I
n
d
on
e
s
ian
Jou
r
n
al
o
f
E
lec
t
r
ica
l
E
n
gin
e
e
r
in
g
a
n
d
Com
p
u
t
e
r
S
c
ience
Vo
l
.
25
,
N
o
.
3
,
M
a
r
c
h
2022
,
pp.
1615
~
1624
I
S
S
N:
2502
-
4752,
DO
I
:
10
.
11591/i
j
e
e
c
s
.
v
25
.i
3
.
pp
1615
-
1624
1615
Jou
r
n
al
h
o
m
e
page
:
ht
tp:
//
ij
e
e
c
s
.
iaes
c
or
e
.
c
om
Op
t
i
m
i
z
e
d
sc
h
e
d
u
li
n
g of
sc
ie
n
t
ific
w
or
k
f
lo
w
s b
ase
d
on
i
t
e
r
a
t
e
d
lo
c
al
se
ar
c
h
Al
aa
Abd
al
q
ah
a
r
Jih
ad
1
,
S
u
f
yan
T
.
F
ar
aj
Al
-
Ja
n
ab
i
2
,
E
s
am
T
ah
a
Yas
s
e
n
1
1
C
o
mput
e
r
C
e
nt
e
r
,
U
ni
ve
r
s
it
y
of
A
nba
r
, R
a
ma
di
, I
r
a
q
2
C
o
ll
e
g
e
of
C
o
mput
e
r
S
c
i
e
n
c
e
a
nd I
n
f
o
r
ma
ti
o
n
T
e
c
hn
o
l
o
g
y
, U
n
iv
e
r
s
it
y
of
A
nba
r
, R
a
ma
di
, I
r
a
q
Ar
t
ic
l
e
I
n
f
o
AB
S
T
RA
CT
A
r
ti
c
le
h
is
tor
y
:
R
e
c
e
i
ve
d
J
u
l
15
,
2021
R
e
vi
s
e
d
J
a
n
13
,
202
2
A
c
c
e
pt
e
d
J
a
n
21
,
202
2
Rece
n
t
y
e
ars
h
av
e
w
i
t
n
e
s
s
ed
a
g
r
e
at
i
n
t
e
r
e
s
t
i
n
s
ci
e
n
t
i
fi
c
ap
p
l
i
c
at
i
o
n
s
w
i
t
h
l
arg
e
d
at
a
an
d
p
ro
ce
s
s
i
n
g
-
i
n
t
en
s
i
v
e,
s
o
cl
o
u
d
co
m
p
u
t
i
n
g
i
s
u
s
e
d
w
h
i
c
h
p
ro
v
i
d
e
s
t
h
e
r
e
s
o
u
r
ce
s
n
e
ed
e
d
t
o
i
m
p
l
eme
n
t
a
n
d
r
u
n
t
h
es
e
ap
p
l
i
c
at
i
o
n
s
.
O
n
e
o
f
t
h
e
c
h
a
l
l
en
g
e
s
i
n
t
h
e
m
an
a
g
eme
n
t
o
f
s
ci
e
n
t
i
f
i
c
w
o
r
k
fl
o
w
ap
p
l
i
c
at
i
o
n
s
i
s
s
c
h
e
d
u
l
i
n
g
t
h
em
t
o
s
o
l
v
e
m
an
y
co
m
b
i
n
at
o
r
i
al
o
p
t
i
mi
zat
i
o
n
p
ro
b
l
em
s
,
i
n
c
l
u
d
i
n
g
r
ed
u
ci
n
g
e
x
ec
u
t
i
o
n
t
i
me,
co
s
t
,
re
s
o
u
r
ce
u
t
i
l
i
zat
i
o
n
,
an
d
e
n
e
r
g
y
c
o
n
s
u
m
p
t
i
o
n
.
D
u
e
t
o
t
h
e
f
ac
t
t
h
a
t
t
h
e
i
t
e
ra
t
e
d
l
o
c
al
s
e
arc
h
al
g
o
ri
t
h
m
(I
L
S
)
h
a
s
b
e
e
n
s
u
c
c
e
s
s
fu
l
l
y
a
p
p
l
i
e
d
t
o
s
o
l
v
e
m
an
y
c
o
m
b
i
n
a
t
o
ri
al
o
p
t
i
m
i
z
a
t
i
o
n
p
ro
b
l
e
m
s
,
t
h
i
s
p
a
p
e
r
i
n
v
e
s
t
i
g
a
t
e
s
t
h
e
p
e
r
fo
rm
an
c
e
o
f
I
L
S
i
n
s
o
l
v
i
n
g
t
h
e
s
c
i
e
n
t
i
fi
c
w
o
rk
fl
o
w
s
c
h
e
d
u
l
i
n
g
p
ro
b
l
e
m
w
h
i
c
h
i
s
a
h
i
g
h
l
y
c
o
n
s
t
r
ai
n
e
d
p
ro
b
l
e
m
.
T
h
e
m
ai
n
c
o
m
p
o
n
e
n
t
s
t
h
a
t
are
d
i
ff
e
re
n
t
fro
m
o
n
e
p
ro
b
l
e
m
t
o
o
t
h
e
r
s
a
re
t
h
e
I
L
S
p
a
r
am
e
t
e
r
s
,
l
o
c
al
s
e
a
rc
h
,
an
d
p
e
r
t
u
r
b
a
t
i
o
n
,
w
h
i
c
h
m
u
s
t
b
e
c
a
re
fu
l
l
y
d
e
s
i
g
n
e
d
.
T
h
e
p
e
r
fo
rm
an
c
e
o
f
t
h
e
s
t
an
d
ard
I
L
S
h
a
s
b
e
e
n
e
x
am
i
n
ed
an
d
c
o
m
p
are
d
w
i
t
h
t
h
e
l
a
t
e
s
t
t
e
c
h
n
o
l
o
g
y
.
T
h
e
e
x
p
e
ri
m
e
n
t
al
re
s
u
l
t
s
s
h
o
w
t
h
a
t
t
h
e
p
ro
p
o
s
e
d
a
l
g
o
ri
t
h
m
(I
L
S
)
o
b
t
ai
n
e
d
g
o
o
d
re
s
u
l
t
s
c
o
m
p
a
re
d
t
o
t
h
e
b
e
s
t
-
k
n
o
w
n
re
s
u
l
t
s
i
n
t
h
e
l
i
t
e
r
a
t
u
re
.
T
h
i
s
i
s
d
u
e
t
o
t
h
e
I
L
S
b
e
i
n
g
an
ad
a
p
t
a
b
l
e
m
e
t
ah
e
u
ri
s
t
i
c
,
w
h
i
ch
c
an
b
e
s
i
m
p
l
y
ad
a
p
t
e
d
t
o
d
i
ff
e
re
n
t
s
e
a
rc
h
s
i
t
u
a
t
i
o
n
s
an
d
i
n
s
t
a
n
c
e
s
.
K
e
y
w
o
r
d
s
:
C
l
o
ud
c
o
m
put
i
n
g
Opt
i
mi
z
a
t
i
o
n
Qua
l
i
t
y
o
f
s
e
r
vi
c
e
S
c
h
e
du
li
ng
S
c
i
e
n
t
i
f
i
c
wo
r
k
f
l
o
ws
Th
i
s
i
s
a
n
o
p
en
a
c
ces
s
a
r
t
i
c
l
e
u
n
d
e
r
t
h
e
CC
B
Y
-
SA
l
i
cen
s
e.
C
or
r
e
s
pon
din
g
A
u
th
or
:
Al
a
a
Ab
da
l
qa
h
a
r
J
i
ha
d
C
o
m
put
e
r
C
e
n
t
e
r
,
Uni
v
e
r
s
i
t
y
o
f
Anb
a
r
R
a
m
a
d
i
,
I
r
a
q
E
m
a
i
l
:
i
t
.
a
l
a
a
.
h
e
e
t
y
@
uo
a
nb
a
r
.
e
du.
i
q
1.
I
NT
RODU
C
T
I
ON
I
n
r
e
c
e
n
t
t
i
m
e
s
,
t
h
e
r
e
h
a
s
b
e
e
n
a
l
o
t
o
f
us
e
o
f
bi
g
da
t
a
a
pp
l
i
c
a
t
i
o
n
s
t
h
a
t
c
o
m
bi
ne
t
h
o
us
a
n
ds
o
f
i
n
t
e
r
r
e
l
a
t
e
d
t
a
s
ks
w
i
t
h
pr
e
c
e
de
n
c
e
c
o
n
s
t
r
a
i
n
t
s
.
T
h
e
s
e
c
o
m
p
l
e
x
i
m
p
l
e
m
e
n
t
a
t
i
o
n
s
a
r
e
c
o
n
s
i
de
r
e
d
a
s
a
di
r
e
c
t
e
d
a
c
y
c
l
i
c
gr
a
ph
s
(
D
A
Gs
)
m
o
de
l
[
1]
.
T
h
e
s
c
i
e
n
t
i
f
i
c
wo
r
kf
l
o
w
m
o
de
l
i
s
w
i
de
ly
u
s
e
d
i
n
m
a
ny
f
i
e
l
ds
t
o
de
s
c
r
i
be
v
a
r
i
o
us
s
c
i
e
n
t
i
f
i
c
pr
o
bl
e
m
s
s
uc
h
a
s
bi
o
i
nf
o
r
m
a
t
i
c
s
,
a
s
t
r
o
i
nf
o
r
m
a
t
i
c
s
,
a
n
d
ge
o
i
nf
o
r
m
a
t
i
c
s
.
T
h
e
s
c
i
e
n
t
i
f
i
c
wo
r
kf
l
o
ws
a
r
e
da
t
a
-
i
n
t
e
n
s
i
ve
,
c
o
m
put
a
t
i
o
n
-
i
n
t
e
n
s
iv
e
,
a
n
d
r
e
qu
i
r
e
m
a
ny
pr
o
c
e
s
s
i
n
g
h
o
ur
s
[
2]
.
T
o
ha
nd
l
e
s
c
i
e
nt
if
i
c
a
p
p
li
c
a
t
i
o
ns
w
hi
c
h
a
r
e
i
nc
r
e
a
s
i
ng
ly
d
a
t
a
-
i
nt
e
ns
ive
,
c
o
m
p
ut
a
t
i
o
na
l
r
e
s
o
ur
c
e
s
t
ha
t
a
i
d
in
p
a
r
a
ll
e
l
e
xe
c
u
t
i
o
n,
s
uc
h
a
s
g
r
i
d
s
,
c
l
u
s
t
e
r
s
,
a
nd
c
l
o
u
d
s
,
a
r
e
u
s
e
d.
C
l
o
ud
c
o
m
p
ut
i
ng
i
s
t
he
l
a
t
e
s
t
t
r
e
nd
i
n
s
c
a
l
a
b
l
e
d
i
s
t
r
i
bu
t
e
d
c
o
m
p
ut
i
ng
,
w
hi
c
h
m
a
k
e
s
a
va
i
l
a
b
l
e
t
e
c
hn
o
l
o
g
y
r
e
s
o
ur
c
e
s
a
t
a
n
a
d
a
pt
i
ve
pr
i
c
e
f
o
r
u
s
e
,
o
n
-
de
m
a
nd
,
a
nd
o
ve
r
t
h
e
I
n
t
e
r
ne
t
.
T
hi
s
c
a
n
be
a
n
i
nt
e
r
e
s
t
i
ng
a
l
t
e
r
na
t
i
ve
i
ns
t
e
a
d
o
f
bu
ying
a
nd
o
w
ning
p
hy
s
i
c
a
l
d
a
t
a
c
e
n
t
e
r
s
[
3]
,
[
4
]
.
W
h
e
n
us
e
i
ng
t
h
e
c
l
o
ud
c
o
m
put
i
n
g
e
nvi
r
o
nm
e
n
t
,
va
r
i
o
us
c
h
a
ll
e
n
ge
s
m
us
t
b
e
de
a
l
t
w
i
t
h
t
o
i
m
p
l
e
m
e
n
t
a
s
c
i
e
n
t
i
f
i
c
wo
r
k
f
l
o
w
a
pp
li
c
a
t
i
o
n
.
One
o
f
t
h
e
s
e
i
s
s
c
h
e
du
li
ng,
whi
c
h
i
s
t
h
e
pr
o
c
e
s
s
o
f
a
ll
o
c
a
t
i
n
g
r
e
s
o
ur
c
e
s
to
t
a
s
ks
to
i
m
pr
o
v
e
o
n
e
o
r
m
o
r
e
g
o
a
l
s
[
5]
.
S
i
n
c
e
D
AG
s
c
he
du
l
i
ng
i
s
a
n
NP
-
c
o
m
p
l
e
t
e
pr
o
bl
e
m
,
o
n
e
o
f
th
e
m
a
in
pr
o
bl
e
m
s
i
s
t
o
f
i
nd
t
h
e
o
pt
i
m
a
l
s
c
he
du
l
e
[
6]
.
T
h
us
,
s
o
m
e
c
h
a
ll
e
n
ge
s
n
e
e
d
t
o
b
e
t
a
ke
n
i
n
t
o
c
o
n
s
i
de
r
a
t
i
o
n
,
s
uc
h
a
s
t
h
e
pe
r
f
o
r
m
a
n
c
e
v
a
r
i
a
t
i
o
n
o
f
vi
r
t
ua
l
m
a
c
hi
ne
s
(
VM
s
)
a
n
d
t
h
e
i
r
c
o
m
m
o
n
a
n
d
h
e
t
e
r
o
ge
n
e
o
us
n
a
t
ur
e
[
7]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2502
-
4752
I
n
do
n
e
s
i
a
n
J
E
l
e
c
E
n
g
&
C
o
m
p
S
c
i
,
Vo
l
.
