I
nte
rna
t
io
na
l J
o
urna
l o
f
E
lect
rica
l a
nd
Co
m
pu
t
er
E
ng
ineering
(
I
J
E
CE
)
Vo
l.
14
,
No
.
6
,
Dec
em
b
er
20
24
,
p
p
.
6
4
3
3
~
6
4
4
4
I
SS
N:
2088
-
8
7
0
8
,
DOI
: 1
0
.
1
1
5
9
1
/ijece.
v
14
i
6
.
pp
6
4
3
3
-
6
4
4
4
6433
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ec
e.
ia
esco
r
e.
co
m
Exploring
optima
l reso
urce allo
ca
ti
o
n methods
f
o
r
i
mpro
v
ed
eff
icie
ncy
in
flyin
g
ad
-
ho
c net
wo
rk
env
iro
nments
:
a
surv
ey
Z
eina
b
E
.
Ahm
ed
1,
2
,
Ais
ha
A
.
H
a
s
him
2,
3
,
Ra
s
hid
A.
Sa
ee
d
4
,
M
a
m
o
o
n M
o
ha
mm
ed
Ali Sa
ee
d
5
1
D
e
p
a
r
t
me
n
t
o
f
C
o
m
p
u
t
e
r
En
g
i
n
e
e
r
i
n
g
,
U
n
i
v
e
r
s
i
t
y
o
f
G
e
z
i
r
a
,
W
a
d
-
M
a
d
a
n
i
,
S
u
d
a
n
2
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
a
n
d
C
o
m
p
u
t
e
r
E
n
g
i
n
e
e
r
i
n
g
,
I
n
t
e
r
n
a
t
i
o
n
a
l
I
sl
a
mi
c
U
n
i
v
e
r
si
t
y
M
a
l
a
y
si
a
,
S
e
l
a
n
g
o
r
,
M
a
l
a
y
si
a
3
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
a
n
d
El
e
c
t
r
o
n
i
c
E
n
g
i
n
e
e
r
i
n
g
S
c
i
e
n
c
e
,
U
n
i
v
e
r
si
t
y
o
f
Jo
h
a
n
n
e
sb
u
r
g
,
J
o
h
a
n
n
e
sb
u
r
g
,
S
o
u
t
h
A
f
r
i
c
a
4
D
e
p
a
r
t
me
n
t
o
f
C
o
m
p
u
t
e
r
En
g
i
n
e
e
r
i
n
g
,
C
o
l
l
e
g
e
o
f
C
o
m
p
u
t
e
r
s,
a
n
d
I
n
f
o
r
ma
t
i
o
n
Te
c
h
n
o
l
o
g
y
,
T
a
i
f
U
n
i
v
e
r
s
i
t
y
,
Ta
i
f
,
S
a
u
d
i
A
r
a
b
i
a
5
D
e
p
a
r
t
me
n
t
o
f
C
o
mm
u
n
i
c
a
t
i
o
n
s
a
n
d
El
e
c
t
r
o
n
i
c
s
En
g
i
n
e
e
r
i
n
g
,
F
a
c
u
l
t
y
o
f
E
n
g
i
n
e
e
r
i
n
g
,
U
n
i
v
e
r
si
t
y
o
f
M
o
d
e
r
n
S
c
i
e
n
c
e
s,
S
a
n
a
'a
,
Y
e
m
e
n
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Ma
y
2
3
,
2
0
2
4
R
ev
is
ed
Au
g
6
,
2
0
2
4
Acc
ep
ted
Au
g
1
4
,
2
0
2
4
Th
is
s
u
rv
e
y
e
x
p
lo
re
s
o
p
ti
m
a
l
re
so
u
rc
e
a
ll
o
c
a
ti
o
n
m
e
th
o
d
s
t
o
e
n
h
a
n
c
e
th
e
e
fficie
n
c
y
o
f
fl
y
in
g
a
d
-
h
o
c
n
e
tw
o
rk
s
(F
AN
ET
s).
Un
m
a
n
n
e
d
a
e
rial
v
e
h
icle
s
(UA
Vs
),
c
o
m
m
o
n
ly
k
n
o
w
n
a
s
d
r
o
n
e
s,
a
re
wi
d
e
ly
d
e
p
l
o
y
e
d
i
n
m
il
it
a
ry
a
n
d
c
i
v
i
li
a
n
a
p
p
l
ica
ti
o
n
s
,
n
e
c
e
ss
it
a
ti
n
g
e
ffe
c
t
i
v
e
c
o
o
r
d
i
n
a
t
i
o
n
a
n
d
c
o
m
m
u
n
i
c
a
t
i
o
n
to
o
v
e
rc
o
m
e
c
h
a
ll
e
n
g
e
s.
F
AN
E
T
s
fa
c
i
l
it
a
te
w
ire
les
s
c
o
m
m
u
n
ica
ti
o
n
a
m
o
n
g
UA
Vs
,
im
p
r
o
v
i
n
g
c
o
o
r
d
i
n
a
t
i
o
n
a
n
d
i
n
f
o
rm
a
t
i
o
n
e
x
c
h
a
n
g
e
i
n
e
n
v
i
ro
n
m
e
n
ts
lac
k
i
n
g
t
ra
d
i
t
i
o
n
a
l
n
e
t
w
o
r
k
s
.
T
h
e
d
y
n
a
m
ic
m
o
b
il
it
y
o
f
UA
Vs
in
tro
d
u
c
e
s
u
n
i
q
u
e
c
o
n
si
d
e
ra
ti
o
n
s
fo
r
n
e
tw
o
rk
d
e
sig
n
a
n
d
c
o
n
n
e
c
ti
v
it
y
,
d
isti
n
g
u
ish
i
n
g
F
AN
ET
s
fro
m
c
o
n
v
e
n
ti
o
n
a
l
a
d
-
h
o
c
n
e
tw
o
rk
s.
Th
is
su
r
v
e
y
re
v
iew
s
v
a
rio
u
s
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
s,
in
c
lu
d
in
g
g
e
n
e
ti
c
a
lg
o
rit
h
m
s,
a
n
t
c
o
lo
n
y
o
p
ti
m
iza
ti
o
n
,
a
n
d
a
rti
ficia
l
n
e
u
ra
l
n
e
two
r
k
s,
w
h
ich
o
p
ti
m
ize
re
so
u
rc
e
a
ll
o
c
a
ti
o
n
b
y
c
o
n
sid
e
ri
n
g
m
issi
o
n
re
q
u
irem
e
n
ts,
n
e
two
r
k
t
o
p
o
l
o
g
y
,
a
n
d
e
n
e
rg
y
c
o
n
stra
i
n
ts.
Th
e
p
a
p
e
r
a
lso
d
isc
u
ss
e
s
th
e
c
rit
ica
l
ro
le
o
f
in
telli
g
e
n
t
a
lg
o
rit
h
m
s
in
e
n
h
a
n
c
i
n
g
n
e
two
r
k
e
n
e
rg
y
m
a
n
a
g
e
m
e
n
t,
q
u
a
li
t
y
o
f
se
rv
ice
(Qo
S
)
,
m
a
x
imiz
in
g
re
so
u
rc
e
a
ll
o
c
a
ti
o
n
,
a
n
d
o
p
t
imiz
in
g
o
v
e
ra
ll
p
e
rfo
rm
a
n
c
e
.
Th
e
sy
ste
m
a
ti
c
li
tera
tu
re
re
v
iew
c
a
teg
o
rize
s
re
so
u
rc
e
a
ll
o
c
a
ti
o
n
stra
teg
ies
b
a
se
d
o
n
p
e
rfo
rm
a
n
c
e
o
p
ti
m
iza
ti
o
n
c
rit
e
ria
a
n
d
su
m
m
a
rize
s
th
e
ir
stre
n
g
th
s,
we
a
k
n
e
ss
e
s,
a
n
d
a
p
p
li
c
a
ti
o
n
s.
Th
is
su
rv
e
y
h
i
g
h
l
ig
h
ts
th
e
p
o
ten
ti
a
l
o
f
F
AN
ET
s
to
re
v
o
l
u
ti
o
n
ize
v
a
ri
o
u
s
in
d
u
stries
a
n
d
u
n
lo
c
k
n
e
w
o
p
p
o
rt
u
n
it
ies
fo
r
UA
V
-
b
a
se
d
a
p
p
li
c
a
ti
o
n
s.
K
ey
w
o
r
d
s
:
E
f
f
icien
cy
o
p
tim
izatio
n
Fly
in
g
ad
-
h
o
c
n
etwo
r
k
I
n
tellig
en
t a
lg
o
r
ith
m
s
Netwo
r
k
p
er
f
o
r
m
an
c
e
R
eso
u
r
ce
allo
ca
tio
n
Un
m
an
n
ed
ae
r
ial
v
eh
icles
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Z
ein
ab
E
.
Ah
m
e
d
Dep
ar
tm
en
t o
f
C
o
m
p
u
ter
E
n
g
i
n
ee
r
in
g
,
U
n
iv
er
s
ity
o
f
Gez
ir
a
W
ad
-
Ma
d
an
i,
Su
d
an
E
m
ail:
Z
ein
ab
.
e.
ah
m
e
d
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
d
e
p
lo
y
m
e
n
t
o
f
u
n
m
an
n
ed
ae
r
ial
v
e
h
icles
(
UAVs)
,
co
m
m
o
n
ly
k
n
o
w
n
as
d
r
o
n
es,
h
as
e
x
p
er
ien
ce
d
a
s
ig
n
if
ican
t
i
n
cr
ea
s
e
in
b
o
th
m
ilit
ar
y
a
n
d
civ
ilian
c
o
n
tex
t
s
,
d
r
iv
en
b
y
t
h
e
wid
esp
r
ea
d
av
ailab
ilit
y
o
f
co
s
t
-
ef
f
ec
tiv
e
elec
tr
o
n
ic
s
en
s
o
r
s
an
d
co
m
m
u
n
icatio
n
tec
h
n
o
lo
g
ies
[
1
]
.
Ho
wev
er
,
ef
f
ec
tiv
e
co
o
r
d
in
ati
o
n
an
d
co
m
m
u
n
icatio
n
am
o
n
g
m
u
ltip
le
UAVs
p
r
esen
t
co
n
s
id
er
a
b
le
ch
allen
g
es.
T
o
o
v
er
co
m
e
th
ese
ch
allen
g
es,
f
ly
in
g
a
d
-
h
o
c
n
etwo
r
k
s
(
FANE
T
s
)
h
av
e
em
er
g
ed
as
p
r
a
ctica
l
s
o
lu
tio
n
s
.
W
ir
eless
co
m
m
u
n
icatio
n
am
o
n
g
UAVs
en
ab
les
im
p
r
o
v
e
d
c
o
o
r
d
in
atio
n
an
d
f
ac
ilit
ates
in
f
o
r
m
atio
n
ex
c
h
an
g
e
[
2
]
.
I
n
v
ar
i
o
u
s
co
n
te
x
ts
,
ter
m
s
lik
e
UAV
n
etwo
r
k
,
FANE
T
,
an
d
d
r
o
n
e
ad
-
h
o
c
n
etwo
r
k
ar
e
o
f
ten
in
ter
ch
a
n
g
ea
b
le.
T
h
i
s
p
ar
ad
ig
m
p
r
o
v
es
esp
ec
ially
u
s
ef
u
l in
en
v
ir
o
n
m
e
n
ts
lack
in
g
tr
ad
itio
n
al
co
m
m
u
n
icatio
n
n
etwo
r
k
s
,
s
u
ch
as d
is
aster
zo
n
es,
r
em
o
te
ar
ea
s
,
an
d
o
f
f
s
h
o
r
e
i
n
s
tallatio
n
s
[
3
]
.
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.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
4
3
3
-
6
4
4
4
6434
T
h
e
d
y
n
am
ic
m
o
b
ilit
y
o
f
U
AVs
in
tr
o
d
u
ce
s
u
n
iq
u
e
co
n
s
i
d
er
atio
n
s
f
o
r
co
n
n
ec
tiv
ity
an
d
n
etwo
r
k
d
esig
n
with
in
FANE
T
s
,
s
ettin
g
th
e
m
ap
a
r
t
f
r
o
m
c
o
n
v
e
n
tio
n
al
ad
-
h
o
c
n
etwo
r
k
s
[
4
]
.
W
ith
th
e
in
cr
ea
s
in
g
d
em
an
d
f
o
r
wir
eless
s
y
s
tem
s
,
p
r
eser
v
in
g
q
u
ality
o
f
s
er
v
ice
(
Qo
S)
an
d
m
ee
tin
g
u
s
er
ex
p
ec
tatio
n
s
p
o
s
e
in
cr
ea
s
in
g
ch
allen
g
es.
C
o
n
s
eq
u
en
tly
,
e
f
f
icien
t
r
eso
u
r
ce
allo
ca
tio
n
p
o
licies
ar
e
cr
u
cial
to
o
p
tim
ize
p
o
wer
an
d
b
an
d
wid
th
u
tili
za
tio
n
.
R
eso
u
r
ce
allo
ca
tio
n
i
n
v
o
lv
es
ass
ig
n
in
g
a
v
ailab
le
r
eso
u
r
ce
s
-
s
u
ch
a
s
tim
e,
en
er
g
y
,
an
d
b
an
d
wid
th
-
t
o
n
etwo
r
k
n
o
d
es
b
ased
o
n
th
eir
r
e
q
u
ir
em
e
n
ts
an
d
p
r
io
r
ities
,
th
er
eb
y
en
s
u
r
i
n
g
ef
f
ec
tiv
e
r
eso
u
r
ce
u
tili
za
tio
n
an
d
Qo
S
p
r
o
v
is
io
n
in
g
[
5
]
.
I
n
t
h
e
co
n
tex
t
o
f
FA
NE
T
s
,
o
p
tim
al
r
eso
u
r
ce
allo
c
atio
n
p
lay
s
a
cr
itical
r
o
le
in
im
p
r
o
v
in
g
n
etwo
r
k
ef
f
icien
cy
an
d
ef
f
ec
tiv
e
n
ess
.
Ach
iev
in
g
o
p
tim
al
r
eso
u
r
ce
allo
ca
tio
n
am
o
n
g
u
n
m
an
n
ed
ae
r
ial
v
eh
icles
is
im
p
er
ativ
e
to
en
h
an
ce
n
etwo
r
k
p
er
f
o
r
m
a
n
ce
an
d
estab
lis
h
r
eliab
le
co
m
m
u
n
icatio
n
ch
an
n
els.
I
n
tellig
en
t
alg
o
r
ith
m
s
ar
e
em
p
l
o
y
ed
with
in
FANE
T
s
to
en
h
an
ce
n
etwo
r
k
Qo
S,
m
ax
im
ize
r
eso
u
r
ce
allo
ca
tio
n
,
an
d
o
p
tim
ize
o
v
er
all
p
er
f
o
r
m
an
ce
[
6
]
.
E
x
am
p
les
o
f
s
u
ch
alg
o
r
ith
m
s
i
n
clu
d
e
g
en
etic
alg
o
r
ith
m
s
,
an
t
co
lo
n
y
o
p
tim
izatio
n
,
an
d
ar
tific
i
al
n
eu
r
al
n
etwo
r
k
s
,
wh
ich
o
p
tim
ize
r
eso
u
r
ce
allo
ca
tio
n
b
y
c
o
n
s
id
er
in
g
v
a
r
io
u
s
f
ac
to
r
s
s
u
ch
as
m
is
s
io
n
r
eq
u
ir
e
m
en
ts
,
n
etwo
r
k
to
p
o
lo
g
y
,
a
n
d
e
n
er
g
y
co
n
s
tr
ain
ts
.
Fly
in
g
ad
-
h
o
c
n
etwo
r
k
s
(
FANE
T
s
)
r
ep
r
esen
t
n
etwo
r
k
s
o
f
u
n
m
a
n
n
ed
ae
r
ial
v
e
h
icles
(
UAVs)
co
llab
o
r
atin
g
to
f
o
r
m
a
n
in
t
eg
r
ated
s
y
s
tem
,
with
ea
ch
UAV
o
p
er
atin
g
u
n
d
er
r
eso
u
r
ce
co
n
s
tr
ain
ts
th
at
en
co
m
p
ass
p
r
o
ce
s
s
in
g
p
o
wer
,
s
to
r
ag
e
ca
p
ac
ity
,
an
d
b
atter
y
l
if
e
lim
itatio
n
s
.
E
f
f
ec
tiv
e
r
eso
u
r
ce
m
an
ag
em
e
n
t
is
ess
en
tial
to
en
s
u
r
e
o
p
tim
al
n
etwo
r
k
p
er
f
o
r
m
a
n
ce
.
I
n
tellig
e
n
t
r
eso
u
r
ce
allo
ca
tio
n
with
in
FANE
T
s
in
v
o
lv
es
an
aly
zin
g
n
etwo
r
k
tr
af
f
ic,
p
r
ed
ictin
g
f
u
tu
r
e
d
em
an
d
s
,
an
d
allo
ca
tin
g
r
eso
u
r
ce
s
ac
c
o
r
d
in
g
l
y
[
7
]
.
T
h
is
o
p
tim
izatio
n
o
f
r
eso
u
r
ce
u
tili
za
tio
n
en
h
a
n
ce
s
n
etwo
r
k
p
e
r
f
o
r
m
an
ce
,
r
ed
u
ce
s
laten
cy
,
a
n
d
f
ac
ilit
ates
ef
f
icien
t
d
ata
th
r
o
u
g
h
p
u
t.
