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6
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7
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Evaluation Warning : The document was created with Spire.PDF for Python.
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8
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I
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A
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6
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ce
s
,
b
o
th
o
n
lin
e
an
d
o
f
f
l
in
e
alg
o
r
it
h
m
s
w
er
e
d
ev
elo
p
e
d
to
p
ar
titi
o
n
task
s
f
o
r
m
u
lt
ip
le
d
ev
ice
s
.
I
n
[
9
]
,
u
s
in
g
q
u
e
u
ein
g
th
eo
r
y
,
o
f
f
lo
ad
in
g
d
ec
i
s
io
n
s
w
er
e
f
o
r
m
u
lated
as
a
n
o
n
-
co
o
p
er
ativ
e
g
a
m
e
in
a
t
h
r
ee
-
ti
er
ME
C
ar
ch
itec
tu
r
e
co
n
s
i
s
ti
n
g
o
f
m
o
b
ile
d
ev
ices,
clo
u
d
lets
an
d
d
is
ta
n
t
clo
u
d
.
Mo
b
ile
ed
g
e
C
o
m
p
u
ti
n
g
is
a
f
o
r
m
o
f
co
m
p
u
ter
ar
ch
itec
tu
r
e
[
1
3
-
15]
.
I
t
is
ab
o
u
t
p
r
o
ce
s
s
i
n
g
t
h
e
d
ata
at
th
e
p
er
ip
h
er
y
o
f
t
h
e
n
et
w
o
r
k
d
ir
ec
tl
y
w
h
er
e
t
h
e
y
ar
e
g
en
er
a
ted
.
R
ath
er
th
a
n
tr
an
s
f
er
i
n
g
t
h
e
d
ata
g
e
n
er
ated
b
y
d
ev
ices
co
n
n
ec
ted
to
th
e
I
o
T
to
th
e
clo
u
d
o
r
th
e
d
ata
ce
n
ter
.
I
t
ca
n
o
f
f
er
n
ea
r
b
y
c
u
s
to
m
ized
s
er
v
ice
s
t
h
at
r
eq
u
ir
e
g
o
o
d
tr
an
s
m
is
s
io
n
b
an
d
w
id
t
h
,
ad
d
itio
n
al
d
ata
s
to
r
ag
e
an
d
p
r
o
ce
s
s
in
g
.
A
s
ill
u
s
tr
ate
d
in
Fig
u
r
e
1
,
MEC
ca
n
a
u
g
m
e
n
t
m
o
b
ile
d
ev
ice
s
’
ca
p
ab
ilit
ies
b
y
o
f
f
lo
ad
in
g
[
3
,
1
6
,
1
7
]
s
o
m
e
p
ar
ts
o
f
th
e
ir
h
e
av
y
ap
p
licatio
n
s
v
ia
w
ir
ele
s
s
ac
ce
s
s
to
a
r
e
s
o
u
r
ce
-
r
ich
ed
g
e
n
o
d
e
,
an
d
t
h
en
e
f
f
e
ctiv
el
y
r
ed
u
ce
s
t
he
ir
p
o
w
er
c
o
n
s
u
m
p
tio
n
s
[
1
8
]
.
T
h
e
f
ir
s
t
w
o
r
k
s
w
h
ich
d
ea
lt
w
i
th
t
h
e
o
f
f
lo
ad
i
n
g
w
i
th
in
M
E
C
en
v
ir
o
n
m
e
n
ts
w
er
e
in
t
er
ested
in
s
t
u
d
y
in
g
th
e
m
u
lti
-
u
s
er
s
i
n
g
le
-
tas
k
ca
s
e.
I
n
t
h
ese
s
ce
n
ar
io
s
,
a
u
s
er
o
n
l
y
tar
g
et
s
to
o
f
f
lo
ad
o
n
l
y
a
u
n
iq
u
e
ta
s
k
.
T
h
e
y
s
tu
d
ied
r
eso
u
r
ce
allo
ca
tio
n
wh
ile
t
h
e
y
o
p
ti
m
ize
th
e
a
v
er
ag
e
task
d
u
r
atio
n
[
1
9
]
.
A
ctu
all
y
,
an
ap
p
licatio
n
is
g
en
er
all
y
p
ar
titi
o
n
ed
i
n
to
m
u
ltip
le
ta
s
k
s
,
a
n
d
t
h
e
o
f
f
lo
ad
in
g
d
ec
is
io
n
s
m
u
s
t
co
n
ce
r
n
ea
ch
o
f
th
e
m
.
C
o
n
s
eq
u
en
tl
y
,
e
v
e
n
a
s
in
g
le
u
s
er
h
as
to
h
a
n
d
le
s
i
m
u
lta
n
e
o
u
s
l
y
m
u
l
tip
le
tas
k
s
.
T
h
er
ef
o
r
e,
th
e
o
f
f
lo
ad
in
g
d
ec
is
io
n
p
ar
a
m
eter
s
s
h
o
u
ld
b
e
s
elec
ted
ac
co
r
d
in
g
to
a
m
u
lti
-
task
s
ce
n
ar
io
.
Fig
u
r
e
1
.
Mo
b
ile
ed
g
e
co
m
p
u
t
in
g
i
llu
s
tr
atio
n
R
ec
en
t
l
y
,
th
e
au
th
o
r
s
o
f
[
2
0
]
s
tu
d
ied
a
s
in
g
le
-
u
s
er
m
u
lti
-
t
a
s
k
o
f
f
lo
ad
in
g
s
e
n
ar
io
b
y
o
p
ti
m
izin
g
r
ad
io
r
eso
u
r
ce
s
a
n
d
lo
ca
l
f
r
eq
u
e
n
c
y
.
T
h
e
y
d
id
n
o
t
co
n
s
id
er
t
h
e
lo
ca
l
en
er
g
y
a
v
ailab
il
it
y
n
o
r
t
h
e
r
e
m
o
te
s
er
v
er
’
s
f
r
eq
u
en
c
y
.
B
esid
es,
th
e
y
co
n
s
id
er
task
s
w
it
h
t
h
e
s
a
m
e
d
ea
d
lin
e
T
d
.
I
n
th
i
s
w
o
r
k
,
w
e
s
tu
d
y
t
h
e
g
en
er
a
l
m
u
l
ti
-
tas
k
o
f
f
lo
ad
in
g
s
en
ar
io
w
h
er
e
w
e
in
tr
o
d
u
ce
th
e
co
n
tr
o
l
o
f
th
e
av
ailab
le
lo
ca
l
en
er
g
y
,
an
d
co
n
s
id
er
th
e
ed
g
e
s
er
v
er
’
s
f
r
eq
u
e
n
c
y
as
a
d
ec
is
io
n
p
ar
a
m
eter
i
n
o
u
r
o
p
ti
m
izatio
n
p
r
o
b
le
m
.
Mo
r
eo
v
er
,
w
e
co
n
s
id
er
a
g
en
er
al
s
etti
n
g
w
h
er
e
ea
ch
o
f
f
lo
ad
ab
le
task
h
as
to
b
e
ex
ec
u
ted
w
i
th
i
n
its
s
p
ec
if
ic
d
ea
d
lin
e
t
i
m
ax
.
A
cc
o
r
d
in
g
to
o
u
r
v
is
io
n
,
w
e
ca
n
p
r
o
lo
n
g
th
e
b
atter
y
li
f
e
o
f
t
h
e
m
o
b
ile
d
ev
ice
b
y
co
n
s
id
er
i
n
g
t
h
e
a
m
o
u
n
t
o
f
it
s
av
a
ilab
le
p
o
w
er
,
an
d
r
ed
u
ce
th
e
task
s
’
p
r
o
ce
s
s
in
g
ti
m
e
b
y
ad
j
u
s
ti
n
g
t
h
e
ed
g
e
s
er
v
er
’
s
f
r
e
q
u
e
n
c
y
.
S
u
b
s
eq
u
e
n
tl
y
,
w
e
h
a
v
e
f
o
r
m
u
lated
a
n
o
p
ti
m
i
za
tio
n
p
r
o
b
le
m
t
h
at
m
i
n
i
m
izes
th
e
p
r
o
ce
s
s
i
n
g
ti
m
e
b
y
j
o
in
tl
y
d
ec
id
in
g
th
e
lo
ca
l
an
d
ed
g
e
co
m
p
u
t
in
g
f
r
eq
u
en
ci
es,
as
w
ell
as t
h
e
o
f
f
lo
ad
in
g
d
ec
is
io
n
s
.
D
u
e
to
its
co
m
b
in
ato
r
ial
n
atu
r
e
a
n
d
a
f
ter
its
d
ec
o
m
p
o
s
it
io
n
,
w
e
p
r
o
p
o
s
e
a
h
e
u
r
is
tic
s
o
lu
tio
n
b
ased
o
n
a
s
i
m
u
lated
an
n
ea
li
n
g
al
g
o
r
ith
m
to
j
o
in
t
ly
d
ec
i
de
th
e
ta
s
k
s
’
o
f
f
lo
ad
in
g
a
n
d
th
e
allo
ca
tio
n
o
f
co
m
p
u
t
in
g
r
eso
u
r
ce
s
.
T
h
e
o
b
j
ec
tiv
e
is
to
m
i
n
i
m
ize
t
h
e
p
r
o
ce
s
s
i
n
g
ti
m
e
v
ia
th
e
o
f
f
lo
ad
in
g
b
y
co
n
s
id
er
in
g
t
h
e
task
s’
laten
c
y
c
o
n
s
tr
ain
ts
an
d
a
th
r
es
h
o
ld
o
f
av
ailab
le
p
r
o
ce
s
s
in
g
ti
m
e
.
T
h
e
r
e
m
ain
d
er
o
f
t
h
is
p
ap
er
is
o
r
g
an
ized
as
f
o
llo
w
s
:
t
h
e
s
y
s
te
m
’
s
m
o
d
el
an
d
th
e
o
p
ti
m
izatio
n
p
r
o
b
lem
f
o
r
m
u
latio
n
ar
e
p
r
esen
ted
i
n
Sectio
n
2
.
I
n
Sectio
n
3
,
we
p
r
e
se
nt
o
u
r
m
et
h
o
d
to
so
lv
e
t
h
e
o
p
ti
m
izat
io
n
p
r
o
b
lem
.
I
n
s
ec
tio
n
4
w
e
p
r
e
s
en
t
th
e
s
i
m
u
latio
n
r
es
u
lts
an
d
th
eir
d
is
c
u
s
s
io
n
.
Fin
a
ll
y
,
S
ec
tio
n
5
co
n
cl
u
d
es
th
e
p
ap
er
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
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&
C
o
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p
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tr
a
in
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fflo
a
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mu
lti
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(
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2.
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M
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P
R
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M
F
O
R
M
UL
AT
I
O
N
2
.
1
.
Sy
s
t
e
m
m
o
del
Fig
u
r
e
2
Sh
o
w
s
a
s
in
g
le
s
m
ar
t
m
o
b
ile
d
ev
ice
(
SMD)
co
n
tai
n
in
g
a
n
o
f
f
lo
ad
ab
le
m
u
lti
-
ta
s
k
l
is
t.
