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e
q
u
a
n
tu
m
is
to
o
lar
g
e,
t
h
e
r
esp
o
n
s
e
ti
m
e
o
f
t
h
e
p
r
o
ce
s
s
e
s
is
to
o
m
u
c
h
w
h
ic
h
m
a
y
n
o
t
b
e
to
ler
ated
in
i
n
ter
ac
ti
v
e
e
n
v
ir
o
n
m
en
t.
I
f
ti
m
e
q
u
an
t
u
m
is
to
o
s
m
all,
it
ca
u
s
e
s
u
n
n
ec
e
s
s
ar
il
y
f
r
eq
u
en
t
co
n
te
x
t
s
w
i
tch
lead
i
n
g
to
m
o
r
e
o
v
e
r
h
ea
d
s
r
esu
l
tin
g
i
n
less
t
h
r
o
u
g
h
p
u
t.
I
n
th
is
p
ap
er
a
m
eth
o
d
u
s
i
n
g
Ma
n
h
attan
d
is
tan
ce
lo
g
ic
h
a
s
b
ee
n
p
r
o
p
o
s
ed
th
at
d
ec
id
es
a
v
alu
e
t
h
at
is
n
eit
h
er
to
o
lar
g
e
n
o
r
to
o
s
m
all
s
u
c
h
th
a
t
ev
er
y
p
r
o
ce
s
s
h
as
g
o
t
r
ea
s
o
n
ab
le
r
es
p
o
n
s
e
ti
m
e
a
n
d
th
e
th
r
o
u
g
h
p
u
t o
f
t
h
e
s
y
s
te
m
is
n
o
t d
ec
r
ea
s
ed
d
u
e
to
u
n
n
ec
e
s
s
ar
i
l
y
co
n
te
x
t s
w
i
tch
e
s
.
T
h
e
v
ar
io
u
s
s
c
h
ed
u
li
n
g
p
ar
a
m
eter
s
ar
e:
1.
C
o
n
te
x
t
S
w
itc
h
:
A
co
n
te
x
t
s
w
itc
h
is
b
asicall
y
s
to
r
i
n
g
an
d
r
esto
r
in
g
co
n
tex
t
o
r
s
tate
o
f
a
p
r
e
-
e
m
p
ted
p
r
o
ce
s
s
,
s
o
th
a
t
at
a
later
p
o
in
t
o
f
t
i
m
e
,
it
ca
n
b
e
s
tar
ted
f
r
o
m
s
a
m
e
p
o
i
n
t
o
n
ce
t
h
e
e
x
ec
u
tio
n
is
s
to
p
p
ed
.
So
th
e
g
o
al
o
f
C
P
U
s
ch
ed
u
lin
g
alg
o
r
it
h
m
s
is
to
o
p
ti
m
ize
o
n
l
y
th
e
s
e
s
w
i
tch
e
s
.
2.
T
h
r
o
u
g
h
p
u
t:
T
h
r
o
u
g
h
p
u
t
is
d
ef
in
ed
a
s
n
u
m
b
er
o
f
p
r
o
ce
s
s
es
co
m
p
leted
i
n
a
p
er
io
d
o
f
ti
m
e.
C
o
n
tex
t
s
w
itc
h
in
g
a
n
d
T
h
r
o
u
g
h
p
u
t a
r
e
in
v
er
s
el
y
p
r
o
p
o
r
tio
n
al
to
ea
ch
o
th
er
.
3.
C
P
U
Utilizat
io
n
:
T
h
is
i
s
t
h
e
f
r
ac
tio
n
o
f
ti
m
e
w
h
e
n
C
P
U
is
in
u
s
e.
U
s
u
al
l
y
,
to
m
ax
i
m
ize
th
e
C
P
U
u
tili
za
t
io
n
is
t
h
e
g
o
al
o
f
th
e
C
P
U
s
ch
ed
u
li
n
g
4.
T
u
r
n
ar
o
u
n
d
T
im
e:
T
h
is
i
s
th
e
to
tal
ti
m
e
w
h
ich
i
s
r
eq
u
ir
ed
to
s
p
en
d
to
co
m
p
lete
t
h
e
w
h
o
le
p
r
o
ce
s
s
an
d
a
m
o
u
n
t o
f
ti
m
e
it ta
k
es to
e
x
e
cu
te
th
a
t p
r
o
ce
s
s
.
5.
W
aitin
g
T
i
m
e:
W
aiti
n
g
ti
m
e
is
d
ef
in
ed
as t
h
e
to
tal
a
m
o
u
n
t o
f
ti
m
e
a
p
r
o
ce
s
s
th
at
w
a
its
i
n
r
ea
d
y
q
u
eu
e.
6.
