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r
k
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sta
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d
a
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d
tec
h
n
iq
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e
s
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late
t
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e
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e
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sp
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se
ti
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fo
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a
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m
a
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telli
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tec
h
n
i
q
u
e
in
se
rv
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rles
s
c
o
m
p
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ti
n
g
.
Re
q
u
ired
e
x
p
e
rime
n
t
we
re
c
o
n
d
u
c
ted
a
n
d
th
e
re
su
lt
s
a
re
g
iv
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n
g
th
e
imp
ro
v
e
m
e
n
t
a
s
c
o
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p
a
re
d
t
o
o
th
e
r
lo
a
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b
a
lan
c
i
n
g
p
rin
c
i
p
les
.
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e
fu
rt
h
e
r
re
se
a
rc
h
in
t
h
is are
a
a
lso
id
e
n
ti
fied
a
n
d
p
re
se
n
ted
.
K
ey
w
o
r
d
s
:
Ar
tific
ial
in
tellig
en
ce
L
o
ad
b
alan
ci
n
g
Q
-
lear
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in
g
R
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f
o
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ce
m
en
t le
ar
n
i
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g
Ser
v
er
less
co
m
p
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T
h
is i
s
a
n
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p
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n
a
c
c
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ss
a
rticle
u
n
d
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CC B
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li
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C
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s
p
o
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A
uth
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r
:
Yash
wan
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B
alan
Dep
ar
tm
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t o
f
C
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m
p
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ter
Scie
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,
C
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n
iv
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s
ity
B
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5
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ail: y
ash
wan
th
.
b
alan
@
r
es.c
h
r
is
tu
n
iv
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s
ity
.
in
1.
I
NT
RO
D
UCT
I
O
N
Ar
tific
ial
in
tellig
en
ce
(
AI
)
h
e
lp
s
to
m
ak
e
th
e
s
o
f
twar
e
r
eli
ab
ilit
y
m
o
r
e
co
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v
en
ien
t
with
in
tellig
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t
s
o
f
twar
e
to
h
an
d
le
th
e
s
itu
ati
o
n
s
an
d
it
wo
r
k
s
au
t
o
m
atica
lly
.
Alig
n
in
g
co
n
ce
p
ts
f
r
o
m
th
eo
r
y
,
p
r
ac
tice
an
d
f
u
tu
r
e
p
er
s
p
ec
tiv
e
an
d
co
n
s
eq
u
en
tly
d
escr
ib
ed
th
e
r
esear
ch
ar
ea
t
o
p
r
o
v
i
d
e
a
n
e
x
tr
a
m
il
e
to
u
n
d
e
r
s
tan
d
t
h
e
AI
-
b
ased
lo
ad
b
alan
cin
g
tec
h
n
iq
u
es.
T
h
e
s
y
s
tem
s
d
is
tr
ib
u
te
th
e
wo
r
k
lo
ad
ac
c
o
r
d
in
g
to
th
e
s
er
v
er
less
s
ch
ed
u
ler
s
b
ased
o
n
th
e
a
p
p
l
icatio
n
ch
ar
ac
ter
is
tics
.
A
s
ch
ed
u
lar
wh
ic
h
ca
n
b
e
u
s
ed
as
ce
n
tr
alize
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o
n
e
to
p
r
o
v
id
e
a
p
ar
allel
f
r
am
ewo
r
k
f
o
r
th
e
s
er
v
er
less
co
m
p
u
tin
g
u
s
in
g
AW
S
lam
b
d
a.
Als
o
,
it
is
id
ea
l
to
co
m
b
in
e
two
ap
p
r
o
ac
h
es.
T
h
e
p
r
im
e
f
o
cu
s
o
f
th
is
p
a
p
er
is
t
o
r
ed
u
ce
th
e
r
esp
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s
e
tim
e
o
f
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h
e
r
eq
u
est
s
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t
b
y
th
e
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s
er
an
d
to
in
cr
ea
s
e
th
e
p
er
f
o
r
m
an
ce
o
f
ev
er
y
r
e
q
u
est
th
r
o
u
g
h
m
ac
h
in
e
lear
n
in
g
lo
ad
-
b
a
lan
cin
g
tech
n
iq
u
es
[
1
]
–
[
3
]
.
Fig
u
r
e
1
p
r
esen
ts
th
e
p
r
in
cip
le
o
f
in
tellig
en
t
lo
a
d
b
alan
cin
g
in
s
er
v
er
less
.
AI
h
elp
s
to
m
ak
e
th
e
s
o
f
twar
e
r
eliab
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m
o
r
e
co
n
v
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ien
t
with
in
tellig
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t
s
o
f
twar
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to
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le
th
e
s
itu
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n
s
an
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it
wo
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s
au
to
m
atica
lly
.
Ser
v
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co
m
p
u
tin
g
with
lo
a
d
b
alan
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g
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a
ch
allen
g
in
g
r
esear
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p
r
o
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lem
m
en
tio
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ed
in
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
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I
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&
C
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p
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,
Vo
l.
15
,
No
.
3
,
J
u
n
e
20
25
:
3
1
7
1
-
3
1
7
9
3172
m
an
y
r
esear
ch
ar
ea
s
.
Dif
f
er
e
n
t
lo
ad
-
b
alan
cin
g
alg
o
r
ith
m
s
ar
e
p
r
o
p
o
s
ed
b
ased
o
n
th
e
lo
ad
b
alan
cin
g
in
s
er
v
er
less
co
m
p
u
tin
g
.
T
h
e
p
r
o
b
lem
atic
r
esear
ch
ar
ea
s
a
r
e
m
ac
h
in
e
lear
n
in
g
-
b
ased
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a
d
-
b
a
lan
cin
g
tec
h
n
iq
u
e
s
u
s
ed
in
s
er
v
er
less
co
m
p
u
tin
g
.
T
h
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esear
ch
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ir
ec
tio
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o
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th
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tag
e
o
f
s
tr
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im
p
lem
en
tatio
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to
co
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id
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th
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m
an
ag
er
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ch
al
len
g
es.