I
n
t
h
i
s
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k
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w
e
p
lan
to
s
t
u
d
y
th
e
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e
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io
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t
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ad
in
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p
r
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s
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o
r
a
m
u
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-
tas
k
SMD
i
n
an
ed
g
e
en
v
ir
o
n
m
e
n
t,
w
h
ile
w
e
o
p
ti
m
ize
co
m
p
u
tati
o
n
r
eso
u
r
ce
s
av
ailab
le
at
t
h
e
ed
g
e
s
er
v
er
as
w
el
l
as
at
th
e
m
o
b
ile
d
ev
ice.
P
ar
ticu
lar
l
y
,
th
e
av
a
ilab
le
en
er
g
y
at
th
e
SM
D
f
o
r
task
s
ex
ec
u
t
io
n
is
li
m
ited
.
B
esid
es
,
in
th
e
co
n
te
x
t
o
f
o
f
f
lo
ad
in
g
,
s
o
m
e
p
iece
s
o
f
a
co
m
p
u
tatio
n
al
l
y
i
n
ten
s
i
v
e
ap
p
licatio
n
ar
e
d
iv
id
ed
in
to
m
u
lt
ip
le
m
u
tu
al
l
y
in
d
ep
en
d
en
t
o
f
f
lo
ad
ab
le
task
s
[
2
1
-
24]
.
T
h
er
ef
o
r
e,
ac
co
r
d
in
g
to
th
e
a
v
ailab
le
co
m
p
u
t
atio
n
al
an
d
r
ad
io
r
eso
u
r
ce
s
,
s
o
m
e
tas
k
s
ar
e
p
i
ck
-
u
p
f
r
o
m
t
h
e
r
es
u
lti
n
g
ta
s
k
s
l
is
t
to
b
e
o
f
f
lo
ad
ed
to
th
e
ed
g
e
s
er
v
er
s
f
o
r
co
m
p
u
ti
n
g
.
T
h
e
o
th
er
s
ar
e
p
er
f
o
r
m
ed
lo
ca
ll
y
o
n
th
e
SMD
it
s
elf
.
T
h
e
ex
ec
u
tio
n
o
f
t
h
e
w
h
o
le
lis
t
m
u
s
t
h
ap
p
e
n
w
it
h
i
n
th
e
ti
m
e
li
m
it
o
f
t
h
e
ap
p
licatio
n
.
A
d
d
itio
n
all
y
,
it
is
ass
u
m
ed
th
a
t
th
e
SMD
co
n
cu
r
r
en
tl
y
p
er
f
o
r
m
s
co
m
p
u
tatio
n
a
n
d
w
ir
ele
s
s
tr
an
s
m
i
s
s
io
n
.
Fo
r
all
t
h
ese
co
n
s
id
er
atio
n
s
,
w
e
d
er
iv
e
a
m
ath
e
m
atica
l
p
r
o
ce
s
s
in
g
ti
m
e
m
o
d
el
th
at
co
n
s
id
er
s
t
h
r
ee
m
ai
n
d
ec
is
io
n
s
:
t
h
e
o
f
f
lo
a
d
in
g
d
ec
is
io
n
f
o
r
ea
ch
tas
k
,
t
h
e
lo
ca
l
ex
ec
u
tio
n
f
r
eq
u
en
c
y
o
f
t
h
e
SMD,
a
n
d
t
h
e
s
er
v
er
e
x
ec
u
tio
n
f
r
eq
u
e
n
c
y
at
th
e
ed
g
e.
T
h
en
,
w
e
f
o
r
m
u
late
a
n
p
r
o
ce
s
s
i
n
g
ti
m
e
p
r
o
b
le
m
.
Fig
u
r
e
2
.
S
y
s
te
m
m
o
d
el
illu
s
tr
atio
n
P
r
ac
tically
,
t
h
e
SMD
is
co
n
n
ec
ted
to
an
ed
g
e
n
o
d
e
(
E
N
)
,
an
d
is
in
ten
d
ed
to
o
f
f
lo
ad
a
s
et
o
f
in
d
ep
en
d
en
t
ta
s
k
s
b
y
th
e
m
ea
n
o
f
a
n
ed
g
e
ac
ce
s
s
p
o
in
t
(
E
AP
)
.
A
d
d
itio
n
all
y
,
t
h
e
w
ir
ele
s
s
ch
an
n
el
co
n
d
itio
n
s
b
et
w
ee
n
t
h
e
SMD
a
n
d
t
h
e
w
i
r
eless
ac
ce
s
s
p
o
i
n
t
ar
e
n
o
t
co
n
s
id
er
ed
i
n
t
h
is
w
o
r
k
.
Mo
r
eo
v
er
,
at
t
h
e
ti
m
e
o
f
th
e
o
f
f
lo
ad
in
g
d
ec
is
io
n
an
d
th
e
tr
an
s
m
is
s
io
n
o
f
t
h
e
o
f
f
lo
ad
ab
le
task
s
,
t
h
e
u
p
lin
k
r
ate
r
is
ass
u
m
ed
al
m
o
s
t
u
n
c
h
a
n
g
ed
.
As
s
h
o
w
n
i
n
Fi
g
u
r
e
2
.
,
th
e
co
n
s
id
er
ed
s
m
ar
t
m
o
b
ile
d
ev
ic
e
co
n
tain
s
N
in
d
ep
en
d
e
n
t
tas
k
s
d
en
o
ted
as
τ
≜
{
τ
1
,
τ
2
,
…
,
τ
N
}
.
I
n
ad
d
itio
n
,
t
h
e
s
e
tas
k
s
ar
e
ass
u
m
ed
to
b
e
co
m
p
u
ta
tio
n
all
y
i
n
ten
s
i
v
e
a
n
d
d
ela
y
s
en
s
iti
v
e
a
n
d
h
a
v
e
to
b
e
co
m
p
leted
.
E
ac
h
tas
k
τ
i
ca
n
b
e
p
r
o
ce
s
s
ed
eit
h
er
lo
ca
ll
y
o
r
at
t
h
e
e
d
g
e.
I
t
r
ep
r
esen
t
s
an
ato
m
ic
i
n
p
u
t
d
ata
tas
k
t
h
at
ca
n
n
o
t
b
e
d
iv
id
ed
in
to
s
u
b
-
ta
s
k
s
.
Mo
r
eo
v
er
,
it
is
ch
ar
ac
ter
iz
ed
b
y
th
e
f
o
llo
w
i
n
g
th
r
ee
p
ar
a
m
eter
s
τ
i
≜
〈
d
i
,
λ
i
,
t
i
m
ax
〉
.
T
h
e
f
ir
s
t
o
n
e
d
en
o
ted
d
i
[
b
its
]
id
en
tif
i
es
th
e
a
m
o
u
n
t
o
f
t
h
e
i
n
p
u
t
p
ar
am
eter
s
an
d
p
r
o
g
r
a
m
co
d
es
to
tr
an
s
f
er
f
r
o
m
th
e
u
s
er
’
s
l
o
ca
l
d
ev
ice
to
th
e
ed
g
e
s
er
v
e
r
.
T
h
e
s
ec
o
n
d
o
n
e
d
en
o
ted
λ
i
[
cy
cle
s
]
s
p
ec
if
ie
s
t
h
e
w
o
r
k
lo
ad
r
ef
er
r
in
g
to
th
e
co
m
p
u
tatio
n
a
m
o
u
n
t
n
ee
d
e
d
to
ac
co
m
p
lis
h
th
e
p
r
o
ce
s
s
in
g
o
f
t
h
i
s
tas
k
.
T
h
e
th
ir
d
p
ar
am
eter
t
i
m
ax
r
ef
er
s
to
th
e
r
eq
u
ir
ed
m
a
x
i
m
u
m
late
n
c
y
f
o
r
th
is
t
as
k
.
T
h
e
ex
ec
u
tio
n
n
at
u
r
e
d
ec
is
io
n
f
o
r
a
tas
k
τ
i
eith
er
lo
ca
ll
y
o
r
b
y
o
f
f
lo
ad
in
g
to
th
e
ed
g
e
s
er
v
er
i
s
d
en
o
ted
x
i
wh
e
r
e
x
i
∈
{
0
;
1
}
.
x
i
=
1
in
d
icate
s
t
h
at
th
e
SMD
h
a
s
to
o
f
f
lo
ad
τ
i
to
th
e
ed
g
e
s
er
v
er
,
an
d
x
i
=
0
in
d
icate
s
t
h
at
τ
i
is
lo
ca
ll
y
p
r
o
ce
s
s
ed
.
Fro
m
t
h
is
p
o
in
t,
all
ti
m
e
ex
p
r
ess
io
n
s
ar
e
g
i
v
e
n
in
S
ec
o
n
d
s
,
an
d
en
er
g
y
co
n
s
u
m
p
tio
n
s
ar
e
g
i
v
en
in
Jo
u
le
.
T
h
en
,
if
th
e
SMD
lo
ca
ll
y
ex
ec
u
tes
tas
k
τ
i
,
th
e
co
m
p
let
io
n
ti
m
e
o
f
it
s
lo
ca
l
ex
ec
u
t
io
n
is
t
i
L
=
λ
i
f
L
.
So
,
f
o
r
all
task
s
,
w
e
h
a
v
e:
t
L
=
∑
(
1
−
x
i
)
λ
i
f
L
N
i
=
1
.
(
1
)
ad
d
itio
n
all
y
,
th
e
co
r
r
esp
o
n
d
in
g
en
er
g
y
co
n
s
u
m
p
tio
n
is
g
iv
e
n
b
y
:
e
i
L
=
k
L
.
f
L
2
.
λ
i
[
1
1
]
.
Hen
ce
,
th
e
to
tal
en
er
g
y
co
n
s
u
m
p
tio
n
w
h
i
le
ex
ec
u
ti
n
g
all
task
s
th
a
t
w
er
e
d
ec
id
ed
to
b
e
lo
ca
lly
e
x
ec
u
ted
in
t
h
e
SM
D
is
g
i
v
e
n
b
y
:
e
L
=
k
L
.
f
L
2
.
∑
λ
i
(
1
−
x
i
)
N
i
=
1
(
2
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
10
,
No
.
4
,
A
u
g
u
s
t 2
0
2
0
:
3
7
5
7
-
3766
3760
if
tas
k
is
o
f
f
lo
ad
ed
to
th
e
ed
g
e
n
o
d
e,
th
e
o
f
f
lo
ad
in
g
p
r
o
ce
s
s
co
m
p
letio
n
ti
m
e
is
:
=
+
+
,
w
h
er
e
t
i
C
o
m
is
th
e
ti
m
e
to
tr
an
s
m
i
t
th
e
task
to
th
e
E
A
P
,
an
d
i
t
is
g
i
v
en
b
y
t
i
C
o
m
=
d
i
r
.
t
i
Exec
is
th
e
ti
m
e
to
ex
ec
u
te
th
e
tas
k
τ
i
at
th
e
E
N,
a
n
d
it
ca
n
b
e
f
o
r
m
u
lated
a
s
t
i
Exec
=
λ
i
f
S
.
t
i
Res
is
th
e
ti
m
e
to
r
ec
eiv
e
t
h
e
r
es
u
lt
o
u
t
f
r
o
m
th
e
ed
g
e
n
o
d
e.
B
ec
au
s
e
t
h
e
d
ata
s
ize
o
f
th
e
r
es
u
lt
is
u
s
u
all
y
i
g
n
o
r
ed
co
m
p
ar
ed
to
th
e
in
p
u
t
d
ata
s
ize,
w
e
ig
n
o
r
e
t
h
is
r
ela
y
ti
m
e
a
n
d
its
e
n
er
g
y
co
n
s
u
m
p
tio
n
a
s
ad
o
p
ted
b
y
[
2
5
]
.