R
esp
o
n
s
e
T
i
m
e:
Fo
r
r
esp
o
n
d
i
n
g
to
a
p
ar
ticu
lar
s
y
s
te
m
t
h
e
a
m
o
u
n
t o
f
ti
m
e
u
s
ed
b
y
t
h
e
s
y
s
t
e
m
.
T
h
e
ch
ar
ac
ter
is
tic
o
f
g
o
o
d
s
ch
ed
u
lin
g
al
g
o
r
ith
m
ar
e:
Min
i
m
u
m
co
n
te
x
t
s
w
i
tch
e
s
,
Ma
x
i
m
u
m
C
P
U
u
ti
lizatio
n
,
Ma
x
i
m
u
m
t
h
r
o
u
g
h
p
u
t,
Min
i
m
u
m
t
u
r
n
ar
o
u
n
d
ti
m
e,
Min
i
m
u
m
w
a
iti
n
g
ti
m
e
2.
B
ACK
G
RO
UND
WO
RK
T
h
er
e
is
a
h
o
s
t
o
f
w
o
r
k
an
d
r
esear
ch
es
g
o
i
n
g
o
n
f
o
r
in
cr
ea
s
i
n
g
th
e
e
f
f
icie
n
c
y
o
f
r
o
u
n
d
r
o
b
in
alg
o
r
ith
m
.
R
a
m
i
J
.
Ma
tar
n
eh
[
4
]
p
r
o
p
o
s
ed
a
m
et
h
o
d
th
at
ca
lcu
late
s
m
ed
ia
n
o
f
b
u
r
s
t
ti
m
e
o
f
all
p
r
o
ce
s
s
es
in
r
ea
d
y
q
u
eu
e.
No
w
if
t
h
is
m
ed
ian
i
s
les
s
t
h
a
n
2
5
th
a
n
ti
m
e
q
u
an
t
u
m
w
o
u
ld
b
e
2
5
o
th
er
w
i
s
e
ti
m
e
q
u
a
n
t
u
m
i
s
s
et
to
th
e
ca
lc
u
lated
v
al
u
e.
Ah
ad
[
5
]
p
r
o
p
o
s
e
d
to
m
o
d
if
y
th
e
t
i
m
e
q
u
an
t
u
m
o
f
a
p
r
o
ce
s
s
b
ased
o
n
s
o
m
e
th
r
es
h
o
ld
v
al
u
e
w
h
ich
i
s
ca
l
cu
lated
b
y
ta
k
i
n
g
a
v
er
ag
e
o
f
lef
t
o
u
t
ti
m
e
o
f
all
p
r
o
ce
s
s
es
in
i
ts
la
s
t
t
u
r
n
.
Hir
an
w
al
et
a
l.
[
6
]
in
tr
o
d
u
ce
d
a
co
n
ce
p
t
o
f
s
m
ar
t
ti
m
e
s
lice
w
h
ic
h
is
ca
lcu
la
ted
b
y
ta
k
in
g
t
h
e
av
er
a
g
e
o
f
b
u
r
s
t
ti
m
e
o
f
all
p
r
o
ce
s
s
es
in
th
e
r
e
ad
y
q
u
e
u
e
if
n
u
m
b
er
o
f
p
r
o
ce
s
s
es
ar
e
ev
en
o
th
er
w
i
s
e
ti
m
e
s
lice
is
s
et
to
m
id
p
r
o
ce
s
s
b
u
r
s
t
ti
m
e.
Da
w
o
o
d
[
7
]
p
r
o
p
o
s
ed
an
alg
o
r
ith
m
t
h
at
f
ir
s
t
s
o
r
ts
al
l
p
r
o
ce
s
s
es
in
r
ea
d
y
q
u
eu
e
a
n
d
th
e
n
ca
lcu
late
th
e
ti
m
e
q
u
a
n
t
u
m
b
y
m
u
ltip
l
y
in
g
s
u
m
o
f
m
a
x
i
m
u
m
a
n
d
m
i
n
i
m
u
m
b
u
r
s
t
b
y
8
0
.
No
o
n
et
al
[
8
]
p
r
o
p
o
s
ed
to
ca
lcu
late
th
e
ti
m
e
q
u
an
t
u
m
b
y
ta
k
i
n
g
a
v
er
ag
e
o
f
th
e
b
u
r
s
t
ti
m
e
o
f
al
l
th
e
p
r
o
ce
s
s
es
in
r
ea
d
y
q
u
eu
e.
B
an
er
j
ee
et
al
[
9
]
p
r
o
p
o
s
ed
an
alg
o
r
ith
m
w
h
ic
h
f
ir
s
t
s
o
r
ts
all
th
e
p
r
o
ce
s
s
es
ac
co
r
d
in
g
to
t
h
e
b
u
r
s
t
ti
m
e
an
d
th
e
n
f
i
n
d
s
t
h
e
ti
m
e
q
u
a
n
t
u
m
b
y
tak
i
n
g
av
er
a
g
e
o
f
b
u
r
s
t
ti
m
e
o
f
all
p
r
o
ce
s
s
f
r
o
m
m
id
to
last
.