25
,
N
o
.
3
,
M
a
r
c
h
20
22
:
1615
-
1624
1616
T
hi
s
pa
pe
r
pr
o
po
s
e
s
i
m
p
l
e
m
e
n
t
a
t
i
o
n
o
f
t
h
e
i
t
e
r
a
t
e
d
l
o
c
a
l
s
e
a
r
c
h
(
I
L
S
)
a
l
go
r
i
t
hm
to
s
o
l
v
e
t
h
e
s
c
i
e
n
t
i
f
i
c
wo
r
kf
l
o
w
s
c
h
e
du
li
ng
pr
o
bl
e
m
t
o
r
e
duc
e
m
a
ke
s
p
a
n
.
W
e
a
n
a
ly
z
e
i
t
s
pe
r
f
o
r
m
a
nc
e
,
a
d
j
us
t
i
t
s
pa
r
a
m
e
t
e
r
s
,
a
n
d
pr
e
s
e
n
t
a
c
o
m
pa
r
i
s
o
n
o
f
t
h
e
r
e
s
u
l
t
s
o
b
t
a
i
ne
d
by
t
h
e
pr
o
po
s
e
d
a
l
go
r
i
t
hm
w
i
t
h
s
o
m
e
o
t
h
e
r
kn
o
wn
a
l
go
r
i
t
hm
s
.
T
h
e
r
e
s
u
l
t
s
s
h
o
w
t
h
a
t
t
h
e
I
L
S
a
l
go
r
i
t
hm
i
s
v
e
r
y
f
l
e
x
i
bl
e
a
n
d
o
f
f
e
r
i
n
g
m
a
ny
im
p
l
e
m
e
n
t
a
t
i
o
n
o
p
t
i
o
ns
to
t
h
e
de
v
e
l
o
p
e
r
s
i
n
t
hi
s
r
e
s
pe
c
t
.
T
h
e
r
e
m
a
i
n
i
ng
o
f
t
hi
s
pa
pe
r
i
s
o
r
ga
ni
z
e
d
a
s
f
o
l
l
o
w
s
:
s
e
c
t
i
o
n
2
r
e
vi
e
ws
s
o
m
e
o
f
t
h
e
r
e
l
a
t
e
d
l
i
t
e
r
a
t
ur
e
.
Ne
x
t
,
t
h
e
r
e
s
e
a
r
c
h
m
e
t
h
o
d
o
f
t
hi
s
wo
r
k
i
s
pr
e
s
e
n
t
e
d
i
n
s
e
c
t
i
o
n
3.
T
h
e
n
,
s
e
c
t
i
o
n
4
de
s
c
r
i
be
s
t
h
e
pe
r
f
o
r
m
a
n
c
e
e
v
a
l
ua
t
i
o
n
o
f
t
h
e
pr
o
p
o
s
e
d
a
l
go
r
i
t
hm
.
S
e
c
t
i
o
n
5
c
o
n
t
a
i
n
s
t
h
e
e
x
pe
r
im
e
n
t
a
l
r
e
s
u
l
t
s
o
f
t
h
e
wo
r
k
a
l
o
n
g
w
i
t
h
t
h
e
d
i
s
c
us
s
i
o
ns
.
F
i
na
l
ly
,
t
h
e
pa
pe
r
i
s
c
o
n
c
l
ude
d
i
n
s
e
c
t
i
o
n
6
.
2.
RE
L
AT
E
D
WORK
S
T
hi
s
s
e
c
t
i
o
n
pr
o
vi
de
s
a
b
r
i
e
f
o
v
e
r
vi
e
w
o
f
t
h
e
r
e
l
a
t
e
d
wor
k
i
n
whi
c
h
m
e
t
a
h
e
ur
i
s
t
i
c
s
ha
ve
be
e
n
us
e
d
i
n
s
c
h
e
du
li
ng
s
c
i
e
n
t
i
f
i
c
wo
r
k
f
l
o
ws
.
I
n
de
e
d,
i
t
i
n
c
l
ud
e
s
a
b
r
i
e
f
pr
e
s
e
n
t
a
t
i
o
n
o
f
t
h
e
pr
o
bl
e
m
s
a
n
d
t
h
e
p
r
o
p
o
s
e
d
im
pr
o
v
e
m
e
n
t
s
to
t
h
e
I
L
S
a
l
go
r
i
t
hm
.
M
e
t
a
h
e
ur
i
s
t
i
c
s
a
r
e
a
l
go
r
i
t
hm
s
t
h
a
t
c
a
n
b
e
us
e
d
t
o
s
o
l
v
e
a
va
r
i
e
t
y
o
f
o
p
t
i
mi
z
a
t
i
o
n
i
s
s
ue
s
.
T
h
e
r
e
a
r
e
m
a
ny
m
e
t
a
h
e
ur
is
t
i
c
s
b
a
s
e
d
o
pt
i
mi
z
a
t
i
o
n
a
ppr
o
a
c
h
e
s
f
o
r
s
c
h
e
d
u
l
i
ng
o
f
wo
r
kf
l
o
w.
Hu
e
t
al.
[
8
]
s
ugge
s
t
e
d
a
n
a
l
go
r
i
t
hm
o
f
m
u
l
t
i
o
bj
e
c
t
i
v
e
s
c
he
du
l
i
ng
(
M
OS)
b
a
s
e
d
o
n
pa
r
t
i
c
le
s
wa
r
m
o
p
t
i
mi
z
a
t
i
o
n
(
P
S
O)
t
h
a
t
a
i
m
s
t
o
de
c
r
e
a
s
e
t
h
e
c
o
s
t
a
n
d
m
a
ke
s
p
a
n
a
n
d
s
a
t
i
s
f
yi
ng
t
e
r
m
s
o
f
t
h
e
r
e
l
i
a
bil
i
t
y
.
Al
s
o
,
M
a
n
a
s
r
a
h
a
n
d
Al
i
[
9]
de
s
i
g
n
e
d
a
GA
-
P
S
O
hy
br
id
i
z
e
d
a
l
go
r
i
t
hm
t
h
a
t
t
a
r
ge
t
s
to
de
c
r
e
a
s
e
t
h
e
m
a
k
e
s
pa
n
a
n
d
c
o
s
t,
a
s
we
ll
a
s
b
a
l
a
n
c
i
ng
t
h
e
l
o
a
d
o
f
c
o
n
t
i
n
ge
n
t
t
a
s
ks
.
T
hi
s
a
l
go
r
i
t
hm
i
s
a
ll
o
c
a
t
i
n
g
t
a
s
ks
t
o
t
h
e
r
e
s
o
ur
c
e
s
.
F
ur
t
h
e
r
m
o
r
e
,
S
o
n
g
e
t
al.
[
10]
i
n
t
r
o
duc
e
d
a
w
o
r
kf
lo
w
m
o
de
l
w
i
t
h
c
o
m
po
s
i
t
e
t
a
s
ks
.
T
h
e
y
de
v
e
l
o
pe
d
a
n
e
s
t
e
d
pa
r
t
i
c
l
e
s
wa
r
m
o
pt
i
m
i
z
a
t
i
o
n
w
hi
c
h
us
e
s
t
wo
t
y
pe
s
o
f
po
pu
l
a
t
i
o
n
(
t
h
e
o
ut
e
r
po
pul
a
t
i
o
n
s
a
n
d
th
e
i
nne
r
po
pul
a
t
i
o
n
s
)
.
T
he
o
ut
e
r
p
o
pul
a
t
i
o
ns
a
r
e
im
pr
o
vi
ng
t
h
e
s
c
he
du
l
i
ng
i
ns
t
r
uc
t
i
o
n
o
f
t
a
s
ks
,
a
n
d
t
h
e
i
nne
r
po
pul
a
t
i
o
n
s
a
r
e
e
nha
n
c
i
ng
t
h
e
s
e
r
vi
c
e
i
ns
t
a
n
c
e
s
mi
s
s
i
o
n
.
M
a
i
o
a
n
d
Kim
o
vs
k
i
[
11]
pr
o
p
o
s
e
d
a
m
u
l
t
i
-
o
bj
e
c
t
i
v
e
wo
r
kf
l
o
w
o
f
f
l
o
a
d
i
n
g
(
M
O
W
O)
a
l
go
r
i
t
hm
ba
s
e
d
o
n
t
h
e
NSGA
-
I
I
m
e
t
a
h
e
ur
i
s
t
i
c
,
w
i
t
h
t
h
e
go
a
l
o
f
r
e
duc
i
n
g
r
e
s
po
n
s
e
t
i
m
e
,
e
f
f
i
c
i
e
n
c
y
,
a
n
d
e
x
pe
n
s
e
.
T
h
e
i
r
s
t
r
a
t
e
gy
i
s
b
a
s
e
d
o
n
t
h
e
pa
r
e
t
o
pr
i
n
c
i
p
l
e
.
Al
s
o
,
M
a
e
t
al.
[
12]
o
f
f
e
r
e
d
a
de
a
d
li
ne
a
n
d
t
h
e
c
o
s
t
a
wa
r
e
ge
n
e
t
i
c
o
pt
i
mi
z
a
t
i
o
n
a
l
go
r
i
t
hm
,
a
i
mi
ng
t
o
r
e
duc
e
t
h
e
c
o
s
t
o
f
e
x
e
c
ut
i
o
n
w
i
t
h
t
e
r
m
s
o
f
de
a
d
li
ne
.
F
i
r
s
t
,
t
h
e
y
d
i
vi
d
e
d
t
h
e
t
a
s
ks
i
n
t
o
di
f
f
e
r
e
n
t
l
e
v
e
l
s
.
Af
t
e
r
t
h
a
t
,
t
h
e
y
g
e
n
e
r
a
t
e
d
i
nd
i
v
i
dua
l
s
w
i
t
h
m
i
n
im
a
l
t
i
m
e
a
n
d
c
o
s
t.
T
o
a
c
c
ur
a
t
e
l
y
r
e
pr
e
s
e
n
t
t
h
e
c
l
o
ud'
s
h
e
t
e
r
o
ge
n
e
o
us
a
n
d
r
o
b
us
t
pr
o
pe
r
t
i
e
s
,
t
h
r
e
e
s
tr
i
n
g
s
we
r
e
us
e
d
to
c
o
de
t
h
e
ge
n
e
s
i
n
t
h
e
pr
o
p
o
s
e
d
a
l
go
r
i
t
hm
.
F
a
r
a
ga
r
d
i
e
t
al.
[
13]
i
n
t
r
o
duc
e
d
a
h
e
t
e
r
o
ge
n
e
o
us
e
a
r
l
i
e
s
t
f
i
n
i
s
h
t
i
m
e
(
HE
F
T
)
m
o
d
i
f
i
c
a
t
i
o
n
a
n
d
a
gr
e
e
d
y
r
e
s
o
ur
c
e
pr
o
v
i
s
i
o
ni
ng
(
GR
P
)
a
l
go
r
i
t
hm
,
t
h
a
t
o
r
ga
ni
z
e
s
t
h
e
i
ns
t
a
n
c
e
t
y
pe
s
i
n
t
o
gr
o
ups
b
a
s
e
d
o
n
t
h
e
i
r
pe
r
f
o
r
m
a
n
c
e
.
T
h
e
a
i
m
wa
s
t
o
m
i
n
im
i
z
e
t
h
e
m
a
k
e
s
pa
n
w
hil
e
t
a
ki
n
g
i
n
t
o
c
o
n
s
i
de
r
a
t
i
o
n
a
b
udge
t
l
i
mi
t
a
t
i
o
n
f
o
r
t
h
e
c
o
s
t
-
pe
r
-
h
o
u
r
.
T
h
e
y
a
d
j
u
s
t
e
d
t
h
e
HE
F
T
a
l
go
r
i
t
hm
to
c
o
n
s
i
de
r
t
h
e
b
udg
e
t
l
im
i
t
.
F
i
na
ll
y
,
i
n
t
h
e
wo
r
k
by
A
d
hi
ka
r
i
e
t
al.
[
14]
t
h
e
wo
r
kl
o
a
d
o
f
c
l
o
ud
s
e
r
v
e
r
s
,
m
a
k
e
s
pa
n
,
r
e
s
o
ur
c
e
us
a
ge
,
a
n
d
s
t
a
bil
i
t
y
we
r
e
t
h
e
go
a
l
s
o
f
a
wo
r
kf
l
o
w
s
c
h
e
du
li
ng
a
ppr
o
a
c
h
b
a
s
e
d
o
n
t
h
e
f
i
r
e
f
ly
a
l
go
r
i
t
hm
(
F
A
)
.
C
o
n
c
e
r
i
n
g
t
h
e
I
L
S
a
l
g
or
i
t
hm
,
I
L
S
h
a
s
b
e
e
n
us
e
d
i
n
m
a
ny
f
i
e
l
ds
i
n
c
l
ud
i
n
g,
th
e
tr
a
v
e
l
l
i
n
g
s
a
l
e
s
m
a
n
pr
o
b
l
e
m
[
15
]
,
[
16
]
,
v
e
hi
c
l
e
r
ou
t
i
n
g
p
r
o
bl
e
m
[
17
]
,
[
1
8
]
,
f
l
ow
-
s
h
o
p
p
r
o
b
l
e
m
[
1
9
]
,
[
20
]
,
tas
k
s
c
h
e
d
u
l
i
ng
o
n
c
l
oud
c
o
m
pu
t
i
n
g
[
2
1
]
,
pr
e
c
e
de
n
c
e
-
c
o
n
s
tr
a
i
n
t
ta
s
k
l
i
s
t
s
c
h
e
dul
i
n
g
[
22
]
,
t
h
e
p
a
r
a
l
l
e
l
m
a
c
hi
n
e
s
c
h
e
dul
i
n
g
p
r
o
b
l
e
m
s
[
2
3
]
,
a
n
d
t
h
e
q
ua
dr
a
t
i
c
a
s
s
i
gnm
e
n
t
p
r
o
b
l
e
m
[
24
]
.