I
n
tellig
en
t
r
e
s
o
u
r
ce
allo
ca
tio
n
p
lay
s
a
p
i
v
o
tal
r
o
le
in
ex
ten
d
in
g
UAV
b
a
tter
y
life
,
e
n
s
u
r
in
g
co
n
tin
u
o
u
s
n
etwo
r
k
c
o
n
n
ec
tiv
ity
,
an
d
m
ee
tin
g
m
is
s
io
n
o
b
je
ctiv
es.
Op
tim
al
an
d
in
tellig
en
t
r
eso
u
r
ce
allo
ca
tio
n
is
v
ital
f
o
r
th
e
s
m
o
o
th
o
p
er
atio
n
o
f
FANE
T
s
,
allo
win
g
th
em
to
f
u
lf
ill
v
ar
io
u
s
ap
p
licatio
n
n
ee
d
s
lik
e
s
u
r
v
eillan
ce
,
s
ea
r
ch
an
d
r
esc
u
e,
an
d
e
n
v
ir
o
n
m
en
tal
m
o
n
i
to
r
in
g
[
8
]
.
FANE
T
s
o
f
f
e
r
d
i
s
tin
ct
ad
v
an
tag
es,
f
u
n
ctio
n
in
g
ef
f
ec
tiv
ely
i
n
ar
ea
s
with
lim
ited
co
m
m
u
n
icatio
n
n
etwo
r
k
s
an
d
f
in
d
in
g
a
p
p
licatio
n
s
ac
r
o
s
s
d
iv
er
s
e
d
o
m
ain
s
,
in
cl
u
d
in
g
s
u
r
v
eillan
ce
,
s
ea
r
ch
an
d
r
escu
e
m
is
s
io
n
s
,
an
d
en
v
ir
o
n
m
en
tal
m
o
n
ito
r
in
g
.
C
o
n
tin
u
o
u
s
ad
v
an
ce
m
e
n
ts
in
r
eso
u
r
ce
all
o
ca
tio
n
a
n
d
c
o
n
tr
o
l
alg
o
r
ith
m
s
h
o
ld
p
r
o
m
is
e
f
o
r
f
u
r
th
er
en
h
a
n
cin
g
FANE
T
ca
p
ab
ilit
ies.
I
n
s
u
m
m
a
r
y
,
FA
NE
T
s
h
av
e
th
e
p
o
ten
tial
t
o
r
e
v
o
lu
tio
n
ize
n
u
m
e
r
o
u
s
in
d
u
s
tr
ies
an
d
u
n
lo
ck
n
o
v
el
o
p
p
o
r
tu
n
ities
f
o
r
UAV
-
b
ased
ap
p
licatio
n
s
[
9
]
.
T
h
e
p
ap
er
'
s
s
tr
u
ctu
r
e
is
o
u
tlin
ed
b
elo
w.
I
n
s
ec
tio
n
2
,
we
in
tr
o
d
u
ce
th
e
s
y
s
tem
atic
liter
atu
r
e
r
ev
iew
f
r
am
ewo
r
k
.
I
n
s
ec
tio
n
3
,
we
o
f
f
er
b
ac
k
g
r
o
u
n
d
in
f
o
r
m
atio
n
o
n
k
e
y
co
n
ce
p
ts
p
er
tin
en
t
to
th
is
p
ap
er
,
in
clu
d
in
g
FANE
T
,
r
eso
u
r
ce
allo
ca
tio
n
,
an
d
in
tellig
en
t
alg
o
r
ith
m
s
.
Sectio
n
4
ex
p
lo
r
es
r
elate
d
r
esear
ch
o
n
o
p
tim
izatio
n
tech
n
i
q
u
es
to
el
ev
ate
th
e
en
er
g
y
ef
f
icien
cy
,
q
u
ality
o
f
s
er
v
ice,
r
o
u
tin
g
p
r
o
to
co
ls
an
d
f
lig
h
t
tr
ajec
to
r
ies
in
FANE
T
.
Sectio
n
5
p
r
esen
ts
an
an
al
y
s
is
an
d
d
is
cu
s
s
io
n
.
Fin
ally
,
th
e
p
ap
er
co
n
clu
d
es
in
s
ec
tio
n
6
.
2.
SYST
E
M
AT
I
C
L
I
T
E
R
AT
U
RE
RE
VI
E
W
SCH
E
M
E
I
n
th
is
s
ec
tio
n
,
we
will
r
ev
i
ew
s
u
r
v
ey
p
a
p
er
s
o
n
FANE
T
f
o
u
n
d
in
t
h
e
liter
atu
r
e.
T
h
ese
ar
ticle
s
in
tr
o
d
u
ce
FANE
T
th
o
r
o
u
g
h
r
e
v
iew
o
f
r
eso
u
r
ce
allo
ca
tio
n
,
i
n
clu
d
in
g
an
s
wer
s
to
e
n
er
g
y
ef
f
icien
cy
,
q
u
ality
o
f
s
er
v
ice,
an
d
r
o
u
tin
g
p
r
o
to
co
l
ch
allen
g
es.
R
eso
u
r
ce
allo
ca
ti
o
n
s
tr
ateg
ies
ar
e
class
if
ied
b
a
s
ed
o
n
p
er
f
o
r
m
a
n
ce
o
p
tim
izatio
n
cr
iter
ia,
an
d
we
will
s
u
m
m
ar
ize
th
ese
ca
teg
o
r
ies
an
d
o
p
tim
izatio
n
s
tr
ateg
ies,
h
ig
h
lig
h
tin
g
th
eir
s
tr
en
g
th
s
,
wea
k
n
ess
es,
an
d
ar
ea
o
f
ap
p
licatio
n
s
.
Sev
er
al
ar
ticles
r
elate
d
to
r
eso
u
r
ce
allo
ca
tio
n
in
FANE
T
,
in
clu
d
in
g
s
p
ec
if
ic
s
o
lu
tio
n
s
to
ad
d
r
ess
is
s
u
es
s
u
ch
as
e
n
er
g
y
co
n
s
u
m
p
tio
n
,
q
u
ality
o
f
s
er
v
ice,
r
o
u
tin
g
p
r
o
to
co
ls
,
an
d
f
lig
h
t
tr
ajec
to
r
y
,
wer
e
r
ev
iewe
d
,
a
n
d
cite
5
0
a
r
ticles
s
elec
ted
f
o
r
th
e
r
ev
iew
s
tu
d
y
in
th
is
p
ap
e
r
.
T
h
e
p
er
ce
n
tag
e
d
is
tr
ib
u
tio
n
o
f
th
e
to
tal
ar
ticles
f
o
r
r
elate
d
wo
r
k
(
5
0
p
ap
e
r
s
)
p
u
b
lis
h
ed
in
I
E
E
E
,
MD
PI,
Sp
r
in
g
er
,
Hin
d
awi,
an
d
o
th
er
s
,
as
s
h
o
wn
in
Fig
u
r
e
1
.
Sch
o
lar
s
h
av
e
e
x
p
lo
r
e
d
u
ti
lizin
g
o
p
tim
izatio
n
tech
n
iq
u
es to
u
p
g
r
a
d
e
v
ar
i
o
u
s
asp
ec
ts
o
f
FANE
T
n
etwo
r
k
s
,
in
clu
d
in
g
e
n
er
g
y
co
n
s
u
m
p
tio
n
,
q
u
ality
o
f
s
er
v
ice,
r
o
u
tin
g
p
r
o
t
o
co
ls
,
an
d
f
lig
h
t tr
ajec
to
r
y
.
I
n
s
u
m
m
a
r
y
,
th
e
o
p
tim
izatio
n
o
f
r
eso
u
r
ce
allo
ca
tio
n
in
FANE
T
s
th
r
o
u
g
h
th
e
i
n
t
eg
r
atio
n
o
f
o
p
tim
izatio
n
m
et
h
o
d
s
h
as
s
er
v
ed
as
a
f
o
u
n
d
atio
n
al
ap
p
r
o
ac
h
f
o
r
e
n
h
an
ci
n
g
v
ar
io
u
s
f
ac
ets
o
f
FANE
T
n
etwo
r
k
s
.
Fig
u
r
e
2
illu
s
tr
ates
th
e
p
er
ce
n
tag
e
d
is
tr
ib
u
tio
n
o
f
o
p
tim
izatio
n
tech
n
iq
u
es
em
p
lo
y
ed
to
en
h
an
ce
d
iv
er
s
e
asp
ec
ts
o
f
FANE
T
n
etwo
r
k
s
.
T
h
ese
tech
n
iq
u
es h
av
e
b
ee
n
ap
p
lied
to
en
h
an
ce
q
u
ality
o
f
s
er
v
ice
with
i
n
FANE
T
n
etwo
r
k
s
[
1
0
]
,
an
d
a
d
d
r
ess
en
er
g
y
co
n
s
u
m
p
tio
n
r
e
d
u
ctio
n
as
d
is
cu
s
s
ed
in
s
tu
d
y
[
1
1
]
.
Fu
r
th
e
r
m
o
r
e
,
o
p
tim
izatio
n
tech
n
iq
u
es
h
av
e
f
o
u
n
d
u
tili
ty
in
im
p
r
o
v
in
g
r
o
u
tin
g
p
r
o
to
c
o
ls
an
d
f
lig
h
t
tr
aj
ec
to
r
ies
with
in
th
e
FANE
T
co
n
tex
t
[
1
2
]
.
Fig
u
r
e
3
illu
s
tr
ates
th
e
n
u
m
b
er
o
f
p
ap
er
s
p
u
b
lis
h
ed
r
elate
d
to
r
es
o
u
r
ce
allo
ca
tio
n
in
FANE
T
o
v
er
th
e
p
ast y
ea
r
s
in
I
E
E
E
,
MD
PI,
Sp
r
in
g
er
,
E
ls
ev
i
er
,
an
d
o
th
er
j
o
u
r
n
als.
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
E
xp
lo
r
in
g
o
p
tima
l res
o
u
r
ce
a
llo
ca
tio
n
meth
o
d
s
fo
r
imp
r
o
ve
d
efficien
cy
in
…
(
Zein
a
b
E
.
A
h
med
)
6435
Fig
u
r
e
1
.
Per
ce
n
ta
g
e
d
is
tr
ib
u
ti
o
n
o
f
to
tal
ar
ticles f
o
r
r
elate
d
wo
r
k
Fig
u
r
e
2
.
Per
ce
n
ta
g
e
d
is
tr
ib
u
ti
o
n
o
f
o
p
tim
izatio
n
tec
h
n
iq
u
es
o
f
FANE
T
Fig
u
r
e
3
.
Nu
m
b
er
o
f
p
u
b
licatio
n
s
f
o
r
y
ea
r
s
3.
F
ANET
R
E
SO
U
RCE
S AL
L
O
CATI
O
N
T
h
is
s
ec
tio
n
s
u
m
m
ar
izes
t
h
e
k
ey
co
n
ce
p
ts
d
is
cu
s
s
ed
in
th
is
p
ap
er
,
in
clu
d
in
g
FANE
T
,
r
eso
u
r
ce
allo
ca
tio
n
,
an
d
in
tellig
en
t
alg
o
r
ith
m
s
.
UAVs
h
av
e
d
iv
er
s
e
ap
p
licatio
n
s
,
s
u
ch
as
s
u
r
v
eillan
c
e,
lo
g
is
tics
,
r
escu
e
o
p
er
atio
n
s
,
an
d
co
m
m
u
n
icatio
n
s
u
p
p
o
r
t
[
1
3
]
.
T
h
er
e
ar
e
two
p
r
im
ar
y
ty
p
es
o
f
UAVs:
f
ix
ed
-
win
g
an
d
r
o
tar
y
-
win
g
,
ea
ch
with
d
is
tin
ct
ch
ar
ac
ter
is
tics
an
d
ca
p
ab
ilit
ies
[
1
4
]
.
Fix
ed
-
win
g
UAVs
o
f
f
er
h
ig
h
s
p
ee
d
an
d
p
ay
lo
a
d
ca
p
ac
ity
b
u
t
r
eq
u
ir
e
co
n
tin
u
o
u
s
m
o
v
em
e
n
t,
lim
itin
g
th
eir
s
u
itab
ilit
y
f
o
r
s
tatio
n
ar
y
task
s
.
R
o
tar
y
-
win
g
UAVs,
s
u
ch
as
q
u
ad
co
p
ter
s
,
p
r
o
v
id
e
ex
ce
llen
t
m
an
eu
v
er
a
b
ilit
y
b
u
t
h
av
e
a
lo
wer
ca
p
ac
ity
.
T
h
e
s
elec
tio
n
o
f
th
e
ap
p
r
o
p
r
iate
UAV
d
ep
e
n
d
s
o
n
th
e
s
p
ec
if
ic
r
e
q
u
ir
em
e
n
ts
o
f
th
e
ap
p
licatio
n
s
.
A
g
r
o
u
p
o
f
UAVs
th
at
en
ab
le
h
ig
h
-
s
p
ee
d
wir
eless
co
m
m
u
n
icatio
n
o
v
er
e
x
ten
s
iv
e
ar
ea
s
,
co
n
n
ec
tin
g
with
g
r
o
u
n
d
n
o
d
e
s
,
f
o
r
m
s
FANE
T
s
.
Dif
f
er
en
t
co
m
m
u
n
icatio
n
a
r
ch
itectu
r
es,
s
u
ch
as
d
ir
ec
t
co
m
m
u
n
icatio
n
,
s
atellite
n
etwo
r
k
s
,
ce
llu
lar
n
etwo
r
k
s
,
an
d
ad
-
h
o
c
n
etwo
r
k
s
,
ca
n
b
e
em
p
lo
y
ed
with
in
UAV
n
etwo
r
k
s
,
as
d
ep
icted
in
Fig
u
r
e
4
.
UAVs
f
u
n
ctio
n
a
s
s
tan
d
alo
n
e
air
cr
af
t,
wh
ile
FANE
T
s
r
ef
er
to
n
etwo
r
k
s
o
f
UAVs
co
m
m
u
n
icatin
g
to
estab
lis
h
a
w
ir
eles
s
n
etwo
r
k
[
1
5
]
.
Her
e
ar
e
m
a
n
y
k
ey
d
if
f
er
en
ce
s
b
etwe
en
UAV
s
an
d
FANE
T
s
:
−
Fu
n
ctio
n
:
UAVs
f
u
n
ctio
n
as
au
to
n
o
m
o
u
s
air
cr
af
t
ca
p
a
b
le
o
f
ex
ec
u
tin
g
s
p
ec
if
ic
task
s
,
wh
er
ea
s
FANE
T
s
co
n
s
is
t o
f
n
etwo
r
k
s
o
f
UAVs c
o
llab
o
r
atin
g
t
o
ac
co
m
p
lis
h
a
s
h
ar
ed
o
b
jectiv
e.
−
C
o
m
m
u
n
icatio
n
:
UAVs
ty
p
ically
o
p
er
ate
in
is
o
latio
n
an
d
d
o
n
o
t
en
g
a
g
e
in
co
m
m
u
n
icatio
n
with
o
th
er
UAVs.
I
n
co
n
tr
ast,
FANE
T
s
n
ec
ess
itate
UA
V
-
to
-
UAV
co
m
m
u
n
icatio
n
to
estab
lis
h
a
n
etwo
r
k
.
−
Netwo
r
k
to
p
o
lo
g
y
:
UAVs
ca
n
b
e
em
p
lo
y
ed
i
n
d
iv
e
r
s
e
n
e
two
r
k
to
p
o
lo
g
ies,
i
n
clu
d
in
g
p
o
in
t
-
to
-
p
o
in
t
o
r
p
o
in
t
-
to
-
m
u
ltip
o
in
t
co
n
f
ig
u
r
at
io
n
s
.
I
n
co
n
tr
ast,
FANE
T
s
ty
p
ically
ad
o
p
t
a
m
esh
to
p
o
lo
g
y
,
wh
er
ein
ea
ch
UAV
co
m
m
u
n
icate
s
with
m
u
l
tip
le
n
eig
h
b
o
r
in
g
UAVs to
estab
lis
h
th
e
n
etwo
r
k
[
1
6
]
.
−
C
o
m
p
lex
ity
:
FANE
T
s
g
en
er
a
lly
ex
h
ib
it
g
r
ea
ter
co
m
p
lex
it
y
co
m
p
a
r
ed
t
o
s
tan
d
alo
n
e
U
AVs
d
u
e
to
th
e
ad
d
itio
n
al
in
f
r
astru
ctu
r
e
a
n
d
c
o
m
m
u
n
icatio
n
p
r
o
to
co
ls
r
eq
u
ir
ed
to
f
o
r
m
a
n
d
m
ain
tain
a
n
et
wo
r
k
.
FANE
T
s
ar
e
s
p
ec
ialized
n
etwo
r
k
s
f
o
r
UAVs,
d
is
tin
ct
f
r
o
m
m
o
b
ile
ad
h
o
c
n
etwo
r
k
s
(
MA
NE
T
s
)
an
d
v
eh
icu
lar
a
d
h
o
c
n
etwo
r
k
s
(
VANE
T
s
)
,
with
u
n
iq
u
e
c
o
n
n
ec
tiv
ity
,
s
en
s
o
r
ty
p
es,
an
d
s
er
v
ice
d
is
co
v
er
y
m
ec
h
an
is
m
s
[
1
7
]
.
T
h
ey
f
ac
e
ch
allen
g
es
lik
e
h
ig
h
UAV
m
o
b
ilit
y
an
d
d
y
n
am
ic
n
etwo
r
k
to
p
o
g
r
a
p
h
ic
[
1
8
]
.