T
h
is
r
esear
ch
p
ap
er
is
s
tr
u
ctu
r
ed
as
f
o
llo
ws:
s
ec
ti
o
n
2
co
m
p
r
is
es
o
f
r
elate
d
wo
r
k
s
an
d
s
ec
tio
n
3
d
is
cu
s
s
e
s
th
e
p
r
o
b
lem
with
u
n
d
er
ly
in
g
ass
u
m
p
tio
n
s
.
A
d
etailed
in
tr
o
d
u
cti
o
n
to
th
e
p
lan
n
e
d
r
e
q
u
est
s
ch
ed
u
li
n
g
p
r
in
cip
le
is
g
i
v
en
in
s
ec
tio
n
4
.
T
h
e
ex
p
e
r
im
en
tal
r
esu
l
ts
an
d
p
er
f
o
r
m
a
n
ce
ev
alu
atio
n
ar
e
p
r
esen
ted
in
s
ec
tio
n
5
,
alo
n
g
with
a
co
m
p
ar
is
o
n
with
a
f
ew
cu
r
r
en
t
s
c
h
ed
u
lin
g
p
r
in
cip
les.
Sectio
n
6
p
r
esen
ts
th
e
co
n
clu
s
io
n
an
d
th
e
f
u
t
u
r
e
d
ir
ec
tio
n
s
f
o
r
th
is
r
esear
ch
wo
r
k
.
Fig
u
r
e
1
.
I
n
tellig
en
t lo
ad
b
ala
n
cin
g
tech
n
iq
u
es in
s
er
v
e
r
less
co
m
p
u
tin
g
2.
M
E
T
H
O
D
T
h
e
m
o
d
er
n
wo
r
ld
is
en
tire
ly
in
to
in
ter
n
et,
an
d
u
s
er
s
alwa
y
s
av
ail
in
f
o
r
m
atio
n
f
r
o
m
in
ter
n
et.
Mo
r
e
u
s
er
s
ar
e
h
elp
in
g
th
e
f
ea
tu
r
e
to
ac
h
iev
e
th
e
d
esire
d
tech
n
o
lo
g
y
in
a
b
etter
wa
y
.
An
ap
p
r
o
p
r
iate
co
m
m
u
n
icatio
n
s
y
s
tem
s
h
o
u
ld
b
e
estab
lis
h
ed
to
g
et
a
p
r
o
p
er
r
esp
o
n
s
e
to
th
e
r
eq
u
est
s
en
t
b
y
th
e
u
s
er
.
T
h
e
in
tellig
en
t
lo
ad
b
alan
cin
g
te
ch
n
iq
u
es
p
r
o
v
id
e
a
p
latf
o
r
m
f
o
r
th
e
a
b
o
v
e
-
m
en
tio
n
e
d
p
r
o
b
lem
.
Sm
ar
t
lo
ad
b
alan
cin
g
tech
n
iq
u
es
f
o
r
th
e
s
er
v
er
less
co
m
p
u
tin
g
m
eth
o
d
.
I
n
th
e
s
er
v
e
r
less
co
m
p
u
tin
g
p
a
r
ad
ig
m
,
th
e
d
if
f
icu
lt
p
ar
t
will
b
e
co
n
tr
o
llin
g
th
e
lo
ad
r
ec
eiv
e
d
f
r
o
m
th
e
d
if
f
er
en
t
u
s
er
s
s
im
u
ltan
eo
u
s
ly
.
T
h
e
r
esp
o
n
s
e
tim
e
ac
cu
r
ac
y
o
f
s
o
lv
in
g
th
e
r
eq
u
e
s
t
cr
ea
tes
a
h
ig
h
d
em
an
d
f
o
r
i
n
tellig
en
t
lo
ad
b
alan
cin
g
[
4
]
–
[
6
]
.
T
h
e
r
e
is
a
n
ee
d
f
o
r
s
m
ar
t
lo
a
d
b
alan
cin
g
p
r
in
cip
les
o
n
s
er
v
er
less
co
m
p
u
tin
g
to
e
n
s
u
r
e
th
e
lo
a
d
b
a
lan
cin
g
s
er
v
er
less
co
m
p
u
tin
g
ca
n
r
ed
u
ce
th
e
r
esp
o
n
s
e
tim
e
a
n
d
e
f
f
icien
tly
in
c
r
ea
s
e
th
e
av
ailab
ilit
y
o
f
s
er
v
e
r
s
f
o
r
th
e
s
u
b
s
eq
u
e
n
t
co
m
in
g
r
eq
u
est.
T
h
e
s
er
v
er
le
s
s
co
m
p
u
tin
g
s
p
in
s
it
u
p
f
r
esh
an
d
s
tar
ts
h
o
s
tin
g
th
e
f
u
n
ct
io
n
th
r
o
u
g
h
a
co
l
d
s
tar
t,
an
d
if
th
e
f
u
n
ctio
n
is
r
u
n
n
in
g
s
u
cc
ess
f
u
lly
,
it
s
ay
s
war
m
s
tar
t.
I
f
th
e
f
u
n
ctio
n
d
o
es
n
o
t
r
eq
u
est
an
y
t
h
in
g
ag
ain
,
it
co
m
es
to
th
e
s
tate
o
f
id
le,
an
d
th
e
f
o
llo
win
g
u
s
er
will
ag
ain
b
e
th
e
co
ld
s
tar
t,
wh
i
ch
m
ak
es
th
e
tim
e
-
s
p
ac
e
tr
ad
e
-
o
f
f
u
s
in
g
s
er
v
er
le
s
s
f
u
n
ctio
n
s
[
7
]
,
[
8
]
.
T
h
r
o
u
g
h
th
at,
th
e
is
s
u
e
o
f
lo
ad
b
alan
ci
n
g
ca
n
b
e
s
o
lv
e
d
to
an
ex
ten
t.
T
h
e
lo
ad
b
alan
cin
g
is
p
r
esen
ted
in
Fig
u
r
e
2
.
