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
.
1
4
, N
o.
1
,
F
e
bua
r
y
202
5
, pp.
822
~
832
I
S
S
N
:
2252
-
8938
,
D
O
I
:
10.11591/
ij
a
i.
v
1
4
.i
1
.pp
822
-
832
822
Jou
r
n
al
h
om
e
page
:
ht
tp
:
//
ij
ai
.
ia
e
s
c
or
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.c
om
D
e
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c
t
i
on
an
d
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l
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ac
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w
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g b
e
e
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a
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on
-
d
e
m
an
d
d
i
st
an
c
e
ve
c
t
or
S
r
ik
an
t
h
P
al
a, P
r
as
ad
M
ad
d
u
la
, K
ir
an
S
r
e
e
P
ok
k
u
l
u
r
i,
S
u
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il
P
at
t
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m
, R
am
ac
h
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d
r
a R
ao Ku
r
ad
a
,
R
am
u
Y
ad
aval
li
D
e
pa
r
t
m
e
nt
of
C
om
put
e
r
S
c
i
e
nc
e
a
nd E
ngi
ne
e
r
i
ng, S
hr
i
V
i
s
hnu E
ngi
ne
e
r
i
ng C
ol
l
e
ge
f
or
W
om
e
n, B
hi
m
a
va
r
a
m
, I
ndi
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
a
n 15, 2024
R
e
vi
s
e
d
O
c
t
18, 2024
A
c
c
e
pt
e
d
O
c
t
23, 2024
Mobile
adhoc
networks
(
MANETs
)
are
self
-
configuri
ng
networks
with
a
dynamic
infrastructure
suit
for
real
world
applications.
Due
to
the
expo
nential
increase
in
the
network
devices
an
efficie
nt
routing
algorithm
for
d
ynamic
network
adhering
the
security
issues
is
a
critical
challenge
needs
to
be
addressed.
This
article
attempt
s
to
address
this
issue
with
the
implemen
tion
of
ad
-
hoc
on
-
demand
distance
vector
(AODV)
routing
approach,
which
is
the
best
of
its
kind
in
the
dynamic
network
design
of
MANETs.
The
prima
ry
goal
is
to
address
securi
ty
attack
weaknesses
through
the
implementat
ion
of
dynamic
topologies
and
reactive
routing.
To
this
end,
a
bio
-
inspired
swarm
intelligence
algorithm
called
Bees
a
lgorithm
is
used
to
emulate
the
AODV
technique.
In
order
to
provide
a
lightweight
solution
that
integrates
t
he
Bee
algorit
hm
and
AODV
routing
,
this
study
presents
a
unique
algorit
hm
called
Bee
-
AODC.
The
proposed
Bee
-
AODC
algorithm
possess
the
bo
th
the
AODV
'
s
dynamic
topology
construction
capabilities
and
the
Bee
algo
rithm'
s
foraging
strategy
which
effectively
address
security
weaknesses
by
cre
ating
a
dynamic
network
topology
for
ad
hoc
routing.
By
using
the
sug
gested
Bee
-
AODC
algorithm
instead
of
the
traditional
AODV
routing
m
ethod,
throughput
is
increase
d
by
12.87%
while
packet
loss,
latency,
and
energy
consumpt
ion are red
uced by 2
0%, 40%,
and 18%,
respectivel
y.
K
e
y
w
o
r
d
s
:
Ad
-
h
oc
o
n
-
d
e
m
a
n
d d
is
ta
nc
e
ve
c
to
r
B
e
e
-
ad
-
hoc
on
-
de
m
a
nd
di
s
ta
nc
e
ve
c
to
r
B
e
e
a
lg
or
it
hm
B
la
c
k
-
hol
e
a
tt
a
c
k
M
obi
le
a
dhoc
ne
twor
k
Q
ua
li
ty
of
s
e
r
vi
c
e
This is an
open
acce
ss artic
le unde
r the
CC BY
-
SA
license.
C
or
r
e
s
pon
di
n
g A
u
th
or
:
S
r
ik
a
nt
h P
a
la
D
e
pa
r
tm
e
nt
of
C
om
put
e
r
S
c
ie
nc
e
a
nd E
ngi
ne
e
r
in
g
,
S
hr
i
V
is
hnu E
ngi
ne
e
r
in
g C
ol
le
ge
f
or
W
om
e
n
B
hi
m
a
va
r
a
m
, A
ndhr
a
P
r
a
de
s
h, I
ndi
a
E
m
a
il
:
s
r
e
e
ka
nt
h
.pa
la
@
gm
a
il
.c
om
1.
I
N
T
R
O
D
U
C
T
I
O
N
T
he
gl
oba
l
m
a
r
ke
t
is
m
a
r
c
hi
ng
to
w
a
r
ds
th
e
di
gi
ti
z
a
ti
on
du
e
to
th
e
e
m
e
r
gi
ng
in
f
or
m
a
ti
on
a
nd
c
om
m
uni
c
a
ti
on
te
c
hnol
ogy
(
I
C
T
)
to
ol
s
[
1
]
w
he
r
e
th
e
da
ta
s
e
a
m
le
s
s
ly
ne
e
d
s
to
be
tr
a
ns
f
e
r
r
e
d
di
gi
ta
l
f
or
m
a
t
f
o
r
e
a
s
e
of
a
c
c
e
s
s
ib
il
it
y ove
r
t
he
s
m
a
r
t
de
vi
c
e
s
c
onne
c
te
d i
n a
w
ir
e
d or
w
ir
e
le
s
s
a
ppr
oa
c
h. I
n
th
e
c
ur
r
e
nt
s
c
e
na
r
io
th
e
gl
oba
l
m
a
r
ke
t
is
f
oc
us
in
g
on
da
ta
tr
a
n
s
f
e
r
us
in
g
th
e
w
ir
e
le
s
s
m
e
di
um
.
W
ir
e
le
s
s
ad
-
hoc
ne
twor
k
s
(
W
A
N
E
T
s
)
us
e
s
th
e
w
ir
e
le
s
s
m
e
di
um
f
or
th
e
da
ta
tr
a
ns
f
e
r
a
m
ong
th
e
he
te
r
oge
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ous
s
ta
ti
c
node
s
in
a
ne
twor
k
us
in
g
a
c
e
nt
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li
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e
d
in
f
r
a
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tr
uc
tu
r
e
f
r
a
m
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w
or
k.
M
obi
le
a
dhoc
ne
twor
k
(
M
A
N
E
T
s
)
a
r
e
th
e
e
xt
e
ns
io
n
of
W
A
N
E
T
s
in
c
or
por
a
te
s
th
e
he
te
r
oge
ne
ous
node
s
w
it
h
m
obi
le
na
tu
r
e
a
nd
doe
s
n’
t
bi
nd
to
th
e
c
e
nt
r
a
li
z
e
d
f
r
a
m
e
w
or
ks
.
M
A
N
E
T
s
a
r
e
in
de
p
e
nde
nt
a
nd
in
f
r
a
s
tr
uc
tu
r
e
le
s
s
ne
twor
k
s
w
hi
c
h
doe
s
n’
t
m
a
in
ta
in
a
c
e
nt
r
a
li
z
e
d
nod
e
f
or
c
ont
r
ol
li
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a
nd
c
oor
di
na
ti
ng
th
e
di
f
f
e
r
e
nt
ne
twor
ki
ng
node
s
.
R
out
in
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of
da
ta
f
r
om
th
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our
nc
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to
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c
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iv
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r
node
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a
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out
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ne
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ds
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be
e
s
ta
bl
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he
d
a
m
ong
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node
s
by
vi
c
in
it
y
a
nd
c
ove
r
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ge
be
twe
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n
th
e
node
s
us
in
g
th
e
in
te
r
f
e
r
e
nc
e
r
a
nge
.
R
out
in
g
of
da
ta
f
r
om
a
s
our
c
e
to
de
s
ti
na
ti
on
in
th
e
M
A
N
E
T
s
ne
e
d
s
to
a
dopt
f
or
ne
twor
k
to
pol
ogy
in
a
dyna
m
ic
a
ppr
oa
c
h
[
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
D
e
te
c
ti
on and av
oi
danc
e
of
bl
ac
k
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hol
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at
ta
c
k
i
n m
obi
le
adho
c
ne
tw
or
k
u
s
in
g be
e
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hoc
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(
Sr
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h P
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a
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823
M
A
N
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T
s
a
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ba
s
ic
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ll
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[
3]
,
[
4]
.
A
n
e
f
f
e
c
ti
ve
r
out
in
g
pr
ot
oc
ol
m
us
t
ha
ndl
e
e
s
ta
bl
i
s
hi
ng
ne
twor
k
li
nk
b
e
twe
e
n
nod
e
s
s
o
th
a
t
da
ta
m
a
y
be
tr
a
ve
r
s
e
d
f
r
om
th
e
s
our
c
e
to
th
e
d
e
s
ti
na
ti
on
w
hi
le
ut
il
iz
in
g
e
ne
r
gy
r
e
s
our
c
e
s
a
nd
a
voi
di
ng
n
e
twor
k
s
e
c
ur
it
y
f
la
w
s
.
A
r
out
in
g
pr
ot
oc
ol
th
a
t
i
s
e
f
f
e
c
ti
ve
m
us
t
c
onve
y
d
a
ta
in
r
e
s
pon
s
e
to
dyna
m
ic
to
pol
ogi
c
a
l
c
ha
ng
e
s
by
m
odi
f
yi
ng
th
e
ne
twor
k
c
onne
c
ti
on
w
it
hout
d
e
pl
e
ti
ng
th
e
ba
tt
e
r
y.
A
n
a
tt
a
c
ke
r
u
s
in
g
a
pa
s
s
iv
e
a
tt
a
c
k
on
a
ne
twor
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w
il
l
li
s
te
n
in
a
nd
ta
ke
m
a
te
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l
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a
c
ke
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in
a
n
a
c
ti
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a
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k
[
5]
is
e
a
ge
r
to
c
ol
le
c
t
c
ont
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ha
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c
om
pr
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gr
it
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tt
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pl
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p by
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it
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f
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bl
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c
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a
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us
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r
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pr
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;
th
is
is
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c
a
n
be
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e
s
ol
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d
by
in
te
gr
a
ti
ng t
he
bi
oi
ns
pi
r
e
d be
e
a
lg
or
it
hm
w
it
h t
he
c
ur
r
e
nt
ad
-
hoc
on
-
de
m
a
nd dis
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nc
e
ve
c
to
r
(
AODV
)
.
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la
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out
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s
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R
e
a
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h
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te
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tu
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e
.
A
n
e
f
f
e
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ti
ve
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out
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a
lg
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hm
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or
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a
t
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s
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s
e
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it
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pr
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s
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ig
ni
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th
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t
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to
th
e
e
xpon
e
n
ti
a
l
r
is
e
in
ne
twor
k
de
vi
c
e
s
.
B
y
a
ppl
yi
ng
th
e
A
O
D
V
r
out
in
g
te
c
hni
que
,
th
e
be
s
t
of
it
s
ty
pe
in
th
e
dyna
m
ic
ne
t
w
or
k
a
r
c
hi
te
c
tu
r
e
of
M
A
N
E
T
s
,
th
is
pa
pe
r
tr
ie
s
to
s
ol
ve
th
is
pr
obl
e
m
.
T
he
m
a
in
obj
e
c
ti
ve
is
to
m
it
ig
a
te
s
e
c
ur
it
y
a
tt
a
c
k
vul
ne
r
a
bi
li
ti
e
s
by
ut
il
iz
in
g
r
e
a
c
ti
ve
r
out
in
g
a
nd
dyna
m
ic
to
pol
ogi
e
s
.
I
n
or
de
r
to
do
th
is
,
th
e
A
O
D
V
m
e
th
od
is
im
it
a
te
d
by
th
e
B
e
e
s
s
ys
t
e
m
,
a
bi
o
-
in
s
pi
r
e
d
s
w
a
r
m
in
te
ll
ig
e
nc
e
s
ys
te
m
.
