I
A
E
S
I
n
t
e
r
n
at
io
n
al
Jou
r
n
al
of
A
r
t
if
ic
ia
l
I
n
t
e
ll
ig
e
n
c
e
(
I
J
-
AI
)
V
ol
. 14, No. 5, O
c
to
be
r
2025
, pp.
4290
~
4298
I
S
S
N
:
2252
-
8938
,
D
O
I
:
10.11591/
ij
a
i.
v
14
.i
5
.pp
4290
-
4298
4290
Jou
r
n
al
h
om
e
page
:
ht
tp
:
//
ij
ai
.
ia
e
s
c
or
e
.c
om
An
al
gor
i
t
h
m
f
or
c
on
t
r
ol
l
i
n
g
t
h
e
t
r
an
sm
i
ss
i
o
n
of
vi
d
e
o
st
r
e
am
s
in
a
f
l
yi
n
g
ad
h
oc
n
e
t
w
or
k
S
al
ah
M
.
M
.
A
lg
h
az
al
i
1
,
Wi
s
am
K
.
M
ad
h
lo
om
A
lj
e
az
n
a
2
,
M
u
r
t
ad
h
a
N
.
R
as
ol
3
,
K
on
s
t
an
t
in
A
.
P
o
ls
h
c
h
yk
ov
4
,
R
od
io
n
V
.
L
ik
h
os
h
e
r
s
t
ov
4
1
D
e
pa
r
t
m
e
nt
of
C
om
put
e
r
S
c
i
e
nc
e
,
C
ol
l
e
ge
of
E
duc
a
t
i
on
f
or
G
i
r
l
s
,
U
ni
ve
r
s
i
t
y
of
K
uf
a
,
K
uf
a
,
I
r
a
q
2
C
ol
l
e
ge
of
C
ont
r
ol
a
nd
S
ys
t
e
m
E
ngi
ne
e
r
i
ng,
U
ni
ve
r
s
i
t
y
of
T
e
c
hnol
ogy,
B
a
ghda
d,
I
r
a
q
3
D
e
pa
r
t
m
e
nt
of
P
hys
i
c
s
S
c
i
e
nc
e
,
C
ol
l
e
g
e
of
S
c
i
e
nc
e
,
U
ni
ve
r
s
i
t
y
of
T
hi
-
Q
a
r
,
N
a
s
i
r
i
ya
h,
I
r
a
q
4
I
ns
t
i
t
ut
e
of
E
ngi
ne
e
r
i
ng
a
nd
D
i
gi
t
a
l
T
e
c
hnol
ogi
e
s
,
B
e
l
gor
od
S
t
a
t
e
U
ni
ve
r
s
i
t
y,
B
e
l
gor
od,
R
us
s
i
a
A
r
t
ic
le
I
n
f
o
A
B
S
T
R
A
C
T
A
r
ti
c
le
h
is
to
r
y
:
R
e
c
e
iv
e
d
J
ul
19, 2024
R
e
vi
s
e
d
J
un 17, 2025
A
c
c
e
pt
e
d
J
ul
10, 2025
This
article
discussing
the
enhancement
of
video
surveillance
in
various
territorie
s
through
the
implementation
of
a
flying
ad
hoc
netwo
rk
(FA
NET).
The
primary
objective
of
the
surveillance
is
for
search
and
rescue
oper
ations.
To
optimize
the
quality
of
FANET
video
broadcasting,
a
decision
-
making
algorit
hm
for
video
stream
manageme
nt
is
introduced
.
This
alg
orithm
evaluates
the
likelihood
of
achieving
high
-
quality
video
transm
ission.
Depending
on
the
assessed
probabilities,
the
algorit
hm
recommends
one
of
the
following
actions:
initiating
a
new
video
stream
transmission,
reducing
the
average
length
of
wireless
channels,
or
discontinuing
the
transmis
sion
of
low
-
information
video
streams.
Computationa
l
experiment
s
demons
trate
a
significant
improvement
in
the
accuracy
of
decision
-
making
reg
ardi
ng
the
manageme
nt
of
video
stream
transmission
to
FANET
when
utilizi
ng
the
proposed
algorit
hm.
K
e
y
w
o
r
d
s
:
D
e
c
is
io
n s
uppor
t
F
ly
in
g a
d hoc
ne
twor
k
V
id
e
o br
oa
dc
a
s
t
V
id
e
o m
oni
to
r
in
g of
t
e
r
r
i
to
r
ie
s
V
id
e
o s
tr
e
a
m
This
is
an
open
access
article
under
the
CC
BY
-
SA
license.
C
or
r
e
s
pon
di
n
g
A
u
th
or
:
S
a
la
h
M
.
M
.
A
lg
ha
z
a
li
D
e
pa
r
tm
e
nt
of
C
om
put
e
r
S
c
ie
nc
e
,
C
ol
l
e
ge
of
E
duc
a
ti
on
f
or
G
ir
ls
,
U
ni
ve
r
s
it
y
of
K
uf
a
C
ol
le
ge
of
E
duc
a
ti
on
f
or
G
ir
ls
S
tr
e
e
t,
Al
-
A
m
i
r
ne
ig
hbor
hood,
An
N
a
ja
f
,
I
r
a
q
E
m
a
il
:
s
a
la
hm
.gha
z
a
li
@
uokuf
a
.e
du.i
q
1.
I
N
T
R
O
D
U
C
T
I
O
N
F
ly
in
g
a
d
hoc
ne
twor
ks
(
F
A
N
E
T
s
)
ha
ve
e
m
e
r
ge
d
as
a
pr
om
in
e
nt
r
e
s
e
a
r
c
h
f
oc
us
due
to
th
e
in
c
r
e
a
s
in
g
a
v
a
il
a
bi
li
ty
of
unm
a
nne
d
a
e
r
ia
l
ve
hi
c
le
s
(
U
A
V
s
)
a
nd
th
e
a
dv
a
nc
e
m
e
nt
of
e
le
c
tr
oni
c
c
om
pone
nt
s
ne
c
e
s
s
a
r
y
f
or
th
e
ir
c
ont
r
ol
a
nd
c
onne
c
ti
vi
ty
,
s
uc
h
as
m
i
c
r
oc
ont
r
ol
le
r
s
,
s
in
gl
e
-
boa
r
d
c
om
put
e
r
s
,
a
nd
c
om
m
uni
c
a
ti
on
r
a
di
os
.
UAVs
a
r
e
in
c
r
e
a
s
in
gl
y
us
e
d
a
c
r
os
s
di
ve
r
s
e
a
ppl
ic
a
ti
ons
[
1]
–
[
3]
,
de
m
ons
tr
a
ti
ng
pa
r
ti
c
ul
a
r
e
f
f
ic
a
c
y
in
s
e
a
r
c
h
a
nd
r
e
s
c
ue
ope
r
a
ti
ons
f
or
m
oni
t
or
in
g
di
s
a
s
te
r
-
a
f
f
e
c
te
d
a
r
e
a
s
.
R
e
a
l
-
time
vi
de
o
s
tr
e
a
m
s
c
a
pt
ur
e
d
by
U
A
V
c
a
m
e
r
a
s
pl
a
y
a
c
r
uc
ia
l
r
ol
e
in
s
w
if
tl
y
id
e
nt
if
yi
ng
vi
c
ti
m
s
a
nd
in
di
vi
dua
ls
r
e
qui
r
in
g
a
s
s
is
t
a
nc
e
,
ne
c
e
s
s
it
a
ti
ng
th
e
ir
br
oa
dc
a
s
t
to
th
e
r
e
s
c
ue
uni
t'
s
di
s
pa
tc
h
c
e
nt
e
r
.
W
he
n
f
a
c
e
d
w
it
h
th
e
a
bs
e
nc
e
or
f
a
il
ur
e
of
a
tr
a
di
ti
ona
l
te
le
c
om
m
uni
c
a
ti
ons
in
f
r
a
s
tr
uc
tu
r
e
,
th
e
F
A
N
E
T
te
c
hnol
ogy
pr
ove
s
a
de
pt
at
tr
a
ns
m
it
ti
ng
vi
de
o
in
f
or
m
a
ti
on
ove
r
s
ubs
ta
nt
ia
l
di
s
ta
nc
e
s
[
4]
–
[
6]
.
N
ode
s
w
it
hi
n
th
is
ne
twor
k,
pos
it
io
ne
d
on
U
A
V
s
,
pe
r
f
or
m
r
e
tr
a
ns
m
is
s
io
n
a
nd
r
out
in
g
f
unc
ti
ons
f
or
tr
a
ns
m
it
te
d
da
ta
pa
c
ke
ts
.
T
hi
s
d
e
c
e
nt
r
a
li
z
e
d
ne
twor
k
e
na
bl
e
s
th
e
tr
a
ns
m
is
s
io
n
of
vi
de
o
in
f
or
m
a
ti
on
s
tr
e
a
m
s
w
it
hi
n
a
r
a
ndom
to
pol
ogy,
dyna
m
ic
a
ll
y
c
ha
ngi
ng
in
th
r
e
e
-
di
m
e
ns
io
na
l
s
pa
c
e
.
In
th
e
p
r
o
c
e
s
s
of
p
e
r
f
or
m
i
ng
s
e
a
r
c
h
a
n
d
r
e
s
c
u
e
op
e
r
a
ti
o
n
s
a
nd
t
im
e
l
y
d
e
t
e
c
ti
on
of
vi
c
ti
m
s
,
it
is
n
e
c
e
s
s
a
r
y
to
e
n
s
u
r
e
h
ig
h
qu
a
l
it
y
F
A
N
E
T
v
id
e
o
b
r
o
a
dc
a
s
ti
n
g.
T
h
e
pr
o
b
le
m
of
im
pr
ov
in
g
t
h
e
qu
a
li
ty
of
c
om
m
u
ni
c
a
ti
on
in
w
ir
e
l
e
s
s
s
e
lf
-
o
r
g
a
ni
z
in
g
n
e
tw
or
k
s
is
s
u
bj
e
c
t
of
p
u
bl
i
c
a
ti
on
s
by
m
a
n
y
r
e
s
e
a
r
c
h
e
r
s
[
7
]
,
[
8
]
.
H
ow
e
v
e
r
,
i
n
s
u
f
f
i
c
ie
n
t
a
t
t
e
n
ti
on
ha
s
b
e
e
n
p
a
id
to
t
he
i
s
s
u
e
s
of
e
n
s
ur
i
ng
h
ig
h
-
qu
a
li
ty
t
r
a
n
s
m
i
s
s
io
n
of
v
id
e
o
s
tr
e
a
m
s
in
F
A
N
E
T
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
r
ti
f
I
nt
e
ll
I
S
S
N
:
2252
-
8938
A
n al
gor
it
hm
f
or
c
ont
r
ol
li
ng t
he
t
r
ans
m
i
s
s
io
n of
v
id
e
o
s
tr
e
am
s
i
n a f
ly
in
g
…
(
Sal
ah M
ahdi
M
adl
ol
A
lg
haz
al
i
)
4291
T
r
a
ns
m
is
s
io
n
of
vi
de
o
s
tr
e
a
m
s
in
a
F
A
N
E
T
is
c
ha
r
a
c
t
e
r
iz
e
d
by
he
ig
ht
e
ne
d
ne
twor
k
to
pol
ogy
dyna
m
is
m
a
nd
f
r
e
que
nt
c
ha
nge
s
in
di
s
t
a
nc
e
s
b
e
twe
e
n
m
ovi
ng
node
s
,
pot
e
nt
ia
ll
y
r
e
a
c
hi
ng
s
ig
ni
f
ic
a
nt
va
lu
e
s
.
T
he
s
e
tr
a
it
s
,
c
oupl
e
d
w
it
h
li
m
it
e
d
ne
twor
k
c
ha
nn
e
l
pe
r
f
or
m
a
nc
e
,
r
e
s
ul
t
in
vi
de
o
s
tr
e
a
m
f
a
il
ur
e
s
[
9]
–
[
11]
a
nd
pa
c
ke
t
lo
s
s
e
s
due
to
bi
t
di
s
to
r
ti
ons
f
r
om
oc
c
a
s
io
na
l
de
c
r
e
a
s
e
s
in
r
e
c
e
iv
e
d
s
ig
na
l
pow
e
r
[
12]
–
[
14]
.