Q
-
lear
n
in
g
ac
tiv
e
m
o
n
ito
r
i
n
g
weig
h
ted
least
co
n
n
ec
tio
n
r
o
u
n
d
r
o
b
in
lo
ad
b
ala
n
cin
g
(
Q
-
L
AM
W
L
R
LB
)
u
s
es
a
r
ein
f
o
r
ce
m
en
t
le
ar
n
in
g
tech
n
iq
u
e,
a
n
d
N
n
u
m
b
er
o
f
r
eq
u
ests
ar
r
iv
es
at
t
h
e
lo
ad
b
alan
ce
r
;
it
co
llects
th
e
s
er
v
er
an
d
f
u
n
ctio
n
in
f
o
r
m
atio
n
at
th
e
ea
r
lier
s
tag
e
[
9
]
,
[
1
0
]
.
T
h
e
r
eq
u
est
f
r
o
m
R
1
to
R
N
will
b
e
s
en
t
to
th
e
Q
-
L
AM
W
L
R
L
B
m
eth
o
d
o
l
o
g
y
,
an
d
with
th
e
h
e
lp
o
f
m
ac
h
in
e
lea
r
n
in
g
tech
n
iq
u
es
ass
o
ciate
d
with
d
if
f
er
en
t
lo
ad
b
alan
cin
g
al
g
o
r
ith
m
s
,
it
will
f
in
alize
t
h
e
h
i
g
h
est
weig
h
t
f
o
r
t
h
e
s
er
v
e
r
T
tim
e
an
i
n
v
o
ca
tio
n
n
ee
d
s
to
s
ch
ed
u
le
an
d
Q
-
L
AM
W
L
R
L
B
will
b
e
h
av
in
g
N
clu
s
ter
s
av
ailab
le
in
to
tal.
Q
-
L
AM
W
L
R
L
B
r
ec
eiv
es
a
b
atch
o
f
th
e
latest
s
tate
R
t=(
R
1
,
.
.
.
,
R
n
,
.
.
.
,
R
N
)
f
r
o
m
th
e
clu
s
ter
,
wh
er
e
n
is
th
e
Nth
av
ailab
le
s
er
v
er
.
On
ce
th
e
d
ata
is
r
ec
eiv
ed
f
o
r
t
h
e
weig
h
t
allo
ttin
g
p
r
o
ce
d
u
r
e,
Q
-
L
AM
W
L
R
L
B
cr
e
ates
th
e
in
d
e
x
tab
le
with
all
th
e
in
f
o
r
m
atio
n
h
ir
ed
,
m
ain
ly
th
e
s
er
v
e
r
an
d
Fu
n
ct
io
n
in
f
o
r
m
atio
n
[
1
1
]
,
[
1
2
]
.
Al
lo
ca
tin
g
weig
h
t
to
th
e
s
er
v
er
is
d
o
n
e
with
th
e
h
e
lp
o
f
r
ein
f
o
r
ce
m
en
t
lea
r
n
in
g
.
T
h
e
ac
to
r
n
etwo
r
k
an
d
cr
itic
n
etwo
r
k
a
r
e
u
s
ed
t
o
g
iv
in
g
weig
h
t
to
th
e
d
if
f
er
e
n
t
s
er
v
er
s
.
Fig
u
r
e
3
p
r
esen
ts
th
e
p
lace
m
en
t
o
f
th
e
d
esig
n
ed
lo
ad
b
ala
n
cin
g
p
r
in
cip
le
s
p
ec
if
ic
to
s
er
v
e
r
less
co
m
p
u
tin
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:
2088
-
8
7
0
8
Q
-
lea
r
n
in
g
b
a
s
ed
a
ctive
mo
n
it
o
r
in
g
w
ith
w
eig
h
ted
lea
s
t c
o
n
n
ec
tio
n
r
o
u
n
d
…
(
Ya
s
h
w
a
n
th
B
a
la
n
)
3173
Fig
u
r
e
2
.
I
d
en
tify
i
n
g
th
e
r
ig
h
t
s
er
v
er
u
s
in
g
Q
-
L
AM
W
L
C
R
R
L
B
Fig
u
r
e
3
.
T
h
e
Q
-
L
AM
W
L
R
L
B
ar
ch
itectu
r
e
Alg
o
r
ith
m
1
p
r
esen
ts
th
e
alg
o
r
ith
m
r
ep
r
esen
ts
th
e
way
o
f
a
p
p
ly
in
g
t
h
e
Q
-
lear
n
in
g
tr
ain
in
g
with
th
e
b
est
s
et
o
f
s
er
v
er
s
w
h
ich
is
a
v
ailab
le
an
d
b
ased
o
n
t
h
at
th
e
s
ec
o
n
d
al
g
o
r
ith
m
will
b
e
p
r
o
v
id
ed
a
n
d
will
f
i
n
d
th
e
b
est
s
er
v
er
f
o
r
t
h
e
r
e
q
u
est
th
at
is
r
aised
an
d
a
n
in
t
ellig
en
t
lo
ad
b
alan
ce
r
b
ased
o
n
th
e
Q
-
lear
n
in
g
tech
n
iq
u
es
an
d
th
e
o
t
h
er
lo
a
d
b
alan
cin
g
alg
o
r
ith
m
s
will
b
e
s
elec
tin
g
th
e
b
est
s
er
v
er
f
o
r
th
e
r
eq
u
est
[
1
3
]
–
[
1
5
]
.
T
h
e
alg
o
r
ith
m
is
ab
o
u
t
two
c
o
n
d
itio
n
s
to
g
et
in
to
th
e
lo
o
p
.
On
e
is
if
it
ex
p
lo
r
es
th
e
o
th
er
is
if
its
ex
p
lo
it.
I
n
th
e
b
o
th
c
o
n
d
itio
n
th
e
alg
o
r
ith
m
s
wo
r
k
s
an
d
m
a
k
e
a
p
r
o
m
p
t
attem
p
t
to
g
et
th
e
r
esu
lt.