T
hi
s
w
or
k
in
tr
oduc
e
s
a
nove
l
m
e
th
od
c
a
ll
e
d
B
e
e
-
A
O
D
C
,
w
hi
c
h
c
o
m
bi
ne
s
th
e
B
e
e
a
lg
or
it
hm
a
nd A
O
D
V
r
out
in
g t
o pr
oduc
e
a
l
ig
ht
w
e
ig
ht
s
ol
ut
io
n. T
he
s
ugg
e
s
te
d
B
e
e
-
A
O
D
C
a
lg
or
it
hm
s
uc
c
e
s
s
f
ul
ly
a
ddr
e
s
s
e
s
s
e
c
ur
it
y
f
la
w
s
by
ge
ne
r
a
ti
ng
a
dyna
m
ic
ne
twor
k
to
pol
ogy
f
or
a
d
hoc
r
out
in
g.
I
t
doe
s
th
is
by
c
om
bi
ni
ng
th
e
A
O
D
V
'
s
dyna
m
ic
to
pol
ogy
c
r
e
a
ti
on
c
a
p
a
bi
li
ti
e
s
w
it
h
th
e
f
or
a
gi
ng
a
ppr
oa
c
h
of
th
e
B
e
e
a
lg
or
it
hm
.
T
he
ove
r
a
ll
c
ont
e
nt
of
th
e
pa
pe
r
is
a
s
m
e
nt
io
ne
d
.
S
e
c
ti
on
2
e
xpl
a
in
s
th
e
ope
r
a
ti
ona
l
f
unc
ti
oni
ng
A
O
D
V
r
out
in
g pr
ot
oc
ol
w
it
h bl
a
c
k
-
hol
e
a
tt
a
c
k
. S
e
c
ti
on
3 de
s
c
r
ib
e
s
t
he
r
e
vi
e
w
of
s
im
il
a
r
w
or
ks
f
or
t
hi
s
w
or
k
.
S
e
c
ti
on
4
e
m
pha
s
iz
e
s
on
th
e
m
e
th
odol
ogi
c
a
l
im
pl
e
m
e
nt
a
ti
on
.
S
e
c
ti
on
5
f
oc
us
e
s
on
th
e
r
e
s
ul
ts
obt
a
in
e
d
.
S
e
c
ti
on
6 i
ll
us
tr
a
te
s
t
he
c
onc
lu
s
io
n w
it
h i
t
it
s
f
ut
ur
e
s
c
op
e
.
2.
F
U
N
C
T
I
O
N
I
N
G
O
F
A
O
D
V
R
O
U
T
I
N
G
P
R
O
T
O
C
O
L
WI
T
H
B
L
A
C
K
-
H
O
L
E
A
T
T
A
C
K
B
la
c
k
-
hol
e
a
tt
a
c
k
is
a
n
a
tt
a
c
k
w
hi
c
h
is
de
li
be
r
a
te
ly
a
c
ti
ve
in
na
tu
r
e
w
he
r
e
th
e
node
tr
ie
s
to
de
c
e
iv
e
s
th
e
ot
he
r
node
s
in
th
e
ne
twor
k
a
s
a
n
a
c
ti
ve
f
unc
ti
ona
l
node
w
it
h
m
in
im
a
l
di
s
ta
nc
e
f
or
th
e
ope
r
a
ti
ona
l
de
s
ti
na
ti
on
node
.
I
n
-
or
de
r
to
de
c
e
iv
e
th
e
s
our
c
e
node
th
e
bl
a
c
k
hol
e
nod
e
s
e
nd
it
s
r
out
in
g
-
ta
bl
e
to
a
s
our
c
e
node
a
s
a
r
e
li
a
bl
e
in
te
r
m
e
di
a
te
node
.
T
he
node
s
a
dj
a
c
e
nt
to
s
our
c
e
is
dr
a
w
n
in
to
a
n
il
lu
s
io
n
a
s
th
e
da
ta
is
tr
a
ve
r
s
in
g
to
r
e
li
a
bl
e
node
w
it
h
m
in
im
a
l
di
s
ta
nc
e
to
th
e
de
s
ti
na
ti
on
node
.
S
ubs
e
que
nt
ly
th
e
il
lu
s
io
n
is
c
r
e
a
te
d
f
or
th
e
ope
r
a
ti
ona
l
-
node
s
i
n t
hi
s
ne
twor
k, t
r
y t
o s
e
nd t
he
d
a
ta
t
hr
ough t
hi
s
node
but
n
e
e
ds
t
o i
de
nt
if
ie
d a
s
a
bl
a
c
k hole
node
.
B
la
c
k
-
hol
e
node
r
e
c
e
iv
e
s
a
ll
th
e
d
a
ta
pa
c
ke
t
s
f
r
om
th
e
di
s
ti
ngui
s
he
d
node
s
in
th
a
t
n
e
twor
k
a
c
ti
ng
a
s
r
e
li
a
bl
e
in
te
r
m
e
di
a
te
node
f
or
th
e
ir
da
ta
tr
a
ve
r
s
a
l
f
r
om
it
s
s
our
c
e
to
th
e
de
s
ti
na
ti
on.
B
la
c
k
-
hol
e
node
in
s
te
a
d
of
f
or
w
a
r
di
ng
th
e
pa
c
ke
ts
,
di
s
c
a
r
ds
th
e
pa
c
k
e
ts
in
th
e
ne
twor
k,
m
a
y
le
a
d
to
th
e
in
c
r
e
a
s
e
in
n
e
twor
k
tr
a
f
f
ic
a
nd
c
r
e
a
ti
ng
a
c
onge
s
te
d
n
e
twor
k
w
il
l
c
ol
la
ps
e
to
ta
l
ne
twor
k.
D
a
ta
-
tr
a
ns
m
is
s
io
n
f
r
om
s
our
c
e
node
to
th
e
de
s
ti
na
ti
on
node
a
c
tu
a
ll
y
in
it
ia
te
s
w
it
h
a
r
e
que
s
t
m
e
s
s
a
ge
f
r
om
th
e
s
our
c
e
node
to
ne
ig
hbor
in
g
node
s
w
it
h
in
it
s
vi
c
in
it
y
r
a
nge
.
S
our
c
e
node
a
f
te
r
r
e
c
e
iv
in
g
a
n
a
c
knowle
dge
m
e
nt
f
o
r
it
s
r
e
que
s
t
b
y
th
e
r
out
in
g
ta
bl
e
s
f
r
om
it
s
c
or
r
e
s
ponding
ne
ig
hbor
node
s
in
r
e
ga
r
ds
th
e
de
s
ti
na
ti
on
node
.
S
our
c
e
node
f
or
w
a
r
ds
th
e
da
ta
pa
c
ke
ts
to
it
s
c
or
r
e
s
ponding neighbor
node
s
t
o t
r
a
ve
r
s
e
t
o i
ts
a
ppr
opr
ia
te
de
s
t
in
a
ti
on. B
la
c
k
-
hol
e
node
c
r
e
a
te
s
a
n i
ll
us
io
n t
o
it
s
c
or
r
e
s
ponding nodes
a
s
a
r
e
li
a
bl
e
node
a
nd r
e
c
e
iv
e
t
he
pa
c
ke
ts
f
r
om
i
ts
ne
ig
hbor
a
nd dis
c
a
r
ds
t
he
r
e
c
e
iv
e
d
pa
c
ke
ts
f
r
om
th
e
s
our
c
e
nod
e
.
I
de
a
ll
y
th
e
c
a
te
gor
iz
a
ti
on
of
th
e
b
l
a
c
k
-
hol
e
is
b
a
s
e
d
upon
it
s
f
unc
ti
ona
l
ope
r
a
ti
on,
s
in
gl
e
a
tt
a
c
ke
r
node
op
e
r
a
ti
ng
in
di
vi
dua
ll
y
a
nd
c
o
-
ope
r
a
ti
ve
b
la
c
k
-
hol
e
a
tt
a
c
k
w
he
r
e
a
tt
a
c
ke
r
is
op
e
r
a
te
d
c
ol
le
c
ti
ve
ly
w
it
h
ot
he
r
f
unc
ti
ona
ll
y
a
c
ti
ve
node
s
.
B
la
c
k
-
hol
e
a
tt
a
c
k
de
gr
a
de
s
th
e
pe
r
f
or
m
a
nc
e
of
th
e
ne
twor
k
th
r
oughput
[
6]
,
[
7]
lo
s
s
e
s
th
e
r
e
li
a
bi
li
ty
of
th
e
ne
twor
k
a
nd
f
in
a
ll
y
c
om
m
uni
c
a
ti
on
s
y
s
te
m
it
to
ta
ll
y
c
ol
la
ps
e
d.
T
he
F
ig
ur
e
1
s
pe
c
if
ie
s
th
e
b
la
c
k
-
hol
e
a
tt
a
c
k
in
M
A
N
E
T
s
,
da
ta
pa
c
ke
ts
ne
e
d
to
be
r
out
e
d
f
r
om
th
e
s
our
c
e
‘
S
’
to
t
he
de
s
ti
na
ti
on
‘
D
’
but
t
he
i
nt
e
r
m
e
di
a
te
nod
e
‘
B
’
w
il
l
b
e
a
bl
a
c
k hole
nod
e
a
nd
i
t
dr
ops
a
ll
t
he
pa
c
ke
t
be
f
or
e
r
e
a
c
hi
ng t
o t
he
de
s
ti
na
ti
on.
2
.1.
Ad
-
h
oc
on
-
d
e
m
an
d
d
is
t
an
c
e
ve
c
t
or
r
ou
t
in
g p
r
ot
oc
ol
AODV
is
r
e
a
c
ti
ve
r
out
in
g
pr
ot
oc
ol
us
e
d
in
M
A
N
E
T
s
,
c
om
bi
ne
s
th
e
f
unc
ti
oni
ng
of
r
e
-
a
c
ti
ve
a
nd
pr
o
-
a
c
ti
ve
r
out
in
g
pr
ot
oc
ol
s
li
ke
dyna
m
ic
s
our
c
e
r
out
in
g
(
D
S
R
)
a
nd
de
s
ti
na
ti
on
s
e
que
nc
e
d
di
s
ta
nc
e
ve
c
to
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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I
nt
J
A
r
ti
f
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nt
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V
ol
.
1
4
, N
o.
1
,
F
e
br
ua
r
y
202
5
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822
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832
824
(
D
S
D
V
)
.
A
O
D
V
is
ha
vi
ng
be
tt
e
r
pe
r
f
or
m
a
nc
e
m
e
tr
ic
s
[
6]
,
[
7]
w
he
n
c
om
pa
r
e
d
to
th
e
ot
he
r
r
e
a
c
ti
ve
r
out
in
g
pr
ot
oc
ol
D
S
R
.
A
O
D
V
[
8]
us
e
s
two
c
ont
r
ol
m
e
s
s
a
ge
s
r
out
e
-
r
e
que
s
t
(
R
-
R
E
Q
)
a
nd
R
-
R
E
P
f
or
th
e
c
onne
c
ti
on
e
s
ta
bl
is
hm
e
nt
f
r
om
th
e
s
our
c
e
to
th
e
de
s
ti
na
ti
on.
I
n
th
e
c
ont
e
xt
of
c
onne
c
ti
on
e
s
ta
bl
is
hm
e
nt
,
th
e
s
our
c
e
node
br
oa
dc
a
s
ts
th
e
R
-
R
E
Q
c
ont
r
ol
m
e
s
s
a
g
e
to
a
ll
of
it
s
a
dj
a
c
e
nt
node
s
a
n
d
th
e
in
te
r
m
e
di
a
te
node
s
f
or
w
a
r
ds
th
e
c
ont
r
ol
m
e
s
s
a
ge
s
to
de
s
ti
na
ti
on
node
.
T
he
de
s
ti
na
ti
on
node
a
c
knowle
dge
s
th
e
in
te
r
m
e
di
a
te
node
s
w
it
h
r
e
pl
y
m
e
s
s
a
ge
R
-
R
E
P
f
or
th
e
r
e
que
s
t
m
e
s
s
a
g
e
it
ha
s
r
e
c
e
iv
e
d.