S
e
v
e
r
a
l
e
n
h
a
n
c
e
m
e
n
t
s
we
r
e
p
r
op
o
s
e
d
o
v
e
r
t
i
m
e
i
n
c
l
udi
n
g,
us
i
n
g
c
l
us
te
r
s
a
n
d
a
m
o
di
f
i
e
d
m
u
l
t
i
-
r
e
s
ta
r
t
[
1
5
]
,
u
s
i
n
g
m
u
l
t
i
t
y
pe
s
o
f
n
e
i
ghb
o
r
h
oods
m
o
v
e
s
[
17
]
,
I
L
S
m
e
m
or
y
-
b
a
s
e
d
[
18
]
,
us
e
o
f
a
b
i
a
s
e
d
-
r
a
n
d
o
m
i
z
e
d
[
2
0
]
,
[2
5
]
,
a
n
d
h
y
b
r
i
d
w
i
t
h
ot
h
e
r
m
e
tah
e
u
r
i
s
t
i
c
s
a
l
g
or
i
t
hm
s
[
21
]
,
[
22
]
.
I
n
t
h
i
s
pa
pe
r
,
t
h
e
I
L
S
a
l
g
o
r
i
t
hm
i
s
i
m
p
l
e
men
ted
f
or
s
c
i
e
n
t
i
f
i
c
w
or
kf
l
o
w
s
c
h
e
d
u
l
i
n
g
,
a
n
d
a
c
c
or
di
n
g
to
th
e
a
u
t
h
or
s
'
kn
ow
l
e
dg
e
,
t
h
i
s
i
m
p
l
e
m
e
n
ta
t
i
o
n
i
s
n
e
w
i
n
t
hi
s
d
o
m
a
i
n
.
I
n
a
d
di
t
i
o
n
,
t
h
e
pe
r
f
or
m
a
n
c
e
o
f
t
h
e
a
l
g
or
i
th
m
i
s
a
n
a
l
y
z
e
d
by
m
od
i
f
y
i
n
g
i
m
p
or
t
a
n
t
p
a
r
a
m
e
ter
s
i
n
t
h
e
a
l
g
or
i
t
hm
.
T
h
e
g
oa
l
o
f
t
h
i
s
w
or
k
i
s
to
r
e
duc
e
t
h
e
m
a
k
e
s
p
a
n
.
3.
RE
S
E
AR
CH
M
E
T
HO
D
I
n
t
hi
s
s
e
c
t
i
o
n
,
s
y
s
t
e
m
m
o
de
l
s
w
il
l
b
e
de
s
c
r
i
be
d
to
i
ll
us
t
r
a
t
e
t
h
e
wo
r
ki
n
g
e
nvi
r
o
nm
e
n
t
.
T
h
e
c
l
o
ud
a
n
d
w
o
r
k
f
l
o
w
m
o
de
l
s
w
il
l
b
e
de
s
c
r
i
b
e
d,
w
hi
c
h
a
r
e
n
e
c
e
s
s
a
r
y
t
o
vi
s
ua
li
z
e
a
n
d
u
n
de
r
s
t
a
n
d
t
h
e
pr
o
pos
e
d
wo
r
k
m
o
de
l
.
T
h
e
n
we
e
x
p
l
a
i
n
t
h
e
i
t
e
r
a
t
e
d
l
o
c
a
l
s
e
a
r
c
h
a
lgo
r
i
t
hm
a
n
d
i
t
s
s
t
e
ps
,
i
n
c
l
ud
i
ng
t
h
e
l
o
c
a
l
s
e
a
r
c
h
a
l
go
r
i
t
hm
.
3
.
1.
S
ys
t
e
m
m
od
e
l
in
g
3.
1.
1.
Cl
ou
d
m
od
e
l
T
h
e
c
l
o
u
d
m
ode
l
c
o
n
s
i
s
t
s
o
f
da
ta
c
e
n
t
e
r
s
,
e
a
c
h
da
ta
c
e
n
ter
c
o
n
s
i
s
t
s
o
f
s
e
v
e
r
a
l
phy
s
i
c
a
l
m
a
c
hi
n
e
s
.
E
a
c
h
r
e
s
ou
r
c
e
h
a
s
p
r
o
c
e
s
s
i
n
g
c
a
pa
c
i
t
y
,
s
tor
a
ge
,
m
e
m
or
y
,
a
n
d
b
a
n
dwi
d
t
h
.
T
h
e
c
l
oud
p
r
o
v
i
de
s
d
i
f
f
e
r
e
n
t
t
y
p
e
s
o
f
VM
s
.
T
h
e
c
o
n
f
i
gur
a
t
i
o
n
o
f
t
h
e
VM
t
y
pe
v
a
r
i
e
s
c
o
n
c
e
r
ni
ng
t
h
e
pe
r
f
or
m
a
n
c
e
o
f
t
h
e
C
P
U
,
m
e
m
or
y
,
s
tor
a
g
e
,
b
a
n
dwi
d
t
h
,
a
n
d
op
e
r
a
t
i
n
g
s
y
s
te
m
.
T
h
e
p
r
i
c
e
o
f
t
h
e
VM
i
s
t
h
e
c
os
t
p
e
r
un
i
t
t
i
m
e
i
n
ter
v
a
l
.
I
t
s
h
oul
d
b
e
n
oted
th
a
t
VM
s
c
a
n
b
e
a
c
q
u
i
r
e
d
a
n
d
te
r
m
i
n
a
t
e
d
a
t
a
ny
t
i
m
e
.
W
o
r
kf
l
o
ws
c
a
n
b
e
s
c
h
e
dul
e
d
f
or
a
ny
o
f
t
h
e
a
v
a
i
l
a
bl
e
r
e
s
ou
r
c
e
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
do
n
e
s
i
a
n
J
E
l
e
c
E
n
g
&
C
o
m
p
S
c
i
I
S
S
N:
2502
-
4752
Optimiz
e
d
s
c
he
duli
ng
of
s
c
ienti
f
ic
w
o
r
k
f
lo
w
s
bas
e
d
on
it
e
r
ated
local
s
e
ar
c
h
(
A
laa
A
bdalqahar
J
ihad
)
1617
3.
1.
2.
Wor
k
f
l
ow
m
od
e
l
T
h
e
wo
r
kf
l
o
w
(
W
)
c
o
ns
i
s
t
s
o
f
a
s
e
t
o
f
c
o
m
put
a
ti
o
n
a
l
t
a
s
ks
w
i
t
h
de
p
e
n
de
n
c
y
c
o
ns
t
r
a
i
n
t
s
b
e
t
we
e
n
t
h
e
m
[
26]
a
n
d
i
s
r
e
pr
e
s
e
n
t
e
d
a
s
a
D
A
G.
I
t
i
s
de
f
i
ne
d
by
t
wo
s
e
t
s
W
(
T
,
E
)
,
wh
e
r
e
T
i
s
t
he
s
e
t
o
f
n
-
t
a
s
ks
,
a
n
d
E
i
s
t
he
s
e
t
o
f
de
pe
n
d
e
n
c
i
e
s
be
t
we
e
n
t
h
e
s
e
t
a
s
ks
.
T
h
e
t
a
s
k
s
t
a
r
t
s
wh
e
n
y
o
u
r
e
c
e
i
ve
i
nput
da
t
a
f
r
o
m
pr
e
vi
o
us
t
a
s
ks
,
a
n
d
e
n
d
s
w
h
e
n
y
o
u
s
e
n
d
o
ut
pu
t
da
t
a
to
s
ubs
e
que
n
t
t
a
s
ks
.
T
h
e
t
a
s
k
t
h
a
t
h
a
s
n
o
pr
e
vi
o
us
t
a
s
k
i
s
c
a
ll
e
d
t
h
e
i
n
put
t
a
s
k,
a
n
d
t
h
e
t
a
s
k
t
h
a
t
d
o
e
s
n
o
t
h
a
v
e
a
ny
s
ub
s
e
que
n
t
t
a
s
k
i
s
c
a
l
l
e
d
t
h
e
e
xi
t
t
a
s
k.
E
a
c
h
T
i
t
a
s
k
i
n
t
h
e
wo
r
kf
l
o
w
h
a
s
l
e
n
gt
h
,
r
e
qu
i
r
e
d
pr
o
c
e
s
s
i
n
g
e
l
e
m
e
n
t
s
,
de
a
dl
i
ne
,
t
r
a
n
s
f
e
r
f
il
e
s
i
z
e
,
l
i
s
t
s
f
o
r
pa
r
e
n
t
a
n
d
c
hil
d
t
a
s
ks
.
T
h
e
e
xe
c
ut
i
o
n
t
i
m
e
o
f
a
t
a
s
k
de
pe
n
d
s
o
n
i
t
s
l
e
n
gt
h
(
i
n
M
I
)
a
n
d
t
h
e
pe
r
f
o
r
m
a
n
c
e
o
f
t
h
e
VM
(
i
n
M
I
P
S
)
t
h
a
t
i
s
us
e
d
t
o
pe
r
f
o
r
m
t
h
e
t
a
s
k.
F
o
r
i
ll
u
s
t
r
a
t
i
o
n
,
F
i
gur
e
1
(
a
)
i
s
a
n
e
x
a
m
p
l
e
o
f
a
wo
r
kf
l
o
w
w
i
t
h
n=
5
t
a
s
ks
.
I
f
t
a
s
k
T
5
i
s
t
h
e
l
a
s
t
t
a
s
k,
we
n
e
e
d
t
o
f
i
ni
s
h
pr
o
c
e
s
s
i
ng
T
3
a
nd
T
4
a
n
d
t
h
e
n
c
o
m
bi
ne
t
h
e
i
r
o
ut
pu
t
s
a
s
i
n
put
f
o
r
t
a
s
k
T
5
to
b
e
pr
o
c
e
s
s
e
d,
t
a
s
k
T
4
do
e
s
n
ot
p
r
o
c
e
s
s
u
n
t
i
l
t
a
s
k
T
2
i
s
c
o
m
p
l
e
t
e
d,
a
n
d
s
o
o
n
.
T
h
e
t
a
s
k
i
s
n
o
t
i
m
p
le
m
e
n
t
e
d
un
t
i
l
a
ll
t
h
e
l
i
s
t
o
f
pa
r
e
n
t
s
a
r
e
pr
o
c
e
s
s
e
d
a
n
d
t
h
e
i
r
o
u
t
pu
t
s
a
r
e
r
e
c
e
i
ve
d
.
E
v
e
r
y
t
a
s
k
t
h
a
t
i
s
h
a
n
d
l
e
d
s
e
n
d
s
i
t
s
o
u
t
pu
t
s
to
i
t
s
l
i
s
t
o
f
c
hil
d
s
.
I
n
de
e
d,
e
a
c
h
wo
r
k
f
l
o
w
t
a
s
k
h
a
s
t
h
e
f
o
ll
o
w
i
ngs
:
i
)
T
a
s
k
e
x
e
c
ut
i
o
n
t
i
me:
F
o
r
a
g
i
v
e
n
t
a
s
k,
t
h
e
t
i
m
e
r
e
qu
i
r
e
d
t
o
e
x
e
c
ut
e
t
h
a
t
t
a
s
k
w
i
t
hi
n
t
h
e
VM
;
ii
)
T
a
s
k
s
t
a
r
t
t
i
m
e
:
T
h
e
s
t
a
r
t
t
i
m
e
o
f
t
h
e
t
a
s
k
i
ns
i
de
t
h
e
VM
i
s
c
a
l
c
u
l
a
t
e
d
by
:
(
)
=
{
m
a
x
{
(
)
,
m
a
x
{
(
)
}
}
ℎ
(
1)
wh
e
r
e
t
j
∈
pa
r
e
n
t
(
t
i
)
,
a
n
d
Av
a
i
T
im
e
(
V
M
t
i
)
i
s
t
h
e
e
a
r
l
i
e
s
t
t
i
m
e
w
h
e
n
V
M
t
i
r
e
a
d
y
t
o
e
x
c
ut
a
ny
t
a
s
k
;
a
n
d
ii
i
)
T
a
s
k
f
i
ni
s
h
t
i
m
e
:
I
t
i
s
t
h
e
s
t
a
r
t
t
i
m
e
o
f
t
h
e
t
a
s
k
wi
t
h
t
h
e
ti
m
e
t
h
e
t
a
s
k
i
s
e
x
e
c
ut
e
d.
T
h
e
t
i
m
e
a
va
i
l
a
bl
e
f
o
r
t
h
e
VM
w
i
ll
a
l
s
o
be
upda
t
e
d
a
t
t
hi
s
t
i
m
e
,
c
a
l
c
u
l
a
t
e
d
by
(
2)
:
(
)
=
(
)
+
(
)
+
∑
(
,
)
(
2)
wh
e
r
e
ET
(
t
i
)
i
s
e
x
e
c
ut
i
o
n
t
i
m
e
,
TT
(
t
j
,
t
i
)
i
s
t
r
a
n
s
f
e
r
c
o
s
t
b
e
t
we
e
n
t
j
a
n
d
t
i
,
a
n
d
t
j
∈
par
e
nt
(
t
i
).
3
.
2
.