Un
lik
e
MA
NE
T
s
,
FANE
T
s
r
ely
o
n
lin
e
-
of
-
s
ig
h
t
c
o
m
m
u
n
icatio
n
with
g
r
o
u
n
d
co
n
tr
o
l
s
tatio
n
s
,
m
ak
in
g
0
2
4
6
8
10
12
2
0
1
7
2
0
1
8
2
0
1
9
2
0
2
0
2
0
2
1
2
0
2
2
2
0
2
3
2
0
2
4
Nu
m
b
e
r
o
f
P
u
b
li
c
a
ti
o
n
s
Nu
m
b
e
r
o
f
Ye
a
rs
S
p
rin
g
e
r
El
se
iv
e
r
IEE
E
M
DPI
h
i
n
d
a
wi
Oth
e
r
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.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
4
3
3
-
6
4
4
4
6436
ef
f
icien
t
r
o
u
tin
g
cr
itical
d
esp
i
te
lim
ited
r
o
u
te
d
u
r
atio
n
s
.
Va
r
io
u
s
r
o
u
tin
g
p
r
o
to
co
ls
ar
e
u
s
ed
,
in
clu
d
i
n
g
s
tatic,
p
r
o
ac
tiv
e,
o
n
-
d
em
a
n
d
,
h
y
b
r
id
,
an
d
g
eo
g
r
a
p
h
ic
ap
p
r
o
ac
h
es.
E
f
f
ec
tiv
e
r
eso
u
r
ce
allo
ca
tio
n
is
cr
u
cial
to
o
p
tim
ize
b
an
d
wid
th
an
d
p
o
wer
f
o
r
q
u
a
lity
o
f
s
er
v
ice
[
1
9
]
.
R
eso
u
r
ce
allo
ca
tio
n
in
FANE
T
s
is
s
tr
u
ctu
r
ed
with
in
p
u
ts
,
co
n
s
tr
ain
ts
,
o
b
jectiv
es,
an
d
o
u
tp
u
ts
,
aim
in
g
to
m
ax
im
ize
n
et
wo
r
k
p
e
r
f
o
r
m
an
ce
m
etr
ics
[
2
0
]
.
I
n
Fig
u
r
e
5
,
th
e
tax
o
n
o
m
y
o
f
en
h
an
ce
d
r
eso
u
r
ce
allo
ca
tio
n
m
eth
o
d
s
is
p
r
ese
n
ted
,
d
iv
i
d
ed
in
t
o
s
tatic
an
d
d
y
n
am
ic
ca
teg
o
r
ies.
Static
m
eth
o
d
s
ar
e
id
ea
l
f
o
r
s
t
ab
le
n
etwo
r
k
s
with
p
r
ed
ictab
l
e
tr
af
f
ic
p
atter
n
s
,
wh
ile
d
y
n
am
ic
m
eth
o
d
s
a
d
ap
t
i
n
r
ea
l
-
tim
e
to
f
lu
ctu
atin
g
co
n
d
itio
n
s
,
o
p
tim
izin
g
r
eso
u
r
ce
u
tili
za
tio
n
an
d
e
n
s
u
r
in
g
r
eliab
le
co
m
m
u
n
icatio
n
[
2
1
]
.
Fig
u
r
e
4
.
Fly
in
g
ad
-
h
o
c
n
etwo
r
k
s
(
FANE
T
s
)
Fig
u
r
e
5
.
T
a
x
o
n
o
m
y
o
f
en
h
an
ce
d
m
eth
o
d
s
f
o
r
r
eso
u
r
ce
allo
c
atio
n
s
ch
em
es
Var
io
u
s
ar
tific
ial
in
tellig
en
t
(
AI
)
tech
n
i
q
u
es
h
av
e
b
ee
n
ap
p
lied
ac
r
o
s
s
n
u
m
er
o
u
s
d
o
m
ain
s
,
in
clu
d
in
g
FANE
T
s
,
to
en
h
an
ce
s
y
s
tem
p
er
f
o
r
m
an
ce
.
I
n
FANE
T
s
,
AI
p
lay
s
a
p
iv
o
tal
r
o
le
in
r
o
u
tin
g
task
s
b
y
em
p
lo
y
in
g
a
d
ec
is
io
n
-
m
ak
in
g
p
a
r
ad
ig
m
.
T
h
e
d
ec
is
io
n
-
m
ak
er
ass
ess
es
t
h
e
en
v
ir
o
n
m
en
t,
s
elec
ts
o
p
tim
al
ac
tio
n
s
,
r
ec
eiv
es
f
ee
d
b
ac
k
as
r
ewa
r
d
s
,
an
d
r
ef
i
n
es
its
d
ec
is
io
n
-
m
ak
in
g
ca
p
a
b
ilit
ies
th
r
o
u
g
h
lear
n
in
g
p
r
o
c
ess
es
[
2
2
]
.
E
n
er
g
y
m
an
ag
em
en
t
is
an
o
th
er
cr
itic
al
asp
ec
t
o
f
FANE
T
s
,
p
r
im
ar
ily
d
u
e
to
th
e
lim
ited
b
atter
y
life
o
f
UAVs.
AI
tech
n
iq
u
es,
s
u
ch
as
m
ac
h
i
n
e
lear
n
in
g
,
f
ac
ilit
ate
en
er
g
y
o
p
tim
izatio
n
b
y
an
ticip
at
in
g
f
u
tu
r
e
e
n
er
g
y
r
eq
u
ir
em
e
n
ts
,
ad
ap
tin
g
n
etwo
r
k
o
p
er
atio
n
s
to
co
n
s
er
v
e
en
er
g
y
,
an
d
im
p
r
o
v
in
g
e
n
er
g
y
s
to
r
a
g
e
an
d
d
is
tr
ib
u
tio
n
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
E
xp
lo
r
in
g
o
p
tima
l res
o
u
r
ce
a
llo
ca
tio
n
meth
o
d
s
fo
r
imp
r
o
ve
d
efficien
cy
in
…
(
Zein
a
b
E
.
A
h
med
)
6437
ef
f
icien
cy
[
2
3
]
.
Fo
r
in
s
tan
ce
,
AI
-
b
ased
alg
o
r
ith
m
s
ca
n
d
y
n
a
m
ically
ad
ju
s
t
UAV
p
o
we
r
le
v
els
b
ased
o
n
m
a
n
y
f
ac
to
r
s
,
s
u
ch
as
lo
ca
tio
n
,
n
etwo
r
k
tr
af
f
ic,
an
d
b
atter
y
s
tatu
s
,
m
in
im
izin
g
en
er
g
y
co
n
s
u
m
p
t
io
n
wh
ile
en
s
u
r
in
g
r
eliab
le
co
m
m
u
n
icatio
n
[
2
4
]
.
4.
RE
L
AT
E
D
WO
RK
S
T
h
is
s
ec
tio
n
ex
am
in
es
v
ar
io
u
s
ap
p
r
o
ac
h
es
p
r
o
p
o
s
ed
i
n
r
ec
en
t
r
esear
ch
to
en
h
an
ce
th
e
p
er
f
o
r
m
a
n
ce
an
d
ef
f
icien
cy
o
f
FANE
T
s
an
d
r
elate
d
tech
n
o
lo
g
ies
.
FANE
T
s
,
co
m
p
r
is
in
g
n
e
two
r
k
s
o
f
UAVs
co
m
m
u
n
icatin
g
wir
eless
ly
,
h
a
v
e
g
ar
n
er
ed
s
ig
n
i
f
ican
t
atten
ti
o
n
d
u
e
to
th
ei
r
d
iv
e
r
s
e
ap
p
lica
tio
n
s
in
f
ield
s
s
u
ch
as
s
u
r
v
eillan
ce
,
d
is
aster
r
es
p
o
n
s
e,
a
n
d
c
o
m
m
u
n
icatio
n
s
u
p
p
o
r
t.
T
h
ese
s
tu
d
ies
d
el
v
e
in
to
in
n
o
v
ativ
e
m
eth
o
d
o
l
o
g
ies,
alg
o
r
ith
m
s
,
an
d
p
r
o
to
c
o
ls
aim
ed
at
o
p
tim
izin
g
r
eso
u
r
ce
u
tili
za
tio
n
,
im
p
r
o
v
in
g
e
n
er
g
y
ef
f
icien
cy
,
an
d
en
h
an
cin
g
o
v
er
all
n
etwo
r
k
p
er
f
o
r
m
an
ce
in
FANE
T
s
an
d
r
elate
d
s
y
s
tem
s
.
Z
h
ao
et
a
l.
[
2
5
]
p
r
o
p
o
s
ed
a
n
ew
m
eth
o
d
t
o
en
h
an
ce
FANE
T
p
er
f
o
r
m
a
n
ce
u
s
in
g
th
e
im
p
r
o
v
ed
a
r
tific
ial
b
ee
co
lo
n
y
o
p
tim
izatio
n
(
I
AB
C
)
alg
o
r
ith
m
f
o
r
b
etter
clu
s
ter
h
ea
d
s
elec
tio
n
d
em
o
n
s
tr
ated
in
Fig
u
r
e
6
an
d
th
e
AI
-
p
r
o
o
f
o
f
witn
ess
co
n
s
en
s
u
s
alg
o
r
ith
m
(
AI
-
Po
W
C
A)
f
o
r
m
in
in
g
.
Fig
u
r
e
6
.
E
f
f
icien
t c
lu
s
ter
in
g
p
r
o
to
co
l
f
o
r
FANE
T
s
T
h
i
s
a
p
p
r
o
a
c
h
i
m
p
r
o
v
e
d
e
f
f
i
c
i
e
n
c
y
a
n
d
r
e
s
i
l
i
e
n
c
e
a
g
a
i
n
s
t
a
t
ta
c
k
s
b
y
u
p
t
o
5
1
%
,
a
c
h
i
e
v
i
n
g
h
i
g
h
p
a
c
k
e
t
d
e
l
i
v
e
r
y
r
a
t
i
o
s
a
n
d
m
i
n
i
m
a
l
en
d
-
to
-
e
n
d
d
e
l
a
y
s
.
E
s
c
o
b
a
r
et
a
l
.
[
2
6
]
e
x
p
l
o
r
e
d
n
e
t
w
o
r
k
r
e
s
o
u
r
c
e
m
a
n
a
g
e
m
e
n
t
i
n
a
d
v
a
n
c
e
d
i
n
t
e
r
n
e
t
o
f
t
h
i
n
g
s
(
I
o
T
)
a
p
p
l
i
c
a
ti
o
n
s
,
i
n
t
r
o
d
u
c
i
n
g
a
v
i
r
t
u
a
l
n
e
tw
o
r
k
e
m
b
e
d
d
i
n
g
(
V
N
E
)
f
r
a
m
e
w
o
r
k
f
o
r
o
p
t
i
m
i
z
i
n
g
d
a
t
a
f
l
o
w
a
p
p
l
ic
a
t
io
n
s
i
n
FA
N
E
T
s
a
n
d
a
i
r
b
o
r
n
e
n
e
t
w
o
r
k
s
.
U
A
Vs
i
n
a
FAN
E
T
p
r
o
v
i
d
e
d
e
d
g
e
c
o
m
p
u
t
i
n
g
f
o
r
r
e
s
c
u
e
o
p
e
r
a
t
i
o
n
s
,
u
s
i
n
g
m
o
d
e
l
-
b
a
s
e
d
r
e
i
n
f
o
r
ce
m
e
n
t
l
e
a
r
n
i
n
g
f
o
r
d
y
n
a
m
i
c
d
e
p
l
o
y
m
e
n
t
d
e
c
i
s
i
o
n
s
[
2
7
]
.
C
h
e
n
e
t
a
l
.
[
2
8
]
a
p
p
l
i
e
d
d
e
e
p
r
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
(
D
R
L
)
t
o
e
n
h
a
n
c
e
m
u
l
t
i
-
UA
V
-
a
s
s
is
t
e
d
u
p
l
i
n
k
c
o
m
m
u
n
i
c
a
t
i
o
n
,
a
c
h
i
e
v
i
n
g
s
i
g
n
i
f
i
c
a
n
t
i
m
p
r
o
v
e
m
e
n
ts
i
n
c
o
v
e
r
a
g
e
r
a
t
e
,
l
a
t
e
n
c
y
,
a
n
d
e
n
e
r
g
y
u
s
a
g
e
.
I
n
s
t
u
d
y
[
2
9
]
,
a
D
R
L
-
b
as
e
d
s
y
s
t
e
m
m
a
n
a
g
e
d
U
A
V
f
l
e
e
ts
a
s
m
o
b
il
e
b
a
s
e
s
ta
t
i
o
n
s
,
o
p
t
i
m
iz
i
n
g
c
o
v
e
r
a
g
e
,
f
a
i
r
n
e
s
s
,
a
n
d
e
n
e
r
g
y
u
t
i
l
i
z
at
i
o
n
.
Qi
a
n
e
t
a
l
.
[
3
0
]
m
i
n
i
m
i
z
e
d
e
n
e
r
g
y
c
o
n
s
u
m
p
t
i
o
n
i
n
m
a
r
i
t
i
m
e
-
I
o
T
(
M
-
I
o
T
)
n
e
tw
o
r
k
s
w
it
h
U
AV
s
u
s
i
n
g
a
d
u
a
l
-
l
a
y
e
r
e
d
D
R
L
a
n
d
L
a
g
r
an
g
i
a
n
m
i
n
i
m
i
z
at
i
o
n
a
p
p
r
o
a
c
h
.
Y
o
u
e
t
a
l
.
[
3
1
]
r
e
d
u
c
e
d
e
n
e
r
g
y
c
o
n
s
u
m
p
t
i
o
n
i
n
a
l
a
y
e
r
e
d
F
AN
E
T
f
o
r
m
o
b
i
l
e
e
d
g
e
c
o
m
p
u
t
i
n
g
(
M
E
C
)
wi
t
h
a
n
i
t
e
r
a
ti
v
e
a
l
g
o
r
i
t
h
m
(
A
F
U
)
a
l
g
o
r
i
t
h
m
,
o
p
t
i
m
i
z
i
n
g
t
a
s
k
s
c
h
e
d
u
l
i
n
g
a
n
d
U
AV
t
r
a
j
e
c
t
o
r
i
es
.
N
a
m
d
e
v
e
t
a
l
.
[
3
2
]
i
n
t
r
o
d
u
c
e
d
A
I
-
b
a
s
e
d
c
l
u
s
te
r
i
n
g
a
l
g
o
r
i
t
h
m
s
f
o
r
F
A
N
E
T
s
,
i
m
p
r
o
v
i
n
g
c
l
u
s
t
e
r
li
f
e
s
p
a
n
,
e
n
e
r
g
y
c
o
n
s
u
m
p
t
i
o
n
,
a
n
d
c
o
n
s
t
r
u
c
t
i
o
n
t
i
m
e
.
M
a
n
s
o
u
r
et
a
l
.
[
3
3
]
p
r
e
s
e
n
t
e
d
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.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
4
3
3
-
6
4
4
4
6438
c
r
o
s
s
-
la
y
e
r
a
n
d
e
n
e
r
g
y
-
a
w
a
r
e
A
O
D
V
(
C
L
E
A
-
AO
D
V
)
,
a
n
e
n
e
r
g
y
-
a
w
a
r
e
r
o
u
t
i
n
g
p
r
o
t
o
c
o
l
f
o
r
F
A
N
E
T
s
,
o
u
t
p
e
r
f
o
r
m
i
n
g
t
r
a
d
i
t
i
o
n
a
l
m
e
t
h
o
d
s
i
n
d
e
l
a
y
a
n
d
p
a
c
k
e
t
d
e
li
v
er
y
r
a
t
i
o
.
I
n
s
t
u
d
y
[
3
4
]
,
a
m
e
t
h
o
d
o
p
t
i
m
i
z
e
d
e
n
e
r
g
y
e
f
f
i
c
i
e
n
c
y
a
n
d
Q
o
S
i
n
m
u
l
t
i
-
U
A
V
s
y
s
t
e
m
s
u
s
i
n
g
L
y
a
p
u
n
o
v
o
p
t
i
m
i
z
a
t
i
o
n
f
o
r
g
a
t
e
w
a
y
s
e
l
e
c
ti
o
n
a
n
d
t
a
s
k
s
c
h
e
d
u
l
i
n
g
i
m
p
r
o
v
e
m
e
n
ts
,
a
s
d
i
s
p
l
a
y
e
d
i
n
F
i
g
u
r
e
7.
L
iu
et
a
l.
[
3
5
]
in
tr
o
d
u
ce
d
a
c
o
llab
o
r
ativ
e
o
p
tim
izatio
n
m
et
h
o
d
f
o
r
r
ed
u
cin
g
p
o
wer
co
n
s
u
m
p
tio
n
i
n
ME
C
n
etwo
r
k
s
with
m
u
ltip
le
UAVs.
T
h
ey
in
teg
r
ated
co
m
p
r
ess
iv
e
s
en
s
in
g
-
b
ased
u
s
er
ass
o
ciatio
n
an
d
f
u
zz
y
c
-
m
ea
n
s
clu
s
ter
in
g
f
o
r
u
s
er
ass
o
ciatio
n
,
p
o
wer
co
n
tr
o
l,
co
m
p
u
tatio
n
ca
p
ac
ity
allo
c
atio
n
,
an
d
lo
ca
tio
n
p
lan
n
in
g
.