S
our
c
e
node
upon
r
e
c
e
iv
in
g
th
e
r
e
pl
y
m
e
s
s
a
ge
f
r
om
th
e
de
s
ti
na
ti
on
node
s
to
ps
br
oa
dc
a
s
ti
ng
of
th
e
r
e
qu
e
s
t
m
e
s
s
a
ge
s
to
it
s
a
dj
a
c
e
nt
node
s
.
T
he
p
e
r
f
or
m
a
nc
e
of
th
e
pr
ot
oc
ol
de
gr
a
de
s
a
s
t
he
i
nt
e
r
m
e
di
a
te
node
a
r
e
vul
ne
r
a
bl
e
f
or
a
tt
a
c
ks
l
ik
e
bl
a
c
k
-
hol
e
a
tt
a
c
k. B
la
c
k
-
hol
e
a
tt
a
c
k
s
ig
ni
f
ic
a
nt
ly
a
f
f
e
c
ts
th
e
ne
twor
k
pe
r
f
or
m
a
nc
e
m
e
tr
ic
s
li
ke
th
e
pa
c
ke
t
-
de
li
ve
r
y
-
r
a
ti
o,
th
r
oughput,
e
nd
-
to
-
e
nd
de
la
y.
2
.
2
.
C
h
al
le
n
ge
s
T
he
ba
s
ic
is
s
u
e
ne
e
d
s
to
be
a
ddr
e
s
s
e
d
in
a
ny
ne
twor
k
is
th
e
s
c
a
la
bi
li
ty
[
9]
pr
obl
e
m
.
I
f
th
e
node
s
of
th
e
th
e
ne
twor
k
‘
n’
in
c
r
e
a
s
e
s
,
th
e
n
th
e
th
e
th
r
oughput
of
th
e
ne
twor
k
de
c
r
e
a
s
e
s
in
th
e
1/
√n
pe
r
c
e
nt
a
g
e
.
H
e
r
e
th
e
ba
s
ic
‘
n’
va
lu
e
de
pe
nds
upon
th
e
th
e
s
im
ul
a
ti
on
c
onduc
te
d
s
qua
r
e
d
a
r
e
a
.
A
O
D
V
is
one
of
th
e
e
f
f
ic
ie
nt
r
e
a
c
ti
ve
r
out
in
g
pr
ot
oc
ol
s
f
or
th
e
c
onne
c
ti
on
e
s
ta
bl
is
hm
e
nt
f
r
om
th
e
s
o
ur
c
e
to
de
s
ti
na
ti
on.
I
t
f
in
ds
a
s
hor
te
s
t
opt
im
a
l
pa
th
f
or
t
he
c
om
m
uni
c
a
ti
on by ma
in
ta
in
in
g t
he
de
c
e
nt
s
e
c
ur
it
y s
ta
nda
r
ds
. B
la
c
k hole
i
s
t
he
one
of
t
he
popula
r
a
tt
a
c
ks
a
im
s
to
pr
e
ve
nt
th
e
c
om
m
uni
c
a
ti
on
be
twe
e
n
th
e
node
s
.
A
O
D
V
a
im
s
on
c
onn
e
c
ti
on
e
s
ta
bl
is
hm
e
nt
f
or
e
f
f
e
c
ti
ve
r
out
in
g
be
twe
e
n
th
e
node
s
but
not
f
oc
us
e
s
on
id
e
nt
if
yi
ng
th
e
bl
a
c
k
hol
e
a
tt
a
c
k
in
th
e
ne
twor
k.
T
hi
s
pa
pe
r
f
oc
us
e
s
on
th
e
im
pr
ovi
ng
th
e
A
O
D
V
a
lg
or
it
hm
in
de
te
c
ti
o
n
a
nd
pr
e
ve
nt
io
n
of
th
e
bl
a
c
k
hol
e
a
tt
a
c
k
us
in
g
th
e
bi
o
-
in
s
pi
r
e
d
te
c
hni
que
s
li
ke
B
e
e
’
s
a
lg
or
it
hm
[
10]
.
A
s
w
a
r
m
in
te
ll
ig
e
nc
e
a
lg
or
it
hm
li
ke
B
e
e
-
A
O
D
V
us
e
d
f
or
de
ve
lo
pi
ng a
dyna
m
ic
ne
twor
k t
opol
ogy a
im
s
on bla
c
k hole
a
tt
a
c
k.
F
ig
ur
e
1. B
la
c
k
-
hol
e
a
tt
a
c
k
in
a
ne
twor
k
3.
L
I
T
E
R
E
A
T
U
R
E
R
E
V
I
E
W
T
hi
s
s
e
c
ti
on
di
s
c
u
s
s
e
s
a
bout
th
e
de
te
c
ti
on
a
nd
pr
e
ve
nt
io
n
of
b
l
a
c
k
-
hol
e
a
tt
a
c
k
in
th
e
M
A
N
E
T
s
.
T
he
c
ha
r
a
c
te
r
is
ti
c
s
of
th
e
node
a
nd
de
pl
oym
e
nt
of
th
e
node
s
in
th
e
ne
twor
k
e
xpl
oi
ts
th
e
vul
ne
r
a
bi
li
ty
of
th
e
ne
twor
k
a
r
e
li
a
bl
e
f
or
th
e
b
la
c
k
-
hol
e
a
tt
a
c
k.
T
hi
s
s
e
c
ti
on
c
le
a
r
ly
e
m
ph
a
s
iz
e
s
th
e
r
ol
e
of
bi
o
-
in
s
pi
r
e
d
a
lg
or
it
hm
s
f
o
r
de
te
c
ti
on
a
nd
pr
e
ve
nt
io
n
of
b
la
c
k
-
hol
e
a
tt
a
c
k
in
M
A
N
E
T
s
.
N
od
e
s
in
M
A
N
E
T
s
a
r
e
lo
w
pow
e
r
e
ne
r
gy
e
qui
ppe
d
de
vi
c
e
s
, t
he
r
e
i
s
a
ne
e
d f
or
t
he
t
im
e
s
ync
hr
oni
z
a
ti
on pr
oc
e
s
s
a
m
ong the
node
s
f
or
t
he
p
r
ope
r
e
nd
-
to
-
e
nd de
la
y
a
m
ong
th
e
node
s
.
A
s
e
c
ur
e
s
ync
hr
oni
z
a
ti
o
n
pr
ot
oc
ol
is
a
lwa
y
s
r
obus
t
f
r
om
th
e
a
tt
a
c
ks
.
A
O
D
V
to
be
r
obu
s
t
th
e
r
e
i
s
hi
ghe
r
i
m
por
ta
nc
e
f
or
t
im
e
-
to
-
l
iv
e
(
T
T
L
)
f
or
t
he
s
ync
hr
oni
z
a
ti
on a
m
ong the
c
ont
r
ol
m
e
s
s
a
g
e
s
R
-
R
E
Q
a
nd
R
-
R
E
P
.
K
a
li
a
a
nd
S
ha
r
m
a
[
11]
s
pe
c
if
ie
s
a
n
e
w
ba
it
in
g
te
c
hni
que
de
ve
lo
pe
d
by
th
e
s
our
c
e
r
out
in
g
node
it
s
e
lf
.
R
R
E
Q
c
ont
r
ol
m
e
s
s
a
ge
c
ons
is
ti
ng
of
th
e
s
our
c
e
-
id
a
nd
s
our
c
e
s
e
que
nc
e
num
be
r
(
S
S
N
)
is
br
oa
dc
a
s
te
d
to
a
ll
a
dj
a
c
e
nt
nod
e
s
in
th
e
r
e
s
pe
c
ti
ve
ne
twor
k.
T
he
bl
a
c
k
node
i
n
th
e
c
or
r
e
s
ponding
ne
twor
k
r
e
s
ponds
w
it
h
R
-
R
E
P
w
it
h
a
de
s
ti
na
ti
on
s
e
que
nc
e
num
be
r
(
D
S
N
)
gr
e
a
te
r
th
a
n
th
e
S
S
N
but
th
e
r
e
is
no
s
uc
h
node
in
th
is
gr
oup
gr
e
a
te
r
th
e
s
pe
c
if
e
d
S
S
N
w
hi
c
h
th
e
s
our
c
e
-
node
is
a
w
a
r
e
of
it
.
T
he
n
s
our
c
e
node
s
ig
na
ls
a
le
r
t
m
e
s
s
a
ge
by
r
a
is
in
g a
n a
la
r
m
t
o a
ll
t
he
ne
ig
hbor
in
g node
s
r
e
ga
r
di
ng t
he
e
f
f
e
c
te
d node
. I
ni
ti
a
l
li
m
it
a
ti
on w
it
h t
hi
s
t
e
c
hni
que
is
, t
he
r
e
i
s
a
pos
s
ib
li
li
ty
a
s
s
um
in
g t
ha
t
e
f
f
e
c
te
d node
i
s
not
s
m
a
r
t
e
nough. I
f
i
t
is
a
s
m
a
r
t
bl
a
c
k hole
node
, t
he
n
it
r
e
c
r
e
a
te
s
th
e
s
our
c
e
nod
e
a
s
a
tt
a
c
ke
r
node
a
nd
s
our
c
e
node
it
s
e
lf
bl
a
c
kl
is
te
d
by
a
ll
th
e
ot
he
r
node
s
in
th
e
ne
twor
k.
A
lo
ta
ib
i
[
12]
pr
opos
e
d
a
c
o
-
ope
r
a
ti
ve
b
a
it
de
te
c
ti
on
s
c
h
e
m
e
(
C
B
D
S
)
c
ons
i
s
ti
ng
of
th
e
th
r
e
e
pha
s
e
s
ba
it
in
g
-
pha
s
e
,
r
e
ve
r
s
in
g
tr
a
c
e
a
nd
d
e
f
e
ndi
ng
r
e
a
c
ti
ve
ly
.
I
n
th
e
pha
s
e
of
ba
it
in
g,
th
e
s
our
c
e
-
node
r
a
ndoml
y
id
e
nt
if
ie
s
a
n
a
dj
a
c
e
nt
node
a
nd
s
e
nd
a
r
e
que
s
t
us
in
g
it
id
.
I
n
t
he
s
e
c
ond
pha
s
e
s
our
c
e
ba
s
in
g
upon
R
-
R
E
P
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I
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J
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D
e
te
c
ti
on and av
oi
danc
e
of
bl
ac
k
-
hol
e
at
ta
c
k
i
n m
obi
le
adho
c
ne
tw
or
k
u
s
in
g be
e
-
ad
-
hoc
…
(
Sr
ik
ant
h P
al
a
)
825
r
e
c
e
iv
e
d
f
or
it
s
c
or
r
e
s
ponding
R
-
R
E
Q
th
e
n
it
c
r
e
a
te
s
a
li
s
t
of
s
us
pi
c
io
us
nod
e
s
in
th
e
n
e
twor
k
a
nd
s
our
c
e
c
onve
r
ts
in
to
pr
om
is
c
uous
nod
e
f
or
id
e
nt
if
ic
a
ti
on
of
th
e
a
tt
a
c
k
e
r
node
s
.
T
he
s
our
c
e
node
in
th
e
pr
om
is
c
uous
node
r
a
is
e
a
bl
a
c
k
hol
e
a
l
a
r
m
a
ll
of
it
s
n
e
ig
hbor
in
g
node
s
of
th
e
a
tt
a
c
ke
r
node
,
a
s
it
is
in
th
e
pr
om
is
c
uou
s
m
ode
ne
ig
hbor
node
s
m
a
y not r
e
c
e
iv
e
t
he
a
la
r
m
f
r
om
i
t.