I
t
e
r
at
e
d
l
oc
a
l
s
e
a
r
c
h
T
h
e
I
L
S
a
l
go
r
i
t
hm
i
s
o
n
e
o
f
t
h
e
m
e
t
a
h
e
ur
i
s
t
i
c
a
l
g
o
r
i
t
hm
s
t
h
a
t
pr
o
c
e
s
s
o
n
e
s
o
l
ut
i
o
n
a
t
a
t
i
m
e
(
s
i
ng
l
e
s
o
l
ut
i
o
n
b
a
s
e
d)
;
i
n
t
hi
s
pa
pe
r
t
h
e
pr
o
p
o
s
e
d
I
L
S
i
s
il
l
us
t
r
a
t
e
d
i
n
A
l
go
r
i
t
hm
1,
h
a
s
a
m
o
du
l
a
r
n
a
t
ur
e
t
h
a
t
m
a
ke
s
i
t
a
da
pt
a
bl
e
a
s
a
b
a
s
i
c
t
e
m
p
l
a
t
e
f
o
r
de
s
i
g
ni
ng
a
l
go
r
i
t
hm
s
[
27]
.
Al
go
r
i
t
hm
1
.
I
t
e
r
a
t
e
d
l
o
c
a
l
s
e
a
r
c
h
Input:
Tasks of workflow (
T
) and available virtual machines (
VMs
)
Output:
The best schedule (
Schedule
) for assigning
VMs
to
T
1: Parameters initializing: number of non improvement iteration
NonItr
, number of
neighbors
N
, and perturbation ratio
Pr
.
2:
S
current
= Generate a random initial solution
3:
S
current
= LocalSearch(
S
current
,
N
)
4:
S
best
= S
curre
nt
5:
i
=1
6: While
i
<
NonItr
do
7:
S
perturbation
= Perturbation(
S
current
,
Pr
)
8:
S
perturbation
= LocalSearch(
S
perturbation
,
N
)
9:
if
f(S
perturbation
)
<
f(S
best
)
10:
S
best=
S
perturbation
11:
i
=1
12:
else
13:
i
=
i
+1
14:
S
current
= AcceptanceCriterion(
S
current
,
S
perturbation
)
15: end while
T
h
e
r
e
a
r
e
f
o
ur
m
a
i
n
c
o
m
po
n
e
n
t
s
o
f
t
h
e
I
L
S
a
l
go
r
i
t
hm
t
o
c
o
n
s
i
d
e
r
[
28]
:
i
)
I
ni
t
i
a
l
s
o
l
ut
i
o
n
:
g
e
n
e
r
a
t
e
a
n
e
m
pt
y
s
c
h
e
du
l
e
(
Sc
he
dule
)
w
h
e
r
e
t
h
e
l
e
n
gt
h
o
f
s
c
h
e
du
l
e
e
qua
l
to
n
u
m
b
e
r
o
f
t
a
s
ks
a
n
d
e
a
c
h
i
nde
x
r
e
pr
e
s
e
n
t
t
h
e
t
a
s
k
i
d
(
t
i
)
.
R
a
n
do
m
ly
a
s
s
i
g
n
V
M
s
f
o
r
e
a
c
h
t
a
s
k
(
t
i
)
c
a
l
c
u
l
a
t
e
t
h
e
c
o
s
t
(
M
a
ke
s
pa
n)
o
f
t
h
e
ge
n
e
r
a
t
e
d
s
o
l
ut
i
o
n
;
i
i
)
L
o
c
a
l
s
e
a
r
c
h
:
i
n
o
r
de
r
to
i
nve
s
t
t
h
e
s
e
a
r
c
h
s
pa
c
e
,
t
h
e
l
o
c
a
l
s
e
a
r
c
h
a
l
go
r
i
t
hm
(
H
il
l
c
l
a
m
p
i
ng
)
i
s
a
do
pt
e
d.
Hi
ll
-
c
l
im
b
i
ng
i
s
pe
r
h
a
p
s
t
h
e
s
im
p
l
e
s
t
a
n
d
o
l
de
s
t
m
e
t
a
h
e
ur
i
s
t
i
c
m
e
t
h
o
d.
I
t
s
t
a
r
t
s
w
i
t
h
a
g
i
v
e
n
i
n
i
t
i
a
l
s
o
l
ut
i
o
n
.
A
t
e
a
c
h
i
t
e
r
a
t
i
o
n
,
t
h
e
h
e
ur
i
s
t
i
c
i
s
r
e
p
l
a
c
e
d
t
h
e
c
ur
r
e
n
t
s
o
l
ut
i
o
n
w
i
t
h
a
n
a
d
j
a
c
e
n
t
s
o
l
ut
i
o
n
t
h
a
t
i
s
be
tt
e
r
t
h
a
n
t
h
e
c
ur
r
e
n
t
o
n
e
t
h
a
t
i
m
pr
o
v
e
s
t
h
e
o
b
j
e
c
t
i
v
e
f
u
n
c
t
i
o
n
[
29]
.
Al
go
r
i
t
hm
2
il
l
us
t
r
a
t
e
d
t
h
e
m
a
i
n
s
t
e
ps
o
f
t
h
e
ut
il
i
z
e
d
l
o
c
a
l
s
e
a
r
c
h
,
i
n
t
hi
s
a
l
go
r
i
t
hm
t
h
e
i
n
i
t
i
a
l
s
o
l
ut
i
o
n
(
S
0
)
c
o
m
e
s
f
r
o
m
t
h
e
s
t
e
ps
o
f
t
h
e
I
L
S
;
i
ii
)
P
e
r
t
u
r
b
a
t
i
o
n
:
i
t
i
s
t
h
e
pr
o
c
e
s
s
o
f
s
e
l
e
c
t
e
d
a
n
d
c
h
a
nge
d
a
pa
r
t
o
f
t
h
e
s
o
l
ut
i
o
n
t
o
e
s
c
a
pe
f
r
o
m
t
h
e
o
pt
i
m
u
m
s
o
l
ut
i
o
n
,
t
h
e
pe
r
t
u
r
b
a
t
i
o
ns
s
h
o
u
l
d
b
e
m
a
de
i
n
a
pr
o
po
r
t
i
o
n
t
h
a
t
i
s
n
o
t
too
l
a
r
ge
a
n
d
a
t
t
h
e
s
a
m
e
t
i
m
e
n
o
t
too
s
m
a
ll
[
27]
;
i
v
)
A
c
c
e
pt
a
n
c
e
c
r
i
t
e
r
i
o
n
:
i
t
i
s
s
e
l
e
c
t
t
h
e
s
o
l
ut
i
o
n
t
h
a
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2502
-
4752
I
n
do
n
e
s
i
a
n
J
E
l
e
c
E
n
g
&
C
o
m
p
S
c
i
,
Vo
l
.
25
,
N
o
.
3
,
M
a
r
c
h
20
22
:
1615
-
1624
1618
w
i
ll
c
o
n
t
i
n
ue
i
n
t
h
e
ne
x
t
i
t
e
r
a
t
i
o
n
;
a
n
d
v
)
T
h
e
s
o
l
ut
i
o
n
i
s
r
e
pr
e
s
e
n
t
e
d
a
s
i
n
F
i
gur
e
1(
b
)
,
wh
e
r
e
t
h
e
l
o
c
a
t
i
o
n
r
e
f
e
r
s
to
t
h
e
t
a
s
k
n
u
m
b
e
r
a
n
d
t
h
e
c
e
l
l
d
a
t
a
r
e
f
e
r
s
to
t
h
e
n
u
m
be
r
o
f
t
h
e
VM
a
s
s
i
g
n
e
d
t
o
i
t
.
(
a
)
(
b
)
F
i
gur
e
1.
T
h
e
w
o
r
kf
l
o
w
m
o
de
l
a
n
d
h
o
w
i
t
i
s
r
e
pr
e
s
e
n
t
e
d
i
n
(
a
)
w
o
r
kf
l
o
w
w
i
t
h
f
i
ve
t
a
s
ks
a
n
d
(
b
)
r
e
pr
e
s
e
n
t
a
t
i
o
n
o
f
t
h
e
s
o
l
ut
i
o
n
Al
go
r
i
t
hm
2
.
L
o
c
a
l
s
e
a
r
c
h
Input:
initial solution (
S
0
), number of neighbors
N // S
0
Solution from ILS Steps
Output:
The best solution
S
best
(local optima).
1:
S
current
=
S
0
2:
NoImprovement
= 0
3: While
NoImprovement
= 0Do
4:
NoImprovement
= 1
5:
Neighbors
(
S
current
)
Generate
N
candidate solutions (
S
c
)
∈
Neighbors of
S
current
6:
for each
S
c
in
Neighbors
(
S
current
)
7:
if
f(S
c
)
<
f(S
current
)
8:
S
current
=
S
c
9:
NoImprovement
= 0
10:
Endfor
11: Endwhile
4.
P
E
R
F
ORM
AN
CE
E
VA
L
UA
T
I
ON
I
n
t
hi
s
s
e
c
t
i
o
n
,
we
e
x
p
l
o
r
e
t
h
e
de
t
a
i
l
s
o
f
t
h
e
r
e
l
e
v
a
n
t
pe
r
f
o
r
m
a
nc
e
e
v
a
l
u
a
t
i
o
n
pa
r
a
m
e
t
e
r
s
a
n
d
e
x
p
l
a
in
h
o
w
t
h
e
y
a
r
e
c
a
l
c
u
l
a
t
e
d
a
n
d
a
d
j
u
s
t
e
d
i
n
t
h
e
v
a
r
i
o
u
s
c
o
n
s
i
d
e
r
e
d
s
c
e
n
a
r
i
o
s
.
T
h
e
e
x
pe
r
im
e
n
t
a
l
s
e
t
up
a
nd
m
e
t
r
i
c
t
h
a
t
wa
s
us
e
d
i
n
t
h
e
e
v
a
l
u
a
t
i
o
n
w
il
l
b
e
e
x
p
l
a
i
ne
d.
I
n
a
dd
i
t
i
o
n
t
o
e
x
p
l
a
i
n
i
ng
t
h
e
c
a
l
c
u
l
a
t
i
o
n
o
f
m
a
ke
s
pa
n
a
l
go
r
i
t
hm
.
4
.
1.
E
x
p
e
r
im
e
n
t
a
l
s
e
t
u
p
T
o
c
o
m
pa
r
e
t
h
e
pe
r
f
o
r
m
a
nc
e
o
f
t
h
e
I
L
S
a
l
go
r
i
t
h
m
,
W
o
r
k
f
l
o
wS
i
m
s
i
m
u
l
a
t
o
r
[
30
]
h
a
s
be
e
n
us
e
d
f
o
r
t
h
e
i
m
p
l
e
m
e
n
t
a
t
i
o
n
.
W
o
r
kf
l
o
wS
im
i
s
a
n
im
pr
o
v
e
m
e
n
t
f
o
r
C
l
o
udS
i
m
t
o
s
i
m
u
l
a
t
e
s
c
i
e
n
t
i
f
i
c
wo
r
kf
l
o
w
i
n
c
l
o
ud
c
o
m
put
i
n
g
.
W
e
ha
v
e
t
a
ke
n
m
e
a
s
ur
e
s
o
n
pe
r
s
o
n
a
l
c
o
m
put
e
r
wi
t
h
t
h
e
f
o
l
l
o
w
i
ng
c
o
nf
i
gur
a
t
i
o
n
:
I
n
t
e
l
C
o
r
e
i
7
2.
10
GH
z
16
GB
m
e
m
o
r
y
,
r
u
n
o
n
W
i
ndo
ws
10.
T
h
e
d
if
f
e
r
e
n
t
e
x
p
e
r
i
m
e
n
t
s
a
r
e
t
h
e
r
e
s
u
l
t
o
f
t
he
a
pp
l
ica
t
i
o
n
o
f
s
e
v
e
r
a
l
V
M
a
ll
o
c
a
t
i
o
n
.
F
i
ve
V
M
s
we
r
e
u
s
e
d
i
n
t
he
t
e
s
t.
T
a
bl
e
1
pr
e
s
e
n
t
s
t
h
e
s
pe
c
i
f
i
c
a
t
i
o
n
s
o
f
VM
s
us
e
d
in
t
h
e
s
im
u
l
a
t
i
o
n
.
T
h
e
pr
o
po
s
e
d
a
l
go
r
i
t
hm
i
s
e
v
a
l
u
a
t
e
d
by
us
i
ng
f
o
ur
t
y
pe
s
o
f
r
e
a
l
i
s
t
i
c
wo
r
kf
l
o
w
s
,
n
a
m
e
l
y
M
o
n
t
a
ge
,
C
y
b
e
r
S
h
a
ke
,
E
p
i
ge
n
o
m
i
c
s
,
I
n
s
p
i
r
a
l
,
a
n
d
f
o
r
s
e
ve
r
a
l
i
ns
t
a
nc
e
s
.
T
a
bl
e
1
.
T
h
e
s
pe
c
i
f
i
c
a
t
i
o
n
s
o
f
VM
s
V
M
s
R
A
M
B
a
ndw
id
th
M
I
P
S
N
o
. C
P
U
0
512
800
800
1
1
512
900
900
1
2
512
500
500
1
3
512
600
600
1
4
512
700
700
1
4
.
2.
E
val
u
at
ion
m
e
t
r
ic
T
h
e
m
a
i
n
m
e
t
r
i
c
u
s
e
d
t
o
s
t
udy
t
h
e
pe
r
f
o
r
m
a
n
c
e
o
f
t
h
e
pr
o
p
o
s
e
d
a
l
go
r
i
t
hm
i
s
m
a
ke
s
pa
n
.
M
a
ke
s
pa
n
i
s
de
f
i
ne
d
a
s
t
h
e
c
o
m
p
l
e
t
i
o
n
t
i
m
e
o
f
t
h
e
o
ut
pu
t
tas
k
t
o
e
n
d
t
h
e
a
pp
l
i
c
a
t
i
o
n
[
29]
.