T
h
e
ac
cu
r
ate
v
alu
es
ar
e
to
g
et
th
e
s
er
v
e
r
in
a
av
er
a
g
e
r
esp
o
n
s
e
tim
e
to
ch
o
o
s
e
a
b
est
s
er
v
er
.
I
f
a
n
a
g
en
t
c
h
o
o
s
e
s
to
ex
p
lo
r
e
(
with
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
3
,
J
u
n
e
20
25
:
3
1
7
1
-
3
1
7
9
3174
p
r
o
b
a
b
ilit
y
ϵ
)
,
it
ev
en
ly
c
h
o
o
s
es
a
r
an
d
o
m
ac
tio
n
f
r
o
m
am
o
n
g
all
o
p
tio
n
s
.
I
f
an
a
g
en
t
ch
o
o
s
es
to
ex
p
lo
it
(
with
p
r
o
b
a
b
ilit
y
1
−ϵ
)
,
it
d
eter
m
i
n
es
th
e
h
ig
h
est
v
alu
e.
T
h
ese
ar
e
t
h
e
co
n
d
itio
n
w
h
ich
ac
ce
p
ts
with
th
e
alg
o
r
ith
m
.
I
f
th
e
ag
en
t
wh
ich
r
elate
with
th
e
Q
-
lear
n
in
g
tec
h
n
iq
u
e
c
h
o
o
s
es
to
ex
p
lo
r
e
th
e
p
r
o
b
ab
i
ilit
y
o
f
v
alu
es
an
d
ch
o
o
s
es a
r
an
d
o
m
ac
tio
n
to
ex
p
lo
it th
e
s
am
e.
Alg
o
r
ith
m
1
.
Fin
d
in
g
t
h
e
b
est
s
er
v
er
u
s
in
g
Q
-
lear
n
in
g
A
l
g
o
r
i
t
h
m:
Q
-
l
e
a
rn
i
n
g
t
r
a
i
n
i
n
g
b
a
s
e
d
on
t
h
e
r
e
q
u
e
s
t
b
e
g
i
n
S
t
e
p
1:
T
h
e
l
o
a
d
b
a
l
a
n
c
e
r
r
e
c
e
i
v
e
s
a
r
e
q
u
e
s
t
.
S
t
e
p
2:
D
e
t
e
r
mi
n
e
w
h
i
c
h
s
e
r
v
e
r
l
e
ss
F
u
n
c
t
i
o
n
is
b
e
s
t
f
o
r
t
h
e
r
e
q
u
e
s
t
S
:
L
i
st
o
f
s
e
r
v
e
r
l
e
ss fu
n
c
t
i
o
n
s
t
h
a
t
a
r
e
a
c
c
e
ssi
b
l
e
.
N
:
T
h
e
n
u
mb
e
r
o
f
ser
v
e
r
l
e
ss fe
a
t
u
r
e
s
i
n
S
W
i
:
T
h
e
w
e
i
g
h
t
of
t
h
e
ser
v
e
r
l
e
ss
F
u
n
c
t
i
o
n
is
i
Ci:
Th
e
C
o
n
n
e
c
t
i
o
n
c
o
u
n
t
f
o
r
ser
v
e
r
l
e
ss
F
u
n
c
t
i
o
n
i
Q
(
i
,
j
)
:
T
h
e
Q
-
v
a
l
u
e
t
h
a
t
i
n
d
i
c
a
t
e
s
t
h
e
a
c
q
u
i
r
e
d
u
s
e
f
u
l
n
e
ss
of
c
h
a
n
g
i
n
g
f
r
o
m
st
a
t
e
i
to
s
t
a
t
e
j.
S
t
e
p
3:
C
r
e
a
t
e
a
Q
-
t
a
b
l
e
of
d
i
m
e
n
s
i
o
n
s
(N,
N)
a
n
d
set
a
l
l
of
i
t
s
v
a
l
u
e
s
to
z
e
r
o
at
f
i
r
s
t
.
S
t
e
p
4
:
I
n
i
t
i
a
l
i
z
e
w
e
i
g
h
t
s W
i
f
o
r
e
a
c
h
s
e
r
v
e
r
l
e
ss
F
u
n
c
t
i
o
n
S
t
e
p
5:
I
n
i
t
i
a
l
i
z
e
c
o
n
n
e
c
t
i
o
n
c
o
u
n
t
s
Ci
f
o
r
e
a
c
h
serv
e
r
l
e
ss
F
u
n
c
t
i
o
n
S
t
e
p
6
:
Q
-
l
e
a
r
n
i
n
g
Tr
a
i
n
i
n
g
∈
+
(
1−∈
)
.
(
,
)
(
1
)
I
n
i
t
i
a
l
i
z
e
s
t
a
t
e
s
a
n
d
C
h
o
o
s
e
a
c
t
i
o
n
a
{
|
|
∑
`
(
,
`)
(
,
)
(
2
)
∑
`
(
,
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π(a
∣
s)
:
T
h
e
p
o
ssi
b
i
l
i
t
y
of
p
i
c
k
i
n
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a
me
t
h
o
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of
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c
t
i
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a
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st
a
t
e
s.
∣
A
∣
:
T
h
e
t
o
t
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1
7
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ith
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ith
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Valu
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r
th
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r
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A
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t
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w
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d
p
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a
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t
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p
2
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f
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6
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7
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a
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w
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S
t
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p
8
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F
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h
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t
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s.
S
t
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p
9
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a
c
k
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S
t
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p
1
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f
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of
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or
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g
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c
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n
d
/*
E
n
d
of
S
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r
a
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c
a
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n
a
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g
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m
*/
O
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t
p
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t
:
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q
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t
a
l
l
o
c
a
t
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to
t
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e
s
e
r
v
e
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N:
2088
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3175
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d
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s
[
2
3
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–
[
2
5
]
.
T
h
r
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g
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lo
g
y
it
ca
n
i
n
cr
ea
s
e
th
e
s
ca
lab
ilit
y
an
d
r
ed
u
ce
th
e
r
esp
o
n
s
e
tim
e
to
an
ex
ten
t
wh
ile
th
e
r
eq
u
ests
ar
e
allo
c
ated
ef
f
icien
tly
to
th
e
s
er
v
er
wh
ich
is
av
ailab
le
.