I
n
s
tu
d
y
[
3
6
]
,
a
jo
i
n
t
o
p
tim
izatio
n
m
o
d
el
co
o
r
d
i
n
ated
ch
ar
g
in
g
o
p
er
atio
n
s
ac
r
o
s
s
m
u
ltip
le
UAVs
ac
tin
g
as
ae
r
ial
b
ase
s
tatio
n
s
,
ac
h
iev
in
g
a
9
.
1
%
r
ed
u
ctio
n
in
en
er
g
y
u
s
ag
e.
Priy
a
a
n
d
Mo
h
an
r
aj
[
3
7
]
e
x
p
lo
r
e
d
UAV
u
tili
za
tio
n
in
VANE
T
s
,
in
tr
o
d
u
cin
g
t
h
e
r
eso
u
r
ce
an
d
en
er
g
y
b
alan
ci
n
g
(
R
AE
B
)
m
eth
o
d
to
en
h
a
n
ce
ef
f
icien
cy
t
h
r
o
u
g
h
lo
ad
b
alan
cin
g
,
e
n
er
g
y
o
p
tim
izatio
n
,
a
n
d
im
p
r
o
v
ed
p
ac
k
et
d
eliv
e
r
y
r
atio
.
He
et
a
l.
[
3
8
]
p
r
o
p
o
s
ed
an
ap
p
r
o
ac
h
f
o
r
en
h
an
cin
g
FANE
T
ef
f
icien
cy
th
r
o
u
g
h
en
e
r
g
y
-
ef
f
icien
t
clu
s
ter
i
n
g
an
d
f
u
zz
y
-
b
ased
p
ath
s
elec
tio
n
,
aim
in
g
to
r
ed
u
ce
en
er
g
y
u
s
ag
e,
ex
te
n
d
clu
s
ter
life
s
p
an
,
an
d
im
p
r
o
v
e
p
a
ck
et
tr
an
s
m
is
s
io
n
.
Gr
ass
o
et
a
l.
[
3
9
]
in
t
r
o
d
u
ce
d
m
u
lti
-
a
g
en
t
in
t
r
a
-
FANE
T
(
MA
NI
A
-
F)
,
a
m
u
lti
-
ag
en
t
d
ee
p
r
ein
f
o
r
ce
m
en
t
lear
n
in
g
f
r
am
ewo
r
k
f
o
r
h
o
r
iz
o
n
tal
o
f
f
lo
ad
in
g
am
o
n
g
FANE
T
UAVs
as
s
h
o
wn
in
Fig
u
r
e
8
,
d
em
o
n
s
tr
atin
g
s
u
p
er
io
r
p
er
f
o
r
m
an
ce
i
n
s
im
u
latio
n
ex
p
e
r
im
en
ts
co
m
p
ar
e
d
to
o
t
h
er
m
o
b
ile
ed
g
e
co
m
p
u
tin
g
f
r
am
ewo
r
k
s
.
Yan
g
et
a
l.
[
4
0
]
p
r
o
p
o
s
ed
a
m
eta
-
h
eu
r
is
tic
o
p
tim
izatio
n
m
o
d
el
f
o
r
f
lig
h
t
p
at
h
p
lan
n
in
g
in
FANE
T
s
,
en
h
an
cin
g
d
ev
ice
-
to
-
d
e
v
ice
th
r
o
u
g
h
p
u
t a
n
d
co
n
tr
ib
u
tin
g
to
m
o
r
e
ef
f
icien
t c
o
m
m
u
n
icatio
n
s
y
s
tem
s
.
Fig
u
r
e
7
.
T
h
e
s
tr
u
ctu
r
e
o
f
th
e
h
eter
o
g
en
e
o
u
s
clo
u
d
-
m
u
lti
-
UAV
Fig
u
r
e
8
.
T
r
af
f
ic
p
r
o
b
lem
o
p
ti
m
izatio
n
I
n
s
tu
d
y
[
4
1
]
,
Attu
n
ed
s
licin
g
-
d
ep
en
d
en
t
co
n
c
u
r
r
en
t
r
eso
u
r
ce
allo
ca
tio
n
(
AS
-
C
R
A)
en
h
a
n
ce
s
UAV
s
er
v
ice
r
eliab
ilit
y
in
6
G
-
NI
B
ar
ch
itectu
r
e
th
r
o
u
g
h
lear
n
i
n
g
-
b
ased
s
licin
g
an
d
r
eso
u
r
ce
allo
ca
tio
n
,
im
p
r
o
v
in
g
ca
p
ac
ity
,
laten
cy
,
r
eso
u
r
ce
u
tili
za
tio
n
,
r
esp
o
n
s
e
r
atio
,
an
d
b
l
o
ck
in
g
r
ate.
J
ailto
n
et
a
l.
[
4
2
]
u
tili
ze
s
m
u
lti
-
ag
en
t
r
ein
f
o
r
ce
m
e
n
t
lear
n
in
g
(
MA
R
L
)
f
o
r
co
o
r
d
in
atin
g
h
eter
o
g
en
eo
u
s
r
eso
u
r
ce
s
,
r
ed
u
ci
n
g
task
tim
e.
T
o
n
g
et
a
l.
[
4
3
]
ap
p
lies
r
ein
f
o
r
ce
m
e
n
t
le
ar
n
in
g
(
R
L
)
with
d
o
u
b
le
d
ee
p
Q
-
lear
n
in
g
(
DDQN
)
f
o
r
ce
n
tr
al
p
r
o
ce
s
s
in
g
u
n
it
(
C
PU)
allo
ca
tio
n
in
v
ir
tu
al
f
u
n
ctio
n
v
ir
tu
aliza
tio
n
,
o
p
t
im
izin
g
UAV
d
e
p
lo
y
m
e
n
t
v
ia
in
teg
er
lin
ea
r
p
r
o
g
r
a
m
m
in
g
(
I
L
P)
.
Pas
an
d
id
eh
et
a
l.
[
4
4
]
i
n
tr
o
d
u
ce
s
MPR
d
ee
p
f
o
r
d
y
n
a
m
ic
r
eso
u
r
ce
all
o
ca
tio
n
in
FANE
T
s
,
r
ed
u
cin
g
e
n
er
g
y
co
n
s
u
m
p
tio
n
.
Ma
n
o
g
ar
a
n
et
a
l.
[
4
5
]
ex
p
lo
r
es
d
u
al
-
b
ased
iter
ativ
e
s
ea
r
ch
alg
o
r
ith
m
(
DI
SA
)
an
d
s
eq
u
en
tial
ex
h
au
s
ted
allo
ca
tio
n
alg
o
r
ith
m
(
SEAA
)
alg
o
r
ith
m
s
f
o
r
s
lo
t
an
d
p
o
wer
al
lo
ca
tio
n
,
en
h
a
n
cin
g
n
etwo
r
k
ca
p
ac
ity
an
d
f
air
n
es
s
.
R
o
v
ir
a
-
Su
g
r
an
es
et
a
l.
[
4
6
]
p
r
o
p
o
s
es
lo
n
g
s
h
o
r
t
ter
m
m
em
o
r
y
(
L
STM
)
f
o
r
b
an
d
wid
th
ef
f
icie
n
cy
in
C
-
V2
X
with
UAV
s
,
p
r
o
m
is
in
g
im
p
r
o
v
ed
air
s
licin
g
f
o
r
v
eh
icu
lar
co
m
m
u
n
icatio
n
.
I
n
s
tu
d
y
[
4
7
]
,
a
m
ath
em
atica
l
f
r
a
m
ewo
r
k
o
p
tim
izes
v
i
r
tu
al
f
u
n
ctio
n
s
(
VF)
allo
ca
tio
n
f
o
r
ed
g
e
s
er
v
ice
c
h
ain
in
g
,
co
n
s
id
er
in
g
UAV
ca
p
ab
ilit
ie
s
,
b
atter
y
co
n
s
tr
ain
ts
,
an
d
l
aten
cy
r
eq
u
i
r
em
en
ts
,
in
teg
r
a
tin
g
with
n
etwo
r
k
f
u
n
ctio
n
v
ir
tu
aliza
tio
n
o
r
ch
e
s
tr
ato
r
s
(
NFVO
)
s
tan
d
ar
d
s
.
L
iu
et
a
l.
[
4
8
]
o
p
tim
izes
U
AV
p
o
s
itio
n
in
g
v
ia
g
en
etic
alg
o
r
ith
m
s
to
m
ax
im
ize
FANE
T
th
r
o
u
g
h
p
u
t
in
d
is
aster
s
ce
n
ar
io
s
.
Saee
d
et
a
l.
[
4
9
]
in
tr
o
d
u
ce
s
r
ein
f
o
r
ce
m
e
n
t
lear
n
in
g
Han
d
o
f
f
(
R
L
H)
to
m
in
im
ize
h
an
d
o
f
f
s
in
UAV
n
etwo
r
k
s
,
ac
h
iev
in
g
a
7
5
%
r
ed
u
cti
o
n
.
Gallu
cc
io
et
a
l.
[
5
0
]
u
tili
ze
f
ly
in
g
ca
ch
es
o
n
UAVs
f
o
r
L
T
E
-
U
s
y
s
tem
s
,
o
u
t
p
er
f
o
r
m
in
g
Q
-
lear
n
i
n
g
in
co
n
v
er
g
en
ce
an
d
p
e
r
f
o
r
m
an
ce
.
L
i
et
a
l.
[
5
1
]
in
tr
o
d
u
ce
s
Q
-
le
ar
n
in
g
-
b
ased
s
m
ar
t
clu
s
ter
in
g
r
o
u
tin
g
m
eth
o
d
(
QSC
R
)
,
a
Q
-
lear
n
in
g
-
b
ased
clu
s
ter
in
g
r
o
u
tin
g
alg
o
r
ith
m
f
o
r
FANE
T
s
.
I
t
en
h
a
n
ce
s
en
er
g
y
ef
f
icien
c
y
an
d
n
etw
o
r
k
lo
n
g
ev
ity
wh
ile
in
cr
ea
s
in
g
en
d
-
to
-
e
n
d
d
elay
an
d
c
o
m
m
u
n
icatio
n
o
v
er
h
ea
d
s
lig
h
tly
c
o
m
p
ar
e
d
to
an
i
n
tellig
en
t
clu
s
ter
in
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
E
xp
lo
r
in
g
o
p
tima
l res
o
u
r
ce
a
llo
ca
tio
n
meth
o
d
s
fo
r
imp
r
o
ve
d
efficien
cy
in
…
(
Zein
a
b
E
.
A
h
med
)
6439
r
o
u
tin
g
ap
p
r
o
ac
h
(
I
C
R
A
)
.
Au
th
o
r
s
also
ex
p
lo
r
ed
UAV
s
war
m
f
lig
h
t
p
ath
s
f
o
r
r
ec
o
n
n
aiss
an
ce
m
is
s
io
n
s
,
ad
d
r
ess
in
g
p
o
wer
co
n
s
tr
ain
ts
an
d
p
r
o
p
ag
atio
n
m
o
d
els
with
a
h
eu
r
is
tic
alg
o
r
ith
m
b
ased
o
n
m
o
d
if
ied
r
ap
id
l
y
-
ex
p
lo
r
in
g
r
an
d
o
m
tr
ee
(
RRT
)
.
B
ay
er
lein
et
a
l.
[
5
2
]
p
r
esen
ted
a
r
ein
f
o
r
ce
m
e
n
t
lear
n
i
n
g
a
p
p
r
o
ac
h
o
p
tim
izin
g
UAV
tr
ajec
to
r
y
f
o
r
m
u
ltip
le
u
s
er
s
,
f
o
cu
s
in
g
o
n
m
ax
im
izin
g
tr
an
s
m
is
s
io
n
r
ates
u
s
in
g
Q
-
lear
n
in
g
.
R
en
et
a
l
.
[
5
3
]
in
tr
o
d
u
ce
d
K
-
m
ea
n
s
o
n
l
in
e
lear
n
in
g
r
o
u
tin
g
p
r
o
to
co
l
(
KM
OR
P)
,
a
K
-
m
ea
n
s
o
n
lin
e
lear
n
in
g
r
o
u
tin
g
p
r
o
to
co
l
f
o
r
UAV
ad
h
o
c
n
etwo
r
k
s
,
im
p
r
o
v
in
g
lo
ad
b
al
an
cin
g
a
n
d
p
ac
k
et
d
eliv
er
y
r
atio
with
d
y
n
am
ic
clu
s
ter
in
g
.
Ad
d
itio
n
ally
,
Xu
et
a
l.
[
5
4
]
en
h
a
n
ce
d
th
e
o
p
ti
m
ized
lin
k
s
tate
r
o
u
tin
g
(
OL
SR
)
p
r
o
to
co
l
in
to
S
-
OL
SR
with
f
u
zz
y
lo
g
ic
f
o
r
n
o
d
e
tr
u
s
t
ass
ess
m
en
t
an
d
i
m
p
r
o
v
e
d
m
u
ltip
o
in
t
r
ela
y
s
(
MPR
)
n
o
d
e
s
elec
tio
n
.
Ho
s
s
ein
za
d
eh
et
a
l.
[
5
5
]
p
r
o
p
o
s
ed
a
Q
-
lear
n
in
g
-
b
ased
r
o
u
ti
n
g
s
ch
em
e
u
s
in
g
an
in
tellig
en
t
f
ilter
in
g
alg
o
r
ith
m
(
QR
F
)
,
a
Q
-
lear
n
in
g
-
b
ased
r
o
u
tin
g
s
ch
em
e
o
p
tim
izin
g
n
etw
o
r
k
p
er
f
o
r
m
an
ce
,
en
er
g
y
d
is
tr
ib
u
tio
n
,
an
d
r
o
u
tin
g
d
elay
.
W
an
g
et
a
l.
[
5
6
]
e
x
p
lo
r
ed
UAV
in
te
g
r
atio
n
with
m
o
b
ile
ed
g
e
co
m
p
u
tin
g
(
ME
C
)
s
er
v
er
s
u
s
in
g
d
ee
p
d
eter
m
in
is
tic
p
o
licy
g
r
ad
ien
t
(
DDPG)
f
o
r
o
p
tim
al
o
f
f
l
o
ad
in
g
an
d
r
eso
u
r
ce
allo
ca
tio
n
.
Z
h
an
g
et
a
l.
[
5
7
]
p
r
esen
ted
th
e
jo
in
t
p
r
e
d
ictio
n
an
d
en
tr
o
p
y
(
J
PE
)
p
r
o
to
co
l
f
o
r
FANE
T
s
,
u
s
in
g
L
STM
to
p
r
ed
ict
UAV
m
o
b
ilit
y
an
d
en
h
a
n
cin
g
p
ac
k
et
d
eliv
er
y
r
atio
.
L
astl
y
,
Nah
i
et
a
l.
[
5
8
]
in
tr
o
d
u
ce
d
R
L
-
m
u
ltid
im
en
s
i
o
n
al
p
er
ce
p
tio
n
an
d
en
er
g
y
awa
r
en
ess
o
p
tim
ized
lin
k
s
tate
r
o
u
tin
g
(
R
L
-
MPE
AOL
SR
)
,
wh
ich
m
in
im
izes
m
e
s
s
ag
e
o
v
er
h
ea
d
an
d
co
n
tr
o
l f
l
o
o
d
in
g
in
FANE
T
s
,
o
u
tp
er
f
o
r
m
in
g
ex
is
tin
g
p
r
o
to
c
o
ls
in
v
ar
io
u
s
m
etr
ics,
as sh
o
w
n
in
Fig
u
r
e
9
.
Fig
u
r
e
9
.
Ad
a
p
tiv
e
co
m
m
u
n
ic
atio
n
-
b
ased
UAV
s
war
m
r
o
u
tin
g
alg
o
r
ith
m
5.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
In
th
is
s
ec
tio
n
,
we
ex
p
lo
r
e
v
ar
io
u
s
o
p
tim
izatio
n
s
tr
ateg
ies
aim
ed
at
en
h
an
cin
g
FANE
T
s
b
y
f
o
cu
s
in
g
o
n
en
er
g
y
co
n
s
u
m
p
tio
n
,
Qo
S,
an
d
r
o
u
tin
g
p
r
o
to
co
ls
.
W
e
ex
am
in
e
en
er
g
y
-
ef
f
icien
t
t
ec
h
n
iq
u
es
s
u
ch
as
ad
ap
tiv
e
r
o
u
tin
g
a
n
d
e
n
er
g
y
h
ar
v
esti
n
g
,
Q
o
S
im
p
r
o
v
em
en
ts
th
r
o
u
g
h
o
p
tim
ized
d
ata
tr
an
s
m
is
s
io
n
an
d
b
an
d
wid
th
allo
ca
tio
n
,
an
d
ad
v
an
ce
d
r
o
u
tin
g
p
r
o
to
c
o
ls
f
o
r
r
eliab
le
an
d
ef
f
icien
t
d
ata
d
eliv
e
r
y
.
T
h
ese
s
tr
ateg
ies
co
llectiv
ely
h
ig
h
lig
h
t
th
eir
p
o
t
en
tial
to
s
ig
n
if
ican
tly
b
o
o
s
t
th
e
p
er
f
o
r
m
an
ce
an
d
ef
f
icien
c
y
o
f
FANE
T
s
ac
r
o
s
s
d
iv
er
s
e
o
p
er
atio
n
al
s
ce
n
ar
io
s
.
T
h
e
an
aly
s
is
u
n
d
er
s
co
r
es
th
e
cr
itical
im
p
ac
t
o
f
th
ese
o
p
tim
izatio
n
s
o
n
ac
h
iev
in
g
m
o
r
e
s
u
s
tain
ab
le
an
d
ef
f
ec
tiv
e
FANE
T
o
p
er
atio
n
s
.