M
a
ke
s
pa
n
c
a
n
a
l
s
o
b
e
de
f
i
ne
d
a
s
t
h
e
s
c
he
du
l
e
l
e
n
gt
h
f
o
r
e
x
e
c
ut
i
n
g
t
h
e
wo
r
kf
l
o
w,
a
l
s
o
kn
o
w
n
a
s
t
h
e
d
e
a
d
l
i
ne
[
6]
.
M
a
k
e
s
pa
n
i
s
c
a
l
c
u
l
a
t
e
d
by
(
3)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
do
n
e
s
i
a
n
J
E
l
e
c
E
n
g
&
C
o
m
p
S
c
i
I
S
S
N:
2502
-
4752
Optimiz
e
d
s
c
he
duli
ng
of
s
c
ienti
f
ic
w
o
r
k
f
lo
w
s
bas
e
d
on
it
e
r
ated
local
s
e
ar
c
h
(
A
laa
A
bdalqahar
J
ihad
)
1619
M
a
k
e
s
p
a
n
=
M
a
x
{
FT
(
t
)
}
w
h
e
r
e
∈
T
a
s
k
s
(
3)
T
h
e
t
i
m
e
o
r
c
o
s
t
o
f
t
r
a
n
s
f
e
r
r
i
n
g
d
a
t
a
TT
ij
b
e
t
we
e
n
a
ny
t
wo
t
a
s
ks
s
uc
h
a
s
t
i
a
n
d
t
j
i
n
a
wo
r
kf
l
o
w,
wh
e
r
e
t
i
i
s
pa
r
e
n
t
to
t
j
,
de
pe
n
d
s
o
n
t
h
e
a
m
o
un
t
o
f
da
t
a
s
e
n
t
f
r
o
m
t
i
to
t
j
,
a
n
d
t
h
e
n
e
t
wor
k
b
a
n
dw
i
dt
h
.
TT
ij
i
s
z
e
r
o
i
f
t
i
a
n
d
t
j
a
r
e
a
s
s
i
g
n
e
d
to
t
h
e
s
a
m
e
VM
[
31]
.
T
h
e
da
t
a
t
r
a
n
s
f
e
r
t
i
m
e
i
s
c
a
l
c
u
l
a
t
e
d
a
s
f
o
l
l
o
w
s
[
32]
:
TT
=
{
/
≠
0
ℎ
wh
e
r
e
data
ij
t
h
e
s
i
z
e
o
f
t
h
e
da
t
a
whi
c
h
ne
e
ds
t
o
b
e
t
r
a
n
s
f
e
r
r
e
d
f
r
o
m
t
h
e
t
i
to
t
j
,
a
n
d
bw
i
s
t
h
e
c
o
m
muni
c
a
t
i
o
n
b
a
n
dw
i
dt
h
be
t
we
e
n
t
he
V
M
t
i
a
n
d
V
M
t
j
.
Al
go
r
i
t
h
m
3
i
ll
s
t
r
a
t
e
s
t
h
e
m
e
t
h
o
d
whi
c
h
i
s
a
do
pt
e
d
to
c
a
l
c
u
l
a
t
e
t
h
e
m
a
ke
s
pa
n
.
Al
go
r
i
t
hm
3
.
C
a
l
c
u
l
a
t
i
o
n
o
f
m
a
ke
s
pa
n
Input:
Solution
S
(Schedule of tasks workflow)
Output:
Makespan of solution
S
1:
vmNum
= number of available VMs,
taskNum
= number of Tasks
2:
k
=0,
MaxTime
=0,
Ready
=0,
TransferCost
=0,
Makespan
=0
3: While
k
<=
taskNum
do
4:
For e
ach task (
t
i
)
in Task List (
TL
) do
5:
If
t
i
is not handled
6:
TransferCost
=0,
MaxTime
=0,
Ready
=1
7:
For each parent of ti (
Pt
i
) do //where
Pt
i
∈
Parent List (
PL
)
t
i
8:
If
Pt
i
is not handled
9:
Ready
=0
10:
else
11:
MaxTime
=
Max(
MaxTime
,
FT
(
Pt
i
))
12:
EndFor
13:
If
Ready
=1
14:
For each
Pt
i
in (
PL
)
t
i
do
15:
If
VM
ti
<>
VM
Pti
16:
TransferCost
=
TransferCost
+ TT(
Pt
i
,
t
i
)
17:
EndFor
18:
ST
(
t
i
) = Max(
MaxTime
,
AvaiTime
(
VM
ti
)) +
TransferCost
// where
AvaiTime(VM
ti
)
is Available Time of VMti
19:
FT
(
t
i
) =
ST
(
t
i
) + (Length of
t
i
/ Mips of
VM
ti
)
20:
Makespan
=Max(
Makespan
,
FT
(
t
i
))
21:
AvaiTime
(
VM
ti
) =
FT
(
t
i
)
22:
k
=
k
+1
23:
EndFor
24: EndWhile
5.
RE
S
UL
T
S
A
ND
DI
S
CU
S
S
I
ON
I
n
t
hi
s
s
e
c
t
i
o
n
,
we
e
x
p
l
a
i
n
t
h
e
r
e
s
u
l
t
s
o
f
a
n
a
ly
z
i
ng
t
h
e
pe
r
f
o
r
m
a
nc
e
o
f
t
he
a
l
go
r
i
t
hm
w
i
t
h
t
h
e
r
e
s
u
l
t
s
o
f
i
t
s
i
m
p
l
e
m
e
n
t
a
t
i
o
n
.
F
o
r
a
dj
us
t
i
n
g
t
h
e
a
l
go
r
i
t
hm
pa
r
a
m
e
t
e
r
s
,
t
h
e
pe
r
f
o
r
m
a
n
c
e
o
f
t
h
e
a
l
go
r
i
t
hm
h
a
s
b
e
e
n
a
n
a
ly
z
e
d
u
s
i
n
g
d
i
f
f
e
r
e
n
t
va
l
ue
s
.
F
i
gur
e
s
2(
a
)
-
(
c
)
(
s
e
e
A
pp
e
n
d
i
x
)
s
h
o
ws
t
h
e
pe
r
f
o
r
m
a
n
c
e
o
f
t
h
e
a
l
go
r
i
t
hm
b
a
s
e
d
o
n
t
h
e
m
a
ke
s
pa
n
v
a
l
ue
,
us
i
ng
d
e
f
e
r
e
n
t
c
a
s
e
s
o
f
M
o
n
t
a
ge
a
n
d
E
p
i
ge
n
o
m
i
c
s
wo
r
kf
l
o
ws
.
T
h
e
pe
r
f
o
r
m
a
n
c
e
h
a
s
be
e
n
a
na
l
y
z
e
d
f
i
r
s
t
l
y
by
a
d
j
us
t
i
n
g
t
h
e
n
u
m
be
r
o
f
i
t
e
r
a
t
i
o
ns
i
n
t
h
e
I
L
S
a
l
go
r
i
t
hm
,
whic
h
i
s
t
h
e
n
u
m
be
r
o
f
pe
r
t
ur
b
a
t
i
o
n
a
n
d
l
o
c
a
l
s
e
a
r
c
h
wo
r
k.
T
h
e
a
l
go
r
i
t
hm
s
t
o
ps
wh
e
n
i
t
r
e
a
c
h
e
s
t
h
e
n
u
m
be
r
o
f
it
e
r
a
t
i
o
n
s
i
n
w
hi
c
h
t
h
e
s
o
l
ut
i
o
n
h
a
s
n
o
t
i
m
pr
o
v
e
d.
S
e
c
o
n
d
l
y
,
t
h
e
n
u
m
be
r
o
f
n
e
i
g
hb
o
r
s
e
x
t
r
a
c
t
e
d
f
r
o
m
t
he
c
ur
r
e
n
t
s
o
l
ut
i
o
n
i
n
t
h
e
l
o
c
a
l
s
e
a
r
c
h
a
l
go
r
i
t
hm
i
s
a
l
s
o
c
o
n
s
i
d
e
r
d.
F
i
n
a
ll
y
,
a
d
j
us
t
i
n
g
t
h
e
pe
r
t
ur
b
a
t
i
o
n
r
a
t
i
o
o
f
t
h
e
s
o
l
ut
i
o
n
.
Af
t
e
r
t
r
y
i
n
g
s
e
v
e
r
a
l
d
if
f
e
r
e
n
t
v
a
l
ue
s
,
we
n
o
t
e
t
h
a
t
a
s
t
h
e
n
u
m
be
r
o
f
i
t
e
r
a
t
i
o
n
s
i
nc
r
e
a
s
e
s
,
t
h
e
s
o
l
ut
i
o
n
im
pr
o
v
e
s
t
o
a
c
e
r
t
a
i
n
e
x
t
e
n
t
,
a
n
d
t
h
e
im
pr
o
v
e
m
e
n
t
s
t
o
ps
e
v
e
n
w
he
n
t
h
e
i
t
e
r
a
t
i
o
n
s
i
nc
r
e
a
s
e
.
T
h
e
nu
m
b
e
r
o
f
n
e
i
g
hb
o
r
s
ge
n
e
r
a
t
e
d
i
n
l
o
c
a
l
s
e
a
r
c
h
i
s
a
ppr
o
xi
m
a
t
e
l
y
b
e
t
t
e
r
de
pe
n
d
i
n
g
o
n
t
h
e
n
u
m
be
r
o
f
t
a
s
ks
.
F
i
n
a
l
ly
,
t
h
e
l
o
we
r
t
h
e
pe
r
c
e
n
t
a
ge
o
f
pe
r
t
ur
b
a
t
i
o
n
,
wo
ul
d
b
e
t
h
e
b
e
t
t
e
r
to
a
c
e
r
t
a
i
n
e
x
t
e
n
t
.
Af
t
e
r
i
m
p
l
e
m
e
nt
i
n
g
t
h
e
a
l
go
r
i
t
hm
o
n
m
a
ny
s
c
i
e
n
t
i
f
i
c
wo
r
kf
l
o
w
i
ns
t
a
n
c
e
s
,
th
e
r
e
s
u
l
t
s
a
r
e
s
h
o
wn
i
n
T
a
bl
e
2,
t
h
e
f
i
r
s
t
c
o
l
u
m
n
r
e
pr
e
s
e
n
t
s
t
h
e
a
pp
l
i
c
a
t
i
o
n
o
f
t
h
e
s
c
i
e
n
t
i
f
i
c
wo
r
kf
l
o
w,
w
hil
e
t
h
e
s
e
c
o
n
d,
t
hi
r
d
a
n
d
f
o
ur
t
h
c
o
l
u
m
ns
r
e
pr
e
s
e
n
t
t
h
e
pr
o
p
o
s
e
d
a
l
go
r
i
t
hm
r
e
s
u
l
t
s
o
b
t
a
i
ne
d.
T
h
e
r
e
m
a
i
n
i
ng
c
o
l
u
m
ns
r
e
pr
e
s
e
n
t
t
h
e
r
e
s
u
l
t
s
o
f
t
h
e
a
l
go
r
i
t
hm
s
t
ha
t
we
r
e
c
o
m
pa
r
e
d.
T
h
e
o
b
t
a
i
n
e
d
r
e
s
u
l
t
s
o
f
t
h
e
pr
o
po
s
e
d
a
l
go
r
i
t
hm
a
r
e
c
o
m
pa
r
e
d
w
i
t
h
h
e
t
e
r
o
ge
n
e
o
us
e
a
r
l
i
e
s
t
f
i
n
i
s
h
t
i
m
e
(
HE
F
T
)
,
m
i
n
im
u
m
c
o
m
p
l
e
t
i
o
n
t
i
m
e
(
M
C
T
)
,
r
o
un
d
r
o
bi
n
(
R
R
)
a
l
go
r
i
t
hm
s
.
A
c
c
o
r
d
i
n
g
t
o
t
h
e
pr
o
p
o
s
e
d
a
l
go
r
i
t
hm
c
o
m
pa
r
e
d
t
o
ot
h
e
r
,
we
n
ot
e
t
h
a
t
t
h
e
r
e
s
u
l
t
s
o
f
i
m
p
l
e
m
e
n
t
i
n
g
t
h
e
pr
o
p
o
s
e
d
a
l
go
r
i
t
hm
a
r
e
b
e
t
t
e
r
i
n
m
a
ny
c
a
s
e
s
e
x
c
e
pt
i
n
C
y
be
r
S
h
a
ke
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2502
-
4752
I
n
do
n
e
s
i
a
n
J
E
l
e
c
E
n
g
&
C
o
m
p
S
c
i
,
Vo
l
.
25
,
N
o
.
3
,
M
a
r
c
h
20
22
:
1615
-
1624
1620
T
a
bl
e
2
.