T
h
is
p
r
o
p
o
s
ed
m
eth
o
d
o
l
o
g
y
o
f
u
s
in
g
Q
-
lear
n
in
g
m
eth
o
d
u
s
ed
b
y
th
e
lo
ad
b
alan
ce
r
to
all
o
ca
te
th
e
s
er
v
er
in
th
e
s
er
v
er
less
co
m
p
u
tin
g
im
p
r
o
v
es
t
h
e
p
e
r
f
o
r
m
an
ce
,
r
eli
ab
ilit
y
an
d
co
s
t
m
a
n
ag
em
en
t
in
th
e
s
er
v
er
less
co
m
p
u
tin
g
.
T
h
e
alg
o
r
ith
m
co
m
p
letely
f
o
cu
s
es
o
n
r
ed
u
cin
g
th
e
r
esp
o
n
s
e
tim
e
an
d
in
cr
e
ase
th
e
s
ca
lab
ilit
y
b
ased
o
n
th
e
ar
r
iv
al
tim
e
an
d
th
e
b
u
r
s
t
tim
e
o
f
t
h
e
r
eq
u
est.
T
h
e
ap
p
r
o
ac
h
clea
r
ly
f
o
cu
s
es
o
n
th
e
ar
ea
s
m
en
tio
n
ed
i
n
th
e
p
r
o
p
o
s
ed
m
e
th
o
d
o
lo
g
y
.
T
ab
le
1
.
T
h
e
p
er
f
o
r
m
a
n
ce
o
f
Q
-
L
AM
W
L
R
L
B
P
r
o
c
e
s
s
S
e
r
v
e
r
A
r
r
i
v
a
l
B
u
r
s
t
E
x
i
t
Tu
r
n
A
r
o
u
n
d
W
a
i
t
P1
S1
3
4
7
4
0
P3
S2
3
5
8
5
0
P5
S1
4
3
7
3
0
P4
S3
6
7
13
7
0
P2
S3
6
8
21
15
7
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
is
r
esear
ch
c
o
n
d
u
cted
e
x
p
er
im
en
ts
d
e
p
lo
y
in
g
Q
-
L
A
MWLR
L
B
o
n
two
d
if
f
er
en
t
C
lo
u
d
Sim
clu
s
ter
s
:
o
n
e
o
n
th
e
C
o
m
p
u
te
C
an
ad
a
C
lo
u
d
an
d
th
e
o
th
er
o
n
an
Am
az
o
n
elastic
co
m
p
u
te
clo
u
d
(
AW
S
E
C
2
)
clu
s
ter
.
E
ac
h
clu
s
ter
c
o
m
p
r
is
e
d
1
3
v
ir
tu
al
m
ac
h
in
es
(
VM
s
)
with
s
p
ec
if
ic
r
o
les:
o
n
e
VM
f
o
r
h
o
s
tin
g
th
e
co
n
tr
o
ller
s
lik
e
ap
p
licatio
n
p
r
o
g
r
am
in
ter
f
ac
e
(
API
)
g
atew
a
y
an
d
R
ed
is
s
er
v
ices
f
o
r
th
e
b
ac
k
en
d
,
m
ess
ag
es
ar
e
d
is
tr
ib
u
ted
an
d
d
atab
ase
as
well,
o
n
e
f
o
r
th
e
Q
-
L
AM
W
L
R
L
B
ag
en
t,
an
d
th
e
f
u
n
ctio
n
in
v
o
k
e
r
s
ar
e
1
0
.
I
n
th
e
C
an
ad
a
clo
u
d
co
m
p
u
te,
ea
ch
3
2
GB
s
o
f
m
em
o
r
y
f
o
r
VM
an
d
v
C
PU
co
r
es
ar
e
8
.
2
GB
s
o
f
r
an
d
o
m
ac
ce
s
s
m
em
o
r
y
(
R
AM
)
f
o
r
i
n
v
o
k
er
s
f
o
r
ea
ch
f
u
n
ctio
n
ex
ec
u
tio
n
,
b
ased
o
n
f
u
n
ctio
n
m
em
o
r
y
r
eq
u
ir
em
e
n
ts
C
PU
p
o
wer
is
allo
ca
ted
p
r
o
p
o
r
tio
n
ally
.
On
th
e
E
C
2
AW
S
clu
s
te
r
,
ea
ch
VM
was
o
f
ty
p
e
c5
d
.
2
x
lar
g
e
with
8
v
C
PU
co
r
es
an
d
1
6
GB
s
o
f
m
em
o
r
y
,
lau
n
c
h
ed
as
s
p
o
t
in
s
tan
ce
s
.
Similar
to
th
e
C
o
m
p
u
te
C
an
ad
a
C
lo
u
d
.
Q
-
L
AM
W
L
R
L
B
in
d
ep
en
d
en
tly
o
n
b
o
th
clu
s
ter
s
an
d
th
en
e
v
alu
ated
its
.
Fig
u
r
e
4
m
en
tio
n
s
ab
o
u
t
th
e
r
eq
u
est
d
is
tr
ib
u
tio
n
in
th
e
s
er
v
er
less
co
m
p
u
tin
g
u
s
in
g
th
e
Q
-
L
AM
W
L
C
R
R
L
B
.
Fig
u
r
e
4.
R
eq
u
est
d
is
tr
ib
u
tio
n
to
th
e
s
er
v
er
s
u
s
in
g
th
e
Q
-
L
A
M
W
L
C
R
R
L
B
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
15
,
No
.
3
,
J
u
n
e
20
25
:
3
1
7
1
-
3
1
7
9
3176
3
.
1
.