T
he
s
e
f
a
c
to
r
s
c
ons
id
e
r
a
bl
y
c
om
pr
om
is
e
th
e
qua
li
ty
of
vi
de
o
br
oa
dc
a
s
ti
ng
in
F
A
N
E
T
.
A
s
s
um
in
g
nod
e
s
tr
a
n
s
m
it
ti
ng
vi
de
o
s
tr
e
a
m
s
ope
r
a
te
at
m
a
xi
m
um
pe
r
m
is
s
ib
le
pow
e
r
le
ve
l
s
,
a
c
hi
e
vi
ng
hi
gh
-
qua
li
ty
vi
de
o
tr
a
ns
m
is
s
io
n
be
c
om
e
s
f
e
a
s
ib
le
th
r
ough
th
e
c
ont
r
ol
of
va
r
io
us
p
a
r
a
m
e
te
r
s
.
T
he
s
e
pa
r
a
m
e
te
r
s
e
nc
om
pa
s
s
th
e
in
te
ns
it
y
of
vi
de
o
s
tr
e
a
m
r
e
que
s
ts
,
a
ve
r
a
ge
vi
de
o
s
tr
e
a
m
dur
a
ti
on,
a
nd
a
ve
r
a
ge
le
ngt
h
of
w
ir
e
le
s
s
c
h
a
nne
ls
.
T
he
c
ont
r
ol
of
th
e
s
e
p
a
r
a
m
e
te
r
va
lu
e
s
,
c
r
it
ic
a
l
f
or
in
f
lu
e
nc
i
ng
vi
de
o
br
oa
dc
a
s
t
qua
li
ty
,
r
e
vol
ve
s
a
r
ound
de
c
is
io
ns
to
tr
a
ns
m
it
or
r
e
f
us
e
ne
w
vi
de
o
s
tr
e
a
m
s
,
di
s
a
bl
e
or
m
a
in
ta
in
tr
a
ns
m
it
te
d
vi
de
o
s
tr
e
a
m
s
,
a
nd
a
lt
e
r
th
e
di
s
ta
nc
e
be
twe
e
n
n
e
twor
k
node
s
.
C
le
a
r
ly
,
pr
ovi
de
r
s
of
vi
de
o
s
ur
ve
il
la
nc
e
de
m
a
nd
e
f
f
e
c
ti
ve
de
c
i
s
io
n
-
m
a
ki
ng
to
ol
s
c
a
pa
bl
e
of
of
f
e
r
in
g
in
f
or
m
e
d
r
e
c
om
m
e
nda
ti
ons
to
e
ns
ur
e
hi
gh
-
qua
li
ty
vi
de
o
br
oa
dc
a
s
ti
ng.
In
li
ght
of
th
is
,
r
e
s
e
a
r
c
h
on
th
e
de
ve
lo
pm
e
nt
of
a
de
c
is
io
n
-
m
a
ki
ng
s
uppor
t
a
lg
or
it
hm
in
th
e
vi
de
o
s
ur
ve
il
la
nc
e
pr
oc
e
s
s
,
le
ve
r
a
gi
ng
F
A
N
E
T
a
ppl
ic
a
ti
ons
,
e
m
e
r
ge
s
as
a
pe
r
ti
ne
n
t
a
nd
va
lu
a
bl
e
a
ve
nue
of
e
xpl
or
a
ti
on.
T
he
pr
e
s
e
nt
e
d
r
e
s
e
a
r
c
h
is
a
im
e
d
at
s
ol
vi
ng
a
pr
e
s
s
in
g
s
c
ie
nt
if
ic
a
nd
te
c
hni
c
a
l
pr
obl
e
m
,
w
hi
c
h
is
to
e
ns
ur
e
hi
gh
qu
a
li
ty
tr
a
ns
m
is
s
io
n
of
s
tr
e
a
m
in
g
da
ta
in
w
ir
e
le
s
s
r
e
m
ot
e
m
oni
to
r
in
g
s
y
s
te
m
s
us
e
d
by
r
e
s
c
ue
s
e
r
vi
c
e
s
to
pr
ovi
de
ti
m
e
ly
a
s
s
i
s
ta
nc
e
.
T
he
pur
pos
e
of
th
e
a
r
ti
c
le
is
to
im
pr
ove
th
e
pr
oc
e
s
s
of
vi
de
o
m
oni
to
r
in
g
of
te
r
r
it
or
ie
s
.
T
hi
s
is
a
c
hi
e
ve
d
th
r
ough
th
e
de
ve
lo
pm
e
nt
of
an
a
lg
or
it
hm
f
or
c
ont
r
ol
li
ng
th
e
tr
a
ns
m
is
s
io
n
of
vi
de
o
s
tr
e
a
m
s
in
a
F
A
N
E
T
.
2.
L
I
T
E
R
A
T
U
R
E
R
E
V
I
E
W
An
a
na
ly
s
is
of
r
e
s
e
a
r
c
h
ha
s
s
how
n
th
a
t
a
s
ig
ni
f
ic
a
nt
num
be
r
of
publ
ic
a
ti
ons
a
r
e
de
vot
e
d
to
th
e
is
s
ue
s
of
da
ta
tr
a
ns
m
is
s
io
n
in
F
A
N
E
T
s.
In
a
f
ly
in
g
pe
e
r
-
to
-
pe
e
r
ne
t
w
or
k
de
s
ig
ne
d
to
w
or
k
in
th
e
e
ve
nt
of
va
r
io
us
e
m
e
r
ge
nc
y
s
it
ua
ti
ons
,
th
e
m
ul
ti
-
c
ha
nne
l
I
E
E
E
802.11p
M
A
C
p
r
ot
oc
ol
ha
s
be
e
n
pr
opos
e
d
f
or
us
e
[
6]
.
In
o
r
de
r
to
pr
ovi
de
gua
r
a
nt
e
e
s
f
or
th
e
ti
m
e
ly
e
xc
ha
nge
of
in
f
or
m
a
ti
on
in
c
ondi
ti
ons
of
a
la
r
ge
num
be
r
of
node
s
a
nd
in
te
ns
iv
e
da
ta
tr
a
f
f
ic
in
F
A
N
E
T
,
it
is
pr
opos
e
d
to
us
e
th
e
M
A
C
s
ubl
a
ye
r
of
th
e
I
E
E
E
802.11p
s
ta
nda
r
d,
w
hi
c
h
pr
ovi
de
s
f
or
th
e
e
s
ta
bl
is
hm
e
nt
of
a
c
c
e
s
s
pr
io
r
it
ie
s
f
or
di
f
f
e
r
e
nt
c
la
s
s
e
s
of
in
f
or
m
a
ti
on
f
lo
w
s
.
M
a
ny
w
or
ks
a
r
e
de
vot
e
d
to
a
na
ly
z
in
g
th
e
e
f
f
e
c
ti
ve
ne
s
s
of
us
in
g
r
out
in
g
pr
oc
e
dur
e
s
in
s
e
lf
-
or
ga
ni
z
in
g
ne
twor
ks
a
nd
de
ve
lo
pi
ng
ne
twor
k
le
ve
l
a
lg
or
it
hm
s
a
da
pt
e
d
to
th
e
op
e
r
a
ti
ng
c
ondi
ti
ons
of
F
A
N
E
T
.
In
or
de
r
to
im
pr
ove
th
e
pe
r
f
or
m
a
nc
e
of
F
A
N
E
T
,
it
is
p
r
opos
e
d
to
ta
ke
in
to
a
c
c
ount
th
e
pr
e
s
e
nc
e
of
noi
s
e
in
w
ir
e
le
s
s
c
ha
nn
e
ls
dur
in
g
th
e
r
out
in
g
pr
oc
e
s
s
[
15]
,
us
e
le
a
r
ni
ng
c
lu
s
t
e
r
a
ut
om
a
ta
[
16]
,
a
nd
f
uz
z
y
lo
gi
c
a
l
in
f
e
r
e
nc
e
s
y
s
te
m
s
[
17]
.
To
le
ve
r
a
ge
th
e
s
tr
e
ngt
hs
of
hybr
id
a
r
c
hi
te
c
tu
r
e
s
th
a
t
in
te
gr
a
te
lo
ng
r
a
nge
(
L
oR
a
)
w
it
h
Wi
-
Fi
to
e
nha
nc
e
c
om
m
uni
c
a
ti
on
c
a
pa
bi
li
ti
e
s
in
F
A
N
E
T
s
te
c
hnol
ogi
e
s
f
or
im
p
r
ove
d
pe
r
f
or
m
a
nc
e
T
he
a
ut
hor
s
c
onduc
te
d
a
th
e
or
e
ti
c
a
l
a
na
ly
s
i
s
of
th
e
op
e
r
a
ti
ng
r
a
nge
of
bot
h
L
oR
a
a
nd
I
E
E
E
802.11s
,
a
lo
ng
w
it
h
a
s
im
pl
e
e
xpe
r
im
e
nt
a
l
a
na
ly
s
is
of
lo
ng
r
a
nge
w
id
e
a
r
e
a
ne
twor
k
’s
(
L
oR
a
W
A
N
'
s
)
ope
r
a
ti
ng
r
a
nge
f
or
UAV
-
to
-
g
r
ound
c
om
m
uni
c
a
ti
ons
.
T
he
s
e
e
va
lu
a
ti
ons
pr
ovi
de
in
s
ig
ht
s
in
to
th
e
pr
a
c
ti
c
a
l
c
a
pa
bi
li
ti
e
s
of
L
oR
a
in
r
e
a
l
-
w
o
r
ld
s
c
e
na
r
io
s
[
18]
.
To
e
nha
nc
e
th
e
c
onc
ur
r
e
nt
tr
a
ns
m
is
s
io
n
of
la
r
g
e
-
s
c
a
le
vi
de
o
s
tr
e
a
m
s
w
it
hi
n
e
dge
c
om
put
in
g
e
nvi
r
onm
e
nt
s
,
a
Q
-
le
a
r
ni
ng
da
ta
s
tr
e
a
m
s
c
he
dul
in
g
m
ode
l
is
e
m
pl
oye
d
to
f
a
c
il
it
a
te
dyna
m
ic
lo
a
d
ba
la
nc
in
g
a
c
r
os
s
m
ul
ti
pl
e
ne
twor
k
in
te
r
f
a
c
e
c
a
r
ds
(
N
I
C
s
)
.
T
hi
s
m
e
th
odo
lo
gy
e
nt
a
il
s
th
e
c
l
a
s
s
if
ic
a
ti
on
of
d
a
ta
s
tr
e
a
m
s
a
nd
th
e
dyna
m
ic
s
e
le
c
ti
on
of
th
e
a
ppr
opr
ia
te
C
P
U
tr
a
ns
m
is
s
io
n
pr
oc
e
s
s
in
g
uni
t
ba
s
e
d
on
a
r
e
w
a
r
d
f
unc
ti
on,
th
e
r
e
by
a
id
in
g
in
lo
a
d
ba
la
nc
in
g
a
nd
th
e
e
nha
nc
e
m
e
nt
of
ove
r
a
ll
s
ys
te
m
pe
r
f
or
m
a
nc
e
.
T
he
f
in
di
ngs
de
m
ons
tr
a
te
th
a
t
th
is
a
ppr
oa
c
h
can
in
c
r
e
a
s
e
ba
ndw
id
th
by
a
f
a
c
to
r
of
3.6
in
c
om
pa
r
is
on
to
a
be
nc
hm
a
r
k
s
c
he
m
e
ut
il
iz
in
g
a
s
in
gl
e
ne
twor
k
por
t,
w
hi
le
c
onc
ur
r
e
nt
ly
r
e
d
uc
in
g
th
e
a
ve
r
a
ge
C
P
U
lo
a
d
r
a
ti
o
by
18%
a
nd
de
c
r
e
a
s
in
g
s
y
s
te
m
la
te
nc
y
by
21%
.