I
n
t
he
t
hi
r
d p
ha
s
e
s
our
c
e
nod
e
w
il
l
c
he
c
k t
he
t
hr
oughput of
th
e
s
us
pi
c
io
us
nod
e
, i
f
l
e
s
s
t
ha
n t
he
t
hr
e
s
hol
d t
he
n onc
e
a
g
a
in
t
he
ba
it
in
g pha
s
e
i
s
a
ppl
ie
d. A
s
m
a
r
t
bl
a
c
k
-
hol
e
node
w
il
l
r
a
is
e
a
f
a
ls
e
a
la
r
m
m
e
s
s
a
ge
a
nd
m
a
ke
s
a
ut
he
nt
i
c
a
te
d
node
s
a
ls
o
to
is
ol
a
te
f
r
om
th
e
ne
twor
k.
T
he
s
our
c
e
node
s
s
e
nd a
f
a
br
ic
a
te
d r
e
que
s
t
to
a
s
s
um
in
g t
ha
t
node
a
s
a
bl
a
c
k
-
hol
e
node
, i
f
t
ha
t
c
o
r
r
e
s
ponding node
r
e
s
ponds
th
e
R
-
R
E
Q
.
S
our
c
e
node
m
a
t
a
in
s
th
e
a
ve
r
a
ge
va
lu
e
of
D
S
N
,
if
a
ny
node
a
c
knowle
dge
s
w
it
h R
-
R
E
P
f
or
c
or
r
e
s
ponding R
-
R
E
Q
f
o
r
t
he
s
our
c
e
node
ve
r
if
ie
s
t
he
D
S
N
va
lu
e
i
t
ha
s
obt
a
in
e
d. T
he
s
our
c
e
node
c
he
c
k
s
th
e
D
S
N
if
it
c
lo
s
e
s
to
a
v
e
r
a
ge
D
S
N
th
e
s
our
c
e
n
od
e
tr
e
a
ts
a
s
b
la
c
k
-
hol
e
node
or
e
ls
e
a
s
a
nor
m
a
l
node
.
H
e
r
e
th
e
i
t
us
e
s
di
gi
ta
l
s
ig
na
tu
r
e
f
or
a
ut
he
nt
ic
a
ti
on i
n i
de
nt
if
yi
ng t
he
b
la
c
k
-
hol
e
node
[
13]
.
D
he
nde
e
t
al
.
[
14]
pr
opos
e
s
a
S
A
O
D
V
pr
ot
oc
ol
f
or
id
e
nt
if
yi
ng
th
e
bl
a
c
k
-
hol
e
a
nd
gr
a
y
-
hol
e
nod
e
ba
s
in
g on opini
on of
t
he
ne
ig
hbor
in
g node
s
. I
n t
hi
s
t
e
c
hni
que
e
a
c
h no ma
in
ta
in
s
t
w
o t
a
bl
e
s
ne
ig
hbor
-
li
s
t
(
N
L
)
a
nd
opi
ni
on
-
li
s
t
(
O
L
)
.
H
e
r
e
th
e
s
our
c
e
node
ge
ne
r
a
ta
te
s
R
-
R
E
Q
m
e
s
s
a
ge
f
or
c
onne
c
ti
on
e
s
ta
bl
is
hm
e
nt
to
th
e
de
s
ti
na
ti
on
node
.
S
our
c
e
node
upon
r
e
c
e
iv
in
g
th
e
r
e
pl
y
m
e
s
s
a
g
e
f
or
th
e
c
or
r
e
s
ponding
r
e
que
s
t
m
e
s
s
a
ge
f
r
om
a
ny of
i
ts
ne
ig
hbor
in
g
node
t
he
n s
our
c
e
node
b
r
oa
dc
a
s
t
opi
ni
on me
s
s
a
ge
c
la
im
in
g t
ha
t
th
is
node
s
hor
te
s
t
pa
th
to
t
he
de
s
ti
na
ti
on.
T
he
r
e
s
t
of
ne
ig
hbor
in
g
node
s
r
e
s
ponds
w
it
h
Y
E
S
o
r
N
O
m
e
s
s
a
ge
.
I
f
r
e
m
a
in
in
g
node
s
r
e
s
ponds
w
it
h
N
O
m
e
s
s
a
g
e
th
e
n
s
our
c
e
node
c
la
im
s
th
a
t
node
a
s
a
b
la
c
k
-
hol
e
node
a
nd
r
a
is
e
s
a
b
la
c
k
-
hol
e
a
la
r
m
in
th
e
ne
twor
k,
if
r
e
s
ponde
d
Y
E
S
m
e
s
s
a
ge
it
is
c
la
im
e
d
a
s
a
nor
m
a
l
node
,
e
ls
e
r
e
s
ponde
d
w
it
h
bot
h
Y
E
S
a
nd N
O
m
e
s
s
a
ge
s
t
h
e
n i
t
is
c
la
im
e
d a
s
a
G
r
a
y
-
H
ol
e
node
[
15]
, [
16]
.
D
ue
to
th
e
e
xc
e
s
s
iv
e
tr
a
s
m
is
s
io
n
of
c
ont
r
ol
m
e
s
s
a
ge
s
be
twe
e
n t
he
s
our
c
e
a
nf
ne
ig
hbor
in
g
node
s
th
e
c
ont
r
ol
ove
r
he
a
d
in
c
r
e
a
s
e
s
in
th
e
ne
twor
k,
le
a
ds
to
c
onge
s
ti
on
i
n
th
e
ne
w
or
k
w
hi
c
h
a
f
f
e
c
t
th
e
qua
li
ty
of
s
e
r
vi
c
e
(
Q
oS
)
m
e
tr
ic
s
.
D
e
te
c
ti
on
a
nd
is
ol
a
ti
on
of
th
e
b
la
c
k
-
hol
e
node
in
ne
twor
k
us
in
g
th
e
A
O
D
V
r
out
in
g
pr
ot
oc
ol
c
a
n
be
a
c
hi
e
ve
d
by
th
e
va
r
io
us
te
c
hni
que
s
[
11]
–
[
14]
.
M
os
tl
y
a
ll
th
e
te
c
hni
que
s
us
e
th
e
D
S
N
f
or
th
e
e
f
f
e
c
ti
ve
r
out
e
e
s
ta
bl
is
hm
e
nt
f
r
om
th
e
s
our
c
e
to
th
e
de
s
ti
na
to
n,
but
a
lwa
ys
a
b
la
c
k
-
h
ol
e
node
c
la
im
w
it
h
a
hi
ghe
s
t
D
S
N
.
W
a
tc
h
-
dog
te
c
hni
que
s
ha
v
e
be
e
n
e
m
pl
oye
d
f
or
th
e
f
or
w
a
r
di
ng
of
th
e
pa
c
ke
ts
a
nd
f
ol
lo
w
e
d
by
s
om
e
tr
ut
h
-
ba
s
e
d
a
lg
or
it
hm
s
in
id
e
nt
if
yi
ng
th
e
nor
m
a
l
nod
e
s
a
nd
bl
a
c
k
hol
e
nod
e
s
.
S
o,
th
e
r
e
is
ne
e
d
f
or
th
e
pr
ope
r
c
or
e
la
ti
on
be
twe
e
n t
he
s
e
nde
r
r
e
que
s
t
m
e
s
s
a
ge
w
it
h ne
ig
hbor
’
s
r
e
s
pon
s
e
m
e
s
s
a
ge
.
T
h
e
r
e
f
or
e
, i
n a
ll
t
he
a
bove
-
m
e
nt
io
ne
d
te
c
hni
que
s
th
e
r
e
is
n
e
e
d
of
pr
ope
r
ti
m
e
s
ync
hr
oni
z
a
ti
on
te
c
hni
que
s
a
r
e
ne
e
de
d
f
or
th
e
r
e
que
s
t
a
nd
r
e
s
pons
e
pa
c
ke
ts
i
n i
de
nt
if
yi
ng t
he
pa
th
a
s
w
e
ll
a
s
t
he
m
a
li
c
io
u
s
node
s
b
l
a
c
k
-
hol
e
node
s
i
n t
ha
t
ne
twor
k.
B
io
-
in
s
pi
r
e
d
a
lg
or
it
hm
s
f
or
opt
im
iz
a
ti
on
ta
ke
r
e
f
e
r
e
nc
e
f
r
om
t
he
ne
twor
ke
d
a
ggr
e
ga
te
be
ha
vi
or
of
li
vi
ng
s
pe
c
ie
s
,
na
m
e
ly
in
s
e
c
t
s
a
nd
a
ni
m
a
ls
,
in
a
ddi
ti
on
to
th
e
pr
in
c
ip
le
s
of
na
tu
r
a
l
e
vol
ut
io
na
r
y
pr
oc
e
s
s
e
s
in
or
de
r
to
de
te
r
m
in
e
th
e
m
os
t
e
f
f
e
c
ti
ve
a
ppr
oa
c
he
s
f
or
c
ha
ll
e
ng
in
g
a
nd
c
om
pl
e
x
opt
im
iz
a
ti
on
pr
obl
e
m
s
[
17]
.
F
r
om
th
e
w
or
k
of
[
18]
r
e
s
e
a
r
c
he
r
s
a
r
e
dr
iv
e
n
to
s
e
e
k
f
or
a
nd
de
ve
lo
p
e
f
f
ic
ie
nt
m
e
th
ods
f
or
di
s
c
ove
r
in
g
a
nd
e
nha
nc
in
g
th
e
s
ol
ut
io
ns
of
c
om
pl
e
x
a
nd
opt
im
iz
a
ti
on
p
r
obl
e
m
s
by
th
e
in
c
r
e
a
s
in
g
c
om
pl
e
xi
ty
of
r
e
a
l
-
w
or
ld
pr
obl
e
m
s
.
I
n
c
om
put
in
g,
one
of
th
e
m
or
e
r
e
now
ne
d
e
vol
ut
io
n
a
r
y
-
ba
s
e
d
te
c
hni
que
s
is
th
e
g
e
ne
ti
c
a
lg
or
it
hm
(
G
A
)
.
S
to
c
ha
s
ti
c
s
e
a
r
c
h t
e
c
hni
que
s
r
e
f
e
r
r
e
d t
o a
s
e
vol
ut
io
na
r
y
-
ba
s
e
d a
lg
or
it
hm
s
(
E
A
)
s
im
ul
a
te
t
he
c
om
m
una
l
dyna
m
ic
s
a
nd
na
tu
r
a
l
e
vol
ut
io
na
r
y
pr
oc
e
s
s
e
s
of
li
vi
ng
th
in
gs
,
e
nc
om
pa
s
s
in
g
r
e
c
om
bi
na
ti
on,
m
ut
a
ti
on,
a
nd
a
da
pt
a
t
io
n
in
r
e
pr
oduc
ti
on.
M
a
s
s
iv
e
opt
im
iz
a
ti
on
pr
obl
e
m
s
c
a
n
go
a
bove
th
e
r
e
a
c
h
of
s
ta
nda
r
d
m
a
th
e
m
a
ti
c
a
l
te
c
hni
que
s
;
in
s
uc
h
in
s
ta
n
c
e
s
,
EA
ha
ve
be
e
n
c
r
e
a
te
d
to
id
e
nt
if
y
th
e
opt
im
a
l
or
ne
a
r
ly
opt
im
a
l
r
e
s
pons
e
of
s
w
a
r
m
in
te
ll
ig
e
nc
e
is
c
onc
e
r
ne
d
w
it
h
de
ve
lo
pi
ng
in
te
ll
ig
e
nt
,
dyna
m
ic
s
ys
te
m
s
w
it
h
m
ul
ti
pl
e
a
ge
nt
s
th
a
t
c
oope
r
a
te
to
a
c
hi
e
ve
a
c
om
m
on goa
l
th
a
t
is
out
s
id
e
t
he
a
bi
li
ti
e
s
of
a
s
in
gl
e
a
ge
nt
. E
s
pe
c
ia
ll
y c
om
pa
r
in
g t
o ot
he
r
t
r
a
di
ti
ona
l
m
e
th
ods
,
bi
o
-
in
s
pi
r
e
d
opt
im
iz
a
ti
on
a
lg
or
it
hm
s
e
xhi
bi
t
out
s
ta
ndi
ng
va
r
ia
nc
e
,
r
e
s
il
ie
nc
e
,
f
le
xi
bi
li
ty
,
le
ve
l
of
c
om
pl
e
xi
ty
,
a
nd
uni
que
e
ve
nt
s
,
w
hi
c
h
h
a
ve
c
ont
r
ib
ut
e
d
to
th
e
ir
de
ve
lo
pi
ng
a
r
e
a
tt
r
a
c
ti
ve
in
th
e
r
e
a
lm
of
c
om
put
a
ti
on.