Na
y
a
k
et
al.
[
1
0
]
ca
lcu
lated
th
e
o
p
tim
a
l
ti
m
e
q
u
a
n
t
u
m
b
y
tak
i
n
g
th
e
av
er
ag
e
o
f
h
i
g
h
e
s
t
b
u
r
s
t
a
n
d
m
ed
ian
o
f
b
u
r
s
t.
Yaa
s
h
u
w
a
n
t
h
et
al
[
1
1
]
in
tr
o
d
u
ce
d
a
ter
m
in
telli
g
en
t
ti
m
e
s
l
ice
w
h
ich
is
ca
lc
u
lated
u
s
i
n
g
th
e
f
o
r
m
u
la
(
r
an
g
e
o
f
b
u
r
s
t
*
to
tal
n
u
m
b
er
o
f
p
r
o
ce
s
s
es)/
(
p
r
io
r
ity
r
an
g
e
*
T
o
tal
n
u
m
b
er
o
f
p
r
io
r
it
y
)
.
Ma
tth
ia
s
et
al.
[
1
2
]
p
r
o
p
o
s
ed
a
s
o
lu
tio
n
f
o
r
L
i
n
u
x
SC
HE
D_
R
R
,
to
ass
i
g
n
e
q
u
al
s
h
ar
e
o
f
C
P
U
to
d
if
f
er
en
t
u
s
er
s
in
s
tead
o
f
p
r
o
ce
s
s
.
R
ac
u
et
al.
[
1
3
]
p
r
es
en
ts
a
n
ap
p
r
o
ac
h
to
co
m
p
u
te
b
est
ca
s
e
an
d
w
o
r
s
t
ca
s
e
r
esp
o
n
s
e
ti
m
e
o
f
r
o
u
n
d
r
o
b
in
s
c
h
ed
u
li
n
g
.
I
n
Me
r
y
w
n
s
et
al
[
1
4
]
u
s
ed
E
u
cl
id
ian
d
i
s
tan
ce
f
o
r
ca
lc
u
lati
n
g
Q
u
an
t
u
m
v
al
u
e.
I
n
[
1
5
]
i
n
th
is
s
ec
tio
n
,
a
n
o
n
-
li
n
ea
r
m
a
th
e
m
atica
l
m
o
d
el
f
o
r
o
p
ti
m
iz
in
g
th
e
ti
m
e
q
u
a
n
t
u
m
v
al
u
e
in
R
R
s
c
h
ed
u
l
in
g
alg
o
r
ith
m
is
p
r
o
p
o
s
ed
.
I
n
th
i
s
p
ap
er
w
e
ap
p
r
o
ac
h
ed
t
h
e
R
o
u
n
d
R
o
b
in
Q
u
a
n
t
u
m
v
al
u
e
u
s
in
g
t
h
e
Ma
n
h
atta
n
Di
s
tan
ce
.
Qu
a
n
tu
m
v
alu
e
=
Hi
g
h
est B
u
r
s
t ti
m
e
–
L
o
w
est B
u
r
s
t ti
m
e.
3.
P
RO
P
O
SE
D
WO
RK
A
m
aj
o
r
d
is
ad
v
an
ta
g
e
o
f
r
o
u
n
d
r
o
b
in
is
th
at
a
p
r
o
ce
s
s
is
p
r
e
-
e
m
p
ted
a
n
d
co
n
tex
t
s
w
itc
h
o
c
cu
r
s
,
ev
e
n
if
t
h
e
r
u
n
n
in
g
p
r
o
ce
s
s
r
eq
u
ir
es
ti
m
e
(
in
f
r
ac
tio
n
s
)
w
h
ic
h
is
s
li
g
h
tl
y
m
o
r
e
t
h
an
a
s
s
i
g
n
ed
ti
m
e
q
u
an
tu
m
.
An
o
th
er
p
r
o
b
le
m
w
it
h
r
o
u
n
d
r
o
b
in
is
th
e
ti
m
e
q
u
a
n
t
u
m
s
el
ec
tio
n
.
I
f
ti
m
e
q
u
a
n
t
u
m
i
s
to
o
lar
g
e,
th
e
r
esp
o
n
s
e
ti
m
e
o
f
t
h
e
p
r
o
ce
s
s
es
i
s
to
o
m
u
c
h
,
t
h
e
alg
o
r
it
h
m
d
e
g
en
er
ates
to
FC
F
S
w
h
ich
m
a
y
n
o
t
b
e
to
ler
ated
in
an
in
ter
ac
ti
v
e
en
v
ir
o
n
m
e
n
t.