N
e
ve
r
th
e
le
s
s
,
th
e
s
tu
dy
doe
s
not
c
ons
id
e
r
pot
e
nt
ia
l
li
m
it
a
ti
ons
,
s
uc
h
as
th
e
s
c
a
la
bi
li
ty
of
th
e
pr
opo
s
e
d
m
e
th
od
in
e
xc
e
pt
io
na
ll
y
la
r
ge
da
ta
c
e
nt
e
r
s
or
th
e
in
f
lu
e
nc
e
of
f
lu
c
tu
a
ti
ng
ne
twor
k
c
ondi
ti
ons
on
th
e
pe
r
f
or
m
a
nc
e
of
th
e
Q
-
le
a
r
ni
ng
a
lg
or
it
hm
,
w
hi
c
h
m
a
y
im
pa
c
t
its
e
f
f
ic
a
c
y
in
pr
a
c
ti
c
a
l
a
ppl
ic
a
ti
ons
.
w
hi
c
h
c
oul
d
a
f
f
e
c
t
its
e
f
f
e
c
ti
ve
ne
s
s
in
r
e
a
l
-
w
or
ld
a
ppl
ic
a
ti
ons
[
19]
.
In
or
de
r
to
im
pr
ove
F
A
N
E
T
r
out
in
g,
th
e
us
e
of
ne
ur
a
l
ne
twor
k
r
e
in
f
or
c
e
m
e
nt
le
a
r
ni
ng
ha
s
be
e
n
pr
opos
e
d
to
s
e
le
c
t
a
ut
il
it
y
in
di
c
a
to
r
as
a
w
e
ig
ht
e
d
s
um
of
th
e
in
di
c
a
to
r
of
s
uc
c
e
s
s
f
ul
de
li
ve
r
y,
de
la
y
a
nd
e
ne
r
gy
c
ons
um
pt
io
n
[
20]
.
R
e
s
e
a
r
c
h
ha
s
be
e
n
c
a
r
r
ie
d
out
on
th
e
f
e
a
tu
r
e
s
of
br
oa
dc
a
s
ti
ng
vi
de
o
s
tr
e
a
m
s
in
F
A
N
E
T
us
in
g
th
e
NS
-
3
s
im
ul
a
ti
on
e
nvi
r
onm
e
nt
[
21]
.
R
e
s
e
a
r
c
h
r
e
s
ul
ts
ha
ve
s
ho
w
n
th
a
t
w
it
h
a
s
m
a
ll
num
be
r
of
node
s
in
th
e
ne
twor
k,
s
ig
ni
f
ic
a
nt
pa
c
ke
t
lo
s
s
e
s
a
r
e
obs
e
r
ve
d.
T
hi
s
is
du
e
to
th
e
r
e
duc
e
d
l
e
ve
l
of
tr
a
ns
m
it
te
d
s
ig
na
ls
at
r
e
la
ti
ve
ly
la
r
ge
di
s
ta
nc
e
s
be
twe
e
n
ne
twor
k
node
s
.
It
ha
s
be
e
n
e
s
ta
bl
is
he
d
th
a
t
th
e
be
s
t
in
di
c
a
to
r
s
of
th
e
qua
li
ty
of
tr
a
ns
m
is
s
io
n
of
vi
de
o
in
f
or
m
a
ti
on
s
tr
e
a
m
s
a
r
e
obs
e
r
ve
d
w
he
n
ope
r
a
ti
ng
in
a
ne
twor
k
of
10
to
15
node
s
.
A
f
ur
th
e
r
in
c
r
e
a
s
e
in
th
e
num
be
r
of
nod
e
s
l
e
a
ds
to
a
de
te
r
io
r
a
ti
on
in
th
e
qua
li
ty
of
tr
a
ns
m
is
s
io
n
of
vi
de
o
s
tr
e
a
m
s
,
w
hi
c
h
is
a
s
s
oc
ia
te
d
w
it
h
an
in
c
r
e
a
s
e
in
th
e
num
be
r
of
in
te
r
m
e
di
a
te
c
ha
nne
ls
w
it
hi
n
th
e
ge
ne
r
a
te
d
pa
c
ke
t
de
li
ve
r
y
r
out
e
s
.
To
r
e
duc
e
p
a
c
ke
t
e
r
r
or
s
th
a
t
oc
c
ur
in
F
A
N
E
T
due
to
ne
twor
k
c
ol
li
s
io
ns
or
in
te
r
f
e
r
e
nc
e
,
a
vi
de
o
s
tr
e
a
m
in
g
m
e
th
od
ba
s
e
d
on
a
ut
om
a
ti
c
r
e
que
s
t
f
or
r
e
tr
a
ns
m
is
s
io
ns
at
th
e
a
ppl
ic
a
ti
on
le
ve
l
ha
s
be
e
n
pr
opo
s
e
d
[
22]
.
H
ow
e
ve
r
,
th
e
a
bove
w
or
ks
do
no
t
e
xa
m
in
e
th
e
is
s
u
e
s
of
a
c
hi
e
vi
ng
th
e
r
e
qui
r
e
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
. 14, No. 5, O
c
to
be
r
2025
:
4290
-
4298
4292
pr
oba
bi
li
ty
of
e
ns
ur
in
g
hi
gh
qua
li
ty
vi
de
o
br
oa
dc
a
s
ti
ng
in
F
A
N
E
T
,
e
s
ti
m
a
ti
ng
th
e
r
e
c
om
m
e
nde
d
di
s
t
a
nc
e
be
twe
e
n
tr
a
ns
m
it
ti
ng
a
nd
r
e
c
e
iv
in
g
node
s
;
little
a
tt
e
nt
io
n
ha
s
be
e
n
pa
id
to
th
e
de
ve
lo
pm
e
nt
of
de
c
is
io
n
s
uppor
t
to
ol
s
in
th
e
F
A
N
E
T
vi
d
e
o
m
oni
to
r
in
g
pr
oc
e
s
s
,
ta
ki
ng
i
nt
o
a
c
c
ount
th
e
hi
gh
pr
oba
bi
li
ty
of
pa
c
ke
t
lo
s
s
a
nd
th
e
s
pe
c
if
ic
c
ondi
ti
ons
f
or
tr
a
ns
m
it
ti
ng
vi
de
o
in
f
or
m
a
ti
on
c
a
pt
ur
e
d
by
UAV
c
a
m
e
r
a
s
.
M
os
t
w
o
r
ks
on
F
A
N
E
T
a
d
dr
e
s
s
th
e
is
s
ue
of
r
ou
t
in
g
a
n
d
ne
two
r
k
a
r
c
h
i
te
c
t
ur
e
w
i
th
o
ut
a
n
y
di
s
c
us
s
io
n
of
th
e
c
ha
r
a
c
te
r
is
ti
c
s
of
m
u
lt
ip
le
c
ha
n
ne
ls
.
T
he
r
ou
ti
n
g
s
tr
a
te
gy
in
th
e
F
A
N
E
T
h
a
s
be
e
n
s
tu
d
ie
d
by
n
um
e
r
ous
r
e
s
e
a
r
c
he
r
s
.
H
a
nd
li
ng
of
ne
tw
or
k
-
le
v
e
l
la
y
e
r
s
r
e
s
e
a
r
c
h
w
or
k
f
oc
us
e
s
on
c
ha
n
ne
l
a
bs
t
r
a
c
t
io
n
th
r
ou
gh
m
ul
ti
pl
e
s
t
r
a
t
e
g
ie
s
in
c
lu
d
in
g
va
r
io
us
c
ha
n
ne
l
c
o
nd
it
i
ons
.
D
ue
to
th
e
dy
na
m
ic
to
po
lo
gi
c
a
l
c
ha
n
ge
s
of
ne
two
r
k
-
r
e
l
a
te
d
s
tu
d
ie
s
,
r
e
s
e
a
r
c
he
r
s
s
uc
h
as
w
i
th
m
o
bi
le
n
ode
s
.
T
h
e
y
a
r
e
c
a
p
a
bl
e
of
a
s
s
e
m
bl
in
g
ne
tw
or
k
pa
th
s
f
o
r
w
i
r
e
l
e
s
s
li
nks
[
23
]
,
[
2
4]
.
T
hus
,
th
e
r
e
s
e
a
r
c
h
of
m
a
ny
s
c
ie
nt
is
ts
a
nd
de
ve
l
ope
r
s
is
de
vo
te
d
to
im
pr
ov
in
g
t
he
pr
oc
e
s
s
e
s
of
in
f
o
r
m
a
t
io
n
t
r
a
ns
m
is
s
io
n
in
w
i
r
e
le
s
s
r
e
m
ot
e
m
on
it
or
in
g
s
ys
te
m
s
[
25
]
.
H
ow
e
ve
r
,
th
e
s
c
ie
nt
if
ic
a
n
d
p
r
a
c
t
ic
a
l
r
e
s
ul
ts
th
e
y
ob
ta
in
e
d
r
e
q
ui
r
e
f
u
r
t
he
r
de
ve
lo
pm
e
nt
in
te
r
m
s
of
e
ns
u
r
i
ng
hi
gh
qua
li
ty
v
id
e
o
b
r
oa
dc
a
s
ti
ng
in
F
A
N
E
T
.
3.
P
R
O
P
O
S
E
D
A
L
G
O
R
I
T
H
M
C
ons
id
e
r
a
s
c
e
na
r
io
w
he
r
e
vi
d
e
o
m
oni
to
r
in
g
of
te
r
r
it
or
ie
s
is
c
onduc
te
d
us
in
g
a
F
A
N
E
T
dur
in
g
a
s
e
a
r
c
h
a
nd
r
e
s
c
ue
op
e
r
a
ti
on.
To
id
e
nt
if
y
vi
c
ti
m
s
,
s
pe
c
if
ic
vi
de
o
s
tr
e
a
m
s
c
a
pt
ur
e
d
by
UAV
-
m
ount
e
d
c
a
m
e
r
a
s
a
r
e
tr
a
ns
m
it
te
d
to
th
e
r
e
s
c
ue
uni
t'
s
di
s
pa
tc
h
c
e
nt
e
r
m
oni
to
r
s
.
H
ow
e
ve
r
,
due
to
va
r
io
us
r
e
a
s
ons
,
s
om
e
tr
a
ns
m
it
te
d
vi
de
o
s
tr
e
a
m
s
m
a
y
be
in
te
r
m
it
te
nt
ly
di
s
c
ont
in
ue
d,
a
nd
th
e
ne
c
e
s
s
it
y
to
tr
a
ns
m
it
ne
w
vi
de
os
m
a
y
a
r
is
e
.
To
e
ns
ur
e
e
f
f
e
c
ti
ve
de
te
c
ti
on
of
in
di
vi
dua
ls
in
ne
e
d
of
r
e
s
c
ue
by
di
s
pa
tc
h
c
e
nt
e
r
obs
e
r
ve
r
s
,
it
is
im
pe
r
a
ti
ve
to
gua
r
a
nt
e
e
hi
gh
-
qua
li
ty
F
A
N
E
T
vi
de
o
tr
a
ns
m
is
s
io
n
to
th
e
ut
il
iz
e
d
m
oni
to
r
s
.
3.1.
R
at
io
n
al
e
f
or
r
e
c
o
m
m
e
n
d
e
d
s
ol
u
t
io
n
s
T
he
pe
r
f
or
m
a
nc
e
of
th
e
F
A
N
E
T
is
bot
h
li
m
it
e
d
a
nd
unpr
e
di
c
ta
bl
e
.
To
pr
e
ve
nt
an
unde
s
ir
a
bl
e
r
e
duc
ti
on
in
th
e
qua
li
ty
of
vi
de
o
br
oa
dc
a
s
t
w
he
n
in
tr
oduc
i
ng
ne
w
vi
de
o
s
tr
e
a
m
s
in
th
e
s
e
c
h
a
ll
e
ngi
ng
c
ondi
ti
ons
,
a
s
e
t
of
r
e
c
om
m
e
nde
d
s
ol
ut
io
ns
is
pr
opos
e
d
a
nd
de
t
a
il
e
d
in
T
a
bl
e
1.