Av
er
a
g
e
re
s
po
ns
e
t
im
e
T
h
e
Q
-
lear
n
in
g
tab
le
will
b
e
u
p
d
ated
f
o
r
th
e
Q
-
L
AM
W
L
R
L
B
alg
o
r
ith
m
u
s
in
g
th
e
f
o
llo
win
g
alg
o
r
ith
m
b
ased
o
n
th
e
alg
o
r
it
h
m
wh
ich
is
p
r
o
v
i
d
ed
t
h
e
a
v
e
r
ag
e
r
esp
o
n
s
e
tim
e
o
f
ac
ce
p
ti
n
g
th
e
r
e
q
u
est
will
b
e
co
n
s
id
er
e
d
[
2
6
]
–
[
2
8
]
.
|
|
+
(
1
−
)
⋅
(
,
)
`
(
,
`
)
if
e
x
plore
(
,
)
`
(
,
`
)
if
e
x
ploi
t
(
4
)
T
h
e
eq
u
atio
n
(
4
)
p
r
o
v
id
es
th
e
u
p
d
atin
g
o
f
q
-
lear
n
in
g
tech
n
iq
u
es
an
d
th
r
o
u
g
h
t
h
e
Q
-
lear
n
in
g
u
p
d
ate
th
e
s
er
v
er
will
b
e
allo
tted
an
d
th
e
r
e
q
u
e
s
t
will
b
e
co
n
s
id
er
ed
b
ased
o
n
it.
On
ce
th
e
r
eq
u
est
is
tr
ea
ted
to
th
e
s
er
v
er
t
h
e
av
er
ag
e
r
esp
o
n
s
e
tim
e
will
b
e
id
en
tifie
d
[
2
9
]
,
[
3
0
]
.
T
h
e
m
at
h
em
atica
l
eq
u
atio
n
is
to
p
r
o
v
i
d
e
th
e
f
in
al
o
u
tp
u
t
o
f
av
er
a
g
e
r
esp
o
n
s
es
tim
e
b
ased
o
n
th
e
r
eq
u
est
r
ec
eiv
es
.
Fig
u
r
e
5
s
h
o
wca
s
es
th
e
r
esu
lt
o
f
co
m
p
a
r
is
o
n
b
etwe
en
th
e
s
ch
ed
u
lin
g
alg
o
r
i
th
m
s
with
th
e
p
r
o
p
o
s
ed
alg
o
r
i
th
m
in
th
e
r
esear
ch
.
Q
-
L
AM
W
L
R
L
B
alg
o
r
ith
m
tak
es
th
e
les
s
tim
e
a
s
co
m
p
ar
ed
to
th
e
o
th
er
alg
o
r
ith
m
s
.
T
h
e
co
m
p
ar
is
o
n
g
iv
es
a
clea
r
p
ictu
r
e
o
f
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
is
wo
r
k
in
g
ef
f
icien
tly
as
co
m
p
ar
ed
to
th
e
o
th
e
r
alg
o
r
ith
m
s
.
T
h
e
r
esu
lt
is
p
u
r
ely
b
ased
o
n
th
e
r
eq
u
est r
ec
eiv
es o
n
th
e
alg
o
r
ith
m
.
Fig
u
r
e
6
r
e
p
r
esen
ts
two
p
ar
a
m
eter
s
tim
e
in
ter
v
al
o
n
t
h
e
X
-
ax
is
an
d
d
ata
in
ter
v
al
o
n
th
e
Y
ax
is
.
T
h
e
f
ig
u
r
e
c
o
m
p
ar
es
th
e
C
an
ad
a
c
lo
u
d
an
d
AW
S
E
C
2
b
ased
o
n
th
e
alg
o
r
ith
m
th
e
r
esu
lt
p
r
o
d
u
ce
s
in
th
is
f
o
r
m
at.
T
h
e
b
lu
e
lin
e
m
ak
es
t
h
e
C
an
ad
a
clo
u
d
an
d
wh
ich
s
h
o
w
c
ases
th
e
d
if
f
er
en
ce
am
o
n
g
th
e
AW
S
E
C
2
in
th
e
d
if
f
er
en
t
in
ter
v
al
o
f
tim
e
an
d
h
o
w
d
ata
is
tr
av
ellin
g
ac
co
r
d
i
n
g
th
e
tim
e
ch
an
g
es.
T
h
e
v
ar
i
atio
n
s
h
o
w
ca
s
es
th
e
d
if
f
er
en
ce
b
ased
o
n
th
e
tim
e
c
h
an
g
es a
n
d
th
e
d
ata
in
te
r
v
al.
Fig
u
r
e
5
.
C
o
m
p
ar
is
o
n
of
th
e
d
i
f
f
er
en
t
alg
o
r
ith
m
s
with
Q
-
L
AM
W
L
R
L
B
Fig
u
r
e
6
.
C
o
m
p
a
r
is
o
n
o
f
th
e
d
if
f
er
en
t a
lg
o
r
ith
m
s
with
Q
-
L
A
MWLR L
B
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:
2088
-
8
7
0
8
Q
-
lea
r
n
in
g
b
a
s
ed
a
ctive
mo
n
it
o
r
in
g
w
ith
w
eig
h
ted
lea
s
t c
o
n
n
ec
tio
n
r
o
u
n
d
…
(
Ya
s
h
w
a
n
th
B
a
la
n
)
3177
3
.
2
.
Av
er
a
g
e
t
urna
ro
un
d t
im
e
T
h
e
tu
r
n
a
r
o
u
n
d
tim
e
o
f
th
e
r
eq
u
est
is
b
ased
o
n
th
e
ar
r
iv
a
l
tim
e
an
d
b
u
r
s
t
tim
e
o
f
th
e
alg
o
r
ith
m
.
B
ased
on
th
ese
v
alu
es
th
e
tu
r
n
a
r
o
u
n
d
tim
e
will
be
ca
lcu
lated
.
T
h
e
Alg
o
r
ith
m
1
p
r
o
v
id
es
th
e
d
ata
clea
r
ly
.
T
h
e
eq
u
atio
n
p
r
o
v
id
es
th
e
s
elec
tio
n
b
est s
er
v
er
o
n
ce
th
e
tu
r
n
ar
o
u
n
d
tim
e
is
ca
lcu
lated
[
2
9
]
.