T
he
ba
s
ic
s
te
p
s
f
or
id
e
nt
if
yi
ng
th
e
m
a
li
c
io
us
no
de
in
th
e
n
e
twor
k
us
in
g
th
e
li
te
r
a
tu
r
e
r
e
vi
e
w
c
onduc
te
d a
s
f
ol
lo
w
s
:
a)
I
ni
ti
a
ll
y
a
ba
c
k
-
bone
ne
twor
k
is
c
r
e
a
te
d,
th
e
s
our
c
e
nod
e
r
a
is
e
s
a
r
e
qu
e
s
t
f
or
unus
e
d
r
e
s
tr
ic
te
d
I
P
.
B
a
c
kbone
ne
twor
k
s
s
e
a
r
c
he
s
f
or
th
e
ne
w
unus
e
d
n
e
twor
k
I
P
a
nd
f
or
w
a
r
ds
it
to
th
e
s
our
c
e
node
[
11]
,
[
12]
.
b)
R
e
que
s
t
in
ti
a
te
d
f
r
om
th
e
s
our
c
e
-
node
f
or
th
e
da
ta
tr
a
ns
m
is
s
io
n
to
it
s
r
e
s
pe
c
ti
ve
de
s
ti
na
ti
on
us
in
g
a
r
e
s
tr
ic
te
d I
P
ge
ne
r
a
te
d by the
ba
c
k bone
ne
twor
k.
c)
D
e
s
ti
na
ti
on
node
upon
r
e
c
e
iv
in
g
th
e
r
e
que
s
t
f
r
om
th
e
s
our
c
e
no
de
,
it
e
nt
e
r
s
I
P
a
ddr
e
s
s
in
th
e
r
out
in
g
ta
bl
e
s
e
nd
ba
c
k
to
s
our
c
e
node
.
U
pon
e
s
t
a
bl
is
hi
ng
th
e
li
nk,
th
e
s
our
c
e
w
il
l
in
it
ia
te
th
e
f
ur
th
e
r
tr
a
ns
m
is
s
io
n
of
da
ta
be
twe
e
n t
he
node
s
[
19]
.
d)
I
f
t
he
node
a
c
c
e
pt
in
g t
he
da
ta
i
s
not
de
s
ti
na
ti
on node
,
t
he
n i
t
f
or
w
a
r
ds
ne
ig
hbor
in
g node
s
by
m
a
ki
ng i
t
I
P
e
nt
r
y
in
th
e
r
out
in
g
ta
bl
e
.
S
our
c
e
node
onl
y
r
e
s
ponds
a
nd
s
e
nds
th
e
da
ta
onl
y
if
it
is
a
de
s
ti
na
ti
on
node
.
B
ut
if
r
e
s
pons
e
obt
a
in
e
d
f
r
om
th
e
de
s
ti
na
t
io
n
h
a
vi
ng
a
r
e
s
tr
ic
te
d
I
P
a
ddr
e
s
s
,
th
e
n
it
s
ta
r
ts
s
e
ndi
ng
th
e
dum
m
y m
e
s
s
a
ge
s
f
or
i
de
nt
if
yi
ng t
he
m
a
li
c
io
us
node
.
e)
S
e
nde
r
node
i
nt
ia
ti
e
s
a
c
a
ut
io
n a
le
r
t
not
e
s
to
i
ts
ne
ig
hbor
s
t
o e
nt
e
r
i
nt
o a
s
a
f
e
z
one
a
nd t
o ke
e
p a
t
r
a
c
k of
th
e
m
a
li
c
io
us
ly
e
f
f
e
c
te
d
node
.
I
f
th
e
s
our
c
e
node
obt
a
in
s
a
D
S
N
va
lu
e
gr
e
a
te
r
th
a
n
th
e
th
r
e
s
hol
d
va
lu
e
f
or
th
e
dum
m
y
m
e
s
s
a
ge
it
ha
s
ge
ne
r
a
te
d
[
11]
.
T
he
s
our
c
e
node
s
ge
ne
r
a
te
a
bl
a
c
k
hol
e
a
la
r
m
to
a
ll
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
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8938
I
nt
J
A
r
ti
f
I
nt
e
ll
,
V
ol
.
1
4
, N
o.
1
,
F
e
br
ua
r
y
202
5
:
822
-
832
826
ne
ig
hbor
in
g
node
s
a
nd
tr
ie
s
to
de
te
r
m
in
e
a
ne
w
s
a
f
e
a
nd
s
e
c
ur
e
p
a
th
to
th
e
de
s
ti
na
ti
on.
T
h
e
r
e
by
in
c
r
e
a
s
in
g
th
e
t
hr
oughput of
t
he
ne
twor
k a
nd de
c
r
e
a
s
in
g t
he
e
nd
-
to
-
e
nd de
la
y.
4.
P
R
O
P
O
S
E
D
R
E
S
E
A
R
C
H
T
he
in
it
ia
l
r
a
ndom
popula
ti
on
is
ut
il
iz
e
d
by
th
e
be
e
li
f
e
a
lg
or
it
hm
s
to
popula
te
th
e
a
r
e
a
of
s
e
a
r
c
h.
A
c
ol
ony
of
be
e
s
in
c
lu
de
s
‘
W
’
w
or
ke
r
s
,
‘
D
’
dr
one
s
,
a
nd
‘
1’
que
e
n.
T
he
two
di
s
ti
nc
t
be
e
be
ha
vi
or
s
w
hi
c
h
m
a
ke
up
e
ve
r
y
a
lg
or
it
hm
c
yc
le
in
c
lu
de
s
e
a
r
c
hi
ng
f
o
r
f
oo
d
a
nd
r
e
pr
odu
c
ti
on.
I
n
r
e
pr
oduc
ti
on,
th
e
f
i
tn
e
s
s
of
th
e
br
oods
is
de
te
r
m
in
e
d a
f
te
r
ge
ne
r
a
ti
on ‘
N
’
br
oods
by mut
a
ti
on a
nd c
r
os
s
ove
r
. T
he
f
it
te
s
t
br
ood s
uc
c
e
e
ds
t
he
que
e
n f
or
a
s
ubs
e
que
nt
popula
ti
on i
f
i
t
i
s
a
be
tt
e
r
f
it
t
ha
n t
he
que
e
n. T
he
n
, us
in
g t
he
‘
D
’
f
i
tt
e
s
t
dr
one
s
a
nd br
oods
o
f
t
he
c
ur
r
e
nt
c
ol
ony,
th
e
‘
D
’
be
s
t
be
e
s
a
r
e
c
hos
e
n
to
pr
oduc
e
th
e
ne
x
t
ge
ne
r
a
ti
on
of
dr
one
s
.
‘
W
’
be
s
t
be
e
s
a
r
e
th
e
n
c
hos
e
n
f
r
om
th
e
‘
W
’
f
it
te
s
t
s
ur
vi
vi
ng
hove
r
s
a
nd
w
or
ke
r
s
of
th
e
c
ur
r
e
nt
c
om
m
uni
ty
to
e
ns
ur
e
f
ood
ga
th
e
r
in
g;
if
ot
he
r
w
is
e
,
th
e
a
lg
or
it
hm
is
a
bor
te
d.
W
he
n
it
c
om
e
s
to
f
ood
f
or
a
gi
ng
be
ha
vi
or
,
‘
W
’
w
or
ke
r
s
in
‘
W
’
r
e
gi
ons
lo
ok
f
or
s
our
c
e
s
of
f
ood
f
ir
s
t.
s
ubs
e
qu
e
nt
ly
be
e
s
a
r
e
c
ho
s
e
n
f
o
r
ne
ig
hbor
hood
s
e
a
r
c
he
s
in
e
a
c
h
lo
c
a
ti
on.
T
h
e
f
it
te
s
t
be
e
s
in
e
a
c
h
lo
c
a
ti
on
w
il
l
be
c
hos
e
n
to
c
r
e
a
te
th
e
f
ol
lo
w
in
g
be
e
popula
ti
on,
a
nd
it
s
f
it
ne
s
s
w
il
l
be
e
va
lu
a
te
d.
I
f
th
e
ha
lt
in
g
r
e
qui
r
e
m
e
nt
is
not
m
e
t
a
f
te
r
th
e
s
e
two
be
e
be
ha
vi
or
s
,
a
ne
w
b
e
e
li
f
e
c
yc
l
e
is
c
a
r
r
ie
d
out
;
if
not
,
th
e
a
lg
or
it
hm
is
te
r
m
in
a
te
d.
T
he
pr
ot
oc
ol
s
us
e
th
e
B
e
e
’
s
be
ha
vi
or
in
s
ol
vi
ng
th
e
s
ur
vi
vi
ng
th
e
f
it
te
s
t
f
unc
ti
on
in
id
e
nt
if
yi
ng
th
e
b
la
c
k
-
hol
e
a
tt
a
c
k.
B
e
e
A
dhoc
[
20]
r
out
in
g
a
lg
or
it
hm
,
th
a
t
bor
r
ow
s
it
s
c
lu
e
s
f
r
om
hone
y
be
e
f
or
a
gi
ng
be
ha
vi
or
, i
s
in
te
nde
d
f
or
us
e
in
m
obi
le
a
d
h
oc
ne
twor
ks
.
I
t
f
unc
ti
ons
a
s
a
n
e
ne
r
gy
-
e
f
f
ic
ie
nt
r
e
a
c
ti
ve
s
our
c
e
r
out
in
g
a
lg
or
it
hm
.
T
o
f
in
d
ne
w
pa
th
w
a
ys
a
nd
m
ove
da
ta
f
r
om
s
our
c
e
to
de
s
ti
na
ti
on
,
th
e
a
lg
or
it
hm
us
e
s
s
c
out
s
a
nd f
or
a
ge
r
s
, r
e
s
pe
c
ti
ve
ly
i
nvol
ve
s
t
he
f
o
ll
ow
in
g s
te
ps
a
s
s
how
n.
S
te
p 1
R
out
e
-
di
s
c
ove
r
y
:
A
f
or
w
a
r
d
-
lo
oki
ng
s
c
out
is
br
oa
dc
a
s
t
to
e
a
c
h
ne
ig
hbor
of
a
node
w
i
th
a
n
in
c
r
e
a
s
in
g
T
T
L
w
he
n
a
r
out
e
f
or
a
de
s
ti
na
ti
on
is
ne
e
de
d.
D
o
w
n
unt
il
th
e
poi
nt
of
d
e
s
ti
na
ti
on,
in
te
r
m
e
di
a
te
node
s
a
ppe
nd t
he
ir
a
ddr
e
s
s
e
s
t
o t
he
s
c
out
'
s
s
our
c
e
r
out
e
.
S
te
p 2
B
a
c
kw
a
r
d
-
s
c
out
:
T
he
ta
r
ge
t
node
gi
ve
s
ba
c
k
th
e
s
c
out
to
s
our
c
e
r
out
e
f
or
c
onf
ig
ur
in
g
th
e
ba
c
kw
a
r
d
s
c
out
a
f
te
r
th
e
f
or
w
a
r
d
s
c
out
r
e
a
c
h
e
s
a
t
th
e
d
e
s
ti
na
ti
on.
T
he
s
our
c
e
r
e
c
e
iv
e
s
th
is
ba
c
kw
a
r
d s
c
out
a
f
te
r
w
a
r
ds
.
S
te
p 3
R
out
e
-
a
dve
r
ti
s
e
m
e
nt
:
T
he
ba
c
kw
a
r
d
s
c
out
not
if
ie
s
s
ub
s
e
que
nt
f
or
a
ge
r
s
r
e
ga
r
di
ng
th
e
r
out
e
a
f
te
r
f
in
di
ng i
ts
w
a
y r
e
tu
r
ni
ng t
o t
he
i
ni
ti
a
l
node
.