T
he
de
c
is
io
n
-
m
a
ki
ng
pr
oc
e
s
s
pr
im
a
r
il
y
c
ons
id
e
r
s
th
e
va
lu
e
of
(
pr
oba
bi
li
ty
of
e
ns
ur
in
g
hi
gh
vi
de
o
qua
li
ty
)
w
he
n
a
n
e
w
vi
de
o
s
tr
e
a
m
is
pr
opos
e
d.
If
th
e
e
s
ti
m
a
te
d
va
lu
e
of
is
e
qua
l
to
or
gr
e
a
te
r
th
a
n
0.95,
th
e
t
r
a
ns
m
is
s
io
n
of
th
e
ne
w
vi
de
o
s
tr
e
a
m
is
a
ppr
ove
d.
A
lt
e
r
na
ti
ve
ly
,
if
th
i
s
va
lu
e
f
a
ll
s
und
e
r
0.9
5,
an
a
ddi
ti
ona
l
f
a
c
to
r
is
ta
k
e
n
in
to
a
c
c
ount
:
th
e
pr
e
s
e
nc
e
of
a
lo
w
-
in
f
or
m
a
ti
on
vi
de
o
s
tr
e
a
m
a
m
ong
th
e
e
xi
s
ti
ng
one
s
,
w
hi
c
h
can
be
de
a
c
ti
va
te
d.
If
an
ongoing
tr
a
ns
m
is
s
io
n
in
vol
ve
s
s
u
c
h
a
lo
w
-
in
f
or
m
a
ti
on
vi
de
o
s
tr
e
a
m
,
it
is
a
dvi
s
a
bl
e
to
di
s
a
bl
e
it.
In
c
a
s
e
s
w
he
r
e
no
lo
w
-
in
f
or
m
a
ti
on
vi
de
o
s
tr
e
a
m
s
a
r
e
id
e
nt
if
ie
d,
th
e
r
e
c
om
m
e
nde
d
c
our
s
e
of
a
c
ti
on
is
to
r
e
duc
e
th
e
a
ve
r
a
ge
w
ir
e
le
s
s
c
ha
nne
l
le
ngt
h
to
th
e
s
pe
c
if
ie
d
rd
v
a
lu
e
.
T
a
bl
e
1.
R
e
c
om
m
e
nde
d
s
ol
ut
io
n
s
V
a
l
ue
Hq
T
r
a
ns
m
i
t
t
e
d/
not
t
r
a
ns
m
i
t
t
e
d
l
ow
-
i
nf
o
r
m
a
t
i
on
vi
de
o
s
t
r
e
a
m
R
e
c
om
m
e
nde
d
s
ol
ut
i
on
s
≥
0.95
No
i
m
por
t
a
nc
e
T
r
a
ns
m
i
t
t
i
ng
a
ne
w
vi
de
o
s
t
r
e
a
m
<0.95
N
ot
t
r
a
ns
m
i
t
t
e
d
R
e
duc
e
t
he
a
ve
r
a
g
e
c
ha
nne
l
l
e
ngt
h
to
rd
m
e
t
e
r
s
<0.95
T
r
a
ns
m
i
t
t
e
d
D
i
s
c
onne
c
t
i
ng
t
he
t
r
a
ns
m
i
s
s
i
on
of
l
ow
-
i
nf
or
m
a
t
i
ona
l
vi
de
o
s
t
r
e
a
m
3.2
.
E
s
t
im
at
in
g
t
h
e
p
r
ob
ab
il
it
y
of
h
ig
h
q
u
al
it
y
b
r
oad
c
as
t
in
g
vi
d
e
o
s
t
r
e
am
s
W
he
n
a
s
s
e
s
s
in
g
th
e
pr
oba
bi
li
ty
of
e
ns
ur
in
g
hi
gh
qua
li
ty
vi
de
o
br
oa
dc
a
s
t
s
ove
r
th
e
n
e
twor
k,
one
s
houl
d
ta
k
e
in
to
a
c
c
ount
th
a
t
in
th
e
m
os
t
und
e
s
ir
a
bl
e
c
a
s
e
,
a
ll
vi
de
o
s
tr
e
a
m
s
pa
s
s
th
r
ough
th
e
s
a
m
e
bus
ie
s
t
c
ha
nne
l.
T
he
n
th
e
va
lu
e
of
is
e
qua
l
to
th
e
pr
oba
bi
li
ty
of
hi
gh
-
qua
li
ty
b
r
oa
dc
a
s
ti
ng
vi
de
o
s
tr
e
a
m
s
ove
r
th
is
c
ha
nne
l
a
nd
can
be
c
a
lc
ul
a
t
e
d
us
in
g
th
e
(
1)
.
=
∑
!
!
(
−
)
!
[
1
−
(
+
)
]
−
(
+
)
=
0
(
1)
H
e
r
e
is
th
e
num
be
r
of
r
e
c
e
iv
e
d
r
e
qu
e
s
ts
to
tr
a
ns
m
it
vi
de
o
s
tr
e
a
m
s
;
is
th
e
va
lu
e
th
a
t
s
houl
d
not
e
xc
e
e
d
th
e
s
um
of
th
e
num
be
r
of
f
a
il
ur
e
s
in
th
e
tr
a
ns
m
is
s
io
n
of
vi
de
o
s
tr
e
a
m
s
a
nd
th
e
num
be
r
of
vi
de
o
s
tr
e
a
m
s
tr
a
ns
m
it
te
d
w
it
h
an
una
c
c
e
pt
a
bl
e
le
v
e
l
of
pa
c
ke
t
lo
s
s
;
is
th
e
pr
oba
bi
li
ty
of
f
a
il
ur
e
in
vi
de
o
s
tr
e
a
m
tr
a
ns
m
is
s
io
n;
is
th
e
pr
oba
bi
li
ty
of
tr
a
ns
m
it
ti
ng
a
vi
de
o
s
tr
e
a
m
w
it
h
an
una
c
c
e
pt
a
bl
e
l
e
ve
l
of
pa
c
ke
t
lo
s
s
.
3.3.
P
r
ob
ab
il
it
y
of
f
ai
lu
r
e
in
vi
d
e
o
s
t
r
e
am
t
r
an
s
m
is
s
io
n
To
c
om
put
e
th
e
v
a
lu
e
p
,
c
on
s
id
e
r
a
m
ul
ti
-
c
ha
nne
l
s
y
s
te
m
w
it
h
a
r
e
s
tr
ic
te
d
que
ue
le
ngt
h.
T
he
c
ha
nc
e
of
f
a
il
in
g
to
s
e
r
vi
c
e
a
r
e
que
s
t
is
gi
ve
n
in
(
2)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
r
ti
f
I
nt
e
ll
I
S
S
N
:
2252
-
8938
A
n al
gor
it
hm
f
or
c
ont
r
ol
li
ng t
he
t
r
ans
m
i
s
s
io
n of
v
id
e
o
s
tr
e
am
s
i
n a f
ly
in
g
…
(
Sal
ah M
ahdi
M
adl
ol
A
lg
haz
al
i
)
4293
=
(
)
(
)
(
)
!
(
)
(
)
(
)
(
)
!
∑
(
)
=
1
+
∑
(
)
!
(
)
=
0
(
2)
H
e
r
e
λ
is
th
e
i
nt
e
n
s
it
y
of
r
e
c
e
ip
t
of
vi
de
o
s
tr
e
a
m
r
e
qu
e
s
ts
on
a
c
ha
nne
l;
τ
is
th
e
a
v
e
r
a
g
e
d
ur
a
ti
o
n
of
tr
a
ns
m
i
s
s
io
n
of
vi
de
o
s
tr
e
a
m
s
on
th
e
c
h
a
nn
e
l;
m
is
th
e
buf
f
e
r
vol
um
e
f
or
th
e
que
u
e
of
vi
de
o
s
tr
e
a
m
r
e
que
s
t
s
pe
r
c
ha
nn
e
l;
R
is
th
e
bi
tr
a
te
of
d
a
ta
tr
a
ns
m
i
s
s
io
n
on
t
he
c
a
na
l;
r
is
c
ha
nne
l
pe
r
f
or
m
a
nc
e
u
s
e
d
to
tr
a
ns
m
it
on
e
vi
de
o
s
tr
e
a
m
w
it
h
a
pe
r
m
i
s
s
ib
le
le
v
e
l
of
pa
c
ka
g
e
lo
s
s
.
I
n
(
2)
is
v
a
li
d
un
de
r
f
ol
l
ow
in
g
c
on
di
ti
on
,
a
s
gi
v
e
n i
n (
3)
.
>
(
3)
3.4.
P
r
ob
ab
il
it
y
of
t
r
an
s
m
it
t
in
g
a
vi
d
e
o
s
t
r
e
am
w
it
h
an
u
n
a
c
c
e
p
t
ab
le
le
ve
l
of
p
ac
k
e
t
lo
s
s
To
c
a
lc
ul
a
te
th
e
pr
oba
bi
li
ty
of
a
vi
de
o
s
tr
e
a
m
c
ha
nn
e
l
ha
vi
ng
an
una
c
c
e
pt
a
bl
e
a
m
ount
of
pa
c
ka
g
e
lo
s
s
us
e
th
e
(
4)
.
=
1
−
[
(
1
−
)
+
∑
,
(
1
−
)
−
=
1
]
(
4)
H
e
r
e
w
is
th
e
qua
nt
it
y
of
pa
c
ke
ts
be
in
g
tr
a
ns
m
it
te
d
in
th
e
vi
de
o
s
tr
e
a
m
;
v
is
th
e
pr
oba
bi
li
ty
of
a
pa
c
ka
ge
be
in
g
lo
s
t
in
th
e
pr
oc
e
s
s
of
tr
a
ns
m
it
ti
ng
th
r
ough
th
e
c
ha
nne
l;
PL
is
th
e
pe
r
m
is
s
ib
le
num
be
r
of
pa
c
ka
ge
s
be
in
g
lo
s
t
dur
in
g
th
e
tr
a
ns
m
is
s
io
n
of
th
e
vi
de
o
f
e
e
d.
T
h
e
va
lu
e
PL
c
a
n
be
c
a
lc
ul
a
te
d
by
th
e
(
5)
.
=
⌈
−
2
⋅
+
1
⌉
(
5)
H
e
r
e
CP
is
th
e
num
be
r
of
pa
c
ke
ts
th
a
t
n
e
e
d
to
be
obt
a
in
e
d
in
a
r
ow
be
f
or
e
a
nd
a
f
te
r
a
lo
s
t
pa
c
ka
g
e
to
c
om
pe
ns
a
te
f
or
its
lo
s
s
.
C
oe
f
f
ic
ie
nt
s
c
a
n
be
c
a
lc
ul
a
te
d
w
it
h
th
e
(
6)
.
,
=
{
−
2
,
=
1
;
0
,
>
1
,
≤
3
+
1
;
∑
,
−
1
,
>
1
,
>
3
+
1
.
−
−
1
=
2
+
1
(
6)
In
(
4)
th
r
ough
(
6)
ta
ke
in
to
a
c
c
ount
th
e
po
s
s
ib
il
it
y
of
a
ppr
ox
im
a
ti
on
pr
oc
e
s
s
e
s
b
e
in
g
us
e
d
at
th
e
r
e
c
e
iv
in
g
node
to
r
e
c
ove
r
lo
s
t
pa
c
ke
ts
.
B
ut
it
'
s
im
por
ta
nt
to
r
e
m
e
m
be
r
th
a
t
at
th
e
r
e
c
e
iv
in
g
node
,
in
or
de
r
to
e
f
f
e
c
ti
ve
ly
r
e
c
ove
r
a
lo
s
t
pa
c
k
e
t,
at
le
a
s
t
on
e
pa
c
ke
t
b
e
f
or
e
a
nd
one
pa
c
ke
t
a
f
te
r
it
m
us
t
be
pr
e
s
e
nt
in
th
e
s
e
que
nc
e
.
T
he
pr
oba
bi
li
ty
of
pa
c
ke
t
lo
s
s
dur
in
g
c
ha
nne
l
tr
a
ns
m
i
s
s
io
n
can
be
c
om
put
e
d
us
in
g
th
e
(
7)
.