5
.
1
.
E
nerg
y
c
o
ns
um
ptio
n
R
esear
ch
er
s
h
av
e
ex
p
l
o
r
ed
v
ar
io
u
s
o
p
tim
izatio
n
s
tr
ateg
ies
to
r
ed
u
ce
en
er
g
y
co
n
s
u
m
p
ti
o
n
with
in
FANE
T
s
,
as
s
u
m
m
ar
ized
in
T
ab
le
1
.
On
e
ap
p
r
o
ac
h
in
v
o
l
v
ed
u
s
in
g
DR
L
to
o
p
tim
ize
UAV
m
o
v
em
en
t
an
d
m
o
b
ile
u
n
it
(
MU
)
ass
o
ciatio
n
,
r
esu
ltin
g
in
a
clo
s
ed
-
f
o
r
m
s
o
l
u
tio
n
f
o
r
MU
tr
an
s
m
it
p
o
wer
[
5
9
]
.
An
o
th
er
s
tu
d
y
in
tr
o
d
u
ce
d
a
d
ec
e
n
tr
alize
d
DR
L
-
b
ased
s
y
s
tem
t
o
c
o
n
tr
o
l
m
u
l
tip
le
UAVs
ac
tin
g
as m
o
b
ile
b
ase
s
tatio
n
s
(
B
Ss
)
,
en
s
u
r
in
g
co
n
tin
u
o
u
s
co
m
m
u
n
icatio
n
co
v
er
a
g
e
f
o
r
g
r
o
u
n
d
m
o
b
ile
u
s
er
s
.
Op
tim
izatio
n
aim
ed
to
r
ed
u
ce
e
n
er
g
y
co
n
s
u
m
p
tio
n
in
a
UAV
-
ass
is
t
ed
M
-
I
o
T
n
etwo
r
k
u
s
in
g
n
o
n
-
o
r
th
o
g
o
n
al
m
u
ltip
le
ac
ce
s
s
(
NOM
A)
b
y
jo
in
tly
p
o
wer
co
n
tr
o
l,
o
f
f
lo
a
d
in
g
r
ati
o
,
r
eso
u
r
ce
allo
ca
tio
n
,
an
d
UAV
tr
ajec
to
r
y
[
6
0
]
.
Mo
th
f
lam
e
o
p
tim
izatio
n
-
b
ased
clu
s
ter
in
g
alg
o
r
ith
m
s
wer
e
p
r
o
p
o
s
ed
as
a
n
en
er
g
y
-
e
f
f
icie
n
t
s
tr
ateg
y
f
o
r
n
etwo
r
k
co
n
s
tr
u
ctio
n
an
d
n
o
d
e
d
ep
lo
y
m
e
n
t
in
s
ce
n
ar
io
s
wh
er
e
s
tatic
an
d
d
y
n
am
ic
r
o
u
tin
g
ap
p
r
o
ac
h
es
wer
e
in
ef
f
ec
tiv
e.
T
h
e
C
L
E
A
-
AODV
r
o
u
tin
g
p
r
o
to
c
o
l
was
s
u
g
g
ested
to
im
p
r
o
v
e
FANE
T
p
er
f
o
r
m
an
ce
[
4
4
]
.
L
y
ap
u
n
o
v
o
p
tim
i
za
tio
n
d
ev
elo
p
e
d
an
o
p
tim
al
s
o
lu
tio
n
f
o
r
n
etwo
r
k
ass
o
ciatio
n
in
m
u
lti
-
UAV
s
y
s
tem
s
s
u
p
p
o
r
ted
b
y
h
eter
o
g
en
e
o
u
s
clo
u
d
s
.
Fin
ally
,
Yan
g
et
a
l
.
[
6
1
]
in
tr
o
d
u
ce
d
a
f
u
zz
y
c
-
m
ea
n
s
clu
s
ter
in
g
-
b
ased
alg
o
r
ith
m
to
m
in
im
ize
to
tal
p
o
wer
co
n
s
u
m
p
tio
n
in
a
ME
C
n
etwo
r
k
with
m
u
ltip
le
UAVs.
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.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
4
3
3
-
6
4
4
4
6440
T
ab
le
1
.
Op
tim
izatio
n
tech
n
iq
u
es f
o
r
en
e
r
g
y
c
o
n
s
u
m
p
tio
n
i
m
p
r
o
v
e
m
en
t in
FANE
T
Ref
O
p
t
i
mi
z
a
t
i
o
n
me
t
h
o
d
s
R
e
s
u
l
t
[
2
4
]
D
e
e
p
r
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
I
n
t
e
r
ms
o
f
M
U
c
o
v
e
r
a
g
e
r
a
t
e
,
s
y
st
e
m
l
a
t
e
n
c
y
,
a
n
d
sy
s
t
e
m
e
n
e
r
g
y
c
o
n
s
u
m
p
t
i
o
n
,
t
h
e
a
l
g
o
r
i
t
h
m
e
x
c
e
e
d
s
e
a
r
l
i
e
r
b
e
n
c
h
m
a
r
k
a
l
g
o
r
i
t
h
ms
i
n
si
m
u
l
a
t
i
o
n
s
.
[
3
0
]
D
e
e
p
r
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
Th
e
r
e
s
u
l
t
s
p
r
o
v
e
d
o
u
r
mo
d
e
l
's s
u
p
e
r
i
o
r
i
t
y
i
n
t
e
r
ms
o
f
e
n
e
r
g
y
e
f
f
i
c
i
e
n
c
y
w
h
e
n
c
o
mp
a
r
e
d
t
o
t
h
e
c
u
t
t
i
n
g
-
e
d
g
e
D
R
L
-
EC
3
a
p
p
r
o
a
c
h
b
a
s
e
d
o
n
D
D
P
G
a
n
d
t
h
r
e
e
a
d
d
i
t
i
o
n
a
l
b
a
s
e
l
i
n
e
s.
[
3
1
]
N
O
M
A
-
b
a
s
e
d
M
EC
mo
d
e
l
f
o
r
t
h
e
U
A
V
-
a
ss
i
st
e
d
marit
i
me
I
o
T
sy
s
t
e
m
O
n
a
v
e
r
a
g
e
,
N
O
M
A
r
e
d
u
c
e
s
i
t
s t
o
t
a
l
e
n
e
r
g
y
u
se
b
y
1
7
.
6
%.
Th
e
se
f
i
n
d
i
n
g
s
d
e
m
o
n
st
r
a
t
e
t
h
a
t
t
h
e
N
O
M
A
i
s
a
n
e
f
f
i
c
i
e
n
t
m
u
l
t
i
p
l
e
a
c
c
e
ss
st
r
a
t
e
g
y
t
h
a
t
c
a
n
b
e
a
p
p
l
i
e
d
t
o
t
h
e
M
-
I
o
T
M
E
C
s
y
st
e
m
u
si
n
g
U
A
V
s.
[
3
2
]
A
n
i
t
e
r
a
t
i
v
e
a
l
g
o
r
i
t
h
m
(AFU)
W
h
e
n
c
o
m
p
a
r
e
d
t
o
L
o
c
a
l
,
F
i
x
U
,
a
n
d
G
u
a
n
g
x
i
U
n
i
v
e
r
si
t
y
(
G
G
U
)
,
A
F
U
r
e
d
u
c
e
s
o
v
e
r
a
l
l
e
n
e
r
g
y
u
sa
g
e
b
y
6
0
.
5
2
%
a
n
d
4
1
.
5
6
%
,
r
e
s
p
e
c
t
i
v
e
l
y
.
M
o
t
h
f
l
a
me
o
p
t
i
mi
z
a
t
i
o
n
Zo
n
e
r
o
u
t
i
n
g
t
e
c
h
n
i
q
u
e
,
a
c
c
o
r
d
i
n
g
t
o
si
mu
l
a
t
i
o
n
r
e
s
u
l
t
s,
h
a
s
k
e
p
t
c
o
mm
u
n
i
c
a
t
i
o
n
r
o
u
t
e
s
se
c
u
r
e
a
n
d
p
r
o
m
i
ses
i
n
c
r
e
a
se
d
s
e
c
u
r
i
t
y
w
i
t
h
o
u
t
i
n
c
u
r
r
i
n
g
c
o
mp
u
t
a
t
i
o
n
a
l
e
x
p
e
n
s
e
s.
[
6
0
]
G
l
o
w
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
(GSO)
W
h
e
n
v
a
r
i
o
u
s
t
y
p
e
s
o
f
i
n
f
o
r
m
a
t
i
o
n
t
r
a
n
s
m
i
s
s
i
o
n
a
r
e
c
a
r
r
i
e
d
o
u
t
o
v
e
r
F
A
N
E
T
s
,
w
e
p
r
o
v
i
d
e
a
n
o
p
t
i
m
i
z
e
d
C
H
s
e
l
e
c
t
i
o
n
m
o
d
e
l
t
h
a
t
g
r
e
a
t
l
y
e
n
h
a
n
c
e
s
c
l
u
s
t
e
r
l
i
f
e
t
i
m
e
a
n
d
m
i
n
i
m
i
z
e
s
e
n
e
r
g
y
u
s
a
g
e
.
[
4
4
]
Ly
a
p
u
n
o
v
o
p
t
i
m
i
z
a
t
i
o
n
Th
e
p
r
o
p
o
s
e
d
g
a
t
e
w
a
y
se
l
e
c
t
i
o
n
t
e
c
h
n
i
q
u
e
u
s
e
d
l
e
ss e
n
e
r
g
y
t
h
a
n
e
x
i
s
t
i
n
g
sy
st
e
ms,
h
o
w
e
v
e
r
t
h
e
p
r
o
p
o
se
d
j
o
b
s
c
h
e
d
u
l
i
n
g
a
n
d
r
e
s
o
u
r
c
e
a
l
l
o
c
a
t
i
o
n
st
r
a
t
e
g
y
i
n
c
r
e
a
s
e
d
Q
o
S
p
e
r
f
o
r
man
c
e
a
n
d
o
b
t
a
i
n
e
d
t
h
e
b
e
st
so
l
u
t
i
o
n
a
f
t
e
r
o
n
l
y
a
f
e
w
i
t
e
r
a
t
i
v
e
r
o
u
n
d
s.
[
6
1
]
F
u
z
z
y
c
-
me
a
n
s
c
l
u
s
t
e
r
i
n
g
-
b
a
s
e
d
a
l
g
o
r
i
t
h
m
Th
e
p
r
o
p
o
s
e
d
a
l
g
o
r
i
t
h
m
o
u
t
p
e
r
f
o
r
ms
c
o
n
v
e
n
t
i
o
n
a
l
a
p
p
r
o
a
c
h
e
s,
a
c
c
o
r
d
i
n
g
t
o
n
u
m
e
r
i
c
a
l
r
e
s
u
l
t
s.
5
.
2
.
Q
ua
lit
y
o
f
s
er
v
ice
Nu
m
er
o
u
s
r
esear
ch
en
d
ea
v
o
r
s
h
av
e
f
o
cu
s
ed
o
n
o
p
tim
izin
g
tech
n
iq
u
es
to
en
h
a
n
ce
th
e
q
u
ality
o
f
s
er
v
ice
in
FANE
T
s
,
as
o
u
tlin
ed
in
T
ab
le
2
.
Gr
ass
o
et
a
l.
[
6
2
]
in
t
r
o
d
u
ce
d
MA
NI
A
-
F,
a
m
u
lti
-
ag
e
n
t
d
ee
p
r
ein
f
o
r
ce
m
e
n
t
lear
n
in
g
f
r
am
e
wo
r
k
f
o
r
m
an
ag
i
n
g
h
o
r
iz
o
n
tal
o
f
f
l
o
ad
in
g
am
o
n
g
FANE
T
UAVs.
L
i
et
a
l
.
[
6
3
]
p
r
o
p
o
s
ed
a
f
lig
h
t
p
ath
p
lan
n
in
g
m
o
d
el
b
ased
o
n
m
eta
-
h
eu
r
is
tic
o
p
tim
izatio
n
tech
n
iq
u
es
to
im
p
r
o
v
e
co
m
m
u
n
icatio
n
ef
f
icien
cy
i
n
FANE
T
s
ce
n
ar
io
s
[
6
4
]
.
AS
-
C
R
A
is
p
r
esen
ted
to
en
h
an
ce
s
er
v
ice
r
eliab
ilit
y
in
UAVs
w
ith
in
th
e
6
G
-
NI
B
ar
c
h
itectu
r
e
[
6
5
]
.
I
n
s
tu
d
y
[
6
6
]
,
MPR
d
ee
p
was
in
tr
o
d
u
ce
d
as
a
DR
L
ap
p
r
o
ac
h
f
o
r
UAV
p
o
s
itio
n
in
g
an
d
r
eso
u
r
ce
allo
ca
tio
n
in
FANE
T
s
d
ea
lin
g
with
d
y
n
a
m
ic
n
etw
o
r
k
co
n
d
itio
n
s
an
d
im
m
ed
iate
co
m
m
u
n
icatio
n
d
em
an
d
s
.
I
n
te
g
r
ate
d
o
u
b
le
d
e
ep
Q
-
lear
n
in
g
(
DDQN
)
,
r
ein
f
o
r
ce
m
en
t
lea
r
n
in
g
(
R
L
)
,
an
d
in
teg
er
lin
ea
r
p
r
o
g
r
am
m
in
g
(
I
L
P)
tech
n
iq
u
es
to
d
ep
lo
y
v
ir
tu
al
f
u
n
ctio
n
s
with
in
ac
tiv
e
UAVs
i
n
FANE
T
s
[
6
7
]
.
A
g
en
etic
alg
o
r
ith
m
was
u
tili
ze
d
in
[
6
8
]
t
o
o
p
tim
ize
UAV
p
o
s
itio
n
s
to
m
ax
im
ize
FANE
T
th
r
o
u
g
h
p
u
t.
Fin
ally
,
Saee
d
et
a
l.
[
6
9
]
in
tr
o
d
u
ce
d
R
L
H,
an
in
n
o
v
ativ
e
u
s
er
ass
o
ciatio
n
alg
o
r
ith
m
d
esig
n
ed
to
m
in
im
ize
r
ed
u
n
d
an
t
h
an
d
o
f
f
s
with
in
UAV
n
etwo
r
k
s
[
7
0
]
–
[
7
2
]
.
T
ab
le
2
.
Su
m
m
a
r
y
o
f
ar
ticles th
at
en
h
an
ce
th
e
q
u
ality
o
f
s
er
v
ice
in
FANE
T
Ref
O
p
t
i
mi
z
a
t
i
o
n
me
t
h
o
d
s
R
e
s
u
l
t
[
6
2
]
A
mu
l
t
i
-
a
g
e
n
t
d
e
e
p
r
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
f
r
a
mew
o
r
k
(
M
A
N
I
A
-
F)
Th
e
r
e
s
u
l
t
s s
h
o
w
t
h
a
t
t
h
e
p
r
o
p
o
s
e
d
f
r
a
mew
o
r
k
o
u
t
p
e
r
f
o
r
ms
o
t
h
e
r
st
a
t
e
-
of
-
t
h
e
-
a
r
t
mo
b
i
l
e
e
d
g
e
c
o
m
p
u
t
i
n
g
f
r
a
mew
o
r
k
s
.
[
6
3
]
B
a
t
a
l
g
o
r
i
t
h
m
a
n
d
g
e
n
e
r
a
l
i
z
e
d
r
e
g
r
e
ss
i
o
n
n
e
u
r
a
l
n
e
t
w
o
r
k
(
G
R
N
N
)
Th
e
si
m
u
l
a
t
i
o
n
f
i
n
d
i
n
g
s s
u
g
g
e
st
t
h
a
t
t
h
e
a
p
p
r
o
a
c
h
i
m
p
r
o
v
e
s
n
e
t
w
o
r
k
p
e
r
f
o
r
man
c
e
.
[
6
4
]
AS
-
CRA
Th
e
p
r
o
p
o
s
e
d
so
l
u
t
i
o
n
o
u
t
p
e
r
f
o
r
ms
t
h
e
c
o
m
p
e
t
i
t
i
o
n
i
n
t
e
r
ms
o
f
c
a
p
a
c
i
t
y
,
l
a
t
e
n
c
y
,
r
e
so
u
r
c
e
u
t
i
l
i
z
a
t
i
o
n
r
a
t
e
,
r
e
sp
o
n
se
r
a
t
i
o
,
a
n
d
b
l
o
c
k
i
n
g
r
a
t
e
,
w
i
t
h
m
e
t
r
i
c
s
o
f
8
9
.
7
2
6
%
,
8
1
.
3
2
%
,
0
.
9
6
3
%,
9
2
.
3
0
9
%
,
a
n
d
0
.
0
4
7
%,
r
e
s
p
e
c
t
i
v
e
l
y
.
[
6
5
]
M
A
R
L
Th
e
r
e
s
u
l
t
s s
h
o
w
t
h
a
t
t
h
e
p
r
o
p
o
s
e
d
t
e
c
h
n
i
q
u
e
i
n
c
r
e
a
se
s c
o
m
p
u
t
i
n
g
r
e
s
o
u
r
c
e
u
t
i
l
i
z
a
t
i
o
n
a
n
d
r
e
d
u
c
e
s
t
a
sk
e
x
e
c
u
t
i
o
n
t
i
m
e
si
g
n
i
f
i
c
a
n
t
l
y
.