Hen
ce
,
f
o
r
t
h
e
tas
k
t
i
O
=
x
i
(
d
i
r
+
λ
i
f
S
)
,
an
d
f
o
r
all
tas
k
s
,
w
e
h
a
v
e:
t
O
=
∑
x
i
(
d
i
r
+
λ
i
f
S
)
N
i
=
1
.
(
3
)
S
o
,
th
e
e
n
er
g
y
co
n
s
u
m
p
tio
n
o
f
th
e
co
m
m
u
n
icatio
n
p
r
o
ce
s
s
ca
n
b
e
o
b
tain
ed
b
y
m
u
ltip
l
y
in
g
th
e
r
e
s
u
l
tin
g
tr
an
s
m
is
s
io
n
p
er
io
d
b
y
t
h
e
tr
a
n
s
m
i
s
s
io
n
u
n
d
er
tak
e
n
p
o
w
er
,
an
d
th
e
r
e
s
t
o
f
t
h
e
e
x
ec
u
tio
n
p
er
io
d
b
y
t
h
e
id
le
m
o
d
e
p
o
w
er
.
T
h
u
s
,
th
i
s
en
er
g
y
is
:
e
C
=
p
T
∑
x
i
d
i
N
i
=
1
r
.
(
4
)
F
in
all
y
,
g
iv
e
n
th
e
o
f
f
lo
ad
in
g
d
ec
is
io
n
v
ec
to
r
f
o
r
all
task
s
,
th
e
lo
ca
l
ex
ec
u
tio
n
f
r
eq
u
en
c
y
o
f
th
e
SM
D,
an
d
th
e
s
er
v
er
ex
ec
u
tio
n
f
r
eq
u
en
c
y
at
th
e
ed
g
e,
t
h
e
to
tal
e
x
ec
u
t
io
n
ti
m
e
f
o
r
th
e
SM
D
is
co
m
p
o
s
ed
o
f
i
ts
lo
ca
l e
x
ec
u
tio
n
ti
m
e,
th
e
co
m
m
u
n
icat
io
n
ti
m
e
as
w
ell
a
s
th
e
ex
ec
u
tio
n
ti
m
e
at
th
e
E
N,
a
n
d
it is
g
i
v
e
n
b
y
:
T
(
,
f
L
,
f
S
)
=
t
L
+
t
O
.
(
5
)
T
h
en
,
ac
co
r
d
in
g
to
(
1
)
an
d
(
3
)
an
d
if
w
e
n
o
te
Λ
=
∑
=
1
,
th
e
to
tal
ex
ec
u
tio
n
ti
m
e
ca
n
b
e
f
o
r
m
u
lated
a
s
:
T
(
,
f
L
,
f
S
)
=
{
Λ
f
L
−
∑
λ
i
x
i
N
i
=
1
f
L
+
∑
d
i
x
i
N
i
=
1
r
+
∑
λ
i
x
i
N
i
=
1
f
S
}
.
(
6
)
2
.
2
.
P
ro
ble
m
f
o
r
m
u
la
t
io
n
I
n
th
i
s
s
ec
t
io
n
,
w
e
p
r
ese
n
t
o
u
r
o
p
tim
iza
tio
n
p
r
o
b
le
m
f
o
r
m
u
latio
n
t
h
at
ai
m
s
to
m
i
n
i
m
ize
t
h
e
o
v
er
all
ex
ec
u
t
io
n
t
i
m
e
i
n
t
h
e
o
f
f
lo
ad
in
g
p
r
o
ce
s
s
.
I
n
itiall
y
,
to
p
r
ep
ar
e
th
e
p
r
o
b
le
m
’
s
d
ata
w
e
s
t
ar
t
w
ith
an
i
n
itial
s
o
r
tin
g
o
f
t
h
e
ta
s
k
s
li
s
t
τ
≜
{
τ
1
,
τ
2
,
…
,
τ
N
}
ac
co
r
d
in
g
to
t
h
eir
d
ea
d
lin
e
s
t
i
m
ax
.
Hen
c
e,
th
e
tas
k
s
ex
ec
u
tio
n
o
r
d
er
w
it
h
i
n
th
e
SMD
o
r
th
e
ed
g
e
s
er
v
er
i
n
th
e
f
in
al
s
o
l
u
tio
n
m
u
s
t
f
u
l
f
ill
th
e
i
n
itial
o
r
d
er
f
o
r
b
o
th
ca
s
es.
A
cc
o
r
d
in
g
l
y
,
t
h
e
o
b
tain
ed
p
r
o
b
le
m
is
f
o
r
m
u
lated
as:
:
m
in
{
x
,
f
L
,
f
S
}
{
Λ
f
L
−
∑
λ
i
x
i
N
i
=
1
f
L
+
∑
d
i
x
i
N
i
=
1
r
+
∑
λ
i
x
i
N
i
=
1
f
S
}
,
s
.
t.
(
C
1
.
1
)
x
i
∈
{
0
;
1
}
;
i
∈
⟦
1
;
N
⟧
;
(
C
1
.
2
)
F
L
m
i
n
≤
f
L
≤
F
L
m
ax
;
(
C
1
.
3
)
0
<
f
S
≤
F
S
;
(
C
1
.
4
)
t
i
L
=
(
1
−
x
i
)
f
L
∑
λ
k
(
1
−
x
k
)
i
k
=
1
≤
t
i
m
ax
;
i
∈
⟦
1
;
N
⟧
;
(
C
1
.
5
)
t
i
O
=
x
i
∑
x
k
(
d
k
r
+
λ
k
f
S
)
i
k
=
1
≤
t
i
m
ax
;
i
∈
⟦
1
;
N
⟧
;
(
C
1
.
6
)
e
L
+
e
C
=
k
L
.
f
L
2
.
∑
λ
i
(
1
−
x
i
)
+
p
T
r
∑
d
i
x
i
N
i
=
1
N
i
=
1
≤
E
m
ax
.
I
n
th
i
s
w
o
r
k
,
ea
ch
o
n
e
o
f
t
h
e
av
ailab
le
tas
k
s
ca
n
b
e
eith
er
e
x
ec
u
ted
lo
ca
ll
y
o
r
o
f
f
lo
ad
ed
t
o
th
e
ed
g
e
n
o
d
e.
T
h
u
s
,
ev
er
y
f
ea
s
ib
le
o
f
f
lo
ad
in
g
d
ec
is
io
n
s
o
lu
t
io
n
h
a
s
to
s
atis
f
y
t
h
e
ab
o
v
e
co
n
s
tr
a
in
ts
.
T
h
e
co
n
s
tr
ain
t
(
C
1
.
1
)
r
ef
er
s
to
t
h
e
o
f
f
lo
ad
in
g
d
ec
i
s
io
n
v
ar
iab
le
x
i
f
o
r
tas
k
τ
i
w
h
ic
h
eq
u
al
s
0
o
r
1
.
T
h
e
s
ec
o
n
d
co
n
s
tr
ain
t
(
C
1
.
2
)
in
d
icate
s
t
h
at
th
e
allo
ca
ted
v
ar
iab
le
lo
ca
l
f
r
eq
u
en
c
y
f
L
b
elo
n
g
s
to
a
p
r
io
r
i
f
ix
in
ter
v
a
l
g
iv
e
n
b
y
[
F
L
m
i
n
,
F
L
m
ax
]
.
Si
m
ilar
l
y
,
t
h
e
al
lo
ca
ted
v
a
r
iab
le
r
em
o
te
ed
g
e
s
er
v
er
f
r
eq
u
en
c
y
f
S
b
elo
n
g
s
to
t
h
e
in
te
r
v
a
l
[
0
,
F
S
m
ax
]
in
co
n
s
tr
ain
t
(
C
1
.
3
)
.
T
h
e
c
o
n
s
tr
ain
t
(
C
1
.
4
)
s
h
o
w
s
th
at
t
h
e
ex
ec
u
tio
n
ti
m
e
o
f
ea
ch
d
ec
id
e
d
l
o
ca
l
task
m
u
s
t
s
ati
s
f
y
its
d
ea
d
lin
e
t
i
m
ax
.
Sim
ilar
l
y
,
in
co
n
s
tr
ai
n
t
(
C
1
.
5
)
,
th
e
o
f
f
lo
a
d
in
g
ti
m
e
o
f
ea
ch
d
ec
id
ed
o
f
f
lo
ad
ab
le
task
m
u
s
t
s
ati
s
f
y
th
e
s
a
m
e
d
ea
d
lin
e
t
i
m
ax
.
T
h
e
f
in
al
co
n
s
tr
ai
n
t
(
C
1
.
6
)
i
m
p
o
s
es
th
a
t
th
e
to
tal
lo
ca
l
ex
ec
u
ti
o
n
en
er
g
y
m
u
s
t
n
o
t
e
x
ce
ed
th
e
t
o
ler
ated
g
iv
e
n
a
m
o
u
n
t
E
m
ax
.
T
h
is
c
o
n
s
tr
ain
t
is
i
m
p
o
r
ta
n
t
esp
ec
ia
ll
y
f
o
r
SMD
s
w
it
h
cr
itical
b
atter
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
Time
a
n
d
r
eso
u
r
ce
co
n
s
tr
a
in
ed
o
fflo
a
d
i
n
g
w
ith
mu
lti
-
ta
s
k…
(
Mo
h
a
med
E
l G
h
ma
r
y
)
3761
3.
P
RO
B
L
E
M
RE
SO
L
UT
I
O
N
I
n
th
i
s
s
ec
tio
n
,
w
e
w
ill
i
n
tr
o
d
u
ce
h
o
w
w
e
d
er
iv
e
o
u
r
s
o
lu
tio
n
f
r
o
m
t
h
e
o
b
tain
ed
o
p
ti
m
izatio
n
p
r
o
b
lem
.
3
.
1
.
P
ro
ble
m
deco
m
po
s
it
io
n
I
n
o
u
r
p
r
o
p
o
s
ed
m
o
d
el,
th
e
o
f
f
lo
ad
in
g
d
ec
i
s
io
n
v
ec
to
r
f
o
r
all
th
e
tas
k
s
is
d
e
n
o
ted
.
L
e
t
d
ef
i
n
e
th
e
v
ec
to
r
t
h
at
co
n
tai
n
s
t
h
e
o
f
f
lo
ad
ab
le
task
s
’
id
en
ti
f
ier
s
:
1
=
{
i
∈
/
x
i
=
1
}
(
7
)
0
=
{
i
∈
/
x
i
=
0
}
(
8
)
A
d
d
itio
n
al
l
y
,
w
e
d
ef
in
e:
Λ
i
=
∑
λ
i
i
k
=
1
,
Λ
i
1
=
∑
x
i
λ
i
i
k
=
1
,
D
i
=
∑
d
i
i
k
=
1
,
D
i
1
=
∑
x
i
d
i
i
k
=
1
.
A
l
s
o
,
g
i
v
e
n
t
h
e
d
ec
is
io
n
v
e
cto
r
1
,
co
n
s
tr
ain
t
(
C
1
.