=
1
−
[
1
−
(
2
(
+
10
(
)
2
(
4
)
2
)
⋅
⋅
⋅
)
]
(
7)
H
e
r
e
P
T
is
th
e
s
ig
na
l
tr
a
ns
m
i
s
s
io
n
pow
e
r
;
c
is
th
e
s
ig
na
l
s
pr
e
a
d
s
p
e
e
d;
f
is
th
e
s
ig
na
l
f
r
e
que
nc
y;
d
is
th
e
a
ve
r
a
ge
di
s
ta
nc
e
be
twe
e
n
tr
a
ns
m
it
ti
ng
a
nd
r
e
c
e
iv
in
g
node
s
;
L
s
a
r
e
s
ys
te
m
lo
s
s
e
s
;
k
is
B
ol
tz
m
a
nn
c
ons
ta
nt
;
T
R
is
th
e
te
m
pe
r
a
tu
r
e
;
N
F
is
th
e
noi
s
e
c
oe
f
f
ic
ie
nt
;
a
nd
s
is
th
e
pa
c
ke
t
bi
t
le
ngt
h.
To
s
uppor
t
de
c
i
s
io
n
-
m
a
ki
ng
in
th
e
pr
oc
e
s
s
of
c
onduc
ti
ng
F
A
N
E
T
vi
de
o
m
oni
to
r
in
g,
th
e
im
pl
e
m
e
nt
a
ti
on
of
th
e
a
lg
or
it
hm
pr
e
s
e
nt
e
d
in
A
lg
or
it
hm
1
is
p
r
opos
e
d.
T
he
pr
opos
e
d
a
lg
or
it
hm
w
a
s
us
e
d
in
c
om
put
a
ti
ona
l
e
xpe
r
im
e
nt
s
pe
r
f
or
m
e
d us
in
g a
s
im
ul
a
ti
on mode
l
of
t
he
de
c
is
io
n
-
m
a
ki
ng pr
oc
e
s
s
f
or
m
a
na
gi
ng
th
e
t
r
a
ns
m
is
s
io
n of
vi
de
o s
tr
e
a
m
s
t
o F
A
N
E
T
.
A
lg
or
it
hm
1. A
da
pt
iv
e
vi
de
o s
tr
e
a
m
t
r
a
ns
m
is
s
io
n de
c
i
s
io
n a
lg
o
r
it
hm
i
n F
A
N
E
T
S
te
p
1
:
be
gi
nni
ng
of
th
e
a
lg
or
it
hm
.
S
te
p
2:
th
e
s
ta
r
ti
ng
da
ta
is
e
nt
e
r
e
d
T
is
th
e
to
ta
l
num
be
r
of
in
te
r
va
ls
of
time
th
e
a
lg
or
it
hm
pe
r
f
or
m
e
d;
Λ
=1
th
e
num
be
r
of
vi
de
o
s
tr
e
a
m
s
ST
=
0;
th
e
to
ta
l
dur
a
ti
on
of
th
e
tr
a
ns
m
is
s
io
n
of
th
e
vi
de
o’
s
s
tr
e
a
m
s
;
th
e
a
v
e
r
a
ge
time
of
tr
a
ns
m
is
s
io
n
vi
de
o
s
tr
e
a
m
on
th
e
c
ha
nne
l
τ
=
0;
th
e
in
te
ns
it
y
of
th
e
r
e
c
e
ip
t
of
r
e
que
s
ts
f
or
tr
a
ns
m
is
s
io
n
vi
de
o
s
tr
e
a
m
s
λ
=
0.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
. 14, No. 5, O
c
to
be
r
2025
:
4290
-
4298
4294
S
te
p
3:
th
e
num
be
r
of
time
in
te
r
va
ls
t
r
is
e
s
by
on
e
.
P
r
oc
e
e
d
to
s
te
p
20
if
th
e
num
be
r
f
or
th
e
c
ur
r
e
nt
time
in
te
r
va
l
is
gr
e
a
te
r
th
a
n
th
e
va
lu
e
.
In
th
e
e
ve
nt
w
he
n
not
,
s
te
p
4
of
th
e
a
lg
or
it
hm
is
e
xe
c
ut
e
d.
S
te
p
4
:
th
e
i
-
vi
de
o
s
tr
e
a
m
num
be
r
in
c
r
e
a
s
e
s
by
1.
If
th
e
vi
de
o
s
tr
e
a
m
num
be
r
e
xc
e
e
ds
Λ,
m
ove
to
s
te
p
7.
O
th
e
r
w
is
e
,
th
e
a
lg
or
it
hm
e
xe
c
ut
e
s
to
s
te
p
5.
S
te
p
5
:
if
th
e
t
r
a
ns
f
e
r
of
t
he
s
tr
e
a
m
num
b
e
r
i
is
c
o
m
pl
e
t
e
d
e
a
r
l
ie
r
th
a
n
t
he
c
ur
r
e
nt
ti
m
e
i
nt
e
r
v
a
l,
m
o
ve
to
s
t
e
p
6.
O
th
e
r
w
is
e
,
th
e
a
lg
or
it
hm
e
xe
c
ut
io
n
r
e
tu
r
ns
to
s
te
p
4.
S
te
p
6
:
th
e
va
lu
e
of
th
e
to
ta
l
dur
a
ti
on
of
tr
a
ns
m
is
s
io
n
of
ST
vi
d
e
o
s
tr
e
a
m
s
in
c
r
e
a
s
e
s
by
on
e
uni
t.
S
te
p
7
:
th
e
de
c
is
io
n
-
m
a
ke
r
is
in
vi
te
d
to
a
ns
w
e
r
que
s
ti
on
1:
"Is
a
ne
w
s
tr
e
a
m
r
e
qui
r
e
d?
"
S
te
p
8
:
if
a
ne
w
s
tr
e
a
m
is
r
e
qui
r
e
d,
m
ove
to
s
te
p
9.
O
th
e
r
w
is
e
,
th
e
a
lg
or
it
hm
e
xe
c
ut
io
n
r
e
tu
r
ns
to
s
te
p
3.
S
te
p
9
:
a
p
r
oc
e
dur
e
is
c
a
r
r
ie
d
out
to
e
s
ti
m
a
te
th
e
va
lu
e
of
pd
is
th
e
f
or
e
c
a
s
te
d
a
ve
r
a
ge
le
ngt
h
of
th
e
w
ir
e
le
s
s
c
ha
nn
e
l.
S
te
p
10
:
c
a
lc
ul
a
te
th
e
in
te
ns
it
y
of
vi
de
o
s
tr
e
a
m
r
e
que
s
ts
pe
r
c
ha
nne
l
a
nd
th
e
a
ve
r
a
ge
vi
de
o
s
tr
e
a
m
dur
a
ti
on
pe
r
c
ha
nne
l
a
c
c
or
di
ng
to
(
8)
a
nd (
9)
.
=
Λ
+
1
(
8)
=
Λ
(
9)
T
he
pr
oba
bi
li
ty
va
lu
e
of
hi
gh
-
qua
li
ty
vi
de
o
tr
a
ns
m
is
s
io
n
is
c
a
lc
ul
a
te
d
us
in
g
(
1)
to
(
7)
.
S
te
p
11
:
th
e
f
ol
lo
w
in
g
c
ondi
ti
on
is
ve
r
if
ie
d:
H
q>=
0.95.
If
th
is
c
ondi
ti
on
is
m
e
t,
m
ov
e
to
s
te
p
12.
O
th
e
r
w
is
e
,
th
e
a
lg
or
it
hm
e
xe
c
ut
e
s
to
s
te
p
13.
S
te
p
12
:
th
e
de
c
is
io
n
-
m
a
ke
r
is
gi
ve
n
a
m
e
s
s
a
ge
1:
"
T
he
tr
a
ns
m
is
s
io
n
of
th
e
vi
de
o
s
tr
e
a
m
w
il
l
not
s
ig
ni
f
ic
a
nt
ly
a
f
f
e
c
t
th
e
vi
de
o
tr
a
ns
m
is
s
io
n
qua
li
ty
.
It
is
r
e
c
o
m
m
e
nde
d
to
ta
ke
de
c
is
io
n
1
to
tr
a
ns
m
it
vi
de
o
s
tr
e
a
m
”
.
R
unni
ng
th
e
a
lg
or
it
hm
goe
s
to
s
t
e
p
18.
S
te
p
13
:
th
e
de
c
is
io
n
-
m
a
ke
r
is
in
vi
te
d
to
a
ns
w
e
r
que
s
ti
on
1:
"Is
th
e
r
e
a
lo
w
-
in
f
o
r
m
a
ti
on
vi
de
o
s
tr
e
a
m
a
m
ongs
t
th
e
vi
de
o
s
tr
e
a
m
s
tr
a
ns
m
it
te
d?
"
S
te
p
14
:
if
th
e
lo
w
-
in
f
or
m
a
ti
on
s
tr
e
a
m
is
tr
a
ns
m
it
te
d
at
th
e
c
ur
r
e
nt
ti
m
e
,
th
e
tr
a
ns
it
io
n
to
s
te
p
17
is
pe
r
f
or
m
e
d.
O
th
e
r
w
is
e
,
th
e
a
lg
or
it
hm
e
xe
c
ut
io
n
goe
s
to
s
te
p
15.
S
te
p
15
:
th
e
pr
oc
e
dur
e
is
pe
r
f
or
m
e
d
to
e
s
ti
m
a
te
th
e
rd
va
lu
e
,
th
e
r
e
c
om
m
e
nde
d
a
ve
r
a
g
e
w
ir
e
le
s
s
c
ha
nne
l
le
ngt
h.
S
te
p
16
:
th
e
de
c
is
io
n
-
m
a
ke
r
r
e
c
e
iv
e
s
a
m
e
s
s
a
ge
2:
"
S
tr
e
a
m
tr
a
ns
m
is
s
io
n
m
a
y
de
t
e
r
io
r
a
te
th
e
qua
li
ty
of
th
e
vi
de
o
tr
a
ns
m
is
s
io
n.
It
is
r
e
c
om
m
e
nde
d
to
t
a
ke
de
c
is
io
n
2
-
to
r
e
duc
e
th
e
a
ve
r
a
ge
le
ngt
h
of
th
e
c
ha
nne
l
to
rd
m
e
te
r
s
"
.
R
unni
ng
th
e
a
lg
or
it
hm
goe
s
to
s
te
p
18.
S
te
p
17
:
th
e
de
c
is
io
n
-
m
a
ke
r
r
e
c
e
iv
e
s
a
m
e
s
s
a
ge
2:
"
S
tr
e
a
m
tr
a
ns
m
is
s
io
n
m
a
y
de
t
e
r
io
r
a
te
th
e
qua
li
ty
of
th
e
vi
de
o
tr
a
ns
m
is
s
io
n.
It
is
r
e
c
om
m
e
nde
d
th
a
t
de
c
is
io
n
3
be
a
dopt
e
d
-
to
di
s
a
bl
e
th
e
tr
a
ns
m
is
s
io
n
of
lo
w
-
in
f
or
m
a
ti
on
f
lo
w
s
"
.
S
te
p
18
:
if
de
c
is
io
n
1
is
a
dopt
e
d,
th
e
tr
a
ns
it
io
n
to
s
te
p
19
ta
k
e
s
pl
a
c
e
.
O
th
e
r
w
is
e
,
th
e
a
lg
or
it
hm
e
xe
c
ut
io
n
r
e
tu
r
ns
to
s
te
p
3.
S
te
p
19
:
th
e
vi
de
o
s
tr
e
a
m
num
be
r
Λ
in
c
r
e
a
s
e
s
by
1.
E
xe
c
ut
in
g
th
e
a
lg
or
it
hm
r
e
tu
r
ns
to
s
te
p
3.
S
te
p
20
:
e
nd
of
a
lg
or
it
hm
.
4.
R
E
S
U
L
T
S
AND
D
I
S
C
U
S
S
I
O
N
As
s
how
n
a
bove
,
in
s
uf
f
ic
ie
nt
a
tt
e
nt
io
n
w
a
s
pa
id
to
th
e
is
s
ue
s
of
e
ns
ur
in
g
hi
gh
-
qua
li
ty
tr
a
ns
m
is
s
io
n
of
vi
de
o
s
tr
e
a
m
s
in
F
A
N
E
T
in
e
a
r
li
e
r
s
tu
di
e
s
.