S
te
p 4
D
a
ta
-
tr
a
ns
por
t
:
D
a
ta
r
out
e
d
to
th
e
ta
r
ge
t
node
by
f
or
a
ge
r
s
us
in
g
a
da
nc
e
m
e
ta
phor
a
s
a
n
a
id
.
T
o
de
te
r
m
in
e
th
e
da
nc
in
g
num
be
r
,
s
ugge
s
ti
ng
s
ta
nda
r
ds
of
th
e
r
out
in
g
pa
th
,
a
lo
ngs
id
e
ga
th
e
r
in
g
th
e
r
out
in
g da
ta
M
a
z
ha
r
a
nd
F
a
r
ooq
[
21]
ha
ve
s
pe
c
if
ie
d
th
e
a
bove
f
r
a
m
e
w
or
k,
B
e
e
S
e
c
,
a
s
e
c
ur
e
a
lt
e
r
na
ti
ve
of
B
e
e
A
dH
oc
w
hi
c
h
e
na
bl
e
s
th
e
us
e
of
di
gi
ta
l
s
ig
n
a
tu
r
e
s
ba
s
e
d
on
a
s
ym
m
e
tr
ic
c
r
ypt
ogr
a
phy.
S
c
out
s
a
nd
f
or
a
ge
r
s
in
B
e
e
S
e
c
r
e
ly
on
di
gi
ta
l
s
ig
na
tu
r
e
s
w
hi
c
h
ha
ve
be
e
n
g
e
ne
r
a
te
d
us
in
g
va
r
io
us
p
a
r
a
m
e
te
r
s
s
uc
h
a
s
s
our
c
e
a
nd
de
s
ti
na
ti
on
a
ddr
e
s
s
e
s
,
pa
c
k
e
t
I
D
s
,
a
nd
r
out
in
g
in
f
or
m
a
ti
on.
A
ddi
ti
ona
ll
y,
th
e
s
our
c
e
r
out
e
'
s
in
te
gr
it
y
is
pr
e
s
e
r
ve
d
to
m
a
ke
s
ur
e
th
a
t
m
a
le
vol
e
nt
node
s
c
a
n'
t
e
li
m
in
a
te
le
gi
ti
m
a
te
node
s
f
r
om
th
e
pa
th
.
A
s
a
r
e
s
ul
t,
B
e
e
S
e
c
s
uc
c
e
s
s
f
ul
ly
th
w
a
r
ts
a
tt
e
m
pt
s
to
ta
m
pe
r
w
it
h
or
f
a
br
ic
a
te
a
tt
a
c
k
s
in
B
e
e
A
dH
oc
a
nd
c
ount
e
r
s
a
tt
a
c
k
s
di
r
e
c
te
d t
ow
a
r
ds
t
he
r
out
in
g. T
he
ps
e
udoc
ode
of
t
he
ba
s
ic
B
e
e
-
a
lg
or
it
hm
.
P
s
e
udo
-
C
od
e
f
or
B
a
s
ic
B
e
e
-
A
lg
or
it
hm
I
ni
ti
a
li
z
a
ti
on
:
P
opua
la
ti
on i
s
a
s
s
ig
ne
d w
it
h R
a
ndom S
ol
ut
io
ns
F
it
ne
s
s
f
unc
ti
on
e
va
lu
a
ti
on
R
e
pe
a
t
-
u
nt
il
(
S
to
ppi
ng
c
r
it
e
r
ia
i
s
m
e
t)
1.
C
hoos
e
t
he
s
it
e
s
f
or
ne
ig
hbor
hood
-
s
e
a
r
c
h
2.
R
e
c
r
ui
t
th
e
B
e
e
s
f
or
c
hos
e
n s
it
e
s
3.
C
hoos
e
t
he
f
it
te
s
t
B
e
e
f
r
om
e
a
c
h s
it
e
4.
A
s
s
ig
n t
he
B
e
e
s
f
or
r
a
ndom s
e
a
r
c
h
E
nd
-
r
e
pe
a
t
D
e
te
c
ti
on
m
e
c
ha
ni
s
m
ne
e
ds
to
pr
ot
e
c
t
th
e
da
ta
bot
h
in
r
e
s
t
a
nd
tr
a
ns
m
is
s
io
n
s
ta
t
e
,
da
ta
pr
ot
e
c
ti
on
in
th
e
r
e
s
t
s
ta
te
i
s
a
l
ik
e
ly
a
ppr
oa
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h. I
f
m
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li
c
io
us
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nt
e
r
s
in
to
th
e
ne
twor
k, i
t
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l
ik
e
ly
t
o
de
s
tr
oy t
he
da
ta
a
nd
m
a
ni
pul
a
te
th
e
ne
twor
k
he
ur
is
ti
c
s
to
in
c
r
e
a
s
e
th
e
ne
twor
k
tr
a
f
f
ic
.
S
o,
th
e
th
e
r
e
is
a
ne
e
d
f
or
th
e
ne
twor
k
s
ur
ve
il
la
nc
e
s
ys
te
m
to
de
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e
nd
th
e
f
or
th
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om
in
g
a
tt
a
c
ks
in
th
e
ne
twor
k.
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de
nt
if
ic
a
ti
on
o
f
th
e
e
f
f
e
c
te
d
node
in
th
e
M
A
N
E
T
s
i
s
s
how
n
i
n F
ig
ur
e
2 ba
s
in
g on
t
he
ne
twor
k i
nc
om
in
g
t
r
a
f
f
ic
m
odul
e
, r
oot
node
f
or
i
nc
r
e
a
s
in
g i
n t
he
ne
twor
k
lo
a
d
w
it
h
tr
a
f
f
ic
in
c
e
pt
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n
m
odul
e
,
a
na
ly
s
is
m
odul
e
w
it
h
e
ve
nt
ge
ne
r
a
ti
on
f
or
id
e
nt
if
ic
a
ti
on
of
th
e
node
.
O
n
s
im
ul
a
ti
ng
th
e
B
e
e
s
a
ppr
oa
c
h
to
th
e
ne
twor
k
f
o
r
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if
yi
ng
th
e
m
a
li
c
io
us
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w
he
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ve
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f
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it
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s
"
a
c
c
um
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s
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out
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e
s
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T
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p
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e
udode
of
t
he
e
li
m
in
a
ti
on of
m
a
li
c
io
us
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F
ig
ur
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2. A
ppr
oa
c
h f
or
i
de
nt
if
yi
ng
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a
c
k
-
hol
e
a
tt
a
c
k
P
s
e
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c
ode
of
e
li
m
in
a
ti
on of
M
a
li
c
io
us
N
ode
S
te
p 1:
I
de
nt
if
ic
a
ti
on of
M
a
li
c
io
us
N
ode
1.1:
A
ddi
ng
M
a
li
c
io
us
N
ode
t
o t
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C
lu
s
te
r
H
e
a
d i
n t
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r
out
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g
ta
bl
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S
te
p 2:
B
r
oa
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s
ti
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he
M
a
li
c
io
us
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o a
ll
t
he
C
lu
s
te
r
H
e
a
d
s
i
n t
he
M
A
N
E
T
N
e
twor
k
S
te
p 3:
C
lu
s
te
r
H
e
a
d
B
r
oa
dc
a
s
t
li
s
t
to
a
ll
t
he
N
ode
s
i
n i
ts
R
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a
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ni
ti
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pe
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t
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(
t
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m
in
a
ti
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c
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on)
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t
‘
s
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numbe
r
of
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th
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f
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om
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s
our
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o t
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s
ti
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ti
on
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hoos
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‘
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r
om
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he
‘
s
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vi
ng mi
ni
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um
di
s
ta
nc
e
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r
om
t
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s
our
c
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o de
s
ti
na
ti
on
3.
ns
p:
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um
be
r
ne
ig
hbor
hood s
e
a
r
c
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s
pe
r
f
or
m
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d a
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s
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n i
d
e
nt
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la
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k
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hol
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node
s
4.
ne
p:
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um
be
r
ne
ig
hbor
hood s
e
a
r
c
he
s
p
e
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f
or
m
e
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r
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e
’
i
n i
d
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nt
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ng t
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b
la
c
k
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hol
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node
s
5.
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t
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p>
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p
6.
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in
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n
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th
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r
if
y w
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th
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r
t
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pa
th
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x
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ts
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r
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c
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to
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R
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L
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[
22]
th
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in
vol
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t
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que
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a
l
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s
im
ul
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ti
on
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ppr
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he
s
[
23]
,
[
24]
.
H
e
r
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th
e
s
im
ul
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ti
on
a
ppr
o
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c
h
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te
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a
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be
r
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m
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gr
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on t
he
Q
oS
m
e
tr
ic
s
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it
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5
.1.
N
e
t
w
or
k
-
s
im
u
la
t
or
ve
r
s
io
n
2
NS
-
2
[
25]
is
a
n
ope
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-
s
our
c
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s
im
ul
a
to
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w
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k
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bl
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−
A
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r
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a
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li
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out
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k.
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s
a
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x ba
s
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us
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t
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c
om
m
a
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la
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t
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c
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if
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ll
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xi
bl
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5
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P
ar
am
e
t
e
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f
or
t
h
e
s
i
m
u
la
t
io
n
I
n
th
is
s
tu
dy,
N
S
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2
is
us
e
d
f
or
th
e
pe
r
f
o
r
m
a
nc
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a
na
ly
s
is
of
Q
oS
m
e
tr
ic
s
on
th
e
nor
m
a
l
A
O
D
V
[
26]
a
nd
B
e
e
-
AODV
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out
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pr
ot
oc
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c
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im
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ti
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[
27]
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s
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c
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he
s
our
c
e
n
ode
.
5
.
3
.
P
ar
am
e
t
e
r
f
or
t
h
e
S
im
u
la
t
io
n
T
he
A
O
D
V
r
out
in
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pr
ot
oc
ol
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r
e
a
s
ona
bl
y
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f
f
e
c
te
d
by
Q
oS
m
e
tr
ic
s
,
a
nd
th
e
bl
a
c
k
hol
e
a
tt
a
c
k
de
te
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io
r
a
te
s
th
e
r
out
in
g
pr
ot
oc
ol
'
s
pe
r
f
or
m
a
nc
e
in
M
A
N
E
T
s
.
T
he
th
r
oughput,
e
ne
r
gy
c
ons
um
pt
io
n,
pa
c
ke
t
lo
s
s
,
a
nd
la
te
nc
y
a
r
e
th
e
e
le
m
e
nt
s
in
f
lu
e
nc
in
g
pe
r
f
or
m
a
nc
e
.
A
ll
o
f
th
e
s
e
in
di
c
a
to
r
s
'
pe
r
f
or
m
a
nc
e
a
na
ly
s
e
s
a
r
e
c
ont
r
a
s
te
d
a
t
n
e
twor
ks
of
10,
20,
30,
a
nd
35
node
s
,
in
v
a
r
yi
ng
s
iz
e
s
.
A
f
te
r
im
pa
c
te
d
node
s
in
th
a
t
ne
twor
k
r
e
gi
on a
r
e
r
e
m
ove
d, a
n a
na
ly
s
is
i
s
c
onduc
te
d
c
om
pa
r
in
g t
he
pe
r
f
or
m
a
nc
e
of
A
O
D
V
w
it
h B
e
e
-
A
O
D
V
.
5.3.1. P
ac
k
e
t
l
os
s
P
a
c
ke
t
lo
s
s
m
e
a
s
ur
e
s
t
he
numbe
r
of
t
he
a
c
knowle
dge
m
e
nt
r
e
c
e
iv
e
d f
r
om
t
he
r
e
c
e
iv
e
r
, us
e
d t
o j
us
ti
f
y
th
e
r
e
li
a
bi
li
ty
of
th
e
pr
ot
oc
ol
.