[
6
6
]
D
I
S
A
a
n
d
S
EA
A
A
c
c
o
r
d
i
n
g
t
o
n
u
mer
i
c
a
l
c
a
l
c
u
l
a
t
i
o
n
s,
b
o
t
h
D
I
S
A
a
n
d
S
EA
A
c
a
n
e
f
f
i
c
i
e
n
t
l
y
a
l
l
o
c
a
t
e
r
e
so
u
r
c
e
s
f
o
r
U
A
V
s w
h
i
l
e
m
a
i
n
t
a
i
n
i
n
g
l
i
n
k
f
a
i
r
n
e
ss
a
n
d
p
r
i
o
r
i
t
y
.
[
6
7
]
LSTM
W
h
e
n
c
o
m
p
a
r
e
d
a
g
a
i
n
s
t
t
w
o
b
e
n
c
h
m
a
r
k
sc
h
e
m
e
s,
t
h
e
si
m
u
l
a
t
i
o
n
r
e
su
l
t
s
sh
o
w
t
h
a
t
t
h
e
p
r
o
p
o
s
e
d
sc
h
e
m
e
i
s
v
a
l
i
d
:
d
e
e
p
Q
-
n
e
t
w
o
r
k
a
n
d
d
e
e
p
p
o
l
i
c
y
g
r
a
d
i
e
n
t
.
[
6
8
]
M
P
R
d
e
e
p
M
P
R
d
e
e
p
c
o
n
v
e
r
g
e
s ra
p
i
d
l
y
a
n
d
h
a
s
st
r
o
n
g
g
e
n
e
r
a
l
i
z
a
t
i
o
n
a
b
i
l
i
t
y
u
n
d
e
r
d
y
n
a
m
i
c
n
e
t
w
o
r
k
c
o
n
d
i
t
i
o
n
s
a
n
d
u
s
e
r
l
o
c
a
t
i
o
n
s
,
a
c
c
o
r
d
i
n
g
t
o
t
h
e
r
e
su
l
t
s
.
[
6
9
]
R
LH
A
c
c
o
r
d
i
n
g
t
o
s
i
m
u
l
a
t
i
o
n
r
e
s
u
l
t
s,
t
h
e
R
LH
a
l
g
o
r
i
t
h
m
c
a
n
r
e
d
u
c
e
t
h
e
n
u
m
b
e
r
o
f
h
a
n
d
o
f
f
s
b
y
7
5
%
.
5
.
3
.
Ro
uting
pro
t
o
co
ls
a
nd
f
lig
ht
t
ra
j
ec
t
o
ry
Sev
er
al
o
p
tim
izatio
n
tech
n
iq
u
es
h
av
e
b
ee
n
ap
p
lie
d
to
im
p
r
o
v
e
r
o
u
tin
g
p
r
o
to
c
o
ls
an
d
f
lig
h
t
tr
ajec
to
r
ies
in
FANE
T
s
,
a
s
o
u
tlin
ed
in
T
ab
le
3
.
I
n
s
tu
d
y
[
7
3
]
,
th
e
p
e
r
f
o
r
m
an
ce
o
f
th
r
ee
n
atu
r
e
-
in
s
p
ir
e
d
alg
o
r
ith
m
s
(
NI
A)
f
o
r
FANE
T
r
o
u
tin
g
s
p
ec
if
ically
a
n
t
co
l
o
n
y
o
p
tim
izatio
n
(
AC
O)
,
m
o
d
if
ie
d
Fire
f
ly
alg
o
r
ith
m
(
MFA)
,
an
d
m
o
d
if
ied
g
e
n
etic
alg
o
r
ith
m
(
MG
A)
was
as
s
es
s
ed
u
s
in
g
m
etr
ics
s
u
ch
as
p
ac
k
et
d
eliv
er
y
,
d
elay
,
o
v
er
h
ea
d
,
an
d
th
r
o
u
g
h
p
u
t
[
7
4
]
.
T
o
a
d
d
r
ess
FANE
T
ch
allen
g
es,
Ho
s
s
ein
za
d
eh
et
a
l.
[
7
5
]
in
tr
o
d
u
ce
d
ASR
-
FANE
T
,
an
ad
ap
tiv
e
s
o
f
twar
e
-
d
ef
in
ed
n
etwo
r
k
in
g
(
SDN)
-
b
ased
r
o
u
tin
g
f
r
a
m
ewo
r
k
f
o
r
FANE
T
.
An
o
th
e
r
ap
p
r
o
ac
h
,
p
r
esen
ted
b
y
Z
h
en
g
et
a
l.
[
7
6
]
,
u
tili
ze
d
R
L
to
p
r
e
d
ict
n
o
d
e
p
o
s
itio
n
s
,
co
n
tr
o
l
c
o
m
m
u
n
icatio
n
,
a
n
d
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
E
xp
lo
r
in
g
o
p
tima
l res
o
u
r
ce
a
llo
ca
tio
n
meth
o
d
s
fo
r
imp
r
o
ve
d
efficien
cy
in
…
(
Zein
a
b
E
.
A
h
med
)
6441
m
an
ag
e
d
ata
tr
a
n
s
m
is
s
io
n
wit
h
in
th
e
n
etwo
r
k
.
FANE
T
r
o
u
t
in
g
alg
o
r
ith
m
b
ased
o
n
f
u
zz
y
lo
g
ic
an
d
R
L
was
in
tr
o
d
u
ce
d
in
a
s
ep
ar
ate
p
ap
er
[
7
7
]
,
aim
in
g
to
m
itig
ate
lim
itatio
n
s
o
f
tr
ad
itio
n
al
AC
O
m
eth
o
d
s
,
s
u
ch
as
h
ig
h
av
er
ag
e
h
o
p
s
an
d
lo
w
lin
k
co
n
n
ec
tiv
ity
.
L
astl
y
,
Hu
an
g
et
a
l.
[
7
8
]
p
r
o
p
o
s
ed
an
ad
a
p
tiv
e
c
o
m
m
u
n
icatio
n
-
b
ased
r
o
u
tin
g
al
g
o
r
ith
m
ex
p
licitly
d
e
s
ig
n
ed
f
o
r
UAV
s
war
m
s
.
T
ab
le
3
.
Su
m
m
a
r
y
o
f
ar
ticles th
at
en
h
an
ce
th
e
r
o
u
tin
g
p
r
o
to
c
o
ls
an
d
f
lig
h
t tr
ajec
to
r
y
in
FANE
T
Ref
O
p
t
i
mi
z
a
t
i
o
n
me
t
h
o
d
s
R
e
s
u
l
t
[
1
2
]
A
C
O
,
M
F
A
,
a
n
d
M
G
A
M
F
A
s
u
r
p
a
s
ses
t
h
e
o
t
h
e
r
t
w
o
me
t
h
o
d
s,
ma
k
i
n
g
i
t
t
h
e
m
o
s
t
e
f
f
i
c
i
e
n
t
r
o
u
t
i
n
g
a
l
g
o
r
i
t
h
m
i
n
F
A
N
ET,
a
c
c
o
r
d
i
n
g
t
o
t
h
e
r
e
p
o
r
t
.
[
1
9
]
A
n
a
d
a
p
t
i
v
e
S
D
N
-
b
a
se
d
r
o
u
t
i
n
g
f
r
a
mew
o
r
k
f
o
r
F
A
N
E
T
(ASR
-
F
A
N
ET)
Th
e
st
u
d
y
u
s
e
s c
o
m
p
r
e
h
e
n
si
v
e
si
m
u
l
a
t
i
o
n
s
t
o
e
v
a
l
u
a
t
e
t
h
e
p
e
r
f
o
r
ma
n
c
e
o
f
t
h
e
A
S
R
-
F
A
N
ET
f
r
a
mew
o
r
k
a
n
d
d
i
sc
o
v
e
r
s t
h
a
t
i
t
o
u
t
p
e
r
f
o
r
ms
o
t
h
e
r
st
a
n
d
a
r
d
p
r
o
t
o
c
o
l
s
.
[
2
0
]
R
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
A
c
c
o
r
d
i
n
g
t
o
t
h
e
s
i
m
u
l
a
t
i
o
n
r
e
s
u
l
t
s,
t
h
e
p
r
o
p
o
s
e
d
a
l
g
o
r
i
t
h
m
o
u
t
p
e
r
f
o
r
ms
p
o
l
i
c
y
i
n
t
e
r
ms
o
f
c
h
o
o
s
i
n
g
t
h
e
r
o
u
t
e
w
i
t
h
t
h
e
h
i
g
h
e
s
t
v
a
l
u
e
f
u
n
c
t
i
o
n
a
n
d
t
h
e
s
h
o
r
t
e
s
t
e
n
d
-
to
-
e
n
d
d
e
l
a
y
.
[
6
4
]
F
u
z
z
y
l
o
g
i
c
a
n
d
r
e
i
n
f
o
r
c
e
me
n
t
l
e
a
r
n
i
n
g
I
n
t
e
r
ms
o
f
p
e
r
f
o
r
ma
n
c
e
,
si
m
u
l
a
t
i
o
n
f
i
n
d
i
n
g
s
i
n
d
i
c
a
t
e
t
h
a
t
t
h
e
p
r
o
p
o
se
d
a
l
g
o
r
i
t
h
m
o
u
t
p
e
r
f
o
r
ms
t
r
a
d
i
t
i
o
n
a
l
r
o
u
t
i
n
g
a
l
g
o
r
i
t
h
ms.
[
6
5
]
M
u
l
t
i
l
a
y
e
r
p
e
r
c
e
p
t
r
o
n
a
l
g
o
r
i
t
h
m
Th
e
r
e
s
u
l
t
s s
h
o
w
t
h
a
t
o
u
r
a
l
g
o
r
i
t
h
ms
c
a
n
a
c
h
i
e
v
e
e
f
f
i
c
i
e
n
t
a
n
d
e
f
f
e
c
t
i
v
e
r
o
u
t
i
n
g
f
o
r
l
a
r
g
e
-
sca
l
e
U
A
V
sw
a
r
m
c
o
l
l
a
b
o
r
a
t
i
o
n
i
n
a
p
a
r
t
l
y
o
b
ser
v
a
b
l
e
d
i
s
t
r
i
b
u
t
e
d
e
n
v
i
r
o
n
m
e
n
t
.
[
6
6
]
K
-
me
a
n
s
a
l
g
o
r
i
t
h
m
a
n
d
g
e
n
e
t
i
c
a
l
g
o
r
i
t
h
m
Th
e
si
m
u
l
a
t
i
o
n
f
i
n
d
i
n
g
s
d
e
mo
n
st
r
a
t
e
t
h
a
t
t
h
e
p
r
o
p
o
s
e
d
sc
h
e
m
e
i
s s
u
c
c
e
ssf
u
l
a
n
d
o
u
t
p
e
r
f
o
r
ms
t
h
e
b
e
n
c
h
m
a
r
k
s
.
[
6
7
]
D
e
e
p
r
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
Th
e
su
g
g
e
s
t
e
d
a
l
g
o
r
i
t
h
m
i
s s
h
o
w
n
t
o
b
e
e
f
f
i
c
i
e
n
t
i
n
s
i
mu
l
a
t
i
o
n
s.
[
6
8
]
R
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
Th
e
r
e
s
u
l
t
s
d
e
m
o
n
st
r
a
t
e
t
h
a
t
t
h
e
p
r
o
p
o
sa
l
w
o
r
k
s
t
o
i
m
p
r
o
v
e
n
e
t
w
o
r
k
p
e
r
f
o
r
man
c
e
.
6.
CO
NCLU
SI
O
N
T
h
is
p
ap
er
e
x
p
lo
r
ed
o
p
tim
al
an
d
in
tellig
e
n
t
r
eso
u
r
ce
allo
ca
tio
n
in
FANE
T
s
.
UAVs,
co
m
m
o
n
ly
k
n
o
wn
as
d
r
o
n
es,
a
r
e
wid
ely
d
ep
lo
y
e
d
in
m
ilit
ar
y
an
d
ci
v
ilian
ap
p
licatio
n
s
,
r
e
q
u
ir
in
g
ef
f
ec
tiv
e
co
o
r
d
in
atio
n
an
d
co
m
m
u
n
icatio
n
to
ad
d
r
ess
ch
allen
g
es.
FANE
T
s
en
ab
le
wir
eless
co
m
m
u
n
icatio
n
am
o
n
g
UAVs,
im
p
r
o
v
in
g
c
o
o
r
d
in
atio
n
an
d
in
f
o
r
m
atio
n
ex
c
h
an
g
e
in
e
n
v
ir
o
n
m
en
ts
with
o
u
t
tr
ad
itio
n
al
n
etwo
r
k
s
.
T
h
e
d
y
n
am
ic
m
o
b
ilit
y
o
f
UAVs
in
tr
o
d
u
ce
s
u
n
iq
u
e
co
n
s
id
e
r
atio
n
s
f
o
r
n
etwo
r
k
d
esig
n
an
d
co
n
n
ec
tiv
ity
,
d
is
tin
g
u
is
h
in
g
FANE
T
s
f
r
o
m
co
n
v
e
n
tio
n
al
a
d
-
h
o
c
n
etw
o
r
k
s
.
T
h
is
s
u
r
v
ey
r
e
v
iews
v
ar
io
u
s
o
p
tim
izatio
n
tech
n
iq
u
es,
in
clu
d
i
n
g
g
e
n
etic
alg
o
r
ith
m
s
,
an
t
co
lo
n
y
o
p
tim
izatio
n
,
an
d
ar
tific
ial
n
e
u
r
a
l
n
etwo
r
k
s
,
wh
ich
o
p
tim
ize
r
eso
u
r
ce
allo
ca
tio
n
b
y
co
n
s
id
er
in
g
m
is
s
io
n
r
eq
u
ir
e
m
en
ts
,
n
etwo
r
k
to
p
o
lo
g
y
,
an
d
en
er
g
y
c
o
n
s
tr
ain
ts
.
I
t
also
d
is
cu
s
s
es
th
e
cr
itical
r
o
le
o
f
in
tellig
en
t
al
g
o
r
ith
m
s
i
n
en
h
a
n
cin
g
n
etwo
r
k
e
n
er
g
y
m
an
ag
em
en
t,
Qo
S,
r
eso
u
r
ce
allo
ca
tio
n
,
a
n
d
o
v
er
a
ll
p
er
f
o
r
m
a
n
ce
.
T
h
e
s
y
s
tem
atic
liter
atu
r
e
r
ev
iew
ca
teg
o
r
izes
r
eso
u
r
ce
allo
ca
tio
n
s
tr
ateg
ies
b
ased
o
n
p
er
f
o
r
m
a
n
ce
o
p
tim
izatio
n
cr
iter
ia
an
d
s
u
m
m
ar
izes
th
eir
s
tr
en
g
th
s
,
wea
k
n
ess
es,
an
d
ap
p
licatio
n
s
.
T
h
is
s
u
r
v
ey
h
ig
h
lig
h
ts
th
e
p
o
ten
tial
o
f
FANE
T
s
to
r
ev
o
lu
tio
n
ize
v
ar
io
u
s
in
d
u
s
tr
ies
an
d
u
n
lo
c
k
n
ew
o
p
p
o
r
tu
n
ities
f
o
r
UAV
-
b
ased
ap
p
licatio
n
s
.
ACK
NO
WL
E
DG
E
M
E
NT
T
h
is
wo
r
k
is
s
u
p
p
o
r
ted
b
y
th
e
Min
is
tr
y
o
f
Hig
h
er
E
d
u
ca
tio
n
(
MO
HE
)
Fu
n
d
am
en
tal
R
esear
ch
Gr
an
t
Sch
em
e
(
FR
GS2
2
-
264
-
0
8
7
3
)
(
Gr
an
t N
o
: FR
GS/1
/2
0
2
2
/I
C
T
1
1
/UI
AM
/0
1
/1
)
.
RE
F
E
R
E
NC
E
S
[
1
]
M
.
K
.
B
a
n
a
f
a
a
e
t
a
l
.
,
“
A
c
o
m
p
r
e
h
e
n
si
v
e
s
u
r
v
e
y
o
n
5
G
-
a
n
d
-
b
e
y
o
n
d
n
e
t
w
o
r
k
s
w
i
t
h
U
A
V
s:
a
p
p
l
i
c
a
t
i
o
n
s
,
e
mer
g
i
n
g
t
e
c
h
n
o
l
o
g
i
e
s
,
r
e
g
u
l
a
t
o
r
y
a
sp
e
c
t
s,
r
e
sea
r
c
h
t
r
e
n
d
s
a
n
d
c
h
a
l
l
e
n
g
e
s
,
”
I
E
EE
A
c
c
e
ss
,
v
o
l
.
1
2
,
p
p
.
7
7
8
6
–
7
8
2
6
,
2
0
2
4
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
2
3
.
3
3
4
9
2
0
8
.
[
2
]
M
.
Y
.
A
r
a
f
a
t
a
n
d
S
.
M
o
h
,
“
R
o
u
t
i
n
g
p
r
o
t
o
c
o
l
s
f
o
r
u
n
m
a
n
n
e
d
a
e
r
i
a
l
v
e
h
i
c
l
e
n
e
t
w
o
r
k
s
:
a
s
u
r
v
e
y
,
”
I
EEE
Ac
c
e
ss
,
v
o
l
.
7
,
p
p
.
9
9
6
9
4
–
9
9
7
2
0
,
2
0
1
9
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
1
9
.
2
9
3
0
8
1
3
.
[
3
]
A
.
C
h
r
i
k
i
,
H
.