4
)
f
o
r
a
lo
ca
l
tas
k
ca
n
b
e
r
ef
o
r
m
u
lated
as
Λ
i
−
Λ
i
1
t
i
m
ax
≤
f
L
;
∀
i
∈
⟦
1
;
N
⟧
.
Fin
all
y
,
it
is
eq
u
i
v
ale
n
t
to
o
n
e
co
n
s
tr
ai
n
t:
ma
x
i
{
Λ
i
−
Λ
i
1
t
i
m
ax
}
≤
f
L
.
L
ik
e
w
i
s
e,
co
n
s
tr
ai
n
t
(
C
1
.
5
)
f
o
r
an
o
f
f
lo
ad
ab
le
tas
k
m
ea
n
s
D
i
1
r
+
Λ
i
1
f
S
≤
t
i
m
ax
(
∀
i
∈
⟦
1
;
N
⟧
)
.
So
D
i
1
r
an
d
Λ
i
1
f
S
m
u
s
t
b
e
s
tr
ictl
y
less
t
h
a
n
t
i
m
ax
(
∀
i
∈
⟦
1
;
N
⟧
)
;
p
ar
ticu
lar
l
y
min
i
{
t
i
m
ax
−
D
i
1
r
}
>
0
.
I
n
t
h
is
ca
s
e
co
n
s
tr
ai
n
ts
(
C
1
.
5
)
ca
n
b
e
r
ef
o
r
m
u
la
ted
as
Λ
i
1
t
i
m
ax
−
D
i
1
r
≤
f
S
;
∀
i
∈
⟦
1
;
N
⟧
.
Fin
all
y
,
it is
eq
u
iv
ale
n
t to
o
n
e
co
n
s
tr
ain
t
:
ma
x
i
{
Λ
i
1
t
i
m
ax
−
D
i
1
r
}
≤
f
S
.
Si
m
i
lar
l
y
,
co
n
s
tr
ai
n
t
(
C
1
.
6
)
m
ea
n
s
k
L
.
f
L
2
.
(
Λ
N
−
Λ
N
1
)
+
p
T
D
N
1
r
≤
E
m
ax
.
So
.
2
.
(
Λ
N
−
Λ
N
1
)
an
d
D
N
1
m
u
s
t b
e
s
tr
ictl
y
le
s
s
t
h
a
n
E
m
ax
.
I
n
th
is
ca
s
e
co
n
s
tr
ain
t
(
C
1
.
6
)
ca
n
b
e
r
ef
o
r
m
u
lated
as
f
L
≤
√
E
m
a
x
−
T
D
N
1
r
k
L
(
Λ
N
−
Λ
N
1
)
.
Fo
r
ea
s
e
o
f
u
s
e,
let
n
o
te:
f
L
−
=
ma
x
i
{
Λ
i
−
Λ
i
1
t
i
m
ax
}
;
(
9
)
f
L
+
=
√
E
m
ax
−
p
T
D
N
1
r
k
L
(
Λ
N
−
Λ
N
1
)
;
(
10
)
f
S
−
=
ma
x
i
{
Λ
i
1
t
i
m
ax
−
D
i
1
r
}
.
(
11
)
T
h
u
s
,
f
o
r
a
g
i
v
en
o
f
f
lo
ad
in
g
d
ec
is
io
n
v
ec
to
r
,
w
e
g
et
t
h
e
f
o
ll
o
w
i
n
g
o
p
ti
m
izatio
n
s
u
b
-
p
r
o
b
le
m
:
(
)
:
min
{
f
L
,
f
S
}
{
Λ
N
−
Λ
N
1
f
L
+
D
N
1
r
+
Λ
N
1
f
S
}
,
s
.
t.
(
C
2
.
1
)
F
L
m
i
n
≤
f
L
≤
F
L
m
ax
;
(
C
2
.
2
)
f
L
−
≤
f
L
;
(
C
2
.
3
)
f
S
−
≤
f
S
≤
F
S
;
(
C
2
.
4
)
k
L
f
L
2
(
Λ
N
−
Λ
N
1
)
+
p
T
D
N
1
r
≤
E
m
ax
.
C
o
n
s
id
er
in
g
t
h
e
co
n
tin
u
o
u
s
v
ar
iab
les
f
L
a
n
d
f
S
,
p
r
o
b
le
m
P
2
is
a
co
n
tin
u
o
u
s
m
u
lti
-
v
ar
iab
le
o
p
tim
izatio
n
p
r
o
b
lem
.
T
h
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
T
(
,
f
L
,
f
S
)
=
Λ
N
−
Λ
N
1
f
L
+
D
N
1
r
+
Λ
N
1
f
S
ca
n
b
e
d
ec
o
m
p
o
s
ed
in
to
th
e
f
o
llo
w
i
n
g
t
w
o
in
d
ep
en
d
e
n
t
f
u
n
ctio
n
s
T
1
(
f
L
)
an
d
T
2
(
f
S
)
w
h
er
e
T
1
(
f
L
)
=
Λ
N
−
Λ
N
1
f
L
an
d
T
2
(
f
S
)
=
D
N
1
r
+
Λ
N
1
f
S
.
Mo
r
eo
v
er
,
g
iv
en
t
h
e
d
is
j
u
n
cti
o
n
b
et
w
ee
n
co
n
s
tr
ai
n
ts
(
C
2
.
1
)
,
(
C
2
.
2
)
a
n
d
(
C
2
.
4
)
o
n
th
e
o
n
e
h
an
d
,
an
d
(
C
2
.
3
)
in
p
r
o
b
lem
P
2
o
n
th
e
o
th
er
h
an
d
,
th
is
last
ca
n
b
e
eq
u
iv
alen
tl
y
d
ec
o
m
p
o
s
ed
in
to
th
e
f
o
llo
w
in
g
t
w
o
i
n
d
ep
en
d
en
t
o
p
tim
izatio
n
s
u
b
-
p
r
o
b
lem
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
10
,
No
.
4
,
A
u
g
u
s
t 2
0
2
0
:
3
7
5
7
-
3766
3762
.
(
)
:
min
{
f
L
}
{
T
1
(
f
L
)
=
Λ
N
−
Λ
N
1
f
L
}
s
.
t.
(
C
3
.
1
.
1
)
F
L
m
i
n
≤
f
L
≤
F
L
m
ax
;
(
C
3
.
1
.
2
)
f
L
−
≤
f
L
≤
f
L
+
.
.
(
)
:
min
{
f
S
}
{
T
2
(
f
S
)
=
D
N
1
r
+
Λ
N
1
f
S
}
s
.
t.
(
C
3
.
2
.
1
)
f
S
−
≤
f
S
≤
F
S
.
3
.
2
.
P
ro
ble
m
s
re
s
o
lut
io
n
Fo
r
th
e
3
.
1
p
r
o
b
lem
,
t
h
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
T
1
(
f
L
)
is
a
s
tr
ictl
y
i
n
c
r
ea
s
in
g
co
n
t
in
u
o
u
s
f
u
n
ctio
n
ac
co
r
d
in
g
to
its
v
ar
iab
le
f
L
.
Hen
ce
,
b
y
tak
i
n
g
in
to
co
n
s
id
er
atio
n
th
e
o
b
tain
ed
co
n
s
tr
ai
n
ts
(
C
3
.
1
.
1
)
an
d
(
C
3
.
1
.
2
)
,
w
e
ca
n
d
er
iv
e
th
e
f
o
llo
w
i
n
g
f
u
n
ctio
n
’
s
o
p
ti
m
u
m
f
L
∗
g
iv
e
n
b
y
:
f
L
∗
=
{
0
if
=
1
∅
if
E
m
ax
≤
p
T
D
N
1
r
or
f
L
−
>
F
L
m
ax
or
f
L
+
<
F
L
m
i
n
or
f
L
−
>
f
L
+
F
L
m
ax
f
L
+
if
f
L
+
>
F
L
m
i
n
othe
r
w
ise
(
12
)
f
o
r
th
e
3
.
2
p
r
o
b
lem
,
th
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
T
2
(
f
S
)
is
s
tr
ictl
y
d
ec
r
ea
s
in
g
w
.
r
.
t.
t
h
e
v
ar
iab
le
.
So
,
b
y
tak
i
n
g
in
to
co
n
s
id
er
atio
n
t
h
e
(
3
.
2
.
1
)
co
n
s
tr
ain
t,
w
e
ca
n
d
er
iv
e
t
h
e
f
o
llo
w
in
g
f
u
n
ctio
n
’
s
o
p
ti
m
u
m
∗
g
i
v
en
b
y
:
f
S
∗
=
{
∅
if
min
i
{
t
i
m
ax
−
D
i
1
r
}
≤
0
or
f
S
−
>
F
S
F
S
othe
r
wi
s
e
(
13
)
3
.
2
.
1.
T
he
pro
ce
s
s
ing
t
i
m
e
d
et
er
m
i
na
t
io
n
Si
m
i
lar
l
y
,
g
i
v
e
n
an
o
f
f
lo
ad
in
g
d
ec
is
io
n
v
ec
to
r
th
e
f
o
llo
w
in
g
alg
o
r
it
h
m
u
s
e
s
th
e
f
ir
s
t
alg
o
r
ith
m
to
d
eter
m
in
e
t
h
e
m
in
i
m
al
p
r
o
ce
s
s
in
g
ti
m
e:
Alg
o
rit
h
m
1
: P
r
o
ce
s
s
in
g
ti
m
e
ca
lcu
latio
n
I
np
ut:
T
h
e
lis
t
o
f
N
s
u
b
-
tas
k
s
,
o
f
f
lo
ad
in
g
p
o
lic
y
.
O
utput
:
(
,
,
)
.
1:
C
alcu
late
(
,
)
u
s
in
g
ac
co
r
d
in
g
to
(
12
)
an
d
(
13
)
;
2:
if
=
∅
o
r
=
∅
t
hen
3:
re
t
urn
∞;
4:
else
5:
C
alcu
late
(
,
,
)
ac
co
r
d
in
g
to
(
14
)
;
6:
r
et
urn
(
,
,
)
;
7:
end if
3
.
3
.
P
ro
po
s
ed
s
o
lutio
ns
Nex
t,
t
h
e
p
r
o
b
le
m
r
elies
o
n
d
eter
m
in
i
n
g
t
h
e
o
p
ti
m
al
o
f
f
lo
ad
in
g
d
ec
is
io
n
v
ec
to
r
th
at
g
i
v
es
th
e
o
p
ti
m
al
p
r
o
ce
s
s
i
n
g
ti
m
e.
Ho
w
e
v
er
,
to
iter
ate
o
v
er
all
p
o
s
s
ib
le
co
m
b
i
n
atio
n
s
o
f
a
li
s
t o
f
N
b
in
ar
y
v
ar
iab
les
,
th
e
ti
m
e
co
m
p
lex
i
t
y
is
e
x
p
o
n
en
tial
(
t
h
e
e
x
h
a
u
s
tiv
e
s
ea
r
ch
o
v
er
all
p
o
s
s
ib
le
s
o
lu
tio
n
s
r
eq
u
ir
es
2
N
iter
atio
n
s
)
.
Su
b
s
eq
u
e
n
tl
y
,
t
h
e
to
tal
ti
m
e
c
o
m
p
le
x
it
y
o
f
t
h
e
w
h
o
le
s
o
l
u
ti
o
n
(
in
clu
d
i
n
g
A
lg
o
r
it
h
m
1
)
is
O(
2
N
)
*
O(
1
)
=O
(
2
N
)
th
at
i
s
n
o
t
p
r
ac
tical
f
o
r
lar
g
e
v
al
u
es
o
f
N.