In
th
is
s
tu
dy,
we
pr
opos
e
d
an
or
ig
in
a
l
a
lg
or
it
hm
th
a
t
e
s
ti
m
a
te
s
th
e
pr
oba
bi
li
ty
of
e
ns
ur
in
g
hi
gh
qua
li
ty
vi
de
o
br
oa
d
c
a
s
ti
ng.
D
e
pe
ndi
ng
on
th
e
va
lu
e
s
of
th
is
pr
oba
bi
li
ty
,
one
of
th
e
f
o
ll
ow
in
g
s
ol
ut
io
ns
is
r
e
c
om
m
e
nde
d:
tr
a
ns
m
it
a
ne
w
vi
de
o
s
tr
e
a
m
,
r
e
duc
e
th
e
a
ve
r
a
ge
le
ngt
h
of
w
ir
e
le
s
s
c
h
a
nne
ls
,
or
di
s
a
bl
e
th
e
tr
a
ns
m
is
s
io
n
of
a
lo
w
-
in
f
o
r
m
a
ti
ve
vi
de
o
s
tr
e
a
m
.
U
s
in
g
th
is
a
lg
or
it
hm
,
c
om
put
a
ti
ona
l
e
xpe
r
im
e
nt
s
w
e
r
e
pe
r
f
or
m
e
d,
th
e
r
e
s
ul
ts
of
w
hi
c
h
a
r
e
pr
e
s
e
nt
e
d
a
s
f
ol
lo
w
s
.
4.1.
C
om
p
u
t
at
io
n
al
e
xp
e
r
im
e
n
t
s
U
s
in
g
(
1)
to
(
6)
,
a
s
e
r
i
e
s
of
c
om
put
a
ti
ona
l
e
xpe
r
im
e
nt
s
w
a
s
c
a
r
r
ie
d
out
.
T
h
e
r
e
s
u
lt
s
obt
a
in
e
d
a
r
e
s
how
n
on
th
e
de
p
e
nde
nc
e
gr
a
ph
s
at
τ
=
0.5
h
(
F
ig
ur
e
1)
.
T
he
gr
a
p
hs
a
t
d
=
480
m
is
pr
e
s
e
nt
e
d
in
F
i
gur
e
s
2
a
nd
3.
A
na
ly
s
is
of
th
e
pr
e
s
e
nt
e
d
r
e
s
ul
ts
of
c
om
put
a
ti
ona
l
e
xpe
r
im
e
nt
s
s
how
e
d
th
a
t
by
c
ont
r
ol
li
ng
th
e
va
lu
e
s
of
pa
r
a
m
e
te
r
s
λ
,
τ
a
nd
d
,
it
is
po
s
s
ib
le
to
in
c
r
e
a
s
e
th
e
pr
oba
bi
li
ty
o
f
pr
ovi
di
ng
hi
gh
qua
li
ty
vi
de
o
tr
a
ns
m
is
s
io
n
in
th
e
F
A
N
E
T
.
I
t
is
pr
opos
e
d
to
c
ont
r
ol
th
e
va
lu
e
s
of
th
e
a
bove
pa
r
a
m
e
te
r
s
by
de
c
id
in
g
on
s
e
ndi
ng
(
or
r
e
f
us
in
g
to
s
e
nd)
vi
de
o
s
tr
e
a
m
s
,
de
le
ti
ng
(
or
not
bl
oc
ki
ng)
s
e
nt
vi
de
o
s
t
r
e
a
m
s
a
nd
c
ha
ngi
ng
th
e
di
s
ta
nc
e
be
twe
e
n
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J
A
r
ti
f
I
nt
e
ll
I
S
S
N
:
2252
-
8938
A
n al
gor
it
hm
f
or
c
ont
r
ol
li
ng t
he
t
r
ans
m
i
s
s
io
n of
v
id
e
o
s
tr
e
am
s
i
n a f
ly
in
g
…
(
Sal
ah M
ahdi
M
adl
ol
A
lg
haz
al
i
)
4295
s
e
ndi
ng
a
nd
r
e
c
e
iv
in
g
ne
twor
k
node
s
.
W
e
w
il
l
de
e
m
th
e
de
c
is
io
n
to
m
a
na
ge
F
A
N
E
T
vi
de
o
m
oni
to
r
in
g
f
e
a
tu
r
e
s
a
s
c
or
r
e
c
t
if
i
ts
i
m
pl
e
m
e
nt
a
ti
on gua
r
a
nt
e
e
s
a
hi
gh qua
li
ty
of
vi
de
o t
r
a
ns
m
is
s
io
n.
F
ig
ur
e
1.
H
q(
d)
de
pe
nde
nc
e
gr
a
phs
at
τ=
0.5
h
F
ig
ur
e
2.
H
q(
λ
)
de
pe
nde
nc
e
gr
a
phs
at
d=
480
m
F
ig
ur
e
3.
H
q(
τ)
de
pe
nde
nc
e
gr
a
phs
at
d=
480
m
4.2.
C
om
p
ar
at
iv
e
an
al
ys
is
L
e
t'
s
in
tr
oduc
e
th
e
va
r
ia
bl
e
sb
,
r
e
pr
e
s
e
nt
in
g
th
e
s
um
of
f
a
il
ur
e
s
in
vi
de
o
s
tr
e
a
m
tr
a
n
s
m
is
s
io
n
a
nd
th
e
num
be
r
of
vi
de
o
s
tr
e
a
m
s
tr
a
ns
m
it
te
d
w
it
h
an
una
c
c
e
pt
a
bl
e
le
ve
l
of
pa
c
ke
t
lo
s
s
.
T
he
hi
gh
qua
li
ty
of
vi
de
o
br
oa
dc
a
s
ti
ng
w
il
l
be
e
ns
ur
e
d
if
th
e
sb
va
lu
e
doe
s
not
e
xc
e
e
d
th
e
va
lu
e
b
,
a
nd
w
he
r
e
a
is
th
e
num
be
r
of
vi
de
o
s
tr
e
a
m
r
e
que
s
ts
.
T
he
va
lu
e
of
sb
is
e
xpe
c
te
d
not
to
e
xc
e
e
d
a
pe
r
c
e
nt
a
ge
of
th
e
num
be
r
of
vi
de
o
s
tr
e
a
m
r
e
que
s
ts
r
e
c
e
iv
e
d.
T
he
v
a
lu
e
can
be
c
a
lc
ul
a
te
d
u
s
in
g
th
e
(
10)
.
=
⌈
∙
100%
⌉
(
10)
In
th
e
pr
oc
e
s
s
of
c
om
put
a
ti
ona
l
e
xp
e
r
im
e
nt
s
us
in
g
a
s
im
ul
a
ti
o
n
m
ode
l
to
a
s
s
e
s
s
th
e
c
or
r
e
c
tn
e
s
s
of
de
c
is
io
n
-
m
a
ki
ng,
th
e
va
lu
e
of
sb
is
c
a
lc
ul
a
t
e
d.
At
th
e
e
nd
of
each
e
xpe
r
im
e
nt
th
is
va
lu
e
is
c
om
pa
r
e
d
to
th
e
va
lu
e
b
.
If
≤
,
th
e
n
th
e
e
xpe
r
im
e
nt
is
c
ons
id
e
r
e
d
to
ha
ve
pr
ovi
de
d
hi
gh
qua
li
ty
vi
de
o
b
r
oa
dc
a
s
ti
ng.
T
he
pr
oba
bi
li
ty
of
m
a
ki
ng
th
e
r
ig
ht
de
c
is
io
n
on
m
a
na
gi
ng
th
e
tr
a
ns
m
is
s
io
n
of
vi
de
o
s
tr
e
a
m
s
in
F
A
N
E
T
is
m
e
a
s
ur
e
d
by
th
e
(
11)
:
=
ℎ
(
11)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
. 14, No. 5, O
c
to
be
r
2025
:
4290
-
4298
4296
H
e
r
e
E
hq
is
th
e
num
be
r
of
e
xpe
r
im
e
nt
s
in
w
hi
c
h
th
e
hi
gh
qua
li
ty
of
vi
de
o
tr
a
ns
m
i
s
s
io
n
is
e
n
s
ur
e
d;
E
to
t
is
th
e
to
ta
l
num
be
r
of
th
e
e
xpe
r
im
e
nt
s
c
a
r
r
ie
d
out
.
In
th
e
r
e
s
e
a
r
c
h
pr
oc
e
s
s
,
E
to
t=
520
c
om
put
a
ti
ona
l
e
xpe
r
im
e
nt
s
w
e
r
e
c
a
r
r
ie
d
out
to
a
s
s
e
s
s
th
e
c
or
r
e
c
tn
e
s
s
of
d
e
c
is
io
n
-
m
a
ki
ng
f
or
m
a
na
gi
ng
th
e
tr
a
ns
m
is
s
io
n
of
vi
de
o
s
tr
e
a
m
s
in
F
A
N
E
T
u
s
in
g
th
e
pr
opos
e
d
a
lg
or
it
hm
.
W
he
n
pe
r
f
or
m
in
g
e
xpe
r
im
e
nt
s
,
c
a
lc
ul
a
ti
ons
of
va
lu
e
s
α
a
nd
sb
w
e
r
e
c
a
r
r
ie
d
out
,
va
lu
e
s
w
e
r
e
c
a
lc
ul
a
te
d
b
a
c
c
or
di
ng
to
th
e
(
9)
.
At
th
e
e
nd
of
each
e
xpe
r
im
e
nt
,
th
e
sb
va
lu
e
w
a
s
c
om
pa
r
e
d
to
th
e
va
lu
e
b
.
If,
≤
th
e
n
in
th
is
e
xpe
r
im
e
nt
it
w
a
s
r
e
c
or
de
d
to
pr
o
vi
de
hi
gh
qua
li
ty
vi
de
o
br
oa
d
c
a
s
ti
ng.
T
a
bl
e
2
pr
e
s
e
nt
s
a
f
r
a
gm
e
nt
of
th
e
r
e
s
ul
ts
obt
a
in
e
d
in
th
e
c
our
s
e
of
th
e
c
om
put
a
ti
ona
l
e
xpe
r
im
e
nt
s
.
T
h
e
de
f
a
ul
t
va
lu
e
w
a
s
10
%
.
A
na
ly
z
in
g
th
e
e
xpe
r
im
e
nt
a
l
da
ta
le
d
to
th
e
c
om
put
a
ti
on
of
th
e
va
lu
e
th
r
ough
(
10
)
.
T
he
r
e
s
ul
ts
de
m
ons
tr
a
te
d
th
a
t,
w
it
h
th
e
a
ppl
ic
a
ti
on
of
th
e
pr
opos
e
d
a
lg
or
it
hm
,
T
a
bl
e
3
s
how
s
a
f
r
a
gm
e
nt
of
th
e
r
e
s
ul
ts
of
th
e
s
e
e
xpe
r
im
e
nt
s
.
T
he
pr
oba
bi
li
ty
of
m
a
ki
ng
a
c
c
ur
a
te
de
c
i
s
io
ns
r
e
ga
r
di
ng
vi
de
o
s
tr
e
a
m
tr
a
ns
m
is
s
io
n
to
F
A
N
E
T
s
ta
nds
a
t
0.924.
C
om
pa
r
a
bl
e
e
xpe
r
im
e
nt
s
w
e
r
e
unde
r
ta
ke
n
to
a
s
s
e
s
s
de
c
i
s
io
n
-
m
a
ki
ng
a
c
c
ur
a
c
y
in
m
a
na
gi
ng t
he
t
r
a
ns
m
is
s
io
n of
vi
de
o s
tr
e
a
m
s
i
n F
A
N
E
T
w
it
hout
e
m
pl
oyi
ng t
he
pr
opos
e
d a
lg
or
it
hm
, yi
e
ld
in
g a
va
lu
e
P
c
or
r
=
0.761
.
T
hus
,
th
e
us
e
of
th
e
pr
opos
e
d
a
lg
or
it
hm
m
a
ke
s
it
po
s
s
ib
le
to
in
c
r
e
a
s
e
th
e
pr
oba
bi
li
ty
of
m
a
ki
ng t
he
r
ig
ht
de
c
is
io
n on c
ont
r
ol
li
ng t
he
t
r
a
ns
m
is
s
io
n of
vi
de
o s
tr
e
a
m
s
i
n F
A
N
E
T
by 16.3%
.