(
,
)
←
(
,
)
⋅
(
1
−
)
+
(
⋅
′
(
′
,
′
)
+
(
,
)
)
)
⋅
(
5
)
T
h
e
Q
-
L
AM
W
L
R
L
B
alg
o
r
ith
m
will
b
e
s
elec
tin
g
th
e
b
est
s
er
v
er
o
n
ce
th
e
eq
u
atio
n
id
en
ties
th
e
s
er
v
er
wh
ich
is
av
ailab
le
at
th
e
m
o
m
en
t
b
ased
on
th
e
Q
-
lea
r
n
in
g
ta
b
le
u
p
d
atin
g
.
C
o
n
s
id
e
r
in
g
th
e
Q
-
lear
n
i
n
g
tab
le
d
ata
wh
ich
is
av
ailab
le
th
e
r
eq
u
est
will
b
e
co
n
s
id
er
ed
an
d
allo
ts
th
e
s
er
v
er
f
o
r
th
e
r
eq
u
est
[
2
9
]
,
[
3
0
]
.
Fig
u
r
e
7
r
ep
r
esen
ts
th
e
co
m
p
ar
is
o
n
o
f
d
if
f
e
r
en
t
alg
o
r
ith
m
with
th
e
p
r
o
p
o
s
ed
alg
o
r
it
h
m
to
s
h
o
wca
s
e
th
e
d
if
f
er
en
ce
.
Fig
u
r
e
7
.
C
o
m
p
ar
is
o
n
am
o
n
g
d
if
f
er
en
t lo
a
d
b
alan
ci
n
g
alg
o
r
i
th
m
s
b
ased
o
n
th
e
Ser
v
er
less
en
v
ir
o
n
m
en
t
T
h
is
wo
r
k
m
ain
ly
f
o
c
u
s
es o
n
th
e
s
er
v
er
less
co
m
p
u
tin
g
p
latf
o
r
m
to
m
ak
e
an
in
tellig
en
t lo
a
d
b
alan
ce
r
.
T
h
e
m
eth
o
d
o
lo
g
y
d
escr
ib
es
th
e
alg
o
r
ith
m
an
d
wh
ich
s
h
o
w
ca
s
es
th
e
wo
r
k
in
g
p
atter
n
o
f
t
h
e
alg
o
r
ith
m
wh
en
th
e
r
eq
u
est
ar
r
iv
es.
T
h
e
lo
a
d
b
alan
ce
r
m
an
ag
es
th
e
r
eq
u
est
an
d
tu
r
n
s
in
to
a
Q
-
lear
n
in
g
tab
l
e
to
m
ak
e
th
e
n
ex
t
r
eq
u
est
wo
r
k
p
r
o
m
p
tly
.
T
h
e
d
i
f
f
er
en
t
in
s
tr
u
m
e
n
ts
an
d
th
e
m
e
th
o
d
s
ar
e
u
s
ed
i
n
th
e
m
et
h
o
d
o
lo
g
y
ar
e
ex
p
lain
e
d
in
th
e
p
r
o
p
o
s
ed
m
eth
o
d
o
lo
g
y
an
d
th
e
wo
r
k
in
g
p
r
o
ce
d
u
r
e
is
in
th
e
e
x
p
er
im
e
n
tal
an
d
d
is
cu
s
s
io
n
p
ar
t.
T
h
er
e
is
d
if
f
er
en
t
ty
p
e
o
f
alg
o
r
ith
m
s
co
m
p
ar
ed
to
m
ak
e
a
s
tatem
en
t
th
at
Q
-
L
AM
W
L
R
L
B
ca
n
b
e
s
o
m
e
k
in
d
o
f
ch
an
g
es
in
th
e
s
er
v
e
r
less
.
co
m
p
u
tin
g
p
latf
o
r
m
w
h
ile
u
s
in
g
th
e
alg
o
r
ith
m
.
B
ased
o
n
th
e
r
eq
u
est
ar
r
iv
es
th
e
s
er
v
er
s
ar
e
allo
tted
an
d
th
e
n
ex
t
r
eq
u
est
will
b
e
p
er
f
ec
tly
allo
tted
to
th
e
s
er
v
er
b
ased
o
n
th
e
r
ein
f
o
r
ce
m
en
t
lear
n
in
g
.
4.
CO
NCLU
SI
O
N
T
h
e
r
ein
f
o
r
ce
m
e
n
t
ac
tiv
e
m
o
n
ito
r
in
g
r
o
u
n
d
-
r
o
b
in
weig
h
ted
least
co
n
n
ec
tio
n
alg
o
r
ith
m
d
escr
ib
ed
in
th
e
in
tr
o
d
u
ctio
n
s
tag
e
p
r
o
p
er
l
y
r
e
d
u
ce
s
th
e
r
esp
o
n
s
e
tim
e
o
n
ce
th
e
r
eq
u
est
ar
r
iv
es
at
th
e
lo
ad
b
ala
n
ce
r
.
T
h
e
Q
-
L
AM
W
L
R
L
B
p
r
in
cip
le
f
in
d
s
th
e
b
est
s
er
v
er
av
ailab
le
th
r
o
u
g
h
m
ac
h
in
e
lear
n
in
g
tech
n
iq
u
es
u
s
in
g
r
ein
f
o
r
ce
m
e
n
t
lear
n
in
g
in
d
et
ail
u
s
in
g
th
e
Q
-
lear
n
in
g
tech
n
iq
u
e.
Q
-
lear
n
in
g
tech
n
iq
u
es
ap
p
lied
to
th
e
t
h
r
e
e
d
if
f
er
en
t
lo
ad
b
alan
cin
g
alg
o
r
ith
m
s
p
r
o
v
id
e
less
r
esp
o
n
s
e
tim
e
to
t
h
e
r
e
q
u
est
r
ec
eiv
ed
at
th
e
lo
ad
b
alan
ce
r
-
v
alu
e
tab
le,
wh
ic
h
will
be
u
p
d
a
ted
all
t
h
e
tim
e
af
ter
s
elec
tin
g
t
h
e
s
er
v
er
f
o
r
th
e
r
e
q
u
est
r
ec
eiv
ed
.