I
n
t
h
e
f
o
llo
w
i
n
g
,
w
e
p
r
o
p
o
s
e
a
lo
w
co
m
p
l
ex
it
y
ap
p
r
o
x
i
m
ate
alg
o
r
ith
m
to
s
o
lv
e
t
h
i
s
q
u
est
io
n
.
3
.
3
.
1
.
B
rut
e
f
o
rc
e
s
ea
rc
h so
lu
t
io
n
Fo
r
co
m
p
ar
is
o
n
p
u
r
p
o
s
e,
w
e
i
n
tr
o
d
u
ce
th
e
B
r
u
te
Fo
r
ce
Sea
r
ch
m
et
h
o
d
f
o
r
f
ea
s
ib
le
s
m
all
v
alu
e
s
o
f
N.
T
h
is
m
eth
o
d
ex
p
lo
r
es
all
ca
s
es
o
f
o
f
f
lo
ad
in
g
d
ec
is
io
n
s
an
d
s
av
e
s
th
e
o
n
e
w
i
th
t
h
e
m
in
i
m
u
m
p
r
o
ce
s
s
i
n
g
ti
m
e
as
w
e
ll a
s
it
s
co
m
p
letio
n
ti
m
e.
No
w
,
th
e
n
ex
t
alg
o
r
it
h
m
s
u
m
m
ar
izes
t
h
e
b
r
u
te
f
o
r
ce
s
e
ar
ch
s
o
lu
tio
n
.
Alg
o
rit
h
m
2
:
B
r
u
te
Fo
r
ce
Sear
ch
Of
f
lo
ad
in
g
I
np
ut:
T
h
e
lis
t
τ
o
f
N
s
u
b
-
tas
k
s
;
O
utput
:
th
e
o
f
f
lo
ad
in
g
p
o
lic
y
∗
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
Time
a
n
d
r
eso
u
r
ce
co
n
s
tr
a
in
ed
o
fflo
a
d
i
n
g
w
ith
mu
lti
-
ta
s
k…
(
Mo
h
a
med
E
l G
h
ma
r
y
)
3763
I
nitia
lize:
m
i
n
T
i
m
e
=
∞
;
1:
←
;
2:
w
hil
e
≤
−
do
3:
Use th
e
N
b
its
r
ep
r
esen
tatio
n
o
f
in
teg
er
i to
b
u
ild
th
e
p
o
licy
;
4:
C
all
Alg
o
rit
h
m
2
to
g
et
n
e
w
T
i
m
e
u
s
in
g
τ
an
d
;
5:
if
<
t
hen
6:
←
;
7:
∗
←
;
8:
end if
9:
←
+
;
10:
end w
hil
e
11:
re
t
urn
∗
;
3
.
3
.
2
.
Si
m
u
la
t
ed
a
nn
ea
lin
g
o
f
f
lo
a
din
g
decisi
o
n
s
o
lutio
n
W
e
p
r
o
p
o
s
e
a
m
et
h
o
d
b
ased
o
n
s
i
m
u
lated
an
n
ea
li
n
g
(
S
A
)
as
th
e
s
ec
o
n
d
s
o
lu
t
io
n
.
I
n
t
h
e
f
ie
ld
o
f
o
p
tim
izatio
n
,
th
e
S
A
tec
h
n
iq
u
e
h
as
b
ee
n
ad
o
p
ted
as
a
h
eu
r
is
tic
s
o
l
u
tio
n
a
n
d
in
p
ar
ticu
lar
f
o
r
d
if
f
ic
u
l
t
p
r
o
b
lem
s
.
T
o
im
p
r
o
v
e
a
s
o
lu
tio
n
,
it
u
s
es
an
iter
ati
v
e
r
an
d
o
m
s
o
lu
t
io
n
v
ar
iatio
n
.
I
n
te
r
ested
r
ea
d
er
s
m
a
y
co
n
s
u
lt
th
e
f
o
llo
w
i
n
g
w
o
r
k
s
[
2
6
]
an
d
[
2
7
]
f
o
r
m
o
r
e
d
etails
ab
o
u
t
th
is
is
s
u
e.
So
m
e
r
ef
er
en
ce
s
d
ea
lin
g
w
it
h
th
e
o
f
f
lo
ad
i
n
g
in
clo
u
d
e
n
v
ir
o
n
m
e
n
t
s
[
7
,
2
8
,
2
9
]
u
s
e
tas
k
s
’
w
o
r
k
lo
ad
d
en
s
it
y
d
ef
in
ed
a
s
ω
i
=
λ
i
d
i
[
c
y
cle
/ b
it]
a
s
a
p
r
io
r
ity
f
ac
to
r
to
d
ec
id
e
th
e
task
s
’
o
f
f
lo
ad
in
g
.
A
d
d
itio
n
all
y
,
th
e
g
e
n
er
ated
task
s
ar
e
g
e
n
er
all
y
w
ith
d
if
f
er
e
n
t
w
o
r
k
lo
ad
d
en
s
it
ies.
Mo
r
eo
v
er
,
if
t
w
o
task
s
ar
e
g
iv
e
n
w
i
th
a
s
lig
h
tl
y
d
if
f
er
en
t
d
ata
s
izes,
th
e
o
n
e
th
at
co
n
s
u
m
e
s
less
p
r
o
ce
s
s
i
n
g
ti
m
e
is
th
e
o
n
e
g
iv
e
n
b
y
th
e
s
m
al
lest
c
y
cles
’
co
u
n
t.
B
esid
es,
w
i
th
al
m
o
s
t
th
e
s
a
m
e
c
y
cles
’
co
u
n
t,
th
e
o
n
e
th
at
co
n
s
u
m
es
les
s
o
f
f
lo
ad
in
g
p
r
o
ce
s
s
i
n
g
t
i
m
e
i
s
th
e
o
n
e
g
i
v
e
n
b
y
th
e
s
m
a
lles
t
d
ata
s
ize.
I
n
b
o
th
ca
s
es,
t
h
e
tas
k
w
i
th
t
h
e
h
i
g
h
est
w
o
r
k
lo
ad
d
en
s
it
y
is
f
av
o
r
ab
le
f
o
r
o
f
f
lo
ad
in
g
(
p
r
o
v
id
ed
to
h
av
e
an
o
f
f
lo
ad
in
g
en
er
g
y
g
ain
co
m
p
ar
ed
to
th
e
lo
ca
l
ex
ec
u
tio
n
a
n
d
n
o
t
to
e
x
ce
ed
it
s
e
x
ec
u
t
io
n
d
ea
d
li
n
e)
.
On
th
e
o
t
h
er
h
a
n
d
,
a
task
w
it
h
a
h
ig
h
w
o
r
k
lo
ad
d
en
s
it
y
o
f
te
n
h
as
a
lar
g
e
n
u
m
b
er
o
f
c
y
cle
s
.
I
ts
lo
ca
l
ex
ec
u
t
io
n
is
g
e
n
er
all
y
v
er
y
ex
p
e
n
s
i
v
e
a
n
d
th
u
s
m
a
k
es
it
s
o
f
f
lo
ad
in
g
o
f
ten
v
er
y
f
a
v
o
r
ab
le.
I
n
th
is
c
o
n
tex
t,
w
e
in
tr
o
d
u
ce
a
w
o
r
k
lo
ad
d
en
s
it
y
t
h
r
es
h
o
ld
ω
T
s
u
ch
t
h
at
:
tas
k
s
w
it
h
ω
i
>
ω
T
ar
e
m
o
r
e
f
av
o
r
ab
le
to
b
e
o
f
f
lo
ad
ed
.
T
h
e
o
th
er
s
ar
e
ex
ec
u
ted
lo
ca
lly
o
r
o
f
f
lo
ad
ed
w
it
h
a
p
r
o
p
o
r
tio
n
al
p
r
o
b
ab
ilit
y
to
th
eir
co
m
p
u
tatio
n
a
l
d
en
s
it
ies.
T
h
o
s
e
w
it
h
s
m
all
d
e
n
s
it
ies
ar
e
f
av
o
r
ab
le
f
o
r
lo
ca
l
ex
ec
u
tio
n
,
an
d
th
o
s
e
w
i
th
h
i
g
h
d
e
n
s
i
ties
ar
e
f
av
o
r
ab
le
to
b
e
o
f
f
lo
ad
ed
.
A
cc
o
r
d
in
g
l
y
,
i
f
w
e
n
o
te
ω
m
i
n
=
min
i
{
ω
i
}
,
ω
m
ax
=
ma
x
i
{
ω
i
}
an
d
th
e
m
id
d
le
o
f
th
e
i
n
ter
v
al
[
ω
m
ax
,
ω
m
i
n
]
as
ω
T
=
(
ω
m
ax
+
ω
m
i
n
)
/
2
th
en
ω
T
ca
n
b
e
ch
o
s
en
s
u
c
h
t
h
at
ω
T
≤
ω
T
<
ω
m
ax
.
I
n
o
u
r
p
r
o
p
o
s
ed
s
ec
o
n
d
s
o
l
u
ti
o
n
,
w
h
ich
w
e
d
en
o
te
s
i
m
u
late
d
an
n
ea
l
in
g
o
f
f
lo
ad
in
g
d
ec
is
io
n
(
S
A
O
D
)
,
w
e
ad
o
p
ted
th
e
f
o
llo
w
i
n
g
g
e
n
er
al
th
r
esh
o
ld
p
r
o
b
ab
ilit
y
:
p
=
e
−
∆
T
i
/
T
0
(
1
4
)
w
h
er
e
T
0
is
th
e
in
itial
te
m
p
er
at
u
r
e
co
n
s
tan
t.
∆
T
i
is
th
e
s
o
lu
tio
n
s
’
p
r
o
ce
s
s
in
g
ti
m
e
v
ar
iatio
n
w
h
ile
ch
a
n
g
i
n
g
th
e
tas
k
i
s
tate.
T
h
en
,
in
ea
c
h
s
tag
e
o
f
o
u
r
s
o
lu
tio
n
a
n
d
w
it
h
th
e
in
te
n
tio
n
to
av
o
id
lo
ca
l
o
p
tim
u
m
s
,
r
a
n
d
o
m
s
o
lu
tio
n
s
w
it
h
p
o
o
r
p
r
o
ce
s
s
in
g
ti
m
e
p
er
f
o
r
m
a
n
ce
ar
e
ac
ce
p
ted
in
lin
e
w
ith
a
ce
r
tain
p
r
o
b
a
b
ilit
y
t
h
r
es
h
o
ld
.
A
cc
o
r
d
in
g
l
y
,
t
h
e
n
ex
t a
l
g
o
r
ith
m
s
u
m
m
ar
ize
s
o
u
r
h
e
u
r
is
tic
s
o
lu
tio
n
.
Alg
o
rit
h
m
3
: Si
m
u
lated
A
n
n
e
alin
g
Of
f
lo
ad
in
g
Dec
i
s
io
n
I
np
ut:
T
h
e
lis
t
o
f
N
s
u
b
-
tas
k
s
,
T
0
,
C
F,
,
;
O
utput
: th
e
o
f
f
lo
ad
i
n
g
p
o
lic
y
∗
.