A
ve
r
a
ge
m
a
ke
s
pa
n
c
o
m
pa
r
i
s
o
n
o
f
I
L
S
w
i
t
h
HE
F
T
,
M
C
T
,
a
n
d
RR
f
o
r
s
c
i
e
n
t
i
f
i
c
wo
r
kf
l
o
ws
W
o
r
k
f
l
o
w
I
L
S
H
E
F
T
M
C
T
RR
M
in
Av
M
a
x
M
o
nt
a
ge
_25
84.76
86.79
88.67
85.71
91.35
87.63
M
o
nt
a
ge
_50
172.97
174.57
175.44
179.1
181.06
183.91
M
o
nt
a
ge
_100
345.16
346.54
347.94
347.79
348.79
353.11
M
o
nt
a
ge
_1000
3536.37
3539.02
3540.77
3538.97
3542.18
3587.62
C
y
be
r
S
ha
k
e
_30
379.96
389.16
396.97
380.46
425.62
393.25
C
y
be
r
S
ha
k
e
_50
544.27
562.27
582.2
521.53
539.9
527.74
C
y
be
r
S
ha
k
e
_100
831.22
853.22
891.05
753.22
761.27
767.34
C
y
be
r
S
ha
k
e
_1000
6831.79
7037.25
7334.78
6807.57
6790.68
6840.51
E
pi
ge
n
o
m
ic
s
_24
6534.76
9170.13
11277.38
6548.63
9837.18
7941.59
E
pi
ge
n
o
m
ic
s
_46
14046.82
18131.44
21325.42
15146.16
18250.16
17270.46
E
pi
ge
n
o
m
ic
s
_100
121506.62
138622.89
159865.11
127531.9
129116.61
131399.43
E
pi
ge
n
o
m
ic
s
_997
1108351.75
1109442.35
1110026.87
1107585.38
1112766.72
1120257.65
I
ns
pi
r
a
l_
30
2103.01
2154.71
2204.35
2306.69
2267.42
2360.8
I
ns
pi
r
a
l_
50
3488.41
3551.4
3603.18
3572.75
3978.44
4154.08
I
ns
pi
r
a
l_
100
6089.93
6597.02
8167.79
7747
6254.53
6640.41
I
ns
pi
r
a
l_
1000
65064.44
65066.06
65069.51
65114.86
65816.79
65669.68
6.
CONC
L
USI
ON
R
e
c
e
n
t
l
y
,
a
s
c
i
e
n
t
i
f
i
c
wo
r
kf
l
o
w
h
a
s
b
e
c
o
m
e
a
r
i
c
h
a
r
e
a
o
f
r
e
s
e
a
r
c
h
t
h
a
t
i
s
a
t
tr
a
c
t
i
n
g
r
e
s
e
a
r
c
h
e
r
s
a
s
we
l
l
a
s
pr
a
c
t
i
t
i
o
n
e
r
s
i
n
d
if
f
e
r
e
n
t
r
e
s
e
a
r
c
h
do
m
a
in
s
.
A
c
c
o
r
di
n
g
ly
,
r
e
duc
i
ng
t
h
e
m
a
ke
s
pa
n
o
f
t
h
e
s
c
i
e
n
t
i
f
ic
wo
r
kf
l
o
w
r
e
pr
e
s
e
n
t
s
t
h
e
m
a
i
n
o
bj
e
c
t
i
ve
o
f
t
hi
s
pa
p
e
r
.
T
h
e
s
t
a
n
da
r
d
I
L
S
m
e
t
a
h
e
ur
i
s
t
i
c
i
s
s
uc
c
e
s
s
f
u
l
i
n
t
a
c
kl
i
ng
v
a
r
i
o
us
c
o
m
bi
na
t
o
r
i
a
l
o
pt
i
mi
z
a
t
i
o
n
pr
o
bl
e
m
s
;
t
h
e
r
e
f
o
r
e
,
t
h
e
pa
pe
r
hy
po
t
h
e
s
i
z
e
s
t
h
a
t
I
L
S
wo
ul
d
b
e
s
uc
c
e
s
s
f
u
l
i
n
t
a
c
k
l
i
ng
s
c
i
e
n
t
i
f
i
c
wo
r
k
f
l
o
w.
B
a
s
e
d
o
n
t
h
e
f
a
c
t
t
h
a
t
t
h
e
I
L
S
c
o
m
po
ne
n
t
s
p
l
a
y
a
pr
o
m
i
ne
n
t
r
o
l
e
i
n
im
pr
o
vi
n
g
t
h
e
i
r
b
e
ha
vi
o
r
dur
i
n
g
t
h
e
s
e
a
r
c
h
,
t
h
e
a
ppr
o
p
r
i
a
t
e
s
e
l
e
c
t
i
o
n
o
f
t
h
e
s
e
c
o
m
po
n
e
n
t
s
l
e
a
ds
t
o
e
nh
a
n
c
i
n
g
t
h
e
pe
r
f
o
r
m
a
n
c
e
o
f
t
h
e
I
L
S
.
T
h
e
I
L
S
h
a
s
b
e
e
n
i
m
p
l
e
m
e
n
t
e
d
o
n
a
r
e
a
l
i
s
t
i
c
s
c
i
e
n
t
i
f
i
c
wo
r
kf
l
o
w
a
n
d
t
h
e
o
b
t
a
i
n
e
d
r
e
s
u
l
t
s
h
a
v
e
be
e
n
c
o
m
pa
r
e
d
w
i
t
h
t
h
e
s
e
o
f
t
h
e
HE
F
T
,
M
C
T
,
a
n
d
R
R
a
l
go
r
i
t
hm
s
.
T
h
e
o
b
t
a
i
ne
d
r
e
s
u
l
t
s
s
uppo
r
t
e
d
t
h
e
a
b
o
v
e
-
m
e
n
t
i
o
n
e
d
hy
po
t
h
e
s
i
s
,
a
s
t
h
e
I
L
S
ha
s
a
t
t
a
i
n
e
d
c
o
m
pe
t
i
t
i
ve
r
e
s
u
l
t
s
,
if
n
o
t
s
upe
r
i
o
r
,
a
nd
ge
n
e
r
a
li
z
e
d
we
ll
o
ve
r
a
l
l
t
e
s
t
e
d
i
n
s
t
a
nc
e
s
.
AP
P
E
ND
I
X
ma
ke
s
pa
n
M
on
t
age
_25
ma
ke
s
pa
n
E
p
ig
e
n
o
m
ic
s
_24
N
umbe
r
of
it
e
r
a
ti
o
ns
N
umbe
r
of
it
e
r
a
ti
o
ns
ma
ke
s
pa
n
M
on
t
age
_50
ma
ke
s
pa
n
E
p
ig
e
n
o
m
ic
s
_46
N
umbe
r
of
it
e
r
a
ti
o
ns
N
umbe
r
of
it
e
r
a
ti
o
ns
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
do
n
e
s
i
a
n
J
E
l
e
c
E
n
g
&
C
o
m
p
S
c
i
I
S
S
N:
2502
-
4752
Optimiz
e
d
s
c
he
duli
ng
of
s
c
ienti
f
ic
w
o
r
k
f
lo
w
s
bas
e
d
on
it
e
r
ated
local
s
e
ar
c
h
(
A
laa
A
bdalqahar
J
ihad
)
1621
ma
ke
s
pa
n
M
on
t
age
_100
ma
ke
s
pa
n
E
p
ig
e
n
o
m
ic
s
_100
N
umbe
r
of
it
e
r
a
ti
o
ns
N
umbe
r
of
it
e
r
a
ti
o
ns
(
a
)
ma
ke
s
pa
n
M
on
t
age
_25
ma
ke
s
pa
n
E
p
ig
e
n
o
m
ic
s
_24
N
umbe
r
of
n
e
ig
hb
or
s
N
umbe
r
of
n
e
ig
hb
or
s
ma
ke
s
pa
n
M
on
t
age
_50
ma
ke
s
pa
n
E
p
ig
e
n
o
m
ic
s
_46
N
umbe
r
of
n
e
ig
hb
or
s
N
umbe
r
of
n
e
ig
hb
or
s
ma
ke
s
pa
n
M
on
t
age
_100
ma
ke
s
pa
n
E
p
ig
e
n
o
m
ic
s
_100
N
umbe
r
of
n
e
ig
hb
or
s
N
umbe
r
of
n
e
ig
hb
or
s
(
b
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2502
-
4752
I
n
do
n
e
s
i
a
n
J
E
l
e
c
E
n
g
&
C
o
m
p
S
c
i
,
Vo
l
.
25
,
N
o
.
3
,
M
a
r
c
h
20
22
:
1615
-
1624
1622
ma
ke
s
pa
n
M
on
t
age
_25
ma
ke
s
pa
n
E
p
ig
e
n
o
m
ic
s
_24
P
e
r
tu
r
ba
ti
o
n r
a
ti
o
P
e
r
tu
r
ba
ti
o
n r
a
ti
o
ma
ke
s
pa
n
M
on
t
age
_50
ma
ke
s
pa
n
E
p
ig
e
n
o
m
ic
s
_46
P
e
r
tu
r
ba
ti
o
n r
a
ti
o
P
e
r
tu
r
ba
ti
o
n r
a
ti
o
ma
ke
s
pa
n
M
on
t
age
_100
ma
ke
s
pa
n
E
p
ig
e
n
o
m
ic
s
_100
P
e
r
tu
r
ba
ti
o
n r
a
ti
o
P
e
r
tu
r
ba
ti
o
n r
a
ti
o
(
c
)
F
i
gur
e
2
.
T
h
e
r
e
l
a
t
i
o
n
be
t
we
e
n
n
u
m
be
r
o
f
i
t
e
r
a
t
i
o
ns
,
n
u
m
be
r
o
f
n
e
i
g
hb
o
r
s
,
a
n
d
pe
r
t
ur
b
a
t
i
o
n
r
a
t
i
o
w
i
t
h
qua
l
i
t
y
o
f
s
o
l
ut
i
o
ns
(
m
a
ke
s
pa
n
)
of
(
a
)
n
u
m
b
e
r
o
f
i
t
e
r
a
t
i
o
ns
,
(
b
)
n
u
m
b
e
r
o
f
n
e
i
g
hb
o
r
s
,
a
n
d
(
c
)
pe
r
t
u
r
b
a
t
i
o
n
r
a
t
i
o
AC
K
NOWL
E
DGE
M
E
NT
S
T
h
e
a
ut
h
o
r
s
wo
ul
d
li
ke
t
o
a
c
kn
o
wl
e
dge
t
he
c
o
n
t
r
i
b
ut
i
o
n
o
f
t
h
e
U
ni
ve
r
s
i
t
y
o
f
Anb
a
r
(
ww
w.
u
o
a
nb
a
r
.
e
du.
i
q)
vi
a
t
h
e
i
r
pr
e
s
t
i
g
i
o
us
a
c
a
d
e
m
i
c
s
t
a
f
f
i
n
s
uppo
r
t
i
n
g
t
hi
s
r
e
s
e
a
r
c
h
w
i
t
h
a
ll
r
e
qu
i
r
e
d
t
e
c
h
ni
c
a
l
a
n
d
a
c
a
de
mi
c
s
uppo
r
t.
RE
F
E
R
E
NC
E
S
[
1]
W
.
A
hma
d,
B
.
A
la
m,
S
.
A
huj
a
,
a
nd
S
.
M
a
li
k,
“
A
dy
na
mi
c
V
M
pr
o
vi
s
io
ni
ng
a
nd
de
-
p
r
ov
is
io
n
in
g
ba
s
e
d
c
o
s
t
-
e
f
f
i
c
i
e
nt
de
a
dl
in
e
-
a
w
a
r
e
s
c
h
e
dul
in
g
a
lg
o
r
it
hm
f
o
r
B
ig
D
a
ta
w
o
r
k
f
l
o
w
a
ppl
i
c
a
ti
ons
in
a
c
l
o
ud
e
n
v
ir
o
nm
e
nt
,”
C
lu
s
te
r
C
om
put
.
,
vo
l.
24,
n
o
.
1,
2
021,
do
i:
10.10
07/
s
10586
-
020
-
03100
-
7.
[
2]
M
.
A
.
R
o
dr
ig
ue
z
a
nd
R
.
B
u
y
y
a
,
“
A
ta
xo
n
o
m
y
a
nd
s
ur
ve
y
o
n
s
c
h
e
dul
in
g
a
lg
o
r
it
hms
f
o
r
s
c
ie
nt
i
f
i
c
w
or
k
f
l
o
w
s
in
I
a
a
S
c
l
o
ud
c
o
mput
in
g
e
n
v
ir
o
nm
e
nt
s
,”
C
onc
ur
r
. C
om
put
.
, v
o
l.
29, n
o
. 8, 20
17, do
i:
10.1002/
c
p
e
.4041.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
do
n
e
s
i
a
n
J
E
l
e
c
E
n
g
&
C
o
m
p
S
c
i
I
S
S
N:
2502
-
4752
Optimiz
e
d
s
c
he
duli
ng
of
s
c
ienti
f
ic
w
o
r
k
f
lo
w
s
bas
e
d
on
it
e
r
ated
local
s
e
ar
c
h
(
A
laa
A
bdalqahar
J
ihad
)
1623
[
3]
J
.
L
iu
,
S
.
L
u,
a
nd
D
.
C
h
e
,
“
A
s
ur
ve
y
of
m
o
d
e
r
n
s
c
i
e
nt
i
f
i
c
w
or
kf
l
o
w
s
c
h
e
dul
in
g
a
lg
or
it
hms
a
nd
s
y
s
t
e
ms
in
th
e
e
r
a
of
bi
g
da
ta
,”
in
P
r
oc
e
e
di
ngs
-
2020
I
E
E
E
13t
h
I
nt
e
r
nat
io
nal
C
onf
e
r
e
n
c
e
on
S
e
r
v
ic
e
s
C
om
put
in
g,
SC
C
2020
,
2020,
do
i:
10.1109/S
C
C
49832.2020.00026.
[
4]
X.
-
F
.
L
iu
,
Z
.
-
H
.
Z
ha
n,
J
.
D
.
D
e
ng,
Y
.
L
i,
T
.
G
u,
a
nd
J
.
Z
h
a
ng,
“
A
n
e
ne
r
g
y
e
f
f
i
c
i
e
nt
a
nt
c
o
l
o
n
y
s
y
s
te
m
f
or
v
ir
tu
a
l
ma
c
hi
ne
pl
a
c
e
m
e
nt
in
c
l
o
ud
c
o
mput
in
g,”
I
E
E
E
T
r
ans
.
E
v
ol
.
C
om
put
.
,
vol
.
22,
n
o
.
1,
pp.
113
-
128,
2016
,
do
i:
10.1109/
T
E
V
C
.2016.2623803.