T
h
e
alg
o
r
ith
m
'
s
p
r
im
ar
y
o
b
jectiv
e
is
s
atis
f
ied
th
r
o
u
g
h
th
e
r
esu
lt
an
d
d
is
cu
s
s
io
n
ar
ea
as
m
en
tio
n
ed
in
th
e
i
n
tr
o
d
u
ctio
n
.
E
v
e
r
y
r
eq
u
est'
s
p
r
im
ar
y
g
o
al
is
to
r
ed
u
ce
t
h
e
r
esp
o
n
s
e
tim
e.
R
esp
o
n
s
e
tim
e
ca
n
b
e
r
ed
u
ce
d
th
r
o
u
g
h
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
s
.
T
h
e
r
esear
c
h
c
h
allen
g
es
ar
e
to
f
in
alize
th
e
test
b
u
d
to
ap
p
ly
th
e
alg
o
r
ith
m
s
in
t
h
e
r
ea
l
wo
r
ld
.
T
h
e
f
u
tu
r
e
e
n
h
an
ce
m
e
n
t
ca
n
b
e
u
s
in
g
m
ac
h
in
e
lear
n
in
g
tech
n
iq
u
es
f
o
r
s
er
v
er
less
co
m
p
u
tin
g
to
m
ak
e
th
e
s
er
v
er
s
ca
lab
le
th
r
o
u
g
h
m
ac
h
i
n
e
lear
n
in
g
tech
n
i
q
u
es.
T
h
e
r
esear
c
h
p
r
o
p
o
s
es
a
n
o
v
el
alg
o
r
ith
m
u
s
in
g
Q
-
lear
n
in
g
tech
n
iq
u
es
o
f
r
ein
f
o
r
ce
m
e
n
t
l
ea
r
n
in
g
a
p
p
lied
t
o
th
e
l
o
ad
b
alan
cin
g
c
o
n
ce
p
t
u
s
in
g
ac
ti
v
e
m
o
n
it
o
r
in
g
lo
ad
b
alan
cin
g
,
weig
h
ted
r
o
u
n
d
r
o
b
in
,
an
d
weig
h
ted
least
co
n
n
ec
ti
o
n
lo
ad
b
alan
cin
g
alg
o
r
ith
m
to
s
atis
f
y
th
e
r
eq
u
est
wh
ich
ar
r
i
v
es
at
th
e
lo
ad
b
al
an
ce
r
to
ap
p
r
o
p
r
iately
tr
a
n
s
f
er
to
th
e
s
er
v
e
r
less
co
m
p
u
tin
g
p
ar
ad
i
g
m
i
n
a
less
r
esp
o
n
s
e
tim
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
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I
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Vo
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15
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3
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J
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20
25
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3178
F
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Au
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alan
✓
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Ar
o
k
ia
Pau
l Rajan
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✓
✓
✓
✓
C
:
C
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n
c
e
p
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DATA AV
AI
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AB
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h
e
d
ata
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upon
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eq
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RE
F
E
R
E
NC
E
S
[
1
]
H
.
M
a
o
,
M
.
A
l
i
z
a
d
e
h
,
I
.
M
e
n
a
c
h
e
,
a
n
d
S
.
K
a
n
d
u
l
a
,
“
R
e
s
o
u
r
c
e
ma
n
a
g
e
me
n
t
w
i
t
h
d
e
e
p
r
e
i
n
f
o
r
c
e
me
n
t
l
e
a
r
n
i
n
g
,
”
i
n
H
o
t
N
e
t
s
2
0
1
6
-
Pro
c
e
e
d
i
n
g
s
o
f
t
h
e
1
5
t
h
A
C
M
W
o
rks
h
o
p
o
n
H
o
t
T
o
p
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n
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s
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p
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6
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o
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:
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0
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1
1
4
5
/
3
0
0
5
7
4
5
.
3
0
0
5
7
5
0
.
[
2
]
S
.
H
o
n
g
,
A
.
S
r
i
v
a
s
t
a
v
a
,
W
.
S
h
a
m
b
r
o
o
k
,
a
n
d
T.
D
u
mi
t
r
a
s,
“
G
o
serv
e
r
l
e
ss:
sec
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r
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c
l
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v
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n
s,
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1
0
t
h
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EN
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o
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o
p
o
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o
t
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n
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p
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(
H
o
t
C
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d
1
8
)
,
J
u
l
.
2
0
1
8
.
[
3
]
S
.
S
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n
h
a
,
A
.
H
a
z
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k
a
,
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o
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)
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a
n
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ms
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JP
P
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G
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:
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c
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rn
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Bi
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Bi
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t
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2
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1
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p
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6
4
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:
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1
0
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/
B
S
B
.
2
0
1
8
.
8
7
7
0
6
5
7
.
[
4
]
P
.
C
a
s
t
r
o
,
V
.
I
sh
a
k
i
a
n
,
V
.
M
u
t
h
u
s
a
m
y
,
a
n
d
A
.
S
l
o
m
i
n
s
k
i
,
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T
h
e
r
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se
o
f
ser
v
e
r
l
e
ss
c
o
m
p
u
t
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n
g
,
”
C
o
m
m
u
n
i
c
a
t
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o
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s
o
f
t
h
e
AC
M
,
v
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l
.
6
2
,
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o
.
1
2
,
p
p
.
4
4
–
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4
,
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o
v
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2
0
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,
d
o
i
:
1
0
.
1
1
4
5
/
3
3
6
8
4
5
4
.
[
5
]
D
.
K
h
a
t
r
i
,
S
.
K
.
K
h
a
t
r
i
,
a
n
d
D
.
M
i
s
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r
a
,
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P
o
t
e
n
t
i
a
l
B
o
t
t
l
e
n
e
c
k
a
n
d
m
e
a
s
u
r
i
n
g
p
e
r
f
o
r
m
a
n
c
e
o
f
serv
e
r
l
e
ss
c
o
m
p
u
t
i
n
g
:
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in
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