I
nitia
lize:
a
r
an
d
o
m
p
o
lic
y
;
1:
C
all
Alg
o
rit
h
m
1
to
ca
lcu
late
o
ld
T
im
e
u
s
i
n
g
an
d
;
2:
m
i
n
T
i
m
e=
∞;
3:
w
hil
e
T
0
>
do
4:
f
o
r
e
a
ch
i in
do
5:
if
>
t
hen
6:
if
task
i n
o
t in
1
t
hen
7:
ad
d
i to
1
;
8:
end if
9:
else if
−
≥
(
−
)
∗
r
a
n
dom
(
0
,
1
)
t
hen
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
10
,
No
.
4
,
A
u
g
u
s
t 2
0
2
0
:
3
7
5
7
-
3766
3764
10:
if
task
i in
1
t
hen
11:
m
o
v
e
i f
r
o
m
1
to
0
;
12:
end if
13:
else if
task
i in
0
t
hen
14:
m
o
v
e
i
f
r
o
m
0
to
1
;
15:
end if
16:
end if
17:
end if
18:
Up
d
ate
u
s
in
g
t
h
e
n
e
w
1
;
19:
C
all
Alg
o
rit
h
m
1
to
g
e
t n
e
w
T
i
m
e
u
s
in
g
an
d
;
20:
if
n
e
w
T
im
e
≠
∞ t
h
e
n
21:
∆
=
n
e
w
Ti
m
e
−
ol
dT
ime
22:
if
∆
<
0
t
hen
23:
o
ld
T
im
e
=
n
e
w
T
i
m
e
;
24:
i
f
n
e
w
T
im
e
<
m
i
n
T
i
m
e
t
hen
25:
m
i
n
T
i
m
e
=
n
e
w
T
i
m
e
;
∗
=
;
26:
end if
27:
else
28:
C
alcu
late
p
ac
co
r
d
in
g
to
(
1
4
)
;
29:
if
−
∆
/
0
>
r
a
n
dom
(
0
,
1
)
t
hen
30:
o
ld
T
im
e
=
n
e
w
T
i
m
e;
31:
else
32:
P
u
t b
ac
k
i to
its
o
r
ig
in
a
l set;
33:
end if
34:
end if
35:
end if
36:
end f
o
r
37:
T
0
=
T
0
*
C
F
38:
end w
ile
39:
re
t
urn
∗
;
I
n
th
i
s
alg
o
r
it
h
m
,
r
a
nd
o
m
(
0
,
1
)
is
a
f
u
n
ctio
n
’
s
ca
ll t
h
at
g
e
n
er
a
tes a
r
an
d
o
m
n
u
m
b
er
i
n
[
0
,
1
]
.
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
4
.
1
.
Si
m
ula
t
io
n set
up
T
h
e
p
r
esen
ted
r
esu
l
ts
i
n
t
h
i
s
w
o
r
k
ar
e
a
v
er
ag
ed
f
o
r
1
0
0
ti
m
e
e
x
ec
u
tio
n
s
.
W
e
i
m
p
l
e
m
en
t
al
l
th
e
al
g
o
r
ith
m
s
o
n
t
h
e
C
++
l
an
g
u
a
g
e.
T
h
e
tr
an
s
m
i
s
s
io
n
b
an
d
w
id
th
b
et
w
ee
n
t
h
e
m
o
b
ile
d
ev
i
ce
n
o
d
e
a
n
d
r
e
m
o
te
ed
g
e
s
er
v
er
i
s
s
et
to
r
=
1
0
0
Kb
/s
.
T
h
e
lo
ca
l
C
P
U
f
r
eq
u
en
c
y
f
L
o
f
th
e
m
o
b
ile
d
ev
ice
w
il
l
b
e
o
p
ti
m
ized
b
et
w
ee
n
F
L
m
i
n
=
1M
Hz
an
d
F
L
m
ax
=
60M
Hz
.
T
h
e
C
P
U
f
r
e
q
u
en
c
y
o
f
th
e
r
e
m
o
te
ed
g
e
s
er
v
er
n
o
d
e
w
ill
b
e
o
p
tim
ized
u
n
d
er
th
e
v
a
lu
e
F
S
=
6G
Hz
.
T
h
e
d
ea
d
lin
es
t
i
m
ax
ar
e
u
n
i
f
o
r
m
l
y
d
e
f
i
n
ed
f
r
o
m
0
.
5
s
to
2
s
.
T
h
e
th
r
esh
o
ld
en
er
g
y
E
m
ax
is
u
n
i
f
o
r
m
l
y
ch
o
s
e
n
in
[
0
.
6
,
0
.
8
]
∗
Λ
.
k
L
.
(
F
L
m
ax
)
2
.
A
d
d
itio
n
all
y
,
th
e
d
ata
s
ize
o
f
ea
ch
o
n
e
o
f
t
h
e
N
tas
k
s
is
ass
u
m
ed
to
b
e
in
[
3
0
,
3
0
0
]
Kb
.
Fo
r
th
e
c
y
c
le
a
m
o
u
n
t
o
f
ea
ch
t
ask
,
i
t
is
as
s
u
m
ed
to
b
elo
n
g
to
[
6
0
,
6
0
0
]
MCy
cle
s
.
T
h
e
id
le
p
o
w
er
an
d
tr
an
s
m
i
s
s
io
n
p
o
w
er
ar
e
s
et
to
b
e
p
I
=
0
.
01
W
att
an
d
p
T
=
0
.
1
W
att
r
esp
ec
tiv
el
y
.
Fo
r
th
e
en
er
g
y
e
f
f
icie
n
c
y
co
e
f
f
ic
ien
t
s
,
w
e
s
et
k
L
=
10
−
26
an
d
k
S
=
10
−
29
.
Fo
r
t
h
e
s
i
m
u
lated
an
n
ea
lin
g
m
et
h
o
d
,
th
e
f
o
llo
w
i
n
g
p
ar
a
m
eter
v
alu
e
s
ar
e
ad
o
p
ted
:
f
ac
to
r
=
0
.
5
,
ε
=
0
.
3
,
ε
m
i
n
=
0
.
1
an
d
ε
m
ax
=
0
.
4
,
T
0
=
2
0
0
,
Δ
t
=
0
.
0
2
,
C
F
=0
.
5
.
4
.
2
.
P
er
f
o
r
m
a
nce
a
na
ly
s
is
W
e
p
r
esen
t
o
u
r
r
esu
lt
s
i
n
te
r
m
s
o
f
a
v
er
ag
e
d
ec
i
s
io
n
ti
m
e
an
d
av
er
ag
e
ta
s
k
s
’
p
r
o
ce
s
s
in
g
ti
m
e.
W
e
s
tar
t
b
y
s
tu
d
y
in
g
t
h
e
a
v
e
r
ag
e
tas
k
s
’
p
r
o
ce
s
s
i
n
g
ti
m
e
f
o
r
ea
ch
m
et
h
o
d
.
T
h
u
s
,
w
e
ca
r
r
ied
an
ex
p
er
i
m
e
n
t
w
h
er
e
w
e
v
ar
y
th
e
n
u
m
b
er
o
f
t
ask
s
p
ar
a
m
eter
b
et
w
ee
n
2
an
d
2
6
task
s
.
4
.
2
.
1
.
T
he
pro
ce
s
s
ing
t
i
m
e
Fo
r
ea
ch
m
et
h
o
d
,
w
e
s
tar
t
b
y
s
t
u
d
y
i
n
g
t
h
e
a
v
er
ag
e
ta
s
k
s
’
p
r
o
ce
s
s
i
n
g
ti
m
e.
T
h
u
s
,
w
e
ca
r
r
ied
an
ex
p
er
i
m
en
t
w
h
er
e
w
e
v
ar
y
th
e
n
u
m
b
er
o
f
tas
k
s
p
ar
a
m
eter
b
et
w
ee
n
2
an
d
2
6
.
T
h
e
ex
p
er
i
m
e
n
t
’
s
r
es
u
lts
ar
e
d
ep
icted
in
th
e
f
o
llo
w
in
g
t
w
o
f
i
g
u
r
es.
Fig
u
r
e
3
r
ep
r
esen
ts
th
e
o
b
tain
ed
r
esu
lt
s
f
o
r
b
o
th
b
as
ed
s
o
lu
tio
n
(
B
FS
)
an
d
Si
m
u
la
ted
An
n
ea
li
n
g
b
a
s
ed
s
o
lu
tio
n
(
S
AO
D
)
.
I
t
s
h
o
w
s
a
s
m
al
l
d
is
ta
n
ce
b
et
w
ee
n
t
h
e
cu
r
v
e
s
r
ep
r
esen
ti
n
g
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
Time
a
n
d
r
eso
u
r
ce
co
n
s
tr
a
in
ed
o
fflo
a
d
i
n
g
w
ith
mu
lti
-
ta
s
k…
(
Mo
h
a
med
E
l G
h
ma
r
y
)
3765
th
e
r
ea
lized
av
er
ag
ed
tas
k
s
’
p
r
o
ce
s
s
in
g
ti
m
e.
A
cc
o
r
d
in
g
l
y
,
th
e
d
if
f
er
en
ce
s
b
et
w
ee
n
th
e
o
p
ti
m
al
B
FS
m
et
h
o
d
an
d
th
e
S
AO
D
m
e
th
o
d
v
ar
y
f
r
o
m
0
.
0
0
% to
2
.
1
5
%.
4
.
2
.
2
.
T
he
a
v
er
a
g
e
ex
ec
utio
n t
i
m
e
No
w
Fi
g
u
r
e
4
d
ep
icts
th
e
av
er
ag
e
o
f
th
e
ex
ec
u
tio
n
ti
m
e
i
n
m
s
to
g
e
t
t
h
e
o
f
f
lo
ad
in
g
d
e
cisi
o
n
s
f
o
r
b
o
th
s
ch
e
m
es
.
W
h
ile
th
e
tas
k
s
co
u
n
t
N
is
b
et
w
ee
n
2
an
d
2
6
,
it
clea
r
ly
s
h
o
w
s
t
h
e
e
x
p
o
n
en
t
ial
v
ar
iat
io
n
o
f
th
e
B
F
S
e
x
ec
u
t
io
n
ti
m
e
w
.
r
.
t.
N.
A
d
d
itio
n
all
y
,
t
h
e
S
A
O
D
c
u
r
v
e
ill
u
s
tr
ate
s
a
s
li
g
h
tl
y
s
tab
le
r
u
n
n
i
n
g
ti
m
e
t
h
at
s
tar
ts
f
r
o
m
0
.
2
m
s
f
o
r
N=
2
an
d
r
ea
ch
es 0
.
6
2
m
s
f
o
r
N=
2
1
.
Fig
u
r
e
3
.
T
ask
s
’
p
r
o
ce
s
s
i
n
g
ti
m
e
f
o
r
N
b
et
w
ee
n
2
an
d
2
6
Fig
u
r
e
4
.
E
x
ec
u
t
io
n
ti
m
e
av
er
ag
e
f
o
r
N
b
et
w
ee
n
2
an
d
2
0
4
.
3
.
Dis
cu
s
io
n
I
n
v
ie
w
o
f
t
h
e
r
es
u
lt
s
p
r
esen
t
ed
b
ef
o
r
e,
o
u
r
h
e
u
r
is
tic
s
o
l
u
t
io
n
s
S
A
O
D
g
i
v
e
s
atis
f
ac
to
r
y
r
esu
lt
s
i
n
ter
m
s
o
f
e
x
ec
u
tio
n
ti
m
e.