[
5]
A
.
O
s
ma
n,
A
.
S
a
ga
h
y
r
oo
n,
R
.
A
bur
ukba
,
a
nd
F
.
A
l
o
ul
,
“
O
pt
i
mi
z
a
ti
o
n
of
e
n
e
r
g
y
c
o
ns
umpt
i
o
n
in
c
l
o
ud
c
o
mput
in
g
da
ta
c
e
nt
e
r
s
,”
I
nt
. J
. E
le
c
tr
. &
C
om
put
. E
ng.
,
vo
l.
11, n
o
. 1, 2021, d
o
i:
10.115
91/
ij
e
c
e
.
v
11i
1.pp686
-
698.
[
6]
M
.
A
.
A
z
iz
a
nd
I
.
H
.
N
in
gga
l,
“
S
c
a
la
bl
e
w
o
r
k
f
l
o
w
s
c
h
e
dul
in
g
a
lg
o
r
it
h
m
f
o
r
mi
ni
mi
z
in
g
ma
k
e
s
pa
n
a
nd
f
a
il
ur
e
pr
o
ba
bi
li
t
y
,”
B
ul
l.
E
le
c
tr
. E
ng. I
nf
or
m
at
ic
s
, v
o
l.
8, n
o
. 1, pp. 283
-
290, 2019
,
d
o
i:
1
0.11591/e
e
i.
v
8i
1.1436.
[
7]
K
.
K
.
C
ha
kr
a
v
a
r
th
i,
L
.
S
h
y
a
ma
la
,
a
nd
V
.
V
a
id
e
hi
,
“
C
o
s
t
-
e
f
f
e
c
ti
ve
w
o
r
k
f
l
o
w
s
c
h
e
dul
in
g
a
ppr
o
a
c
h
o
n
c
l
o
ud
unde
r
d
e
a
dl
in
e
c
o
ns
tr
a
in
t
us
in
g
f
ir
e
f
l
y
a
lg
or
it
hm,”
A
ppl
.
I
nt
e
ll
.
,
vo
l.
51, n
o
. 3,
2021, do
i:
10.1007/s
10489
-
020
-
01875
-
1.
[
8]
H
.
H
u
e
t
al
.
,
“
M
ul
ti
-
o
bj
e
c
t
i
v
e
s
c
h
e
dul
in
g
f
or
s
c
i
e
nt
i
f
i
c
w
o
r
k
f
l
o
w
in
mul
ti
c
l
o
ud
e
n
v
i
r
o
nm
e
nt
,”
J
.
N
e
tw
.
C
om
put
.
A
ppl
.
,
v
o
l.
114,
2018, do
i:
10.1016/j
.
jn
c
a
.2018.03.028.
[
9]
A
.
M
. M
a
na
s
r
a
h
a
nd
H
.
B
.
A
li
,
“
W
o
r
k
f
l
o
w
S
c
h
e
dul
in
g
U
s
in
g
H
y
br
id
G
A
-
P
S
O
A
lg
o
r
it
hm
in
C
lo
ud
C
omput
in
g,”
W
ir
e
l.
C
om
m
un.
M
ob. C
om
put
.
, vo
l.
2018, 2018, d
o
i:
10.1155/2018
/1
934784.
[
10]
A
.
S
o
ng,
W.
-
N
.
C
h
e
n,
X
.
-
N
.
L
u
o
,
Z
.
-
H
.
Z
ha
n,
a
nd
J
.
Z
ha
ng,
“
S
c
h
e
dul
in
g
W
o
r
k
f
l
o
w
s
w
it
h
C
o
mp
o
s
it
e
T
a
s
ks
:
A
N
e
s
te
d
P
a
r
t
ic
l
e
S
w
a
r
m Opti
mi
z
a
ti
o
n A
pp
r
o
a
c
h,”
I
E
E
E
T
r
ans
. Se
r
v
. C
om
put
.
, 2
020, do
i:
10.1109/
T
S
C
.2020.2975774.
[
11]
V
.
D
.
M
a
io
a
nd
D
.
K
im
ov
s
ki
,
“
M
ul
ti
-
o
bj
e
c
ti
ve
s
c
h
e
dul
in
g
of
e
x
tr
e
m
e
da
ta
s
c
i
e
nt
i
f
i
c
w
o
r
k
f
l
o
w
s
in
F
o
g,”
F
ut
ur
.
G
e
ne
r
.
C
om
put
.
Sy
s
t.
, v
ol
. 106, pp. 171
-
184, 2020, d
o
i:
10.1016/j
.
f
ut
ur
e
.2019.1
2.054.
[
12]
X
. M
a
, H
.
G
a
o
,
H
. X
u, a
nd M
.
B
ia
n, “
A
n I
oT
-
ba
s
e
d t
a
s
k s
c
h
e
d
ul
in
g
o
pt
im
i
z
a
ti
o
n s
c
h
e
m
e
c
o
ns
id
e
r
in
g t
h
e
d
e
a
dl
in
e
a
nd
c
o
s
t
-
a
w
a
r
e
s
c
ie
nt
i
f
i
c
w
or
k
f
l
o
w
f
or
c
l
o
ud
c
o
mput
in
g,”
E
ur
as
ip
J
.
W
ir
e
l.
C
om
m
un.
N
e
tw
.
,
vo
l.
2019,
n
o
.
1,
2019,
do
i:
ht
tp
s
:
10.1186/s
13638
-
019
-
1557
-
3.
[
13]
H
.
R
.
F
a
r
a
ga
r
di
,
M
.
R
.
S
.
S
e
dghp
o
ur
,
S
.
F
a
z
li
a
hma
di
,
T
.
F
a
hr
i
nge
r
,
a
nd
N
.
R
a
s
o
ul
i,
“
G
R
P
-
HE
F
T
:
A
budg
e
t
-
c
o
ns
tr
a
in
e
d
r
e
s
our
c
e
pr
ov
is
i
o
ni
ng
s
c
h
e
m
e
f
or
w
o
r
k
f
l
o
w
s
c
h
e
dul
in
g
in
I
a
a
S
c
l
o
uds
,”
I
E
E
E
T
r
ans
.
P
ar
al
le
l
D
is
tr
ib
.
Sy
s
t.
,
vo
l.
31,
n
o
.
6,
pp.
1239
-
12
54,
2019, do
i:
10.1109/
T
P
D
S
.2019.2961098.
[
14]
M
.
A
dhi
ka
r
i,
T
.
A
mgo
th
,
a
nd
S
.
N
.
S
r
ir
a
ma
,
“
M
ul
ti
-
o
bj
e
c
ti
ve
s
c
he
dul
in
g
s
tr
a
t
e
g
y
f
or
s
c
i
e
nt
i
f
ic
w
o
r
k
f
l
o
w
s
in
c
l
o
ud
e
n
v
ir
o
n
m
e
nt
:
A
F
ir
e
f
l
y
-
ba
s
e
d a
ppr
o
a
c
h,”
A
ppl
. Sof
t
C
om
put
. J
.
, vo
l.
93, 2020
, do
i:
10.1016/j
.a
s
oc
.2020.106411.
[
15]
G
.
E
.
A
.
F
u
e
nt
e
s
,
E
.
S
.
H
.
G
r
e
s
s
,
J
.
C
.
S
.
T
.
M
or
a
,
a
nd
J
.
M
.
M
a
r
in
,
“
S
o
lu
ti
o
n
t
o
tr
a
ve
ll
in
g
s
a
le
s
ma
n
pr
o
bl
e
m
b
y
c
lu
s
te
r
s
a
nd
a
mo
di
f
ie
d
mul
ti
-
r
e
s
ta
r
t
it
e
r
a
t
e
d
l
oc
a
l
s
e
a
r
c
h
m
e
ta
he
u
r
is
ti
c
,”
P
L
oS
O
ne
,
vo
l.
13,
n
o
.
8,
p.
e
0201868,
2018,
do
i:
10.1371/j
o
u
r
na
l.
po
n
e
.0201868.
[
16]
C
.
A
r
c
he
tt
i,
D
.
F
e
il
l
e
t,
A
.
M
or
,
a
nd
M
.
G
.
S
pe
r
a
nz
a
,
“
A
n
i
te
r
a
te
d
l
o
c
a
l
s
e
a
r
c
h
f
or
th
e
T
r
a
v
e
li
ng
S
a
le
s
ma
n
P
r
o
bl
e
m
w
it
h
r
e
l
e
a
s
e
da
te
s
a
nd c
o
mpl
e
ti
o
n t
im
e
mi
ni
m
iz
a
ti
o
n,”
C
om
put
.
\
&
O
pe
r
. R
e
s
.
, v
o
l.
98, pp. 24
-
37, 2018, d
o
i:
10.1016/j
.
c
o
r
.2018.05.001.
[
17]
J
.
B
r
a
ndã
o
,
“
I
te
r
a
te
d
l
o
c
a
l
s
e
a
r
c
h
a
lg
o
r
it
hm
w
it
h
e
je
c
ti
o
n
c
h
a
in
s
f
o
r
th
e
o
pe
n
ve
hi
c
l
e
r
o
u
ti
ng
pr
o
bl
e
m
w
it
h
ti
m
e
w
in
d
ow
s
,”
C
om
put
.
\
&
I
nd.
E
ng.
,
vo
l.
120, pp. 146
-
159, 2018, d
o
i:
10.101
6/
j.
c
i
e
.2018.04.032.
[
18]
J
.
B
r
a
ndã
o
,
“
A
m
e
m
o
r
y
-
ba
s
e
d
i
te
r
a
te
d
l
oc
a
l
s
e
a
r
c
h
a
lg
o
r
i
th
m
f
or
th
e
mul
ti
-
d
e
p
o
t
o
p
e
n
ve
hi
c
le
r
o
ut
in
g
pr
o
bl
e
m,”
E
ur
.
J
.
O
pe
r
.
R
e
s
.
, vo
l.
284, n
o
. 2, pp. 559
-
571, 2020
,
d
o
i:
10.1016
/j
.e
j
o
r
.202
0.01.008.
[
19]
H
.
Z
o
ha
li
,
B
.
N
a
de
r
i,
M
.
M
o
ha
mm
a
di
,
a
nd
V
.
R
o
s
ha
na
e
i,
“
R
e
f
o
r
mul
a
ti
o
n,
li
n
e
a
r
i
z
a
ti
o
n,
a
nd
a
hy
br
i
d
it
e
r
a
t
e
d
l
o
c
a
l
s
e
a
r
c
h
a
lg
o
r
it
h
m
f
or
e
c
o
n
o
mi
c
l
o
t
-
s
i
z
in
g
a
nd
s
e
que
n
c
in
g
in
h
y
br
id
f
l
ow
s
ho
p
pr
o
bl
e
ms
,”
C
om
put
.
\
&
O
pe
r
.
R
e
s
.
,
v
ol
.
104,
pp.
127
-
138,
2019
,
do
i:
10.1016/j
.
c
or
.2018.12.008.
[
20]
D
.
F
e
r
o
n
e
,
S
.
H
a
ta
mi
,
E
.
M
.
G
o
n
z
á
le
z
-
N
e
ir
a
,
A
.
A
.
J
ua
n,
a
nd
P
.
F
e
s
ta
,
“
A
bi
a
s
e
d
-
r
a
nd
o
mi
z
e
d
it
e
r
a
t
e
d
l
o
c
a
l
s
e
a
r
c
h
f
o
r
th
e
di
s
tr
ib
ut
e
d
a
s
s
e
mbl
y
pe
r
mut
a
ti
o
n
f
l
o
w
-
s
h
o
p
pr
o
bl
e
m,”
I
nt
.
T
r
ans
.
O
pe
r
.
R
e
s
.
,
v
o
l.
27,
n
o
.
3,
pp.
1368
-
1391,
2020
,
do
i:
10.1111/i
to
r
.12719.
[
21]
K
.
L
o
h
e
s
w
a
r
a
n,
T
.
D
a
ni
y
a
,
a
nd
K
.
K
a
r
th
i
c
k,
“
H
y
br
id
c
uc
k
oo
s
e
a
r
c
h
a
lg
or
it
hm
w
it
h
it
e
r
a
ti
ve
l
oc
a
l
s
e
a
r
c
h
f
or
o
pt
i
mi
z
e
d
ta
s
k
s
c
he
dul
in
g
o
n
c
l
o
ud
c
o
mput
in
g
e
n
v
i
r
o
nme
nt
,”
J
.
C
om
put
.
T
he
or
.
N
anos
c
i.
,
v
o
l.
16,
n
o
.
5
-
6,
pp.
2065
-
2071,
2019,
do
i:
10.1166/j
c
tn
.2019.7851.
[
22]
A
.
S
a
nt
ia
go
e
t
al
.
,
“
G
R
A
S
P
a
nd
I
te
r
a
t
e
d
L
oc
a
l
S
e
a
r
c
h
-
B
a
s
e
d
C
e
ll
ul
a
r
P
r
oc
e
s
s
in
g
a
lg
o
r
i
th
m
f
o
r
P
r
e
c
e
d
e
n
c
e
-
C
o
ns
tr
a
in
t
T
a
s
k
L
is
t
S
c
h
e
dul
in
g
o
n
H
e
te
r
o
g
e
ne
o
us
S
y
s
t
e
ms
,”
A
ppl
. Sc
i.
, vol
. 10, n
o
.
21, p. 7500, 2020, do
i:
10.3390/app102175
00.
[
23]
E
.
Q
ue
ir
o
ga
,
R
.
G
.
S
.
P
in
h
e
ir
o
,
Q
.
C
hr
is
t,
A
.
S
ubr
a
ma
ni
a
n,
a
n
d
A
.
A
.