T
a
bl
e
2.
R
e
s
ul
ts
of
c
om
put
a
ti
ona
l
e
xpe
r
im
e
nt
s
us
in
g
th
e
pr
opos
e
d
a
lg
or
it
hm
E
xpe
r
i
m
e
nt
num
be
r
a
b
sb
≤
1
52
6
4
+
2
46
5
3
+
3
48
5
7
–
…
…
…
…
…
519
56
6
5
+
520
50
5
4
+
T
a
bl
e
3.
R
e
s
ul
ts
of
c
om
put
a
ti
ona
l
e
xpe
r
im
e
nt
s
w
it
hout
us
in
g
th
e
pr
opos
e
d
a
lg
or
it
hm
E
xpe
r
i
m
e
nt
num
be
r
a
b
sb
≤
1
5
0
5
4
+
2
4
8
5
7
–
3
56
6
6
+
…
…
…
…
…
519
4
6
5
6
–
520
5
2
6
5
+
5.
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s
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[
1]
J
.
A
gr
a
w
a
l
,
M
.
K
a
poor
,
a
nd
R
.
T
om
a
r
,
“
A
nove
l
unm
a
nne
d
a
e
r
i
a
l
ve
hi
c
l
e
-
s
i
nk
e
na
bl
e
d
m
obi
l
i
t
y
m
ode
l
f
or
m
i
l
i
t
a
r
y
ope
r
a
t
i
ons
i
n
s
pa
r
s
e
f
l
yi
ng
a
d
-
hoc
ne
t
w
or
k,”
T
r
ans
ac
t
i
ons
on
E
m
e
r
gi
ng
T
e
l
e
c
om
m
uni
c
at
i
ons
T
e
c
hnol
ogi
e
s
,
vol
.
33,
no.
5,
2022,
doi
:
10.1002/
e
t
t
.4466.
[
2]
E
. C
r
uz
, “
A
c
om
pr
e
he
n
s
i
ve
s
ur
ve
y i
n t
ow
a
r
ds
t
o f
ut
ur
e
F
A
N
E
T
s
,”
I
E
E
E
L
at
i
n A
m
e
r
i
c
a T
r
an
s
ac
t
i
ons
, vol
.
16, no. 3,
pp. 876
–
884
,
2018, doi
:
10.1109/
T
L
A
.2018.8358668.
[
3]
I
.
U
.
K
ha
n
e
t
al
.
,
“
M
oni
t
or
i
ng
s
ys
t
e
m
-
ba
s
e
d
f
l
yi
ng
I
oT
i
n
publ
i
c
he
a
l
t
h
a
nd
s
por
t
s
us
i
ng
a
nt
-
e
na
bl
e
d
e
n
e
r
gy
-
a
w
a
r
e
r
out
i
ng,”
J
our
nal
of
H
e
al
t
hc
ar
e
E
ngi
ne
e
r
i
ng
, vol
. 2021, 2021, doi
:
10.1155/
2021/
1686946.
[
4]
A
.
S
r
i
va
s
t
a
va
a
nd
J
.
P
r
a
ka
s
h,
“
F
ut
ur
e
F
A
N
E
T
w
i
t
h
a
ppl
i
c
a
t
i
on
a
nd
e
na
bl
i
ng
t
e
c
hni
que
s
:
a
na
t
om
i
z
a
t
i
on
a
nd
s
u
s
t
a
i
na
bi
l
i
t
y
i
s
s
ue
s
,
”
C
om
put
e
r
Sc
i
e
n
c
e
R
e
v
i
e
w
, vol
. 39, 2021, doi
:
10.1016/
j
.c
os
r
e
v.2020.100359.
[
5]
A
.
H
.
W
he
e
b,
“
F
l
yi
ng
A
d
ho
c
ne
t
w
or
ks
(
F
A
N
E
T
)
:
pe
r
f
or
m
a
nc
e
e
va
l
ua
t
i
on
of
t
opol
ogy
ba
s
e
d
r
out
i
ng
pr
ot
oc
ol
s
,”
I
nt
e
r
nat
i
onal
J
our
nal
of
I
nt
e
r
ac
t
i
v
e
M
obi
l
e
T
e
c
hnol
ogi
e
s
, vol
. 16, no. 4, pp. 137
–
149, 2022,
doi
:
10.3991/
i
j
i
m
.v16i
04.28235.
[
6]
T
. D
. D
i
nh, D
. T
.
L
e
, T
. T
. T
. T
r
a
n, a
nd
R
. K
i
r
i
c
he
k,
“
F
l
yi
ng
a
d
ho
c
ne
t
w
or
k f
or
e
m
e
r
ge
nc
y ba
s
e
d on I
E
E
E
802.11p m
ul
t
i
c
ha
nne
l
M
A
C
pr
ot
oc
o
l
,”
i
n
D
i
s
t
r
i
but
e
d
C
om
put
e
r
and
C
om
m
uni
c
at
i
on
N
e
t
w
or
k
s
(
D
C
C
N
2019)
,
C
ha
m
,
S
w
i
t
z
e
r
l
a
nd:
S
pr
i
nge
r
,
2019,
pp. 479
–
494, doi
:
10.1007/
978
-
3
-
030
-
36614
-
8_37.
[
7]
O
.
T
.
A
bdul
ha
e
,
J
.
S
.
M
a
nde
e
p,
a
nd
M
.
I
s
l
a
m
,
“
C
l
us
t
e
r
-
ba
s
e
d
r
out
i
ng
pr
ot
oc
ol
s
f
or
f
l
yi
ng
a
d
hoc
ne
t
w
or
ks
(
F
A
N
E
T
s
)
,”
I
E
E
E
A
c
c
e
s
s
, vol
. 10, pp. 32981
–
33004, 2022, doi
:
10.1109/
A
C
C
E
S
S
.2022.3161446.
[
8]
F
.
N
oor
,
M
.
A
.
K
ha
n,
A
.
A
l
-
Z
a
hr
a
ni
,
I
.
U
l
l
a
h,
a
nd
K
.
A
.
A
l
-
D
hl
a
n,
“
A
r
e
vi
e
w
on
c
om
m
uni
c
a
t
i
ons
pe
r
s
pe
c
t
i
ve
of
f
l
yi
ng
ad
-
hoc
ne
t
w
or
ks
:
K
e
y
e
na
bl
i
ng
w
i
r
e
l
e
s
s
t
e
c
hnol
ogi
e
s
,
a
ppl
i
c
a
t
i
ons
,
c
ha
l
l
e
nge
s
a
nd
ope
n
r
e
s
e
a
r
c
h
t
opi
c
s
,”
D
r
one
s
,
vol
.
4,
no.
4,
pp.
1
–
14,
2020, doi
:
10.3390/
dr
one
s
4040065.
[
9]
A
.
P
a
nde
y,
P
.
K
.
S
hukl
a
,
a
nd
R
.
A
gr
a
w
a
l
,
“
A
n
a
da
pt
i
ve
f
l
yi
ng
ad
-
hoc
ne
t
w
or
k
(
F
A
N
E
T
)
f
or
di
s
a
s
t
e
r
r
e
s
pons
e
ope
r
a
t
i
ons
t
o
i
m
pr
ove
qua
l
i
t
y of
s
e
r
vi
c
e
(
Q
oS
)
,”
M
ode
r
n P
hy
s
i
c
s
L
e
t
t
e
r
s
B
, vol
. 34, no. 10, 2
020, doi
:
10.1142/
S
0217984920500104.
[
10]
M
.
J
.
Y
a
s
e
r
,
K
.
A
.
P
ol
s
hc
hykov,
a
nd
I
.
K
.
P
ol
s
hc
hi
kov,
“
A
l
gor
i
t
hm
f
or
e
ns
u
r
i
ng
t
he
m
i
n
i
m
um
pow
e
r
c
ons
um
pt
i
on
of
t
he
e
nd
node
i
n
t
he
L
oR
a
W
A
N
ne
t
w
or
k,”
P
e
r
i
odi
c
al
s
of
E
ngi
ne
e
r
i
ng
and
N
at
ur
al
Sc
i
e
nc
e
s
,
vol
.
11,
no.
4,
pp.
168
–
174,
2023,
doi
:
10.21533/
pe
n.v11.i
4.208.
[
11]
S
. W
. L
e
e
e
t
al
.
, “
A
n
e
ne
r
gy
-
a
w
a
r
e
a
nd pr
e
di
c
t
i
ve
f
uz
z
y l
ogi
c
-
ba
s
e
d r
out
i
ng s
c
he
m
e
i
n f
l
yi
ng A
d hoc
ne
t
w
or
ks
(
F
A
N
E
T
s
)
,”
I
E
E
E
A
c
c
e
s
s
, vol
. 9, pp. 129977
–
130005, 2021, doi
:
10.1109/
A
C
C
E
S
S
.2021.311144
4.
[
12]
S
.
B
ha
r
a
ny
e
t
al
.
,
“
E
ne
r
gy
-
e
f
f
i
c
i
e
nt
c
l
us
t
e
r
i
ng
s
c
he
m
e
f
or
f
l
yi
ng
ad
-
hoc
ne
t
w
or
ks
us
i
ng
a
n
opt
i
m
i
z
e
d
l
e
a
c
h
pr
ot
oc
ol
,”
E
ne
r
gi
e
s
,
vol
. 14, no. 19, 2021, doi
:
10.3390/
e
n14196016.
[
13]
S
.
R
e
z
w
a
n
a
nd
W
.
C
hoi
,
“
A
s
ur
ve
y
on
a
ppl
i
c
a
t
i
ons
of
r
e
i
nf
or
c
e
m
e
nt
l
e
a
r
ni
ng
i
n
f
l
yi
ng
ad
-
hoc
ne
t
w
or
ks
,”
E
l
e
c
t
r
oni
c
s
,
vol
.
10,
no. 4, pp. 1
–
19, 2021, doi
:
10.3390/
e
l
e
c
t
r
oni
c
s
10040449.
[
14]
D
.
Y
.
K
i
m
a
nd
J
.
W
.
L
e
e
,
“
I
nt
e
gr
a
t
e
d
t
opol
ogy
m
a
na
ge
m
e
nt
i
n
f
l
yi
ng
a
d
ho
c
ne
t
w
or
ks
:
t
opol
ogy
c
on
s
t
r
uc
t
i
on
a
nd
a
dj
u
s
t
m
e
nt
,”
I
E
E
E
A
c
c
e
s
s
, vol
. 6, pp. 61196
–
61211, 2018, doi
:
10.1109/
A
C
C
E
S
S
.2018.2875679.
[
15]
S
.
D
a
s
,
A
.
S
.
P
a
r
i
ha
r
,
a
nd
S
.
K
.
C
ha
kr
a
bor
t
y,
“
Q
-
F
A
N
E
T
G
S
-
B
S
:
a
s
i
x
-
s
t
a
t
e
r
out
i
ng
m
ode
l
i
n
F
A
N
E
T
f
o
r
pe
r
f
or
m
i
ng
e
f
f
i
c
i
e
nt
da
t
a
t
r
a
ns
f
e
r
,”
W
i
r
e
l
e
s
s
P
e
r
s
onal
C
om
m
uni
c
at
i
ons
, vol
. 135, no. 4, pp. 2145
–
2
164, 2024, doi
:
10.1007/
s
11277
-
024
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11118
-
y.
[
16]
S
.
D
a
ne
s
h
a
nd
J
.
A
.
T
or
ke
s
t
a
ni
,
“
C
L
A
R
A
:
c
l
us
t
e
r
e
d
l
e
a
r
ni
ng
a
ut
om
a
t
a
-
ba
s
e
d
r
out
i
ng
a
l
gor
i
t
hm
f
or
e
f
f
i
c
i
e
nt
F
A
N
E
T
c
om
m
uni
c
a
t
i
on,”
C
l
us
t
e
r
C
om
put
i
ng
, vol
. 27, no. 7, pp. 9569
–
9585, 2024, doi
:
10.1007/
s
10586
-
024
-
04299
-
5.