I
n
ad
d
itio
n
,
o
u
r
s
o
lu
tio
n
g
i
v
es
a
n
a
v
er
ag
e
tas
k
s
’
p
r
o
ce
s
s
i
n
g
ti
m
e
th
at
i
s
co
m
p
ar
ab
l
e
an
d
v
er
y
clo
s
e
to
t
h
e
o
p
ti
m
al
s
o
lu
tio
n
w
it
h
a
n
al
m
o
s
t li
n
ea
r
ex
ec
u
t
io
n
ti
m
e.
5.
CO
NCLU
SI
O
N
In
t
h
is
p
ap
er
,
w
e
p
r
o
p
o
s
e
a
s
i
m
u
lated
a
n
n
ea
l
in
g
b
a
s
ed
h
e
u
r
is
tic
s
o
l
u
tio
n
to
s
o
lv
e
a
h
ar
d
d
ec
is
io
n
p
r
o
b
lem
th
at
j
o
in
tl
y
o
p
ti
m
izes
th
e
p
r
o
ce
s
s
in
g
ti
m
e
an
d
co
m
p
ut
in
g
r
eso
u
r
ce
s
f
o
r
a
s
m
ar
t
m
o
b
ile
d
ev
ice
w
i
th
i
n
a
m
o
b
ile
ed
g
e
-
co
m
p
u
ti
n
g
n
o
d
e.
T
h
e
m
o
b
ile
d
ev
ice
i
n
ten
d
s
t
o
o
p
tim
all
y
o
f
f
lo
ad
th
e
co
n
ten
t
o
f
a
lis
t
o
f
h
ea
v
y
task
s
.
E
ac
h
ta
s
k
in
its
lis
t
is
ti
m
e
-
co
n
s
tr
ain
ed
w
it
h
a
p
r
o
p
er
d
ea
d
lin
e.
T
h
e
o
b
ta
in
ed
r
esu
lts
s
h
o
w
th
e
p
er
f
o
r
m
a
n
ce
o
f
th
e
p
r
o
p
o
s
ed
s
i
m
u
lated
an
n
ea
li
n
g
b
ase
d
alg
o
r
ith
m
.
B
y
o
p
ti
m
al
l
y
ad
j
u
s
ti
n
g
th
e
lo
ca
l
an
d
th
e
r
e
m
o
te
co
m
p
u
t
in
g
f
r
eq
u
e
n
cies,
t
h
e
p
r
o
p
o
s
ed
i
m
p
le
m
e
n
tatio
n
s
h
o
w
s
t
h
e
e
f
f
ec
ti
v
en
e
s
s
o
f
o
u
r
s
o
l
u
tio
n
.
I
t b
r
o
u
g
h
t
a
r
ea
l
p
r
o
ce
s
s
i
n
g
ti
m
e
e
f
f
icie
n
c
y
w
it
h
al
m
o
st
a
li
n
ea
r
ex
ec
u
tio
n
ti
m
e
th
at
s
ati
s
f
ies
t
h
e
d
ec
is
io
n
ti
m
e
co
n
s
tr
ain
t
s
in
s
u
c
h
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.
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o
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d
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u
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icatio
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in
ter
f
er
e
n
ce
.
RE
F
E
R
E
NC
E
S
[1
]
R.
Ch
e
tan
a
n
d
R.
S
h
a
h
a
b
a
d
k
a
r,
“
A
c
o
m
p
re
h
e
n
siv
e
su
rv
e
y
o
n
e
x
it
in
g
so
l
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ti
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n
a
p
p
ro
a
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h
e
s
to
w
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rd
s
se
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u
rit
y
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n
d
p
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c
y
r
e
q
u
irem
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n
ts
o
f
Io
T
,
”
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n
ter
n
a
ti
o
n
a
l
J
o
u
r
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a
l
o
f
El
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c
tric
a
l
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d
Co
mp
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En
g
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rin
g
,
v
o
l.
8
,
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o
.
4
,
p
p
.
2
3
1
9
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2
3
2
6
,
2
0
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8
.
[2
]
M
.
ET
S
I,
"
M
o
b
il
e
e
d
g
e
c
o
m
p
u
ti
n
g
-
in
tro
d
u
c
t
o
ry
tec
h
n
ica
l
w
h
it
e
p
a
p
e
r,
"
ET
S
I2
0
1
4
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o
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il
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,
2
0
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4
.
[
On
li
n
e
].
Av
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il
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w
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o
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/n
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w
s/
[3
]
P
.
M
a
c
h
a
n
d
Z
.
Be
c
v
a
r,
“
M
o
b
il
e
Ed
g
e
Co
m
p
u
ti
n
g
:
A
S
u
rv
e
y
o
n
A
rc
h
it
e
c
tu
re
a
n
d
Co
m
p
u
tatio
n
Of
f
l
o
a
d
in
g
,
”
IEE
E
Co
mm
u
n
ica
ti
o
n
s S
u
rv
e
y
s
&
T
u
to
ria
ls,
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l
.
1
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p
.
1
6
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6
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6
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.
[4
]
T
.
S
o
y
a
ta,
R.
M
u
ra
lee
d
h
a
ra
n
,
C.
F
u
n
a
i,
M
.
Kw
o
n
,
a
n
d
W
.
He
in
z
e
l
m
a
n
,
“
Clo
u
d
-
v
isi
o
n
:
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l
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ti
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it
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,
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in
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[5
]
M
.
P
a
tel,
B.
Na
u
g
h
t
o
n
,
C.
C
h
a
n
,
N.
S
p
re
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h
e
r,
S
.
A
b
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ta,
a
n
d
A
.
Ne
a
l,
“
M
o
b
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g
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o
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ti
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o
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c
to
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ica
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”
W
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a
p
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mo
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0
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4
.
[6
]
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.
L
y
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,
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T
ian
,
C.
S
e
n
g
u
l,
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P
.
Z
h
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g
,
“
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u
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g
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n
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o
p
ti
m
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ti
o
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i
n
p
ro
x
im
a
te
c
lo
u
d
s,”
I
EE
E
T
r
a
n
s
a
c
ti
o
n
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n
V
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la
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6
6
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.
4
,
p
p
.
3
4
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-
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4
4
7
,
2
0
1
6
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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[7
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M.
-
H.
C
h
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n
,
B.
L
ian
g
,
a
n
d
M
.
Do
n
g
,
“
Jo
i
n
t
o
f
f
lo
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e
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isio
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n
d
re
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ll
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,
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p
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ted
a
t
t
h
e
2
0
1
6
IEE
E
In
ter
n
a
ti
o
n
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l
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fer
e
n
c
e
o
n
Co
mm
u
n
ica
ti
o
n
s (
ICC),
2
0
1
6
.
[8
]
L
.
Ya
n
g
,
J.
Ca
o
,
H.
Ch
e
n
g
,
a
n
d
Y.
Ji,
“
M
u
lt
i
-
u
se
r
c
o
m
p
u
tatio
n
p
a
rti
ti
o
n
i
n
g
f
o
r
late
n
c
y
s
e
n
siti
v
e
m
o
b
il
e
c
lo
u
d
a
p
p
li
c
a
ti
o
n
s,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
C
o
mp
u
ter
s
,
v
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l.
6
4
,
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o
.
8
,
p
p
.
2
2
5
3
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2
2
6
6
,
2
0
1
4
.
[9
]
V
.
Ca
rd
e
ll
in
i
,
e
t
a
l
.
,
“
A
g
a
m
e
-
th
e
o
re
ti
c
a
p
p
ro
a
c
h
to
c
o
m
p
u
ta
ti
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n
o
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f
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d
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g
in
m
o
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il
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c
lo
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d
c
o
m
p
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ti
n
g
,
”
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a
th
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l
Pro
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ra
mm
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g
,
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o
l
.
1
5
7
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o
.
2
,
p
p
.
4
2
1
-
4
4
9
,
2
0
1
6
.
[1
0
]
X
.
Ch
e
n
,
“
De
c
e
n
tralize
d
c
o
m
p
u
tatio
n
o
f
f
lo
a
d
in
g
g
a
m
e
f
o
r
m
o
b
il
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lo
u
d
c
o
m
p
u
ti
n
g
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Pa
ra
ll
e
l
a
n
d
Distri
b
u
ted
S
y
ste
ms
,
v
o
l.
2
6
,
n
o
.
4
,
p
p
.
9
7
4
-
9
8
3
,
2
0
1
4
.
[1
1
]
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.
C
h
e
n
,
L
.
Jia
o
,
W
.
L
i,
a
n
d
X
.
F
u
,
“
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f
icie
n
t
m
u
lt
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-
u
se
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o
m
p
u
tatio
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o
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f
lo
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d
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g
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o
r
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o
b
il
e
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e
d
g
e
c
lo
u
d
c
o
m
p
u
ti
n
g
,
”
IEE
E/
ACM
T
r
a
n
sa
c
t
io
n
s
o
n
Ne
tw
o
rk
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g
,
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o
l.
2
4
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o
.
5
,
p
p
.
2
7
9
5
-
2
8
0
8
,
2
0
1
6
.
[1
2
]
L
.
P
u
,
X
.
C
h
e
n
,
J.
X
u
,
a
n
d
X
.
F
u
,
“
D2
D
f
o
g
g
in
g
:
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n
e
n
e
rg
y
-
e
ff
icie
n
t
a
n
d
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e
n
ti
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e
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w
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re
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a
sk
o
ff
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f
ra
m
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rk
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n
e
t
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o
rk
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s
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d
D2
D
c
o
ll
a
b
o
ra
ti
o
n
,
”
IEE
E
J
o
u
rn
a
l
o
n
S
e
lec
ted
Are
a
s
in
Co
mm
u
n
i
c
a
ti
o
n
s
,
v
o
l.
3
4
,
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o
.
1
2
,
p
p
.
3
8
8
7
-
3
9
0
1
,
2
0
1
6
.
[1
3
]
A
.
A
l
-
S
h
u
w
a
il
i
a
n
d
O.
S
im
e
o
n
e
,
“
En
e
rg
y
-
e
ff
icie
n
t
re
so
u
rc
e
a
ll
o
c
a
ti
o
n
f
o
r
m
o
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il
e
e
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g
e
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o
m
p
u
ti
n
g
-
b
a
se
d
a
u
g
m
e
n
ted
re
a
li
ty
a
p
p
li
c
a
ti
o
n
s,”
I
EE
E
W
ire
les
s Co
mm
u
n
ica
t
io
n
s L
e
tt
e
rs
,
v
o
l.
6
,
n
o
.
3
,
p
p
.
3
9
8
-
4
0
1
,
2
0
1
7
.
[1
4
]
T
.
F
ra
n
c
is
a
n
d
M
.
M
a
d
h
iaja
g
a
n
,
“
A
Co
m
p
a
riso
n
o
f
Clo
u
d
Ex
e
c
u
ti
o
n
M
e
c
h
a
n
ism
s:
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o
g
,
Ed
g
e
a
n
d
Cl
o
n
e
C
lo
u
d
Co
m
p
u
ti
n
g
,
”
Pro
c
e
e
d
in
g
o
f
t
h
e
E
lec
trica
l
En
g
in
e
e
rin
g
Co
m
p
u
ter
S
c
ien
c
e
a
n
d
In
f
o
rm
a
ti
c
s
,
p
p
.