To
u
a
t
i
,
H
.
S
n
o
u
ssi
,
a
n
d
F
.
K
a
m
o
u
n
,
“
F
A
N
ET
:
c
o
mm
u
n
i
c
a
t
i
o
n
,
mo
b
i
l
i
t
y
m
o
d
e
l
s
a
n
d
se
c
u
r
i
t
y
i
s
su
e
s
,
”
C
o
m
p
u
t
e
r
N
e
t
w
o
rks
,
v
o
l
.
1
6
3
,
2
0
1
9
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
c
o
m
n
e
t
.
2
0
1
9
.
1
0
6
8
7
7
.
[
4
]
M
.
M
.
S
a
e
e
d
e
t
a
l
.
,
“
T
a
s
k
r
e
v
e
r
s
e
o
f
f
l
o
a
d
i
n
g
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
m
u
l
t
i
-
a
c
c
e
ss
e
d
g
e
c
o
m
p
u
t
i
n
g
,
”
i
n
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
9
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
t
e
r
a
n
d
C
o
m
m
u
n
i
c
a
t
i
o
n
En
g
i
n
e
e
ri
n
g
,
I
C
C
C
E
2
0
2
3
,
2
0
2
3
,
p
p
.
3
2
2
–
3
2
7
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
C
C
E
5
8
8
5
4
.
2
0
2
3
.
1
0
2
4
6
0
8
1
.
[
5
]
I
.
B
e
k
m
e
z
c
i
,
O
.
K
.
S
a
h
i
n
g
o
z
,
a
n
d
Ş
.
Te
m
e
l
,
“
F
l
y
i
n
g
a
d
-
h
o
c
n
e
t
w
o
r
k
s
(
F
A
N
ETs)
:
a
s
u
r
v
e
y
,
”
A
d
H
o
c
N
e
t
w
o
r
k
s
,
v
o
l
.
1
1
,
n
o
.
3
,
p
p
.
1
2
5
4
–
1
2
7
0
,
2
0
1
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
a
d
h
o
c
.
2
0
1
2
.
1
2
.
0
0
4
.
[
6
]
B
.
L
i
,
Z.
F
e
i
,
a
n
d
Y
.
Z
h
a
n
g
,
“
U
A
V
c
o
mm
u
n
i
c
a
t
i
o
n
s
f
o
r
5
G
a
n
d
b
e
y
o
n
d
:
r
e
c
e
n
t
a
d
v
a
n
c
e
s
a
n
d
f
u
t
u
r
e
t
r
e
n
d
s
,
”
I
EEE
I
n
t
e
r
n
e
t
o
f
T
h
i
n
g
s
J
o
u
rn
a
l
,
v
o
l
.
6
,
n
o
.
2
,
p
p
.
2
2
4
1
–
2
2
6
3
,
2
0
1
9
,
d
o
i
:
1
0
.
1
1
0
9
/
JI
O
T.
2
0
1
8
.
2
8
8
7
0
8
6
.
[
7
]
Y
.
Ze
n
g
,
R
.
Zh
a
n
g
,
a
n
d
T
.
J.
L
i
m,
“
W
i
r
e
l
e
ss c
o
mm
u
n
i
c
a
t
i
o
n
s wi
t
h
u
n
ma
n
n
e
d
a
e
r
i
a
l
v
e
h
i
c
l
e
s:
o
p
p
o
r
t
u
n
i
t
i
e
s
a
n
d
c
h
a
l
l
e
n
g
e
s
,
”
I
EE
E
C
o
m
m
u
n
i
c
a
t
i
o
n
s
M
a
g
a
zi
n
e
,
v
o
l
.
5
4
,
n
o
.
5
,
p
p
.
3
6
–
4
2
,
2
0
1
6
,
d
o
i
:
1
0
.
1
1
0
9
/
M
C
O
M
.
2
0
1
6
.
7
4
7
0
9
3
3
.
[
8
]
I
.
B
e
k
mez
c
i
,
I
.
S
e
n
,
a
n
d
E.
Er
k
a
l
k
a
n
,
“
F
l
y
i
n
g
a
d
-
h
o
c
n
e
t
w
o
r
k
s
(
F
A
N
ET
)
t
e
s
t
b
e
d
i
m
p
l
e
m
e
n
t
a
t
i
o
n
,
”
i
n
2
0
1
5
7
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
c
o
n
f
e
re
n
c
e
o
n
rec
e
n
t
a
d
v
a
n
c
e
s
i
n
s
p
a
c
e
t
e
c
h
n
o
l
o
g
i
e
s
(
RA
S
T
)
,
2
0
1
5
,
p
p
.
6
6
5
–
6
6
8
,
d
o
i
:
1
0
.
1
1
0
9
/
R
A
S
T.
2
0
1
5
.
7
2
0
8
4
2
6
.
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.
14
,
No
.
6
,
Dec
em
b
e
r
20
24
:
6
4
3
3
-
6
4
4
4
6442
[
9
]
D
.
K
a
p
i
l
a
,
N
.
U
l
l
o
a
,
S
.
A
n
i
t
a
,
R
.
S
.
S
u
b
r
a
ma
n
i
a
n
,
P
.
K
a
n
d
e
w
a
r
,
a
n
d
P
.
S
u
j
a
t
h
a
,
“
A
p
p
l
i
c
a
t
i
o
n
s
o
f
d
r
o
n
e
s
i
n
p
r
e
d
i
c
t
i
v
e
a
n
a
l
y
t
i
c
s,”
Pre
d
i
c
t
i
v
e
An
a
l
y
t
i
c
s
i
n
S
m
a
r
t
A
g
r
i
c
u
l
t
u
re
,
p
p
.
2
5
0
–
2
7
4
,
2
0
2
3
,
d
o
i
:
1
0
.
1
2
0
1
/
9
7
8
1
0
0
3
3
9
1
3
0
2
-
1
4
.
[
1
0
]
A
.
P
u
r
o
h
i
t
,
F
.
M
o
k
a
y
a
,
a
n
d
P
.
Z
h
a
n
g
,
“
C
o
l
l
a
b
o
r
a
t
i
v
e
i
n
d
o
o
r
s
e
n
s
i
n
g
w
i
t
h
t
h
e
S
e
n
s
o
r
F
l
y
a
e
r
i
a
l
s
e
n
s
o
r
n
e
t
w
o
r
k
,
”
i
n
I
P
S
N
’
1
2
-
Pro
c
e
e
d
i
n
g
s
o
f
t
h
e
1
1
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
I
n
f
o
rm
a
t
i
o
n
Pro
c
e
ssi
n
g
i
n
S
e
n
so
r
N
e
t
w
o
rks
,
2
0
1
2
,
p
p
.
1
4
5
–
1
4
6
,
d
o
i
:
1
0
.
1
1
4
5
/
2
1
8
5
6
7
7
.
2
1
8
5
7
2
0
.
[
1
1
]
M
.
F
.
K
h
a
n
,
K
.
L.
A
.
Y
a
u
,
R
.
M
.
N
o
o
r
,
a
n
d
M
.
A
.
I
mr
a
n
,
“
R
o
u
t
i
n
g
s
c
h
e
mes
i
n
F
A
N
ETs
:
a
s
u
r
v
e
y
,
”
S
e
n
s
o
rs
(
S
w
i
t
z
e
rl
a
n
d
)
,
v
o
l
.
2
0
,
n
o
.
1
,
2
0
2
0
,
d
o
i
:
1
0
.
3
3
9
0
/
s2
0
0
1
0
0
3
8
.
[
1
2
]
A
.
R
i
b
e
i
r
o
,
“
O
p
t
i
ma
l
r
e
s
o
u
r
c
e
a
l
l
o
c
a
t
i
o
n
i
n
w
i
r
e
l
e
ss
c
o
mm
u
n
i
c
a
t
i
o
n
a
n
d
n
e
t
w
o
r
k
i
n
g
,
”
EU
RA
S
I
P
J
o
u
r
n
a
l
o
n
Wi
r
e
l
e
s
s
C
o
m
m
u
n
i
c
a
t
i
o
n
s
a
n
d
N
e
t
w
o
r
k
i
n
g
,
v
o
l
.
2
0
1
2
,
n
o
.
1
,
2
0
1
2
,
d
o
i
:
1
0
.
1
1
8
6
/
1
6
8
7
-
1
4
9
9
-
2
0
1
2
-
2
7
2
.
[
1
3
]
Z.
W
a
n
g
,
M
.
Ei
s
e
n
,
a
n
d
A
.
R
i
b
e
i
r
o
,
“
Le
a
r
n
i
n
g
d
e
c
e
n
t
r
a
l
i
z
e
d
w
i
r
e
l
e
ss
r
e
s
o
u
r
c
e
a
l
l
o
c
a
t
i
o
n
s
w
i
t
h
g
r
a
p
h
n
e
u
r
a
l
n
e
t
w
o
r
k
s,”
I
E
EE
T
ra
n
s
a
c
t
i
o
n
s
o
n
S
i
g
n
a
l
Pr
o
c
e
ssi
n
g
,
v
o
l
.
7
0
,
p
p
.
1
8
5
0
–
1
8
6
3
,
2
0
2
2
,
d
o
i
:
1
0
.
1
1
0
9
/
TSP
.
2
0
2
2
.
3
1
6
3
6
2
6
.
[
1
4
]
X
.
F
e
r
n
a
n
d
o
,
A
.
S
u
l
t
a
n
a
,
S
.
H
u
ss
a
i
n
,
a
n
d
L
.
Z
h
a
o
,
“
Ta
x
o
n
o
my
f
o
r
t
h
e
r
e
so
u
r
c
e
a
l
l
o
c
a
t
i
o
n
i
n
C
R
N
s,
”
C
o
o
p
e
ra
t
i
v
e
S
p
e
c
t
ru
m
S
e
n
si
n
g
a
n
d
Re
s
o
u
r
c
e
Al
l
o
c
a
t
i
o
n
S
t
r
a
t
e
g
i
e
s
i
n
C
o
g
n
i
t
i
v
e
Ra
d
i
o
N
e
t
w
o
r
k
s
,
p
p
.
4
1
–
5
8
,
2
0
1
9
,
d
o
i
:
1
0
.
1
0
0
7
/
9
7
8
-
3
-
3
1
9
-
7
3
9
5
7
-
1
_
3
.
[
1
5
]
X
.
G
u
a
n
a
n
d
Y
.
M
a
,
“
W
i
r
e
l
e
ss
n
e
t
w
o
r
k
v
i
r
t
u
a
l
i
z
a
t
i
o
n
r
e
s
o
u
r
c
e
s
h
a
r
i
n
g
c
o
n
s
i
d
e
r
i
n
g
d
y
n
a
m
i
c
r
e
so
u
r
c
e
a
l
l
o
c
a
t
i
o
n
a
l
g
o
r
i
t
h
m,
”
Ad
v
a
n
c
e
s i
n
Mu
l
t
i
m
e
d
i
a
,
v
o
l
.
2
0
2
2
,
2
0
2
2
,
d
o
i
:
1
0
.
1
1
5
5
/
2
0
2
2
/
7
3
3
8
3
0
9
.
[
1
6
]
Z.
E.
A
h
me
d
,
A
.
A
.
H
a
sh
i
m,
R
.
A
.
S
a
e
e
d
,
a
n
d
M
.
M
.
S
a
e
e
d
,
“
Ti
n
y
M
L
n
e
t
w
o
r
k
a
p
p
l
i
c
a
t
i
o
n
s
f
o
r
smar
t
c
i
t
i
e
s
,
”
T
i
n
y
ML
f
o
r
E
d
g
e
I
n
t
e
l
l
i
g
e
n
c
e
i
n
I
o
T
a
n
d
L
P
WA
N
N
e
t
w
o
rks
,
p
p
.
4
2
3
–
4
5
1
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
B
9
7
8
-
0
-
44
-
3
2
2
2
0
2
-
3
.
0
0
0
2
3
-
3.
[
1
7
]
Z.
G
u
o
,
Y
.
W
a
n
g
,
Y
.
S
u
n
,
J
.
Li
,
C
.
F
u
,
a
n
d
J
.
Z
h
o
n
g
,
“
R
e
s
i
l
i
e
n
c
e
a
n
a
l
y
si
s
o
f
c
o
o
p
e
r
a
t
i
v
e
mi
ss
i
o
n
b
a
se
d
o
n
s
p
a
t
i
o
–
t
e
mp
o
r
a
l
n
e
t
w
o
r
k
d
y
n
a
mi
c
s
f
o
r
f
l
y
i
n
g
a
d
h
o
c
n
e
t
w
o
r
k
,
”
I
EE
E
T
ra
n
s
a
c
t
i
o
n
s
o
n
R
e
l
i
a
b
i
l
i
t
y
,
v
o
l
.
7
3
,
n
o
.
2
,
p
p
.
1
0
3
4
–
1
0
4
3
,
2
0
2
4
,
d
o
i
:
1
0
.
1
1
0
9
/
T
R
.
2
0
2
3
.
3
3
4
4
7
2
6
.
[
1
8
]
T
.
L
i
u
,
G
.
B
a
i
,
J
.
T
a
o
,
Y
.
A
.
Z
h
a
n
g
,
a
n
d
Y
.
F
a
n
g
,
“
A
m
u
l
t
i
s
t
a
t
e
n
e
t
w
o
r
k
a
p
p
r
o
a
c
h
f
o
r
r
e
s
i
l
i
e
n
c
e
a
n
a
l
y
s
i
s
o
f
U
A
V
s
w
a
r
m
c
o
n
s
i
d
e
r
i
n
g
i
n
f
o
r
m
a
t
i
o
n
e
x
c
h
a
n
g
e
c
a
p
a
c
i
t
y
,
”
R
e
l
i
a
b
i
l
i
t
y
E
n
g
i
n
e
e
r
i
n
g
a
n
d
S
y
s
t
e
m
S
a
f
e
t
y
,
v
o
l
.
2
4
1
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
r
e
s
s
.
2
0
2
3
.
1
0
9
6
0
6
.
[
1
9
]
A
.
P
h
a
d
k
e
a
n
d
F
.
A
.
M
e
d
r
a
n
o
,
“
I
n
c
r
e
a
si
n
g
o
p
e
r
a
t
i
o
n
a
l
r
e
s
i
l
i
e
n
c
y
o
f
U
A
V
sw
a
r
ms:
a
n
a
g
e
n
t
-
f
o
c
u
se
d
s
e
a
r
c
h
a
n
d
r
e
sc
u
e
f
r
a
mew
o
r
k
,
”
Ae
r
o
s
p
a
c
e
Re
s
e
a
r
c
h
C
o
m
m
u
n
i
c
a
t
i
o
n
s
,
v
o
l
.
1
,
2
0
2
4
,
d
o
i
:
1
0
.
3
3
8
9
/
a
r
c
.
2
0
2
3
.
1
2
4
2
0
.
[
2
0
]
S
.
H
u
sse
i
n
,
A
.
Th
a
si
n
,
A
.
S
a
m
i
,
a
n
d
A
.
S
.
B
a
n
u
,
“
S
e
c
u
r
e
A
I
-
b
a
se
d
f
l
y
i
n
g
a
d
-
h
o
c
n
e
t
w
o
r
k
s
:
t
r
u
st
e
d
c
o
mm
u
n
i
c
a
t
i
o
n
,
”
i
n
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
I
n
n
o
v
a
t
i
v
e
C
o
m
p
u
t
i
n
g
a
n
d
C
o
m
m
u
n
i
c
a
t
i
o
n
s:
Pro
c
e
e
d
i
n
g
s
o
f
I
C
I
C
C
2
0
2
2
,
2
0
2
2
,
p
p
.
5
2
1
–
5
2
8
.
[
2
1
]
U
.
H
a
i
d
e
r
,
H
.
S
h
o
u
k
a
t
,
M
.
Y
.
A
y
u
b
,
M
.
T
.
A
.
T
a
sh
f
e
e
n
,
T
.
K
.
B
h
a
t
i
a
,
a
n
d
I
.
U
.
K
h
a
n
,
“
C
y
b
e
r
a
t
t
a
c
k
d
e
t
e
c
t
i
o
n
a
n
a
l
y
s
i
s
u
s
i
n
g
mac
h
i
n
e
l
e
a
r
n
i
n
g
f
o
r
I
o
T
-
b
a
s
e
d
U
A
V
n
e
t
w
o
r
k
,
”
C
y
b
e
r
S
e
c
u
r
i
t
y
f
o
r
N
e
x
t
-
G
e
n
e
ra
t
i
o
n
C
o
m
p
u
t
i
n
g
T
e
c
h
n
o
l
o
g
i
e
s
,
p
p
.
2
5
3
–
2
6
4
,
2
0
2
4
,
d
o
i
:
1
0
.
1
2
0
1
/
9
7
8
1
0
0
3
4
0
4
3
6
1
-
1
3
.
[
2
2
]
H
.
A
l
q
a
h
t
a
n
i
a
n
d
G
.
K
u
mar,
“
M
a
c
h
i
n
e
l
e
a
r
n
i
n
g
f
o
r
e
n
h
a
n
c
i
n
g
t
r
a
n
s
p
o
r
t
a
t
i
o
n
se
c
u
r
i
t
y
:
a
c
o
m
p
r
e
h
e
n
s
i
v
e
a
n
a
l
y
s
i
s
o
f
e
l
e
c
t
r
i
c
a
n
d
f
l
y
i
n
g
v
e
h
i
c
l
e
s
y
st
e
ms,
”
E
n
g
i
n
e
e
r
i
n
g
Ap
p
l
i
c
a
t
i
o
n
s
o
f
Ar
t
i
f
i
c
i
a
l
I
n
t
e
l
l
i
g
e
n
c
e
,
v
o
l
.