[
17]
J
.
S
ouz
a
,
J
.
J
a
i
l
t
on,
T
.
C
a
r
va
l
ho,
J
.
A
r
a
új
o,
a
nd
R
.
F
r
a
nc
ê
s
,
“
Q
oS
a
nd
Q
o
E
a
w
a
r
e
r
out
i
ng
p
r
ot
oc
ol
f
o
r
f
l
yi
ng
ad
-
hoc
s
ur
ve
i
l
l
a
nc
e
ne
t
w
or
ks
us
i
ng
f
uz
z
y
i
nf
e
r
e
nc
e
s
ys
t
e
m
s
,”
J
ou
r
nal
of
M
i
c
r
o
w
av
e
s
,
O
pt
oe
l
e
c
t
r
oni
c
s
and
E
l
e
c
t
r
om
agne
t
i
c
A
ppl
i
c
at
i
ons
,
vol
.
19
,
no. 1, pp. 11
–
25, 2020, doi
:
10.1590/
2179
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10742020v19i
11842.
[
18]
W
.
D
.
P
a
r
e
de
s
,
H
.
K
a
us
h
a
l
,
I
.
V
a
ki
l
i
ni
a
,
a
nd
Z
.
P
r
oda
nof
f
,
“
L
oR
a
t
e
c
hnol
ogy
i
n
f
l
yi
ng
a
d
hoc
ne
t
w
or
ks
:
a
s
ur
ve
y
of
c
ha
l
l
e
nge
s
a
nd ope
n i
s
s
ue
s
,”
Se
n
s
or
s
, vol
. 23, no. 5, 2023, doi
:
10.3390/
s
23052403.
[
19]
H
.
L
i
u,
Q
.
C
he
n,
a
nd
P
.
L
i
u,
“
A
n
opt
i
m
i
z
a
t
i
on
m
e
t
hod
of
l
a
r
ge
-
s
c
a
l
e
vi
de
o
s
t
r
e
a
m
c
onc
ur
r
e
nt
t
r
a
ns
m
i
s
s
i
on
f
or
e
dge
c
om
put
i
ng,”
M
at
he
m
at
i
c
s
, vol
. 11, no. 12, 2023, doi
:
10.3390/
m
a
t
h11122622.
[
20]
X
.
Q
i
,
J
.
L
i
,
Z
.
L
v,
a
nd
L
.
X
i
a
o,
“
R
e
i
nf
or
c
e
m
e
nt
l
e
a
r
ni
ng
ba
s
e
d
e
n
e
r
gy
-
e
f
f
i
c
i
e
nt
r
out
i
ng
w
i
t
h
l
a
t
e
nc
y
c
ons
t
r
a
i
nt
s
f
or
F
A
N
E
T
s
,”
G
L
O
B
E
C
O
M
2023
-
2023
I
E
E
E
G
l
obal
C
om
m
uni
c
at
i
ons
C
onf
e
r
e
nc
e
,
K
ua
l
a
L
um
pur
,
M
a
l
a
ys
i
a
,
pp.
2638
–
2643,
2023,
doi
:
10.1109/
G
L
O
B
E
C
O
M
54140.2023.10437037.
[
21]
I
.
K
a
i
s
i
na
,
A
.
A
bi
l
ov,
D
.
V
a
s
i
l
i
e
v,
M
.
A
.
L
a
m
r
i
,
a
nd
A
.
N
i
s
t
yuk,
“
S
i
m
ul
a
t
i
on
a
nd
e
xpe
r
i
m
e
nt
a
l
s
t
udy
of
m
ul
t
i
-
s
our
c
e
a
ppl
i
c
a
t
i
o
n
l
a
ye
r
A
R
Q
f
or
F
A
N
E
T
,”
i
n
I
nt
e
r
ne
t
of
T
hi
ngs
,
Sm
a
r
t
Spac
e
s
,
and
N
e
x
t
G
e
ne
r
at
i
on
N
e
t
w
or
k
s
and
Sy
s
t
e
m
s
(
N
E
W
2A
N
2021,
r
uSM
A
R
T
2021)
,
S
pr
i
nge
r
, 2022, pp. 268
–
283, doi
:
10.1007/
978
-
3
-
030
-
97777
-
1_23.
[
22]
A
.
A
bi
l
ov,
A
.
C
huna
e
v,
M
.
A
.
L
a
m
r
i
,
a
nd
I
.
K
a
i
s
i
na
,
“
R
e
a
l
-
t
i
m
e
vi
de
o
s
t
r
e
a
m
i
ng
w
i
t
h
a
ppl
i
c
a
t
i
on
l
a
ye
r
A
R
Q
i
n
U
A
V
n
e
t
w
or
ks
:
f
i
e
l
d
t
e
s
t
s
,”
2021
44t
h
I
nt
e
r
nat
i
onal
C
onf
e
r
e
nc
e
on
T
e
l
e
c
o
m
m
uni
c
at
i
ons
and
Si
gnal
P
r
oc
e
s
s
i
ng,
T
SP
2021
,
pp.
324
–
328,
2021,
doi
:
10.1109/
T
S
P
52935.2021.9522615.
[
23]
T
.
R
.
B
e
e
gum
,
M
.
Y
.
I
.
I
dr
i
s
,
M
.
N
.
B
.
A
yub,
a
nd
H
.
A
.
S
he
ha
de
h,
“
O
pt
i
m
i
z
e
d
r
out
i
ng
of
U
A
V
s
us
i
ng
bi
o
-
i
ns
pi
r
e
d
a
l
gor
i
t
hm
i
n
F
A
N
E
T
:
a
s
ys
t
e
m
a
t
i
c
r
e
vi
e
w
,”
I
E
E
E
A
c
c
e
s
s
, vol
. 11, pp. 15588
–
15622, 2023,
doi
:
10.1109/
A
C
C
E
S
S
.2023.3244067.
[
24]
G
.
A
m
poni
s
,
T
.
L
a
gka
s
,
P
.
S
a
r
i
gi
a
nni
di
s
,
V
.
V
i
t
s
a
s
,
P
.
F
oul
i
r
a
s
,
a
nd
S
.
W
a
n,
“
A
s
ur
ve
y
on
F
A
N
E
T
r
out
i
ng
f
r
o
m
a
c
r
os
s
-
l
a
ye
r
de
s
i
gn pe
r
s
pe
c
t
i
ve
,”
J
our
nal
of
Sy
s
t
e
m
s
A
r
c
hi
t
e
c
t
ur
e
, vol
. 120, 2021, doi
:
10.1
016/
j
.s
ys
a
r
c
.2021.102281.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
. 14, No. 5, O
c
to
be
r
2025
:
4290
-
4298
4298
[
25]
T
. N
. M
a
hdi
, J
. Q
. J
a
m
e
e
l
,
K
. A
. P
ol
s
hc
hykov, S
. A
.
L
a
z
a
r
e
v, I
. K
. P
ol
s
hc
hyko
v, a
nd V
. K
i
s
e
l
e
v,
“
C
l
us
t
e
r
s
pa
r
t
i
t
i
on a
l
gor
i
t
hm
f
or
a
s
e
l
f
-
or
ga
ni
z
i
ng
m
a
p
f
or
de
t
e
c
t
i
ng
r
e
s
our
c
e
-
i
nt
e
ns
i
ve
da
t
a
ba
s
e
i
nqui
r
i
e
s
i
n
a
ge
o
-
e
c
ol
ogi
c
a
l
m
oni
t
or
i
ng
s
ys
t
e
m
,”
P
e
r
i
odi
c
al
s
of
E
ngi
ne
e
r
i
ng and N
at
ur
al
Sc
i
e
nc
e
s
, vol
. 9, no. 4, pp. 1138
–
1145, D
e
c
. 2021, doi
:
10.21533/
pe
n.v10i
1.2584.
B
I
O
G
R
A
P
H
I
E
S
OF
A
U
T
H
O
R
S
Salah
M
.
M
.
Alghazali
received
a
Ph.D
degree
of
Informatic
s
degree
from
Belogorod
State
University,
Russia
2022.
He
also
holds
his
M.Sc.
(A
pplied
Mathematics
and
Computer
Scienc
e
)
from
Kursk
State
University
,
Russia,
and
his
B.
Sc.
(
Computer
Scienc
e
)
from
Al
Mustansiriya
University
.
Iraq
2005.
He
is
currently
an
Associate
Profes
sor
at
Department
of
Computer
Scienc
e
in
University
of
Kufa,
An
Najaf,
Ira
q.
His
research
includes,
analyze
queries,
image
processing,
prediction
techniques,
self
-
organizing
network
,
and
fuzzy
logic
.
He
has
published
over
12
papers
in
internationa
l
journals
and
conferences.
He
can
be
contacted
at
email:
s
alahm.gh
azali@
uokufa.edu
.iq
.
Wisam
K
.
Madhlo
om
Aljeazna
holds
a
Ph.D
.
of
Engineering
and
Technology
degree
from
South
Russian
State
Polytec
hnic
University,
Russia
202
2.
He
also
received
hi
s
M.Sc.
(Applied
Computer
Systems
Engineering)
from
University
of
East
London,
Malaysi
a
2015,
and
his
B.Sc.
(Computer
Technologies
Engineering)
from
Al
Rafidain
University
College.
Iraq
2010
.
He
is
currently
an
Associate
Profes
sor
at
Control
and
Systems
Engineering
in
University
of
Technology
-
Iraq,
Baghdad,
Iraq.
His
research
inc
ludes,
s
ystem
analysis
,
computer
systems
engineerin
g,
wireless
technologie
s,
using
the
O
bjectARX
programming
environm
ent,
features
of
the
implementation
of
the
NTP
protocol
for
microproc
essor
systems.
He
has
published
over
12
papers
in
internationa
l
journals
and
c
onferences.
He
can
be
contacted
at
email:
wisam.k.madhloo
m@
uotechnology.edu.i
q
.
Murtadh
a
N
.
Rasol
holds
a
Ph.D
.
of
Information
Scienc
e
and
Computer
Equipment
from
Souther
n
Feder
al
University,
Russia
2021.
He
a
lso
received
his
M.Sc
.
(Computer
Scienc
e)
from
the
same
university
2015,
and
his
B.Sc.
(
Computer
Scienc
e)
from
University
of
Thi
-
Qar.
Ir
aq
2007.
He
is
currently
an
associate
prof
essor
at
Department
of
Physics
Scienc
e,
College
of
Scienc
e,
University
of
Thi
-
Qar,
Nasiri
yah,
Iraq.
His
researc
h
includes
:
system
analysis
,
information
science,
and
wireless
technol
ogies.
He
has
published
over
15
papers
in
internationa
l
journals
and
conferences.
He
can
be
contacted
at
email:
murtadha@sci.utq.edu.iq
.
Konstantin
A
.
Polshchykov
is
a
Doctor
of
Technical
Scienc
es,
specializing
in
"
System
analysis
,
control
and
information
processing"
and
a
Profess
or
at
the
Department
of
Information
and
Robotic
Systems
at
Belgorod
State
University,
Russi
a.
His
research
interests
include
mobile
ad
hoc
networks
,
internet
of
things
,
decision
suppo
rt
methods
and
models,
neural
networks,
and
fuzzy
inferenc
e.
He
is
the
author
of
more
than
15
0
scientific
publications
in
peer
-
reviewed
publications.
He
can
be
contacted
at
email:
polshchykov@
mail.ru
.
Rodion
V
.
Likhoshersto
v
completed
his
postgraduate
studies
in
the
specialty
"
System
analysis
,
manageme
nt
and
information
processing"
at
the
Department
of
Applied
Informatics
and
Information
Technologies
of
Belgorod
State
Universi
ty,
Russia.
His
research
interests
include
wireless
self
-
organizing
networks,
decision
support
methods
and
models,
and
artificial
intelligence
.
He
is
the
author
of
more
than
10
scientific
publi
cations
in
peer
-
reviewed
publications.
He
can
be
contacted
at
email:
oaqwater@yandex.ru
.
Evaluation Warning : The document was created with Spire.PDF for Python.