4
4
6
-
4
5
0
,
2
0
1
7
.
[1
5
]
L
.
P
a
ll
a
v
i,
A
.
Ja
g
a
n
,
a
n
d
B.
T
.
Ra
o
,
“
ERM
O²
a
lg
o
rit
h
m
:
a
n
e
n
e
rg
y
e
ff
i
c
ien
t
m
o
b
il
it
y
m
a
n
a
g
e
m
e
n
t
in
m
o
b
il
e
c
l
o
u
d
c
o
m
p
u
ti
n
g
sy
st
e
m
f
o
r
5
G
h
e
tero
g
e
n
e
o
u
s
n
e
tw
o
rk
s,”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
Co
m
p
u
t
e
r
En
g
i
n
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
9
,
n
o
.
3
,
p
p
.
1
9
5
7
-
1
9
6
7
,
2
0
1
9
.
[1
6
]
P
.
P
ra
k
a
sh
,
K.
Da
rsh
a
u
n
,
P
.
Ya
a
z
h
len
e
,
M
.
V
.
G
a
n
e
sh
,
a
n
d
B.
V
a
su
d
h
a
,
“
F
o
g
Co
m
p
u
ti
n
g
:
Iss
u
e
s,
Ch
a
ll
e
n
g
e
s
a
n
d
F
u
tu
re
Dire
c
ti
o
n
s,”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
Co
mp
u
ter
E
n
g
i
n
e
e
rin
g
(
IJ
ECE
)
,
v
o
l
.
7
,
n
o
.
6
,
p
p
.
3
6
6
9
-
3
6
7
3
,
2
0
1
7
.
[1
7
]
J.
W
a
n
g
,
J.
P
a
n
,
F
.
Esp
o
sito
,
P
.
Ca
l
y
a
m
,
Z.
Ya
n
g
,
a
n
d
P
.
M
o
h
a
p
a
tra,
“
Ed
g
e
Clo
u
d
Of
f
lo
a
d
in
g
A
l
g
o
rit
h
m
s:
Iss
u
e
s,
M
e
th
o
d
s,
a
n
d
P
e
rsp
e
c
ti
v
e
s,”
ACM
Co
mp
u
ti
n
g
S
u
rv
e
y
s
,
v
o
l.
5
2
,
n
o
.
1
,
p
p
.
1
-
2
3
,
F
e
b
.
2
0
1
9
[1
8
]
Y.
Ja
ra
r
w
e
h
,
M
.
A
l
-
Ay
y
o
ub
,
M
.
A
l
-
Qu
ra
a
n
,
A
.
T
.
L
o
’a
i,
E.
Be
n
k
h
e
li
f
a
,
“
De
la
y
-
a
wa
re
p
o
w
e
r
o
p
ti
m
iz
a
ti
o
n
m
o
d
e
l
f
o
r
m
o
b
il
e
e
d
g
e
c
o
m
p
u
ti
n
g
sy
ste
m
s,”
Per
so
n
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n
d
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u
s Co
mp
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ti
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g
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2
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,
n
o
.
6
,
p
p
.
1
0
6
7
-
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0
7
7
,
2
0
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7
.
[1
9
]
M.
-
H.
Ch
e
n
,
B.
L
ian
g
,
a
n
d
M
.
D
o
n
g
,
“
Jo
i
n
t
o
f
f
lo
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in
g
a
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re
so
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r
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e
a
ll
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a
ti
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f
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p
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tati
o
n
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n
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m
m
u
n
ica
ti
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n
in
m
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b
il
e
c
lo
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d
w
it
h
c
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m
p
u
ti
n
g
a
c
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e
ss
p
o
in
t,
”
p
re
se
n
ted
a
t
t
h
e
IEE
E
INFOCOM
2
0
1
7
-
IEE
E
Co
n
fer
e
n
c
e
o
n
Co
mp
u
ter
C
o
mm
u
n
ica
ti
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n
s
,
2
0
1
7
.
[2
0
]
H.
L
i,
“
M
u
lt
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tas
k
Off
lo
a
d
in
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n
d
Re
so
u
rc
e
A
ll
o
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ti
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E
n
e
rg
y
-
E
ff
icie
n
c
y
i
n
M
o
b
il
e
E
d
g
e
Co
m
p
u
ti
n
g
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
C
o
mp
u
ter
T
e
c
h
n
iq
u
e
s
,
v
o
l.
5
,
n
o
.
1
,
p
p
.
5
-
1
3
,
2
0
1
8
.
[2
1
]
B.
-
G
.
Ch
u
n
,
S
.
Ih
m
,
P
.
M
a
n
iatis,
M
.
Na
ik
,
a
n
d
A
.
P
a
tt
i,
“
Clo
n
e
c
lo
u
d
:
e
las
ti
c
e
x
e
c
u
ti
o
n
b
e
tw
e
e
n
m
o
b
il
e
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e
v
ice
a
n
d
c
lo
u
d
,
”
p
re
se
n
ted
a
t
t
h
e
Pro
c
e
e
d
i
n
g
s
o
f
t
h
e
six
th
c
o
n
fer
e
n
c
e
o
n
Co
mp
u
ter
sy
ste
ms
,
2
0
1
1
.
[2
2
]
Y.
M
a
o
,
J.
Z
h
a
n
g
,
a
n
d
K.
B
.
L
e
taie
f
,
“
D
y
n
a
m
ic
c
o
m
p
u
tatio
n
o
f
f
lo
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d
in
g
f
o
r
m
o
b
il
e
-
e
d
g
e
c
o
m
p
u
ti
n
g
w
it
h
e
n
e
rg
y
h
a
rv
e
stin
g
d
e
v
ice
s,”
IEE
E
J
o
u
rn
a
l
o
n
S
e
lec
ted
Are
a
s i
n
C
o
mm
u
n
ica
ti
o
n
s
,
v
o
l
.
3
4
,
n
o
.
1
2
,
p
p
.
3
5
9
0
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3
6
0
5
,
2
0
1
6
.
[2
3
]
M
.
EL
G
h
m
a
r
y
,
M
.
O.
C
h
e
rk
a
o
u
i
M
a
lk
i,
Y.
Hm
i
m
z
,
a
n
d
T
.
Ch
a
n
y
o
u
r,
“
En
e
rg
y
a
n
d
Co
m
p
u
tatio
n
a
l
Re
so
u
rc
e
s
Op
ti
m
iza
ti
o
n
in
a
M
o
b
il
e
Ed
g
e
Co
m
p
u
ti
n
g
No
d
e
,
”
in
2
0
1
8
9
th
I
n
ter
n
a
ti
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l
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y
mp
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siu
m
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n
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ig
n
a
l,
Ima
g
e
,
Vi
d
e
o
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d
Co
mm
u
n
ica
t
io
n
s (
IS
IVC),
p
p
.
3
2
3
-
3
2
8
,
2
0
1
8
.
[2
4
]
M
.
El
G
h
m
a
r
y
,
T
.
Ch
a
n
y
o
u
r,
Y.
H
m
i
m
z
,
a
n
d
M
.
O.
C
h
e
rk
a
o
u
i
M
a
lk
i,
“
Eff
icie
n
t
m
u
lt
i
-
tas
k
o
ff
lo
a
d
in
g
w
it
h
e
n
e
rg
y
a
n
d
c
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m
p
u
tatio
n
a
l
re
so
u
rc
e
s
o
p
ti
m
iz
a
ti
o
n
in
a
m
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b
il
e
e
d
g
e
c
o
m
p
u
ti
n
g
n
o
d
e
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
and
Co
m
p
u
ter
E
n
g
i
n
e
e
rin
g
(
IJ
E
CE)
,
v
o
l.
9
,
n
o
.
6
,
p
p
.
4
9
0
8
-
4
9
1
9
,
2
0
1
9
.
[2
5
]
K.
Zh
a
n
g
,
e
t
a
l.
,
“
En
e
rg
y
-
e
ff
icie
n
t
o
f
f
lo
a
d
in
g
f
o
r
m
o
b
il
e
e
d
g
e
c
o
m
p
u
ti
n
g
in
5
G
h
e
tero
g
e
n
e
o
u
s
n
e
tw
o
rk
s,”
IEE
E
a
c
c
e
ss
,
v
o
l.
4
,
p
p
.
5
8
9
6
-
5
9
0
7
,
2
0
1
6
.
[2
6
]
Z.
F
a
n
,
H.
S
h
e
n
,
Y.
W
u
,
a
n
d
Y.
L
i,
“
S
im
u
late
d
-
A
n
n
e
a
li
n
g
L
o
a
d
Ba
lan
c
in
g
f
o
r
Re
so
u
rc
e
A
ll
o
c
a
ti
o
n
i
n
Cl
o
u
d
En
v
iro
n
m
e
n
ts,”
p
re
se
n
ted
a
t
t
h
e
2
0
1
3
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Pa
r
a
ll
e
l
a
n
d
Distri
b
u
t
e
d
Co
mp
u
ti
n
g
,
Ap
p
li
c
a
ti
o
n
s
a
n
d
T
e
c
h
n
o
l
o
g
ies
,
2
0
1
3
.
[2
7
]
L
.
Ch
e
n
,
J.
W
u
,
X
.
L
o
n
g
,
a
n
d
Z
.
Zh
a
n
g
,
“
ENG
INE:
Co
st
Eff
e
c
ti
v
e
O
ff
lo
a
d
in
g
in
M
o
b
il
e
E
d
g
e
Co
m
p
u
ti
n
g
w
it
h
F
o
g
-
Clo
u
d
C
o
o
p
e
ra
ti
o
n
,
”
a
rXiv
p
re
p
rin
t
a
rX
iv:1
7
1
1
.
0
1
6
8
3
,
p
p
.
1
-
1
1
,
2
0
1
7
.
[2
8
]
K.
L
iu
,
J.
P
e
n
g
,
H.
L
i,
X
.
Zh
a
n
g
,
a
n
d
W
.
L
iu
,
“
M
u
lt
i
-
d
e
v
ice
ta
sk
o
ff
lo
a
d
in
g
w
it
h
ti
m
e
-
c
o
n
stra
in
ts
f
o
r
e
n
e
rg
y
e
ff
ici
e
n
c
y
in
m
o
b
il
e
c
lo
u
d
c
o
m
p
u
ti
n
g
,
”
Fu
t
u
re
Ge
n
e
r
a
ti
o
n
C
o
mp
u
t
e
r S
y
ste
ms
,
v
o
l.
6
4
,
p
p
.
1
-
1
4
,
2
0
1
6
.
[2
9
]
W
.
Ch
e
n
,
D.
W
a
n
g
,
a
n
d
K.
L
i,
“
M
u
lt
i
-
u
se
r
m
u
lt
i
-
tas
k
c
o
m
p
u
tatio
n
o
f
f
lo
a
d
in
g
in
g
re
e
n
m
o
b
il
e
e
d
g
e
c
lo
u
d
c
o
m
p
u
ti
n
g
,
”
IEE
E
T
r
a
n
s
a
c
ti
o
n
s o
n
S
e
rv
ice
s Co
mp
u
ti
n
g
,
v
o
l
1
2
,
n
o
.
5
,
p
p
.
7
2
6
-
7
3
8
,
2
0
1
8
.
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