I
f
ti
m
e
q
u
a
n
t
u
m
is
to
o
s
m
all,
it
ca
u
s
e
s
u
n
n
ec
es
s
ar
il
y
f
r
eq
u
e
n
t
co
n
te
x
t
s
w
itc
h
es
lead
in
g
to
m
o
r
e
o
v
er
h
ea
d
s
r
es
u
lti
n
g
i
n
le
s
s
er
th
r
o
u
g
h
p
u
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2088
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
6
,
Dec
em
b
er
201
7
:
3
6
6
4
–
3
6
6
8
3666
I
n
th
i
s
p
ap
er
u
s
ed
th
e
o
p
ti
m
al
R
o
u
n
d
R
o
b
in
Sc
h
ed
u
li
n
g
u
s
i
n
g
Ma
n
h
atta
n
d
is
ta
n
ce
f
o
r
o
p
tim
u
m
T
i
m
e
Qu
a
n
tu
m
v
al
u
e
i
n
R
o
u
n
d
R
o
b
in
p
r
o
ce
s
s
i
n
Sch
ed
u
lin
g
a
lg
o
r
ith
m
.
Her
e
C
alc
u
late
th
e
Q
u
an
t
u
m
v
al
u
e
u
s
i
n
g
th
e
b
elo
w
E
q
u
a
tio
n
.
D
=
∑
|
X
=
0
i
-
Y
i
|
X
an
d
Y
v
al
u
es a
r
e
th
e
b
u
r
s
t ti
m
es o
f
P
r
o
ce
s
s
.
X=
h
i
g
h
e
s
t b
u
r
s
t ti
m
e
Y=
lo
w
e
s
t b
u
r
s
t ti
m
e
B
y
u
s
in
g
t
h
e
ab
o
v
e
f
o
r
m
u
la
we
ca
n
g
et
t
h
e
Q
v
al
u
e.
I
t
g
iv
e
s
th
e
m
i
n
i
m
u
m
co
n
tex
t
s
w
i
tch
e
s
,
b
est cp
u
u
tili
za
t
io
n
an
d
also
it
g
i
v
es t
h
e
m
in
i
m
u
m
av
er
a
g
i
n
g
ti
m
e.
3
.
1
.
O
ptim
a
l R
o
u
nd
Ro
bin
S
cheduli
ng
us
ing
M
a
nh
a
t
t
a
n
Dis
t
a
nce
Alg
o
rit
h
m
T
h
e
f
o
llo
w
i
n
g
d
ata
s
tr
u
ct
u
r
es
ar
e
n
ee
d
ed
:
P
r
o
ce
s
s
(
P
i)
.
N
u
m
b
er
o
f
p
r
o
ce
s
s
es i
n
r
ea
d
y
q
u
e
u
e
f
o
r
i=1
,
2
,
3
,
4
,
….
.
.
n
B
u
r
s
t Time
(
B
i
)
:
P
r
o
ce
s
s
in
g
ti
m
e
r
eq
u
ir
ed
b
y
ea
c
h
P
i
1
.
C
alcu
late
t
h
e
Ma
n
h
atta
n
Di
s
tan
ce
‘
MD
’
o
f
t
h
e
cp
u
b
u
r
s
t t
i
m
es o
f
p
r
o
ce
s
s
es.
2
.
T
im
e
q
u
a
n
t
u
m
=
h
i
g
h
est b
u
r
s
t ti
m
e
–
lo
w
est b
u
r
s
t ti
m
e.
3
.
Sch
ed
u
le
p
r
o
ce
s
s
es a
cc
o
r
d
in
g
to
t
h
e
ca
lcu
la
ted
ti
m
e
q
u
a
n
tu
m
.
4.
E
XP
E
R
I
M
E
NT
A
L
ANA
L
Y
SI
S
Fo
r
th
e
p
u
r
p
o
s
e
o
f
s
i
m
p
lic
it
y
,
a
d
e
m
o
n
s
tr
atio
n
is
d
o
n
e
u
s
i
n
g
g
r
o
u
p
o
f
f
iv
e
p
r
o
ce
s
s
e
s
in
th
r
ee
d
if
f
er
e
n
t
ca
s
es
t
h
at
th
e
O
R
R
S
M
alg
o
r
it
h
m
is
m
o
r
e
e
f
f
icie
n
t
th
an
t
h
e
clas
s
ic
Si
m
p
le
R
o
u
n
d
R
o
b
in
(
S
R
R
)
.
Fo
r
SR
R
,
a
ti
m
e
q
u
a
n
t
u
m
is
as
s
u
m
ed
in
all
ca
s
es i
n
o
r
d
er
to
co
m
p
ar
e
th
e
t
w
o
al
g
o
r
ith
m
s
f
air
l
y
.