P
e
s
s
o
a
,
“
I
te
r
a
te
d
l
oc
a
l
s
e
a
r
c
h
f
or
s
in
gl
e
ma
c
h
in
e
t
o
ta
l
w
e
ig
ht
e
d t
a
r
di
n
e
s
s
ba
tc
h s
c
h
e
dul
in
g,”
J
. H
e
ur
is
ti
c
s
, v
o
l.
27, n
o
.
3, pp. 353
-
438, 2021, do
i
:
10.1007/s
10732
-
020
-
09461
-
x.
[
24]
S
.
S
ha
h,
“
I
mpl
e
m
e
nt
a
ti
o
n
of
it
e
r
a
ti
ve
l
o
c
a
l
s
e
a
r
c
h
(
I
L
S
)
f
or
th
e
q
ua
dr
a
ti
c
a
s
s
ig
nme
nt
pr
o
bl
e
m,”
2020
,
do
i:
10.36227/t
e
c
hr
x
i
v
.12814232.
[
25]
A
.
E
s
tr
a
da
-
M
or
e
n
o
,
M
.
S
a
ve
ls
be
r
gh,
A
.
A
.
J
ua
n,
a
nd
J
.
P
a
na
de
r
o
,
“
B
ia
s
e
d
-
r
a
nd
o
mi
z
e
d
it
e
r
a
t
e
d
l
oc
a
l
s
e
a
r
c
h
f
or
a
mul
ti
p
e
r
io
d
ve
hi
c
le
r
o
ut
in
g
pr
o
bl
e
m
w
it
h
pr
i
c
e
di
s
c
o
unt
s
f
o
r
de
li
v
e
r
y
f
le
xi
bi
li
t
y
,”
I
nt
.
T
r
ans
.
O
pe
r
.
R
e
s
.
,
v
o
l.
26,
no
.
4,
pp.
1293
-
1314,
2
019,
do
i:
10.1111/i
t
o
r
.12625C
.
[
26]
J
. L
iu
,
E
. P
a
c
i
tt
i,
P
. V
a
ld
ur
i
e
z
, a
nd M
. M
a
tt
o
s
o
, “
P
a
r
a
ll
e
li
z
a
ti
o
n
of
s
c
i
e
nt
i
f
i
c
w
o
r
k
f
l
o
w
s
i
n t
he
c
l
o
ud,”
I
N
R
I
A
, 2014.
[
27]
H
.
R
.
L
o
ur
e
nç
o
,
O
.
C
.
M
a
r
ti
n,
a
nd
T
.
S
tü
t
z
l
e
,
“
I
te
r
a
te
d
lo
c
a
l
s
e
a
r
c
h
:
F
r
a
me
w
or
k
a
nd
a
ppl
ic
a
ti
o
ns
,”
in
H
andbook
o
f
m
e
ta
he
ur
is
ti
c
s
, S
pr
in
ge
r
, pp. 129
-
168,
2019,
d
o
i
:
10.1007/978
-
3
-
319
-
91086
-
4_5.
[
28]
N
.
G
a
r
g,
D
.
S
in
gh,
a
nd
M
.
S
.
G
o
r
a
y
a
,
“
E
n
e
r
g
y
a
nd
r
e
s
o
u
r
c
e
e
f
f
i
c
ie
nt
w
o
r
k
f
l
o
w
s
c
h
e
dul
in
g
in
a
v
ir
tu
a
li
z
e
d
c
l
o
ud
e
n
v
ir
o
nm
e
nt
,”
C
lu
s
te
r
C
om
put
.
, v
ol
. 24, n
o
. 2, pp. 767
-
797, 2021, d
o
i:
10.100
7/
s
10586
-
020
-
03149
-
4.
[
29]
M
.
A
la
’
A
nz
y
a
nd
M
.
O
th
ma
n,
“
L
o
a
d
ba
la
nc
in
g
a
nd
s
e
r
ve
r
c
o
n
s
o
li
da
ti
o
n
in
c
l
o
ud
c
o
mput
in
g
e
n
v
ir
o
n
me
nt
s
:
A
m
e
ta
-
s
tu
d
y
,”
I
E
E
E
A
c
c
e
s
s
, v
o
l.
7, pp. 141868
-
141887, 2019
,
d
o
i:
10.1109
/AC
C
E
S
S
.2019.2944420.
[
30]
W
.
C
he
n
a
nd
E
.
D
e
e
lm
a
n,
“
W
o
r
k
f
l
o
w
s
im
:
A
to
o
lk
it
f
o
r
s
im
u
la
ti
ng
s
c
ie
nt
i
f
ic
w
o
r
k
f
l
o
w
s
in
di
s
tr
ib
ut
e
d
e
n
v
i
r
o
nm
e
nt
s
,”
in
2012
I
E
E
E
8t
h i
nt
e
r
nat
io
nal
c
onf
e
r
e
n
c
e
on E
-
s
c
ie
nc
e
, 2012, pp. 1
-
8,
do
i:
10.1109/
e
S
c
i
e
n
c
e
.2012.6404430.
[
31]
A
.
T
a
r
a
f
da
r
,
K
.
K
a
r
ma
ka
r
,
S
.
K
ha
tu
a
,
a
nd
R
.
K
.
D
a
s
,
“
E
ne
r
g
y
-
E
f
f
i
c
i
e
nt
S
c
h
e
dul
in
g
of
D
e
a
dl
in
e
-
S
e
ns
it
i
ve
a
nd
B
u
dge
t
-
C
o
ns
tr
a
in
e
d
W
or
k
f
l
o
w
s
in
th
e
C
l
o
ud,”
in
I
nt
e
r
nat
io
nal
C
onf
e
r
e
nc
e
on
D
is
t
r
ib
ut
e
d
C
om
put
in
g
and
I
nt
e
r
ne
t
T
e
c
hnol
ogy
,
20
21,
pp. 65
-
80, do
i
:
10.1007/978
-
3
-
030
-
65621
-
8_4.
[
32]
P
.
H
a
n,
C
.
D
u,
J
.
C
h
e
n,
F
.
L
in
g,
a
nd
X
.
D
u,
“
C
o
s
t
a
nd
ma
ke
s
pa
n
s
c
he
dul
in
g
of
w
or
k
f
l
o
w
s
in
c
l
o
uds
us
in
g
li
s
t
mul
ti
o
b
je
c
t
iv
e
o
pt
im
i
z
a
ti
o
n t
e
c
hni
qu
e
,”
J
. Sy
s
t.
A
r
c
hi
t.
, vo
l.
112, 2021, d
o
i:
10
.1016/j
.s
y
s
a
r
c
.2020.101837.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2502
-
4752
I
n
do
n
e
s
i
a
n
J
E
l
e
c
E
n
g
&
C
o
m
p
S
c
i
,
Vo
l
.
25
,
N
o
.
3
,
M
a
r
c
h
20
22
:
1615
-
1624
1624
B
I
OG
RA
P
HI
E
S
OF
AU
T
HO
RS
A
l
a
a
A
bda
l
qa
h
a
r
J
i
h
a
d
w
as
b
o
rn
i
n
A
n
b
ar
-
I
raq
i
n
1
9
8
5
.
H
e
r
ece
i
v
e
d
h
i
s
B.
S
c
.
fro
m
Fa
c
u
l
t
y
o
f
C
o
m
p
u
t
e
r
S
c
i
en
ce
at
A
n
b
ar
U
n
i
v
e
rs
i
t
y
,
I
raq
i
n
2
0
0
9
.
T
h
e
MS
c.
d
eg
r
ee
Fa
cu
l
t
y
o
f
Co
m
p
u
t
e
r
S
c
i
en
ce
at
A
n
b
ar
U
n
i
v
e
rs
i
t
y
,
I
raq
2
0
1
2
.
H
i
s
re
s
e
ar
c
h
i
n
t
e
r
e
s
t
s
are,
Me
t
ah
e
u
r
i
s
t
i
c
s
,
S
ch
e
d
u
l
i
n
g
,
A
rt
i
f
i
c
i
a
l
In
t
el
l
i
g
en
t
,
D
at
a
Mi
n
i
n
g
,
Ma
c
h
i
n
e
L
e
ar
n
i
n
g
a
n
d
N
at
u
ra
l
L
an
g
u
ag
e
Pro
ce
s
s
i
n
g
.
H
e
c
an
b
e
co
n
t
a
c
t
ed
at
em
ai
l
:
i
t
.
al
aa.
h
ee
t
y
@
u
o
a
n
b
ar.
ed
u
.
i
q
.
Suf
y
a
n
T.
F
a
ra
j
A
l
-
J
a
n
a
bi
w
as
b
o
rn
i
n
H
a
d
i
t
h
a
,
Iraq
(1
9
7
1
).
H
e
o
b
t
ai
n
e
d
h
i
s
B.
Sc.
(1
9
9
2
),
M.
Sc
.
(1
9
9
5
),
an
d
Ph
.
D
.
(1
9
9
9
)
i
n
E
l
ec
t
ro
n
i
c
an
d
C
o
mm
u
n
i
c
at
i
o
n
s
E
n
g
i
n
ee
ri
n
g
fro
m
t
h
e
Co
l
l
eg
e
o
f
E
n
g
i
n
ee
r
i
n
g
,
N
a
h
rai
n
U
n
i
v
e
rs
i
t
y
i
n
Bag
h
d
ad
.
H
e
w
as
s
t
art
e
d
as
a
facu
l
t
y
mem
b
e
r
i
n
t
h
e
Co
m
p
u
t
e
r
E
n
g
i
n
ee
ri
n
g
D
e
p
t
.
,
t
h
e
U
n
i
v
e
r
s
i
t
y
o
f
Bag
h
d
a
d
i
n
1
9
9
9
.
Pro
f.
(Faraj
)
Al
-
J
an
ab
i
i
s
t
h
e
w
i
n
n
e
r
o
f
t
h
e
1
s
t
A
w
ar
d
fo
r
t
h
e
B
e
s
t
Re
s
e
ar
ch
Pap
e
r
i
n
In
fo
r
m
at
i
o
n
S
ec
u
r
i
t
y
fro
m
t
h
e
A
s
s
o
ci
at
i
o
n
o
f
A
rab
U
n
i
v
e
rs
i
t
i
e
s
(A
A
RU
),
J
o
r
d
an
,
2
0
0
3
.
H
e
i
s
al
s
o
t
h
e
w
i
n
n
e
r
o
f
t
h
e
I
S
E
P
fel
l
o
w
s
h
i
p
2
0
0
9
a
n
d
t
h
e
Fu
l
b
ri
g
h
t
fel
l
o
w
s
h
i
p
2
0
1
0
,
U
SA
.
H
e
i
s
a
mem
b
e
r
o
f
A
CM
,
A
SE
E
,
I
A
C
R,
an
d
IE
E
E
.
H
e
c
an
b
e
co
n
t
a
c
t
ed
at
em
ai
l
:
s
u
f
y
an
.
al
j
an
ab
i
@
u
o
an
b
ar.
e
d
u
.
i
q
.
Es
a
m
Ta
h
a
Y
a
s
s
en
i
s
a
l
ec
t
u
r
e
r
i
n
t
h
e
co
l
l
e
g
e
o
f
Co
m
p
u
t
e
r
an
d
I
n
f
o
r
m
at
i
o
n
T
e
ch
n
o
l
o
g
y
at
t
h
e
U
n
i
v
e
rs
i
t
y
o
f
A
n
b
ar,
I
raq
s
i
n
ce
2
0
0
2
.
H
e
h
as
o
b
t
ai
n
ed
h
i
s
Ph
D
i
n
C
o
m
p
u
t
e
r
Sci
en
ce
at
T
h
e
U
n
i
v
e
rs
i
t
y
K
e
b
an
g
s
aan
Ma
l
a
y
s
i
a
(
U
K
M)
i
n
2
0
1
5
.
H
i
s
m
a
i
n
re
s
e
ar
c
h
ar
e
as
i
n
c
l
u
d
e
me
t
ah
eu
ri
s
t
i
c
s
,
h
y
p
e
r
-
h
eu
ri
s
t
i
c
s
an
d
c
o
m
b
i
n
at
o
ri
al
O
p
t
i
m
i
zat
i
o
n
p
ro
b
l
em
s
e
s
p
eci
al
l
y
,
ro
u
t
i
n
g
an
d
s
c
h
ed
u
l
i
n
g
.
H
e
h
as
b
e
en
s
e
rv
ed
as
a
p
ro
g
ramme
c
o
mmi
t
t
ee
fo
r
fo
u
r
i
n
t
e
r
n
at
i
o
n
a
l
c
o
n
f
e
r
e
n
ce
s
a
n
d
r
e
v
i
ew
e
rs
f
o
r
h
i
g
h
i
m
p
a
c
t
j
o
u
r
n
al
s
.
H
e
i
s
a
r
e
s
e
ar
c
h
e
r
i
n
D
at
a
Mi
n
i
n
g
an
d
Opt
i
m
i
zat
i
o
n
R
e
s
e
ar
c
h
G
ro
u
p
(D
M0
),
C
e
n
t
r
e
fo
r
A
rt
i
fi
c
i
a
l
I
n
t
e
l
l
i
g
e
n
t
(CA
I
T
),
U
K
M
.
Cu
rren
t
l
y
,
h
e
i
s
t
h
e
m
an
a
g
e
r
o
f
C
o
m
p
u
t
e
rs
Cen
t
re
i
n
U
n
i
v
e
rs
i
t
y
o
f
A
n
b
ar.
H
e
c
a
n
b
e
c
o
n
t
ac
t
e
d
at
em
ai
l
:
co
.
e
s
a
m
t
ah
a@
u
o
an
b
ar.
ed
u
.
i
q
.
Evaluation Warning : The document was created with Spire.PDF for Python.