L
os
s
of
pa
c
ke
ts
s
im
pl
y
s
ig
ni
f
ie
s
t
he
num
be
r
of
th
e
pa
c
ke
ts
r
e
c
e
iv
e
d
a
t
r
e
c
e
iv
e
r
f
or
t
he
numbe
r
of
t
he
pa
c
ke
ts
s
e
nd
by t
he
s
e
nde
r
,
he
r
e
w
e
a
r
e
us
in
g t
he
s
e
que
n
c
e
numbe
r
f
or
e
ve
r
y H
E
L
L
O
i
n
id
e
nt
if
yi
ng t
he
numbe
r
of
pa
c
ke
t.
T
he
pa
c
ke
t
lo
s
s
r
a
ti
o
[
28]
is
s
ig
ni
f
ie
d a
s
t
he
dr
op r
a
ti
o i
n (
2)
.
=
+
+
(
2
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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J
A
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ti
f
I
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ll
I
S
S
N
:
2252
-
8938
D
e
te
c
ti
on and av
oi
danc
e
of
bl
ac
k
-
hol
e
at
ta
c
k
i
n m
obi
le
adho
c
ne
tw
or
k
u
s
in
g be
e
-
ad
-
hoc
…
(
Sr
ik
ant
h P
al
a
)
829
T
h
e
F
i
gur
e
3
pa
c
k
e
t
l
o
s
s
f
o
r
th
e
A
O
D
V
r
ou
ti
n
g
pr
ot
o
c
o
l
in
t
h
e
b
l
a
c
k
-
h
ol
e
a
t
ta
c
k
a
t
di
f
f
e
r
e
nt
i
nt
e
r
v
a
l
s
i
n
p
a
u
s
e
t
im
e
f
or
e
ve
r
y
10
s
e
c
on
d
s
,
t
he
b
yt
e
s
/
s
e
c
s
pe
c
if
ie
s
t
h
a
t
t
h
e
n
um
b
e
r
of
t
he
d
a
t
a
i
n
t
he
b
yt
e
s
i
s
l
o
s
t
. T
h
e
pe
r
c
e
n
ta
g
e
o
f
t
h
e
p
a
c
k
e
t
l
o
s
s
c
o
m
p
a
r
e
d
to
nor
m
a
l
A
O
D
V
to
B
e
e
-
A
O
D
V
i
s
r
e
d
u
c
e
d
i
n
th
e
n
e
tw
or
k
w
it
h
d
if
f
e
r
e
nt
r
a
n
g
e
of
no
d
e
s
.
F
ig
ur
e
3. P
a
c
ke
t
lo
s
s
c
om
pa
r
is
on i
n pe
r
c
e
nt
a
ge
be
twe
e
n
A
O
D
V
a
nd
B
ee
-
AODV
5.3.2. T
h
r
ou
gh
p
u
t
T
hr
oughput
in
r
out
in
g
pr
ot
oc
ol
s
ig
ni
f
ie
s
th
e
num
be
r
of
tr
a
f
f
ic
pa
c
ke
ts
th
a
t
e
a
c
h
node
in
th
e
ne
twor
k
r
e
c
e
iv
e
s
ove
r
a
c
e
r
ta
in
ti
m
e
in
te
r
va
l
a
nd
is
m
e
a
s
ur
e
d
in
m
e
ga
byt
e
s
(
M
bps
)
.
E
ve
r
y
pos
s
ib
le
de
la
y
ob
s
e
r
ve
d
w
hi
le
tr
a
ns
m
it
ti
ng
th
e
da
ta
pa
c
ke
t
f
r
om
th
e
s
our
c
e
node
to
t
h
e
de
s
ti
na
ti
on
node
s
is
in
c
lu
de
d
in
th
e
a
ve
r
a
ge
e
nd
-
to
-
e
nd l
a
te
nc
y
[
29]
.
ℎ
ℎ
=
∑
(
∗
(
)
=
1
)
(
3
)
T
he
th
r
oughput
a
t
di
f
f
e
r
e
nt
pa
us
e
ti
m
e
a
nd
s
im
ul
a
ti
ons
f
or
A
O
D
V
r
out
in
g
pr
ot
oc
ol
in
th
e
b
la
c
k
-
hol
e
a
tt
a
c
k
w
it
h
pe
r
c
e
nt
a
ge
of
im
pr
ove
m
e
nt
in
th
r
oughput
w
he
n
c
om
pa
r
e
d
w
it
h
nor
m
a
l
A
O
D
V
r
out
in
g
p
r
ot
oc
ol
to
th
e
B
e
e
-
A
O
D
V
r
out
in
g pr
ot
oc
ol
i
s
s
how
n i
n t
he
F
ig
ur
e
4.
5.3.3. E
n
d
-
to
-
e
n
d
d
e
la
y
E
nd
-
to
-
E
nd
d
e
la
y
c
l
e
a
r
l
y
s
pe
c
if
ie
s
t
he
a
v
e
r
a
g
e
ti
m
e
t
a
k
e
n
f
or
th
e
tr
a
n
s
m
i
s
s
i
on
of
th
e
d
a
t
a
pa
c
k
e
t
f
r
om
th
e
s
o
ur
c
e
to
t
h
e
d
e
s
ti
n
a
t
io
n
.
D
e
la
y
in
c
lu
de
s
f
a
c
t
or
s
li
k
e
th
e
tr
a
n
s
m
is
s
io
n
t
i
m
e
,
w
a
it
i
ng
t
i
m
e
, r
e
c
e
i
vi
ng
ti
m
e
[
30]
.
=
∑
+
+
=
1
(
4)
T
he
pe
r
c
e
nt
a
ge
im
pr
ove
m
e
nt
in
th
e
de
la
y
w
he
n
c
om
pa
r
e
d
nor
m
a
l
A
O
D
V
w
it
h
B
e
e
-
A
O
D
V
r
out
in
g
pr
o
to
c
ol
is
s
how
n
in
th
e
F
ig
ur
e
5.
T
he
gr
a
ph
c
le
a
r
ly
s
ig
ni
f
ie
s
th
a
t
B
e
e
-
A
O
D
V
c
le
a
r
ly
r
e
duc
e
s
th
e
e
nd
-
to
-
e
nd
de
la
y
in
c
om
pa
r
is
on
w
it
h
th
e
nor
m
a
l
A
O
D
V
r
out
in
g
p
r
ot
oc
ol
.
A
s
B
e
e
-
A
O
D
V
a
im
s
in
e
li
m
in
a
ti
on
o
f
th
e
m
a
li
c
io
us
node
s
, de
f
in
it
e
ly
i
m
pr
ove
s
t
he
e
nd
-
to
-
e
nd de
la
y be
twe
e
n t
he
s
o
ur
c
e
t
o t
he
de
s
ti
na
ti
on.
F
ig
ur
e
4. T
hr
oughput c
om
pa
r
is
on i
n pe
r
c
e
nt
a
ge
be
twe
e
n A
O
D
V
a
nd
B
e
e
-
AODV
F
ig
ur
e
5.
E
nd
-
to
-
e
n
d d
e
l
a
y
c
om
pa
r
is
on
i
n
p
e
r
c
e
nt
a
ge
be
t
w
e
e
n A
O
D
V
a
n
d
pr
o
po
s
e
d
B
e
e
-
A
O
D
V
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
.
1
4
, N
o.
1
,
F
e
br
ua
r
y
202
5
:
822
-
832
830
5.3.2. E
n
e
r
gy
-
c
on
s
u
m
e
d
E
ne
r
gy
-
c
ons
um
e
d
[
31]
is
s
ig
ni
f
ic
a
nt
f
a
c
to
r
f
o
r
e
nha
nc
in
g
th
e
pe
r
f
or
m
a
nc
e
.
A
s
th
e
M
A
N
E
T
s
lo
w
pow
e
r
e
ne
r
gy
e
qui
ppe
d
de
vi
c
e
s
th
e
r
e
is
ne
e
d
f
or
th
e
e
ne
r
gy
opt
im
iz
a
ti
on.
E
ne
r
gy
c
ons
um
e
d
c
ons
is
ts
of
th
e
to
ta
l
e
ne
r
gy
r
e
qui
r
e
d
f
or
di
s
s
e
m
in
a
ti
on
of
th
e
da
ta
p
a
c
ke
t
f
r
om
th
e
in
ti
a
l
to
t
h
e
ta
r
ge
t
nod
e
,
r
e
c
e
iv
in
g
e
ne
r
gy
f
or
a
c
c
qui
r
ng t
he
da
ta
a
t
ta
r
ge
t
node
a
nd w
a
it
in
g e
ne
r
gy a
t
in
te
r
m
e
di
a
te
node
s
.
=
∑
+
+
=
1
(
5
)
T
he
e
ne
r
gy
c
ons
um
e
d
in
p
e
r
c
e
nt
a
ge
c
om
pa
r
e
d
to
c
onve
nt
io
na
l
A
O
D
V
to
B
e
e
-
A
O
D
V
r
out
in
g
pr
ot
oc
ol
is
s
how
n
in
F
ig
ur
e
6.
H
e
r
e
a
ls
o
th
e
gr
a
ph
c
le
a
r
ly
s
ig
ni
f
ie
s
th
e
im
pr
ove
m
e
nt
in
th
e
e
ne
r
gy
c
ons
um
pt
io
n
w
he
n
c
om
pa
r
e
d
w
it
h
th
e
c
onve
nt
io
na
l
A
O
D
V
to
B
e
e
-
A
O
D
V
r
o
ut
in
g
pr
ot
o
c
ol
.
T
he
ove
r
a
ll
pe
r
f
or
m
a
nc
e
of
pa
r
a
m
e
te
r
s
on
a
ve
r
a
ge
a
na
ly
s
i
s
of
th
e
c
onve
nt
io
na
l
A
O
D
V
r
out
in
g
pr
ot
oc
ol
c
om
pa
r
e
d
w
it
h
th
e
pr
opos
e
d
B
e
e
-
A
O
D
V
r
out
in
g
pr
ot
oc
ol
is
s
how
n
in
T
a
bl
e
2.
I
t
is
c
le
a
r
ly
i
nf
e
r
r
in
g
f
r
o
m
th
e
pe
r
f
or
m
a
nc
e
m
e
tr
ic
a
na
ly
s
is
th
a
t
th
e
pr
opos
e
d
B
e
e
-
A
O
D
V
r
out
in
g
pr
ot
oc
ol
pe
r
f
o
r
m
s
be
tt
e
r
th
a
n
c
onve
nt
io
na
l
nor
m
a
l
A
O
D
V
r
out
in
g
pr
ot
oc
ol
i
n a
ll
t
he
pa
r
a
m
e
te
r
s
l
ik
e
pa
c
ke
t
lo
s
s
,
e
nd
-
to
-
e
nd de
la
y
,
a
nd
e
ne
r
gy
-
c
ons
um
pt
io
n
.
F
ig
ur
e
6. E
ne
r
gy c
ons
um
e
d
c
om
pa
r
is
on i
n pe
r
c
e
nt
a
ge
be
twe
e
n
A
O
D
V
a
nd pr
opos
e
d B
e
e
-
AODV
T
a
bl
e
2
. P
e
r
f
or
m
a
nc
e
c
om
pa
r
is
on of
c
onve
nt
io
na
l
A
O
D
V
a
nd
pr
opos
e
d B
e
e
-
A
O
D
V
pr
ot
oc
ol
P
a
r
a
m
e
t
e
r
pr
ot
oc
ol
P
a
c
ke
t
l
os
s
(%)
E
nd
-
to
-
e
nd
de
l
a
y
(
%
)
T
hr
oughput
(
%
)
E
ne
r
gy c
ons
um
pt
i
on
(%)
C
onve
nt
i
ona
l
A
O
D
V
50
56.25
40
23.125
P
r
opos
e
d B
e
e
-
AODV
20
40.5
18
12.875
6.
C
O
N
C
L
U
S
I
O
N
A
N
D
F
U
T
U
R
E
S
C
O
P
E
T
he
r
e
s
e
a
r
c
h
w
or
k
a
im
s
f
or
id
e
ndi
ti
f
ic
a
ti
on
of
m
a
li
c
io
us
node
in
th
e
ne
twor
k
a
nd
to
c
ount
e
r
a
c
t
f
or
th
e
b
la
c
k
-
hol
e
a
tt
a
c
k
in
A
O
D
V
r
out
in
g
pr
ot
oc
ol
.
