
8
9
7
8
1
4
-
M
i
ss
i
o
n
d
2
4
7
1
2
2
5
1
5
6
4
4
4
-
M
i
ss
i
o
n
e
1
7
0
1
8
1
8
0
6
9
1
0
5
1
-
M
i
ss
i
o
n
f
1
2
0
5
0
1
3
2
8
9
1
2
3
9
-
M
i
ss
i
o
n
g
1
9
0
3
5
2
1
4
8
6
2
4
5
1
2
1
4
8
6
M
i
ss
i
o
n
h
1
3
9
1
1
1
4
6
0
2
6
9
1
-
M
i
ss
i
o
n
i
8
0
1
6
8
5
3
6
5
2
0
-
M
i
ss
i
o
n
j
1
3
6
1
8
1
4
5
9
6
9
7
8
-
M
i
ss
i
o
n
k
2
7
8
6
1
2
8
1
5
6
2
9
5
-
M
i
ss
i
o
n
l
4
3
3
3
6
4
4
7
3
1
1
3
9
5
-
4
.
3
.
3
.
Ca
s
e
3
.
When c
o
m
pa
ri
ng
E
CT
ij
t
o
M
SV
i,
t
he
la
t
t
er
is
s
up
er
io
r
As
p
ar
t
o
f
t
h
e
MSVi
ca
lcu
latio
n
,
th
e
MSV
v
alu
e
is
co
m
p
ar
ed
to
th
e
ea
r
lies
t
esti
m
ated
c
o
m
p
letio
n
tim
e
o
f
o
th
er
task
s
.
Fo
r
ex
a
m
p
le,
in
T
ab
le
7
,
m
is
s
io
n
i
i
s
ass
ig
n
ed
to
clien
t
n
o
d
e
j
if
MSVi
>
E
C
T
ij
an
d
E
E
C
T
i
AE
C
T
j
o
f
Sj,
ass
u
m
in
g
th
at
E
C
T
i
is
m
o
r
e
th
a
n
o
r
e
q
u
al
to
AE
C
T
j.
T
h
u
s
,
we
ca
n
r
ep
r
o
d
u
ce
th
e
ab
o
v
e
s
itu
atio
n
s
in
o
u
r
tr
ial.
T
o
a
d
ju
s
t
to
th
e
h
ig
h
-
h
eter
o
g
en
eity
cl
im
ate,
th
e
q
u
a
n
tity
o
f
p
o
s
itio
n
s
is
f
ir
s
t
ch
an
g
ed
in
ac
co
r
d
an
ce
with
5
0
to
1
0
0
,
wh
ile
th
e
5
o
n
lin
e
s
er
v
er
s
’
hubs
’
co
m
b
in
ed
p
r
o
ce
s
s
in
g
p
o
wer
is
lim
ited
to
5
0
0
to
1
,
0
0
0
u
n
its
.
B
esid
es
th
at,
th
e
Su
f
f
er
a
g
e,
Ma
x
Su
f
f
er
a
g
e,
a
n
d
AC
SS
ca
lcu
latio
n
s
ar
e
th
o
u
g
h
t
ab
o
u
t
as
f
ar
as
Ma
k
eSp
an
an
d
lo
a
d
ad
ju
s
tin
g
m
u
ltip
le
as
s
h
o
wn
in
Fig
u
r
es
2
to
5
,
an
d
t
h
e
u
s
u
al
v
alu
e
o
f
co
m
p
u
tatio
n
tim
e
is
th
en
tak
en
.
Fig
u
r
e
2
illu
s
tr
ates
th
at
th
e
s
u
g
g
ested
p
r
o
ce
d
u
r
e
b
ea
ts
th
e
o
th
er
s
co
n
ce
r
n
in
g
Ma
k
eSp
an
,
p
ar
ticu
lar
ly
w
h
ile
m
an
a
g
in
g
h
u
g
e
jo
b
s
.
T
h
e
r
m
in
/r
m
a
x
,
wh
er
e
r
m
i
n
is
th
e
b
r
ief
est
g
o
tten
d
o
n
e
with
jo
b
s
ea
s
o
n
r
m
ax
is
th
e
s
h
o
r
test
co
m
p
leted
wo
r
k
s
ea
s
o
n
o
f
all
m
is
s
io
n
s
,
an
d
o
f
all
m
is
s
io
n
s
.
Ma
h
eswar
an
et
a
l.
[
2
3
]
,
c
an
lik
ewise
b
e
u
tili
ze
d
t
o
d
ec
id
e
th
e
h
ea
p
a
d
ju
s
tin
g
f
il
e.
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:
2
5
0
2
-
4
7
52
N
etw
o
r
k
r
o
u
tin
g
a
n
d
s
ch
ed
u
li
n
g
a
r
ch
itectu
r
e
in
a
fu
lly
d
is
tr
ib
u
ted
clo
u
d
…
(
V
ija
y
a
K
u
ma
r
S
)
1249
T
ab
le
7
.