C
ase
1
:
Ass
u
m
e
f
i
v
e
p
r
o
ce
s
s
es
ar
r
iv
e
at
ti
m
e
0
w
it
h
f
o
llo
win
g
b
u
r
s
t
ti
m
e
s
:
P
1
=2
4
,
P2
=1
1
,
P
3
=3
1
,
P
4
=1
2
,
P
5
=2
0
.
P1
P2
P3
P4
P5
P1
P2
P3
P4
P5
P1
P3
P5
P3
0
8
1
6
2
4
3
2
4
0
4
8
5
1
5
9
6
3
7
1
7
9
8
7
9
1
9
8
F
ig
u
r
e
1.
Gan
tt C
h
at
f
o
r
SR
R
(
ca
s
e1
)
Qu
a
n
tu
m
=M
a
x
_
b
u
r
s
t
T
i
m
e
-
Mi
n
_
B
u
r
s
t
T
im
e=
3
1
-
1
1
=2
P1
P2
P3
P4
P5
P3
P5
0
2
0
3
1
5
1
6
3
8
3
8
7
9
8
Fig
u
r
e
2
.
Gan
tt C
h
at
f
o
r
OR
R
SM
(
ca
s
e1
)
T
ab
le
1
.
C
o
m
p
u
ta
tio
n
al
tab
le
f
o
r
ca
s
e1
P
r
o
c
e
ss
B
u
r
s
t
T
i
me
W
a
i
t
i
n
g
T
i
me
T
u
r
n
A
r
o
u
n
d
T
i
me
P1
24
63
87
P2
11
20
31
P3
31
67
98
P4
12
51
63
P5
20
63
83
Av
e
ra
g
e
W
a
it
in
g
T
i
m
e
=
2
6
4
/5
=
5
2
.
8
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2088
-
8708
Op
tima
l R
o
u
n
d
R
o
b
in
C
P
U
S
ch
ed
u
lin
g
A
lg
o
r
ith
m
u
s
in
g
Ma
n
h
a
tta
n
Dis
ta
n
ce
(
N
.
S
r
ila
th
a
)
3667
T
ab
le
2
.
C
o
m
p
ar
is
o
n
b
et
w
ee
n
SR
R
an
d
OR
R
SM
A
l
g
o
r
i
t
h
m
T
i
me
Q
u
a
n
t
u
m
A
v
e
r
a
g
e
W
a
i
t
i
n
g
T
i
me
A
v
e
r
a
g
e
T
u
r
n
a
r
o
u
n
d
t
i
me
C
o
n
t
e
x
t
S
w
i
t
c
h
S
R
R
8
5
6
.
7
7
6
.
4
14
O
R
R
S
M
20
5
2
.
8
7
2
.
4
7
C
ase
2
:
A
s
s
u
m
e
f
iv
e
p
r
o
ce
s
s
e
s
ar
r
iv
e
at
ti
m
e
0
w
it
h
f
o
llo
w
i
n
g
b
u
r
s
t ti
m
es: P
1
=7
,
P
2
=
1
3
,
P
3
=2
4
,
P
4
=1
0
,
P
5
=1
8
.
P1
P
2
P3
P4
P5
P1
P2
P3
P4
P5
P2
P3
P5
P3
0
6
1
2
1
8
2
4
3
0
3
1
3
7
4
3
4
7
5
3
5
4
6
0
6
6
Fig
u
r
e
3
.
Gan
tt C
h
at
f
o
r
SR
R
(
ca
s
e2
)
Qu
a
n
tu
m
=
Ma
x
_
B
u
r
s
t
T
im
e
-
Min
_
B
u
r
s
t
T
im
e
=
17
P1
P2
P3
P4
P5
P3
P5
0
7
2
0
3
7
4
7
6
4
7
1
7
2
Fig
u
r
e
4
.
Gan
tt C
h
at
f
o
r
OR
R
SM
(
ca
s
e
2)
T
ab
le
3
.
C
o
m
p
u
ta
tio
n
al
tab
le
f
o
r
ca
se
2
P
r
o
c
e
ss
B
u
r
s
t
T
i
me
W
a
i
t
i
n
g
T
i
me
T
u
r
n
A
r
o
u
n
d
T
i
me
P1
7
0
7
P2
13
7
20
P3
24
47
71
P4
10
37
47
P5
18
54
72
Av
er
ag
e
W
aiti
n
g
T
im
e
=
1
4
5
/5
=2
9
Av
er
ag
e
T
u
r
n
A
r
o
u
n
d
ti
m
e
=
43
T
ab
le
4
.
C
o
m
p
ar
is
o
n
b
et
w
ee
n
SR
R
an
d
OR
R
SM
A
l
g
o
r
i
t
h
m
T
i
me
Q
u
a
n
t
u
m
A
v
e
r
a
g
e
W
a
i
t
i
n
g
T
i
me
A
v
e
r
a
g
e
T
u
r
n
a
r
o
u
n
d
t
i
me
C
o
n
t
e
x
t
S
w
i
t
c
h
S
R
R
6
3
9
.