A
O
D
V
r
out
in
g
pr
ot
oc
ol
in
te
gr
a
te
d
w
it
h
bi
oi
ns
pi
r
e
d
b
e
e
a
lg
or
it
hm
(
B
e
e
-
A
O
D
V
)
not
onl
y
e
nha
nc
e
s
th
e
s
e
c
ur
it
y
but
a
ls
o
out
r
a
te
s
th
e
pe
r
f
or
m
a
nc
e
of
nor
m
a
l
A
O
D
V
r
out
in
g
pr
ot
oc
ol
in
th
e
Q
oS
m
e
tr
ic
s
.
T
he
pr
opos
e
d
B
e
e
-
A
O
D
V
r
out
in
g
a
lg
or
it
hm
de
c
r
e
a
s
e
s
th
e
pa
c
ke
t
lo
s
s
,
de
la
y
,
a
nd
e
ne
r
gy
c
ons
um
pt
io
n
by
20%
,
40.5%
,
a
nd
12.875%
. T
he
th
r
oug
hput
is
im
pr
ove
d
on
18%
but
not
a
r
e
a
s
ona
bl
e
im
pr
ove
m
e
nt
c
om
pa
r
e
d
to
no
r
m
a
l
A
O
D
V
r
ou
ti
ng
pr
o
to
c
ol
.
T
hus
,
th
e
a
r
ti
c
le
ju
s
ti
f
ie
s
th
e
us
e
of
c
onve
nt
io
na
l
A
O
D
V
pr
ot
oc
ol
m
im
ic
e
d
w
it
h
be
e
a
lg
or
it
hm
s
,
id
e
nt
if
ie
d
a
n
d
r
e
m
ove
d
th
e
num
be
r
of
b
la
c
k
-
hol
e
s
w
hi
le
e
s
ta
bl
is
hi
ng
a
s
a
f
e
pa
th
by
r
e
di
r
e
c
ti
ng
th
e
a
tt
a
c
ki
ng
node
s
.
A
f
ur
th
e
r
r
e
s
e
a
r
c
h
c
a
n
be
c
a
r
r
ie
d
out
in
th
e
f
ut
ur
e
us
in
g s
of
t
c
om
put
in
g t
e
c
hni
que
s
f
or
e
nha
nc
in
g t
he
Q
oS
m
e
tr
ic
s
of
t
he
A
O
D
V
.
R
E
F
E
R
E
N
C
E
S
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T
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-
l
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i
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T
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i
l
i
z
a
t
i
on:
a
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oj
e
c
t
m
a
na
ge
m
e
nt
pe
r
s
pe
c
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i
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bl
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k
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a
t
t
a
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i
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M
A
N
E
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us
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r
ba
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d
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r
oduc
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N
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,”
I
nt
e
r
nat
i
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R
e
s
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a
r
c
h
J
our
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ngi
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A
r
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vi
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w
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pr
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va
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a
nd
s
e
c
ur
i
t
y
i
m
pr
ove
m
e
nt
m
e
c
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ni
s
m
s
i
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M
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N
E
T
s
,”
I
nt
e
r
nat
i
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J
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na
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l
l
i
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Sy
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n
m
obi
l
e
A
dhoc
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e
t
w
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ks
,”
I
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r
nat
i
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R
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s
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a
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I
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A
r
ti
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e
ll
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S
N
:
2252
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8938
D
e
te
c
ti
on and av
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of
bl
ac
k
-
hol
e
at
ta
c
k
i
n m
obi
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adho
c
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tw
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k
u
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g be
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ad
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hoc
…
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Sr
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t
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c
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i
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ot
oc
ol
f
r
om
bl
a
c
k hol
e
a
t
t
a
c
k i
n W
S
N
,”
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r
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nt
s
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c
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t
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on a
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pa
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a
d hoc
ne
t
w
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ks
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A
r
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vi
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w
,”
E
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pt
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an I
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pa
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a
na
l
yz
i
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r
e
a
c
t
i
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r
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pr
ot
oc
ol
s
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A
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D
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S
R
a
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Q
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I
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r
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a
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d
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i
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a
r
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c
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a
l
gor
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t
hm
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l
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s
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M
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V
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r
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m
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m
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h
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r
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“
P
a
r
t
i
c
l
e
s
w
a
r
m
opt
i
m
i
z
a
t
i
on
ba
s
e
d
c
l
u
s
t
e
r
i
ng
a
l
gor
i
t
hm
w
i
t
h
m
obi
l
e
s
i
nk
f
or
W
S
N
s
,”
F
ut
ur
e
G
e
ne
r
at
i
on C
om
put
e
r
Sy
s
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e
m
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N
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M
a
z
h
a
r
a
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M
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F
a
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ooq,
“
V
ul
ne
r
a
bi
l
i
t
y
a
na
l
y
s
i
s
a
nd
s
e
c
ur
i
t
y
f
r
a
m
e
w
or
k
(
B
e
e
S
e
c
)
f
or
na
t
ur
e
i
ns
pi
r
e
d
M
A
N
E
T
r
out
i
ng
pr
ot
oc
ol
s
,
”
i
n
9t
h annual
c
onf
e
r
e
nc
e
on G
e
n
e
t
i
c
and e
v
ol
ut
i
onar
y
c
o
m
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i
on
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B
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T
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K
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,
B
.
P
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H
ung,
a
nd
M
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e
j
s
a
l
e
m
-
B
r
a
hm
i
,
“
Q
ua
l
i
t
a
t
i
ve
r
e
s
e
a
r
c
h
i
n
s
oc
i
a
l
s
c
i
e
nc
e
s
:
d
a
t
a
c
ol
l
e
c
t
i
on,
da
t
a
a
na
l
ys
i
s
a
nd
r
e
por
t
w
r
i
t
i
ng,”
I
nt
e
r
nat
i
onal
J
our
nal
of
P
ubl
i
c
Se
c
t
or
P
e
r
f
or
m
anc
e
M
anage
m
e
nt
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T
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l
da
bi
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r
a
ni
, R
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a
ul
, a
nd P
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. d. L
ov
e
, “
Q
ua
nt
i
t
a
t
i
ve
a
nd qua
l
i
t
a
t
i
ve
d
e
c
i
s
i
on
-
m
a
ki
ng m
e
t
hods
i
n
s
i
m
ul
a
t
i
on m
ode
l
l
i
ng,
”
M
anage
m
e
nt
D
e
c
i
s
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on
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S
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os
s
a
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dm
onds
, “
S
oc
i
ol
ogy a
nd
s
i
m
ul
a
t
i
on:
S
t
a
t
i
s
t
i
c
a
l
a
nd qua
l
i
t
a
t
i
ve
c
r
os
s
-
va
l
i
da
t
i
on,”
A
m
e
r
i
c
an
J
our
nal
of
Soc
i
ol
ogy
,
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K
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a
l
l
a
nd K
. V
a
r
a
dha
n, “
T
he
ns
m
a
nua
l
(
F
or
m
e
r
l
y ns
not
e
s
a
nd doc
um
e
nt
a
t
i
on)
,”
T
he
V
I
N
T
pr
oj
e
c
t
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H
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G
ha
f
f
a
r
i
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n
a
nd
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S
a
de
ghi
z
a
de
h,
“
P
a
r
s
i
m
:
A
p
a
r
a
m
e
t
r
i
c
s
i
m
ul
a
t
i
on
a
ppl
i
c
a
t
i
on
f
or
w
i
r
e
l
e
s
s
s
e
ns
or
ne
t
w
or
ks
b
a
s
e
d
on
N
S
2
s
i
m
ul
a
t
or
,”
I
nt
e
r
nat
i
onal
J
our
nal
of
N
onl
i
ne
ar
A
nal
y
s
i
s
and A
ppl
i
c
at
i
ons
(
I
J
N
A
A
)
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S
. S
a
r
ka
r
a
nd R
. D
a
t
t
a
, “
A
O
D
V
-
ba
s
e
d t
e
c
hni
que
f
or
qui
c
k a
nd
s
e
c
ur
e
l
oc
a
l
r
e
c
o
ve
r
y f
r
om
l
i
nk
f
a
i
l
ur
e
s
i
n
M
A
N
E
T
s
,”
I
nt
e
r
nat
i
onal
J
our
nal
of
C
om
m
uni
c
at
i
on
N
e
t
w
or
k
s
and
D
i
s
t
r
i
but
e
d
Sy
s
t
e
m
s
,
vol
.
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P
.
G
upt
a
a
nd
P
.
B
a
ns
a
l
,
“
P
a
c
ke
t
dr
op
a
na
l
ys
i
s
w
i
t
h
va
r
i
a
t
i
on
i
n
a
r
e
a
a
nd
num
be
r
of
node
s
i
n
M
A
N
E
T
,”
SA
M
R
I
D
D
H
I
:
A
J
our
nal
of
P
hy
s
i
c
al
Sc
i
e
nc
e
s
, E
ngi
ne
e
r
i
ng and T
e
c
hnol
ogy
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a
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.v11i
01.2.
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T
.
H
øi
l
a
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-
J
ør
ge
ns
e
n,
B
.
A
hl
gr
e
n,
P
.
H
ur
t
i
g,
a
nd
A
.
B
r
uns
t
r
om
,
“
M
e
a
s
ur
i
ng
l
a
t
e
nc
y
va
r
i
a
t
i
on
i
n
t
he
i
nt
e
r
ne
t
,”
C
oN
E
X
T
2016
-
P
r
oc
e
e
di
ngs
of
t
he
12t
h
I
nt
e
r
nat
i
onal
C
onf
e
r
e
nc
e
on
E
m
e
r
gi
ng
N
e
t
w
o
r
k
i
ng
E
X
pe
r
i
m
e
nt
s
and
T
e
c
hnol
ogi
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R
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ngo,
N
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J
a
m
a
l
,
a
nd
M
.
I
.
A
ba
s
,
“
A
na
l
y
s
i
s
of
e
nd
-
to
-
e
nd
de
l
a
y
vi
de
o
c
o
nf
e
r
e
nc
i
ng
s
e
r
vi
c
e
s
on
a
m
obi
l
e
a
d
hoc
ne
t
w
or
k,”
J
our
nal
of
I
nf
or
m
at
i
c
s
and T
e
l
e
c
om
m
uni
c
at
i
on E
ngi
ne
e
r
i
ng
, vol
. 6, no. 2, pp. 393
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j
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t
e
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[
31]
V
.
D
a
t
t
a
na
a
nd
P
.
K
.
K
r
i
s
hna
,
“
O
pt
i
m
i
z
i
ng
r
out
i
ng
i
n
M
A
N
E
T
s
w
i
t
h
e
ne
r
g
y
c
ons
e
r
va
t
i
on,”
I
nt
e
r
nat
i
onal
J
our
nal
of
A
ppl
i
e
d
E
ngi
ne
e
r
i
ng and M
anage
m
e
nt
L
e
t
t
e
r
s
, pp. 75
–
87, 2023, doi
:
10.47992/
i
j
a
e
m
l
.2
581.7000.0189.
B
I
O
G
R
A
P
H
I
E
S
O
F
A
U
T
H
O
R
S
Srikanth
Pala
holds
a
Ph.D
.
d
egree
in
Computer
Science
Engineerin
g
from
Andhra
University,
Visakhapatnam,
2022.
He
is
currently
working
as
the
Associate
Profes
sor
in
Computer
Science
Enginee
ring,
Shri
Vishnu
Enginee
ring
College
for
Women’s
since
2015.
His
research
int
e
rests
include
the
routing
protocols
in
IoT
&
MANET’s,
so
ft
computing
approaches
like
fuzzy
logic
and
ANFIS
for
the
time
series
problems.
He
can
be
contacted
at
email:
sreekanth.pa
la@
gmail.com
.
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