C
o
m
p
a
r
in
g
a
v
er
ag
e
E
C
T
v
alu
es f
o
r
n
o
d
e
D
ac
r
o
s
s
c
ase
3
s
ce
n
ar
io
s
N
o
d
e
A
N
o
d
e
B
SV
MS
V
M
i
ss
i
o
n
b
6
0
0
2
3
4
9
8
2
7
1
0
1
9
6
-
M
i
ss
i
o
n
e
6
0
3
7
4
4
9
9
6
6
1
0
4
0
8
-
M
i
ss
i
o
n
f
5
5
4
0
6
4
5
1
8
6
1
0
2
2
0
-
M
i
ss
i
o
n
h
5
7
2
6
7
4
6
4
9
9
1
0
7
6
8
-
M
i
ss
i
o
n
i
5
1
3
7
2
4
0
4
3
3
1
0
9
3
9
5
1
3
7
2
M
i
ss
i
o
n
j
5
6
9
7
4
4
6
4
9
3
1
0
4
8
1
-
A
v
e
r
a
g
e
-
4
6
4
0
0
-
-
Fig
u
r
e
2
.
AC
SS
,
Su
f
f
er
ag
e,
an
d
Ma
x
Su
f
f
er
i
n
g
in
Ma
k
eSp
an
with
n
=4
an
d
1
0
0
m
is
s
io
n
s
Fig
u
r
e
3
.
L
o
ad
b
alan
cin
g
i
n
d
e
x
o
f
S
u
f
f
er
ag
e
f
o
r
n
=4
an
d
1
0
0
m
is
s
io
n
s
As
a
g
en
er
al
r
u
le,
th
e
h
ea
p
ad
ju
s
tin
g
f
ile
h
as
a
wo
r
th
o
f
0
to
1
,
with
0
ad
d
r
ess
in
g
th
e
m
o
s
t
u
n
f
o
r
t
u
n
ate
b
u
r
d
en
eq
u
ilib
r
i
u
m
an
d
1
ad
d
r
ess
in
g
th
e
b
est b
u
r
d
en
b
alan
ce
.
T
h
e
AC
SS
s
tr
ateg
y
ca
n
ac
co
m
p
lis
h
th
e
b
est
b
u
r
d
en
ad
ju
s
tin
g
lis
t
(
0
.
8
8
)
o
v
er
Su
f
f
er
a
g
e
(
0
.
8
7
)
an
d
Ma
x
Su
f
f
er
ag
e
(
0
.
8
8
)
,
as
o
u
tlin
ed
in
Fig
u
r
es
3
.
T
h
e
Ma
k
eSp
an
o
f
e
v
er
y
h
u
b
ca
n
y
ield
tan
tam
o
u
n
t
o
u
tco
m
es
in
lig
h
t
o
f
th
e
f
ac
t
th
at
th
e
AC
SS
ca
lcu
latio
n
u
tili
ze
s
th
e
s
ca
tter
in
g
o
f
th
e
ty
p
ical
wo
r
th
.
B
e
th
at
as
it
m
ay
,
wh
ile
Ma
x
Su
f
f
er
a
g
e
h
as
a
q
u
ick
er
f
in
is
h
tim
e
th
an
Su
f
f
e
r
ag
e,
th
e
h
ea
p
ad
ju
s
tin
g
r
esu
lts
ar
e
co
m
p
a
r
ab
le.
T
h
is
is
b
ec
au
s
e
o
f
th
e
way
t
h
at
wh
ile
ch
o
o
s
in
g
p
o
s
itio
n
,
Ma
x
Su
f
f
e
r
ag
e
d
id
n
'
t
co
n
s
id
er
th
e
h
u
b
'
s
h
ea
p
c
o
n
d
itio
n
.
Pro
p
o
s
ed
AC
SS
alg
o
r
ith
m
o
p
tim
izes
h
eter
o
g
en
e
o
u
s
d
is
tr
ib
u
ted
c
o
m
p
u
tin
g
n
etwo
r
k
f
o
r
ef
f
icie
n
t
tim
e
an
d
lo
ad
b
alan
cin
g
,
y
ield
in
g
s
u
p
er
i
o
r
o
u
tco
m
es.
B
esid
es th
i
s
,
th
e
f
o
r
m
u
la
=
=1
×
test
if
th
e
p
ap
e
r
’
s
co
n
s
u
m
p
t
io
n
o
f
r
eso
u
r
ce
s
is
id
ea
l,
th
e
r
atio
o
f
r
eso
u
r
ce
Nm
is
ca
lcu
lated
a
s
1
0
0
%.
T
h
e
T
C
j
in
f
ac
t
o
r
R
U
r
ep
r
esen
ts
th
e
all
-
out
e
x
p
e
cted
co
n
s
u
m
m
atio
n
tim
e
o
n
a
co
m
p
u
ter
s
im
u
latio
n
j,
N
f
o
r
th
e
to
tal
n
u
m
b
er
o
f
VM
s
,
an
d
m
f
o
r
s
u
c
h
n
u
m
b
er
o
f
co
r
es
v
ir
tu
al
m
ac
h
in
e
’
s
last
f
u
lf
illme
n
t
tim
e.
Fig
u
r
e
4
p
o
r
tr
ay
s
t
h
e
ass
et
u
s
e
r
elate
d
p
r
o
p
o
r
tio
n
r
esu
lts
.
Fig
u
r
e
5
s
h
o
ws
th
at
AC
C
S
m
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I
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In
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m
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.
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
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SS
N:
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(
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1251
RE
F
E
R
E
NC
E
S
[
1
]
V
.
V
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e
g
e
s
n
a
,
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v
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p
p
.
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–
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4
4
,
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0
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.
[
2
]
V
.
Y
a
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b
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l
.
,
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Pr
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.
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–
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6
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6
.
[
3
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N
.
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h
a
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y
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A
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b
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.
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.
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4
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