4
54
14
O
R
R
S
M
17
29
43
7
Fro
m
t
h
e
ab
o
v
e
co
m
p
ar
is
o
n
s
an
d
as
ca
n
b
e
s
ee
n
i
n
F
ig
u
r
e
7
,
F
ig
u
r
e
8
a
n
d
F
ig
u
r
e
9
,
th
e
OR
R
S
M
alg
o
r
ith
m
u
s
i
n
g
E
u
clid
ea
n
d
i
s
tan
ce
m
et
h
o
d
f
o
r
ca
lc
u
lati
n
g
ti
m
e
q
u
an
tu
m
i
s
clea
r
l
y
m
o
r
e
ef
f
icie
n
t
t
h
an
th
e
SR
R
alg
o
r
it
h
m
r
es
u
lti
n
g
i
n
r
ed
u
ctio
n
o
f
t
u
r
n
ar
o
u
n
d
ti
m
e,
waitin
g
ti
m
e
a
n
d
co
n
te
x
t
s
w
itc
h
es.
A
lt
h
o
u
g
h
th
r
ee
ca
s
es
w
i
th
ea
ch
ca
s
e
h
av
in
g
f
i
v
e
p
r
o
ce
s
s
es
ar
e
s
h
o
w
n
,
t
h
e
n
u
m
b
er
o
f
p
r
o
ce
s
s
es
d
o
es n
o
t a
f
f
ec
t t
h
e
w
o
r
k
i
n
g
o
f
OR
R
SM
alg
o
r
it
h
m
as it
w
o
r
k
s
w
ell
e
v
en
w
i
th
lar
g
e
n
u
m
b
er
o
f
p
r
o
ce
s
s
es.
5.
CO
NCLU
SI
O
N
T
h
e
p
er
f
o
r
m
a
n
ce
o
f
r
o
u
n
d
r
o
b
in
alg
o
r
ith
m
i
s
en
tire
l
y
d
e
p
en
d
en
t
o
n
t
h
e
ti
m
e
q
u
a
n
t
u
m
s
elec
ted
.
Ma
n
y
atte
m
p
ts
h
a
v
e
b
ee
n
m
a
d
e
in
t
h
e
p
ast
to
s
elec
t
an
o
p
ti
m
u
m
ti
m
e
q
u
a
n
t
u
m
.
So
m
e
a
p
p
r
o
ac
h
es
r
eq
u
ir
ed
m
ak
in
g
u
s
e
o
f
o
t
h
er
al
g
o
r
ith
m
s
l
ik
e
s
h
o
r
test
j
o
b
f
ir
s
t
o
r
p
r
io
r
ity
s
c
h
ed
u
lin
g
,
t
h
er
eb
y
ca
r
r
ies
f
o
r
w
ar
d
t
h
e
d
ef
icien
c
ies
o
f
t
h
o
s
e
al
g
o
r
it
h
m
s
i
n
to
r
o
u
n
d
r
o
b
i
n
s
ch
e
d
u
lin
g
.
T
h
e
Op
ti
m
al
R
o
u
n
d
R
o
b
in
(
O
R
R
SM)
d
eter
m
in
e
s
th
e
ti
m
e
q
u
a
n
tu
m
b
y
ta
k
i
n
g
ac
co
u
n
t
th
e
s
i
m
ilar
it
y
o
r
d
if
f
er
en
ce
s
o
f
t
h
e
b
u
r
s
t
ti
m
es
o
f
all
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2088
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
6
,
Dec
em
b
er
201
7
:
3
6
6
4
–
3
6
6
8
3668
p
r
o
ce
s
s
es
p
r
esen
t
i
n
th
e
r
ea
d
y
q
u
eu
e.
T
h
e
OR
R
SM
d
o
es
n
o
t
r
eq
u
ir
e
p
r
io
r
ities
to
b
e
ass
ig
n
ed
to
th
e
j
o
b
s
n
o
r
d
o
es
it
r
eq
u
ir
e
th
e
j
o
b
s
to
b
e
s
o
r
ted
ac
co
r
d
in
g
to
th
e
ir
b
u
r
s
t
ti
m
e
s
.
I
t
r
es
u
lt
s
i
n
b
etter
p
er
f
o
r
m
a
n
ce
o
f
r
o
u
n
d
r
o
b
in
alg
o
r
ith
m
w
i
th
r
ed
u
ctio
n
i
n
co
n
te
x
t
s
w
itc
h
es,
t
u
r
n
ar
o
u
n
d
ti
m
e
s
an
d
w
a
iti
n
g
ti
m
es.