1
2
9
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
n
g
a
p
p
a
i
.
2
0
2
3
.
1
0
7
6
6
7
.
[
2
3
]
S
.
B
h
a
r
a
n
y
,
S
.
S
h
a
r
ma,
S
.
B
h
a
t
i
a
,
M
.
K
.
I
.
R
a
h
ma
n
i
,
M
.
S
h
u
a
i
b
,
a
n
d
S
.
A
.
La
sh
a
r
i
,
“
E
n
e
r
g
y
e
f
f
i
c
i
e
n
t
c
l
u
s
t
e
r
i
n
g
p
r
o
t
o
c
o
l
f
o
r
F
A
N
ETS u
s
i
n
g
m
o
t
h
f
l
a
m
e
o
p
t
i
mi
z
a
t
i
o
n
,
”
S
u
st
a
i
n
a
b
i
l
i
t
y
(
S
w
i
t
zer
l
a
n
d
)
,
v
o
l
.
1
4
,
n
o
.
1
0
,
2
0
2
2
,
d
o
i
:
1
0
.
3
3
9
0
/
s
u
1
4
1
0
6
1
5
9
.
[
2
4
]
P
.
T
h
a
n
t
h
a
r
a
t
e
,
A
.
T
h
a
n
t
h
a
r
a
t
e
,
a
n
d
A
.
K
u
l
k
a
r
n
i
,
“
G
R
E
E
N
S
K
Y
:
a
f
a
i
r
e
n
e
r
g
y
-
a
w
a
r
e
o
p
t
i
m
i
z
a
t
i
o
n
m
o
d
e
l
f
o
r
U
A
V
s
i
n
n
e
x
t
-
g
e
n
e
r
a
t
i
o
n
w
i
r
e
l
e
s
s
n
e
t
w
o
r
k
s
,
”
G
r
e
e
n
E
n
e
r
g
y
a
n
d
I
n
t
e
l
l
i
g
e
n
t
T
r
a
n
s
p
o
r
t
a
t
i
o
n
,
v
o
l
.
3
,
n
o
.
1
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
g
e
i
t
s
.
2
0
2
3
.
1
0
0
1
3
0
.
[
2
5
]
L.
Zh
a
o
,
M
.
B
i
n
S
a
i
f
,
A
.
H
a
w
b
a
n
i
,
G
.
M
i
n
,
S
.
P
e
n
g
,
a
n
d
N
.
Li
n
,
“
A
n
o
v
e
l
i
m
p
r
o
v
e
d
a
r
t
i
f
i
c
i
a
l
b
e
e
c
o
l
o
n
y
a
n
d
b
l
o
c
k
c
h
a
i
n
-
b
a
s
e
d
sec
u
r
e
c
l
u
s
t
e
r
i
n
g
r
o
u
t
i
n
g
sc
h
e
m
e
f
o
r
F
A
N
ET,
”
C
h
i
n
a
C
o
m
m
u
n
i
c
a
t
i
o
n
s
,
v
o
l
.
1
8
,
n
o
.
7
,
p
p
.
1
0
3
–
1
1
6
,
2
0
2
1
,
d
o
i
:
1
0
.
2
3
9
1
9
/
JC
C
.
2
0
2
1
.
0
7
.
0
0
9
.
[
2
6
]
J.
J
.
Ló
p
e
z
Esc
o
b
a
r
,
M
.
R
i
c
a
r
d
o
,
R
.
C
a
m
p
o
s
,
F
.
G
i
l
-
C
a
s
t
i
ñ
e
i
r
a
,
a
n
d
R
.
P
.
D
í
a
z
R
e
d
o
n
d
o
,
“
R
e
s
o
u
r
c
e
a
l
l
o
c
a
t
i
o
n
f
o
r
d
a
t
a
f
l
o
w
a
p
p
l
i
c
a
t
i
o
n
s
i
n
F
A
N
ETs
u
si
n
g
a
n
y
p
a
t
h
r
o
u
t
i
n
g
,
”
I
n
t
e
r
n
e
t
o
f
T
h
i
n
g
s (N
e
t
h
e
r
l
a
n
d
s)
,
v
o
l
.
2
2
,
2
0
2
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
i
o
t
.
2
0
2
3
.
1
0
0
7
6
1
.
[
2
7
]
G
.
F
a
r
a
c
i
,
S
.
A
.
R
i
z
z
o
,
a
n
d
G
.
S
c
h
e
mb
r
a
,
“
G
r
e
e
n
e
d
g
e
i
n
t
e
l
l
i
g
e
n
c
e
f
o
r
smar
t
ma
n
a
g
e
m
e
n
t
o
f
a
F
A
N
ET
i
n
d
i
s
a
st
e
r
-
r
e
c
o
v
e
r
y
sce
n
a
r
i
o
s,
”
I
EE
E
T
r
a
n
s
a
c
t
i
o
n
s
o
n
Ve
h
i
c
u
l
a
r
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
7
2
,
n
o
.
3
,
p
p
.
3
8
1
9
–
3
8
3
1
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
TV
T.
2
0
2
2
.
3
2
1
7
3
3
1
.
[
2
8
]
J.
C
h
e
n
e
t
a
l
.
,
“
D
e
e
p
r
e
i
n
f
o
r
c
e
me
n
t
l
e
a
r
n
i
n
g
b
a
s
e
d
r
e
s
o
u
r
c
e
a
l
l
o
c
a
t
i
o
n
i
n
mu
l
t
i
-
UAV
-
a
i
d
e
d
M
E
C
n
e
t
w
o
r
k
s,”
I
EEE
T
r
a
n
s
a
c
t
i
o
n
s
o
n
C
o
m
m
u
n
i
c
a
t
i
o
n
s
,
v
o
l
.
7
1
,
n
o
.
1
,
p
p
.
2
9
6
–
3
0
9
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
T
C
O
M
M
.
2
0
2
2
.
3
2
2
6
1
9
3
.
[
2
9
]
J.
S
.
R
a
j
,
“
A
n
o
v
e
l
h
y
b
r
i
d
se
c
u
r
e
r
o
u
t
i
n
g
f
o
r
f
l
y
i
n
g
a
d
-
h
o
c
n
e
t
w
o
r
k
s
,
”
J
o
u
r
n
a
l
o
f
T
re
n
d
s
i
n
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
a
n
d
S
m
a
r
t
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
2
,
n
o
.
3
,
p
p
.
1
5
5
–
1
6
4
,
2
0
2
0
,
d
o
i
:
1
0
.
3
6
5
4
8
/
j
t
c
ss
t
.
2
0
2
0
.
3
.
0
0
5
.
[
3
0
]
L.
P
.
Q
i
a
n
,
H
.
Zh
a
n
g
,
Q
.
W
a
n
g
,
Y
.
W
u
,
a
n
d
B
.
L
i
n
,
“
J
o
i
n
t
m
u
l
t
i
-
d
o
ma
i
n
r
e
so
u
r
c
e
a
l
l
o
c
a
t
i
o
n
a
n
d
t
r
a
j
e
c
t
o
r
y
o
p
t
i
mi
z
a
t
i
o
n
i
n
U
A
V
-
a
ssi
s
t
e
d
mari
t
i
m
e
I
o
T
n
e
t
w
o
r
k
s,”
I
EEE
I
n
t
e
rn
e
t
o
f
T
h
i
n
g
s
J
o
u
r
n
a
l
,
v
o
l
.
1
0
,
n
o
.
1
,
p
p
.
5
3
9
–
5
5
2
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
JI
O
T.
2
0
2
2
.
3
2
0
1
0
1
7
.
[
3
1
]
W
.
Y
o
u
,
C
.
D
o
n
g
,
Q
.
W
u
,
Y
.
Q
u
,
Y
.
W
u
,
a
n
d
R
.
H
e
,
“
Jo
i
n
t
t
a
sk
sc
h
e
d
u
l
i
n
g
,
r
e
s
o
u
r
c
e
a
l
l
o
c
a
t
i
o
n
,
a
n
d
U
A
V
t
r
a
j
e
c
t
o
r
y
u
n
d
e
r
c
l
u
st
e
r
i
n
g
f
o
r
F
A
N
ETs
,
”
C
h
i
n
a
C
o
m
m
u
n
i
c
a
t
i
o
n
s
,
v
o
l
.
1
9
,
n
o
.
1
,
p
p
.
1
0
4
–
1
1
8
,
2
0
2
2
,
d
o
i
:
1
0
.
2
3
9
1
9
/
J
C
C
.
2
0
2
2
.
0
1
.
0
0
9
.
[
3
2
]
M
.
N
a
m
d
e
v
,
S
.
G
o
y
a
l
,
a
n
d
R
.
A
g
a
r
w
a
l
,
“
A
met
h
o
d
f
o
r
i
m
p
r
o
v
i
n
g
e
f
f
i
c
i
e
n
c
y
a
n
d
se
c
u
r
i
t
y
o
f
F
A
N
ET
u
s
i
n
g
c
h
a
o
t
i
c
b
l
a
c
k
h
o
l
e
o
p
t
i
m
i
z
a
t
i
o
n
-
b
a
se
d
r
o
u
t
i
n
g
(
B
H
O
R
)
t
e
c
h
n
i
q
u
e
,
”
L
e
c
t
u
r
e
N
o
t
e
s
i
n
E
l
e
c
t
ri
c
a
l
En
g
i
n
e
e
r
i
n
g
,
v
o
l
.
9
0
7
,
p
p
.
1
5
–
2
7
,
2
0
2
2
,
d
o
i
:
1
0
.
1
0
0
7
/
9
7
8
-
981
-
19
-
4
6
8
7
-
5
_
2
.
[
3
3
]
H
.
S
.
M
a
n
s
o
u
r
e
t
a
l
.
,
“
C
r
o
ss
-
l
a
y
e
r
a
n
d
e
n
e
r
g
y
-
a
w
a
r
e
A
O
D
V
r
o
u
t
i
n
g
p
r
o
t
o
c
o
l
f
o
r
f
l
y
i
n
g
a
d
-
h
o
c
n
e
t
w
o
r
k
s
,
”
S
u
st
a
i
n
a
b
i
l
i
t
y
(
S
w
i
t
zer
l
a
n
d
)
,
v
o
l
.
1
4
,
n
o
.
1
5
,
2
0
2
2
,
d
o
i
:
1
0
.
3
3
9
0
/
su
1
4
1
5
8
9
8
0
.
[
3
4
]
R
.
D
u
a
n
,
J.
W
a
n
g
,
C
.
Ji
a
n
g
,
Y
.
R
e
n
,
a
n
d
L
.
H
a
n
z
o
,
“
Th
e
t
r
a
n
smi
t
-
e
n
e
r
g
y
v
s
c
o
m
p
u
t
a
t
i
o
n
-
d
e
l
a
y
t
r
a
d
e
-
o
f
f
i
n
g
a
t
e
w
a
y
-
s
e
l
e
c
t
i
o
n
f
o
r
h
e
t
e
r
o
g
e
n
o
u
s c
l
o
u
d
a
i
d
e
d
m
u
l
t
i
-
U
A
V
sy
st
e
ms,
”
I
EEE
T
r
a
n
sa
c
t
i
o
n
s
o
n
C
o
m
m
u
n
i
c
a
t
i
o
n
s
,
v
o
l
.
6
7
,
n
o
.
4
,
p
p
.
3
0
2
6
–
3
0
3
9
,
2
0
1
9
,
d
o
i
:
1
0
.
1
1
0
9
/
T
C
O
M
M
.
2
0
1
8
.
2
8
8
9
6
7
2
.
[
3
5
]
C
.
H
.
Li
u
,
X
.
M
a
,
X
.
G
a
o
,
a
n
d
J.
Ta
n
g
,
“
D
i
s
t
r
i
b
u
t
e
d
e
n
e
r
g
y
-
e
f
f
i
c
i
e
n
t
mu
l
t
i
-
U
A
V
n
a
v
i
g
a
t
i
o
n
f
o
r
l
o
n
g
-
t
e
r
m
c
o
mm
u
n
i
c
a
t
i
o
n
c
o
v
e
r
a
g
e
b
y
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
EE
E
T
r
a
n
sa
c
t
i
o
n
s
o
n
M
o
b
i
l
e
C
o
m
p
u
t
i
n
g
,
v
o
l
.
1
9
,
n
o
.
6
,
p
p
.
1
2
7
4
–
1
2
8
5
,
2
0
2
0
,
d
o
i
:
1
0
.
1
1
0
9
/
T
M
C
.
2
0
1
9
.
2
9
0
8
1
7
1
.
[
3
6
]
N
.
A
.
M
o
h
a
mm
e
d
,
S
.
M
.
M
.
A
l
mu
t
o
k
i
,
R
.
M
a
n
s
o
o
r
,
A
.
K
.
J
a
b
e
r
,
B
.
A
.
H
.
K
.
A
l
G
h
z
a
w
i
,
a
n
d
A
.
H
.
A
l
s
a
l
a
m
y
,
“
R
e
so
u
r
c
e
a
l
l
o
c
a
t
i
o
n
w
i
t
h
e
n
e
r
g
y
b
a
l
a
n
c
i
n
g
f
o
r
u
a
v
s
a
ssi
s
t
e
d
v
a
n
e
t
s
b
a
s
e
d
i
n
t
e
l
l
i
g
e
n
t
t
r
a
n
s
p
o
r
t
a
t
i
o
n
sy
s
t
e
m
,
”
Al
-
S
a
d
i
q
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
m
u
n
i
c
a
t
i
o
n
a
n
d
I
n
f
o
rm
a
t
i
o
n
T
e
c
h
n
o
l
o
g
y
,
p
p
.
2
8
2
–
2
8
7
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
A
I
C
C
I
T5
7
6
1
4
.
2
0
2
3
.
1
0
2
1
7
9
4
6
.
[
3
7
]
S
.
S
.
P
r
i
y
a
a
n
d
M
.
M
o
h
a
n
r
a
j
,
“
A
n
e
n
e
r
g
y
-
e
f
f
i
c
i
e
n
t
c
l
u
s
t
e
r
i
n
g
a
n
d
f
u
z
z
y
-
b
a
se
d
p
a
t
h
se
l
e
c
t
i
o
n
f
o
r
f
l
y
i
n
g
a
d
-
h
o
c
n
e
t
w
o
r
k
s,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
C
o
m
p
u
t
a
t
i
o
n
a
l
I
n
t
e
l
l
i
g
e
n
c
e
a
n
d
Ap
p
l
i
c
a
t
i
o
n
s
,
v
o
l
.
2
2
,
n
o
.
1
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
4
2
/
S
1
4
6
9
0
2
6
8
2
3
4
1
0
0
3
1
.
[
3
8
]
C
.
H
e
,
S
.
L
i
u
,
a
n
d
S
.
H
a
n
,
“
A
f
u
z
z
y
l
o
g
i
c
r
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
-
b
a
s
e
d
r
o
u
t
i
n
g
a
l
g
o
r
i
t
h
m
f
o
r
f
l
y
i
n
g
a
d
-
h
o
c
n
e
t
w
o
r
k
s,
”
i
n
2
0
2
0
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
t
i
n
g
,
N
e
t
w
o
rki
n
g
a
n
d
C
o
m
m
u
n
i
c
a
t
i
o
n
s,
I
C
N
C
2
0
2
0
,
2
0
2
0
,
p
p
.
9
8
7
–
9
9
1
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
N
C
4
7
7
5
7
.
2
0
2
0
.
9
0
4
9
7
0
5
.
[
3
9
]
C
.
G
r
a
ss
o
,
R
.
R
a
f
t
o
p
o
u
l
o
s
,
a
n
d
G
.
S
c
h
e
mb
r
a
,
“
M
u
l
t
i
-
a
g
e
n
t
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
f
l
y
i
n
g
a
d
-
h
o
c
n
e
t
w
o
r
k
s
f
o
r
d
e
l
a
y
-
c
o
n
st
r
a
i
n
e
d
a
p
p
l
i
c
a
t
i
o
n
s,
”
Pr
o
c
e
d
i
a
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
v
o
l
.
2
0
3
,
p
p
.
6
9
–
7
8
,
2
0
2
2
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
p
r
o
c
s
.
2
0
2
2
.
0
7
.
0
1
1
.
[
4
0
]
Z
.
Y
a
n
g
,
C
.
P
a
n
,
K
.
W
a
n
g
,
a
n
d
M
.
S
h
i
k
h
-
B
a
h
a
e
i
,
“
E
n
e
r
g
y
e
f
f
i
c
i
e
n
t
r
e
s
o
u
r
c
e
a
l
l
o
c
a
t
i
o
n
i
n
U
A
V
-
e
n
a
b
l
e
d
m
o
b
i
l
e
e
d
g
e
c
o
m
p
u
t
i
n
g
n
e
t
w
o
r
k
s
,
”
I
E
E
E
T
r
a
n
s
a
c
t
i
o
n
s
o
n
W
i
r
e
l
e
s
s
C
o
m
m
u
n
i
c
a
t
i
o
n
s
,
v
o
l
.
1
8
,
n
o
.
9
,
p
p
.
4
5
7
6
–
4
5
8
9
,
2
0
1
9
,
d
o
i
:
1
0
.
1
1
0
9
/
T
W
C
.
2
0
1
9
.
2
9
2
7
3
1
3
.
Evaluation Warning : The document was created with Spire.PDF for Python.