T
h
e
ti
m
e
q
u
a
n
t
u
m
d
eter
m
in
ed
t
h
r
o
u
g
h
O
R
R
SM
is
d
y
n
a
m
ic
i
n
t
h
e
s
e
n
s
e
t
h
a
t
n
o
u
s
er
in
ter
v
e
n
tio
n
i
s
r
eq
u
ir
ed
an
d
t
h
e
ti
m
e
q
u
an
t
u
m
is
r
elate
d
to
th
e
b
u
r
s
t
ti
m
es o
f
p
r
o
ce
s
s
es.
RE
F
E
R
E
NC
E
S
[1
]
S
il
b
e
rsc
h
a
tz,
A
.
,
P
e
ters
o
n
,
J.
L
.
,
a
n
d
G
a
lv
in
,
P
.
B.
,
Op
e
ra
t
in
g
S
y
ste
m Co
n
c
e
p
ts,
A
d
d
is
o
n
W
e
sle
y
,
7
th
Ed
it
i
o
n
,
2
0
0
6
.
[2
]
A
n
d
re
w
S
.
T
a
n
e
n
b
a
u
m
,
a
n
d
A
lb
e
rt
S
.
W
o
o
d
f
h
u
l
l
,
Op
e
ra
ti
n
g
S
y
ste
m
s
De
sig
n
a
n
d
Im
p
lem
e
n
tatio
n
,
S
e
c
o
n
d
Ed
i
ti
o
n
,
2
0
0
5
.
[3
]
W
il
li
a
m
S
talli
n
g
s,
Op
e
ra
ti
n
g
S
y
st
e
m
s In
tern
a
l
a
n
d
De
sig
n
P
r
in
c
ip
les
,
5
th
Ed
it
io
n
,
2
0
0
6
.
[4
]
Ra
m
i
J
M
a
tarn
e
h
,
“
S
e
lf
a
d
ju
stm
e
n
t
ti
m
e
q
u
a
n
t
u
m
in
ro
u
n
d
ro
b
in
a
lg
o
rit
h
m
d
e
p
e
n
d
in
g
o
n
b
u
rst
ti
m
e
o
f
th
e
n
o
w
ru
n
n
in
g
p
r
o
c
e
ss
”
,
Am
e
rica
n
Jo
u
r
n
a
l.
[5
]
M
o
h
d
A
b
d
u
l
A
h
a
d
,
“
M
o
d
ify
in
g
r
o
u
n
d
r
o
b
i
n
a
lg
o
rit
h
m
f
o
r
p
ro
c
e
ss
sc
h
e
d
u
li
n
g
u
sin
g
d
y
n
a
m
ic
q
u
a
n
tu
m
p
re
c
isio
n
”
,
In
tern
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Co
m
p
u
te
r
a
p
p
l
ica
ti
o
n
s(
0
9
7
5
-
8
8
8
7
)
o
n
Iss
u
e
s
a
n
d
Ch
a
ll
e
n
g
e
s
i
n
Ne
tw
o
rk
in
g
,
In
tell
ig
e
n
c
e
a
n
d
Co
m
p
u
ti
n
g
T
e
c
h
n
o
lo
g
ies
-
IC
NICT
2
0
1
2
.
[6
]
S
a
r
o
j
Hira
n
w
a
l
a
n
d
Dr.
K.C.
Ro
y
,
“
A
d
a
p
ti
v
e
ro
u
n
d
ro
b
i
n
sc
h
e
d
u
li
n
g
u
sin
g
sh
o
rtes
t
b
u
rst
a
p
p
ro
a
c
h
b
a
se
d
o
n
sm
a
rt
ti
m
e
slic
e
”
,
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
Da
ta E
n
g
in
e
e
rin
g
,
v
o
lu
m
e
2
,
I
ss
u
e
.
3
,
2
0
1
1
.
[7
]
A
li
Jb
a
e
e
r
Da
w
o
o
d
,
“
Im
p
ro
v
in
g
e
ff
ici
e
n
c
y
o
f
ro
u
n
d
r
o
b
in
sc
h
e
d
u
li
n
g
u
si
n
g
a
sc
e
n
d
in
g
q
u
a
n
t
u
m
a
n
d
m
in
im
u
m
-
m
a
x
i
m
u
m
b
u
rst
ti
m
e
”
,
Jo
u
rn
a
l
o
f
Un
iv
e
rsit
y
o
f
a
n
b
a
r
f
o
r
p
u
re
sc
ien
c
e
:
V
o
l
.
6
:
No
2
,
2
0
1
2
.
[8
]
A
b
b
a
s
No
o
n
,
A
li
Ka
lak
e
c
h
a
n
d
S
a
if
e
d
in
e
Ka
d
r
y
,
“
A
n
e
w
ro
u
n
d
ro
b
i
n
b
a
se
d
sc
h
e
d
u
li
n
g
a
lg
o
rit
h
m
f
o
r
o
p
e
ra
ti
n
g
s
y
ste
m
s:
d
y
n
a
m
ic
q
u
a
n
tu
m
u
sin
g
th
e
m
e
a
n
a
v
e
r
a
g
e
”
,
IJCSI
In
tern
a
ti
o
n
a
l
Jo
u
r
n
a
l
o
f
Co
m
p
u
ter
S
c
ien
c
e
Iss
u
e
s,
V
o
l.
8
,
Iss
u
e
3
,
No
.
1
,
M
a
y
2
0
1
1
.
[9
]
P
a
ll
a
b
Ba
n
e
rjee
,
P
r
o
b
a
l
Ba
n
e
rjee
a
n
d
S
h
w
e
ta
S
o
n
a
li
Dh
a
l
,
“
C
o
m
p
a
ra
ti
v
e
p
e
rf
o
r
m
a
n
c
e
a
n
a
l
y
sis
o
f
m
id
a
v
e
r
a
g
e
ro
u
n
d
r
o
b
i
n
sc
h
e
d
u
li
n
g
(M
A
RR)
u
sin
g
d
y
n
a
m
ic
ti
m
e
q
u
a
n
tu
m
w
it
h
ro
u
n
d
ro
b
in
sc
h
e
d
u
li
n
g
a
lg
o
rit
h
m
h
a
v
in
g
sta
ti
c
ti
m
e
q
u
a
tu
m
”
,
In
tern
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
tro
n
ics
a
n
d
Co
m
p
u
ter S
c
ien
c
e
En
g
in
e
e
rin
g
,
IS
S
N
-
2
2
7
7
-
1
9
5
6
2
0
1
2
.
[1
0
]
De
b
a
s
h
re
e
Na
y
a
k
,
S
a
n
jee
v
Ku
m
a
r
M
a
ll
a
a
n
d
De
b
a
sh
re
e
De
b
a
d
a
rsh
in
i,
“
Im
p
ro
v
e
d
ro
u
n
d
ro
b
in
sc
h
e
d
u
li
n
g
u
si
n
g
d
y
n
a
m
ic
ti
m
e
q
u
a
n
tu
m
”
,
In
tern
a
ti
o
n
a
l
Jo
u
r
n
a
l
o
f
Co
m
p
u
ter
A
p
p
li
c
a
ti
o
n
s
(0
9
7
5
-
8
8
8
7
)
Vo
l
u
m
e
3
8
-
No
5
,
Ja
n
u
a
r
y
2
0
1
2
.
[1
1
]
Ya
a
sh
u
w
a
n
th
C.
&
R.
Ra
m
e
sh
,
“
In
telli
g
e
n
t
ti
m
e
slice
f
o
r
ro
u
n
d
ro
b
in
i
n
re
a
l
ti
m
e
o
p
e
ra
ti
n
g
s
y
ste
m
,
IJRRA
S
2
(2
),
F
e
b
ru
a
ry
2
0
1
0
.
[1
2
]
Bra
u
n
h
o
f
e
r
M
a
tt
h
ias
,
S
tr
u
m
f
lo
h
n
e
r
Ju
ri,
“
F
a
ir
r
o
u
n
d
r
o
b
in
sc
h
e
d
u
li
n
g
”
,
S
e
p
tem
b
e
r
1
7
,
2
0
0
9
.
[1
3
]
Ra
z
v
a
n
R
a
c
u
,
L
i
L
i,
R
a
f
ik
H
e
n
ia,
A
rn
e
Ha
r
m
a
n
n
,
Ro
lf
Ern
st,
“
I
m
p
ro
v
e
d
Re
sp
o
n
se
ti
m
e
a
n
a
l
y
sis
o
f
tas
k
sc
h
e
d
u
led
u
n
d
e
r
p
re
e
m
p
ti
v
e
ro
u
n
d
ro
b
in
,
C
OD
ES
+
IS
S
S
’0
7
”
,
P
r
o
c
o
f
5
th
IEE
E/
A
CM
In
tern
a
ti
o
n
a
l
c
o
n
f
e
re
n
c
e
o
n
Ha
r
w
a
re
/
S
o
f
tw
a
r
e
c
o
d
e
g
ig
n
a
n
d
sy
ste
m
su
n
th
e
sis.
[1
4
]
M
e
rwy
n
D’So
u
z
a
,
F
io
n
a
Ca
iero
,
S
u
w
a
rn
a
S
u
rlak
a
r
,
“
Op
ti
m
a
l
Ro
u
n
d
R
o
b
i
n
C
P
U
S
c
h
e
d
u
li
n
g
Alg
o
rit
h
m
u
sin
g
Eu
c
li
d
e
a
n
Dista
n
c
e
”
,
p
u
b
li
sh
e
d
in
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
C
o
mp
u
t
e
r A
p
p
li
c
a
ti
o
n
s
.
V
o
lu
m
e
9
6
,
N
o
.
1
8
,
J
u
n
e
2
0
1
4
.
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