I
nd
o
ne
s
ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
nd
Co
m
p
u
t
er
Science
Vo
l.
10
,
No
.
1
,
A
p
r
il
2
0
1
8
,
p
p
.
295
~
3
0
1
I
SS
N:
2502
-
4752
,
DOI
: 1
0
.
1
1
5
9
1
/
i
j
ee
cs
.
v
1
0
.
i1
.
p
p
295
-
3
0
1
295
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ia
e
s
co
r
e.
co
m/jo
u
r
n
a
ls
/in
d
ex
.
p
h
p
/
ijeec
s
Ant
Ba
sed
Cro
ss
La
y
ered O
p
ti
m
i
za
tion Proto
co
l
for
WMSN
w
ith
Fu
zz
y
Cluste
ring
D
i
pa
li
P
a
ra
g
Adhy
a
pa
k
1
,
S
ri
dh
a
ra
n
B
ha
v
a
ni
2
,
A
pa
rna
P
ra
deep
L
a
t
ur
k
a
r
3
1,
3
De
p
a
rtm
e
n
t
o
f
E
lec
tro
n
ics
&
Tele
c
o
m
m
u
n
ica
ti
o
n
,
P
ES
’s
M
o
d
e
rn
Co
l
leg
e
o
f
En
g
in
e
e
rin
g
,
S
a
v
it
rib
a
i
P
h
u
le
P
u
n
e
Un
iv
e
rsit
y
,
P
u
n
e
,
I
n
d
ia
2
De
p
a
rt
m
e
n
t
o
f
El
e
c
tro
n
ics
&
Co
m
m
u
n
ica
ti
o
n
,
Ka
rp
a
g
a
m
A
c
a
d
e
m
y
o
f
Hig
h
e
r
Ed
u
c
a
ti
o
n
,
Co
im
b
to
re
,
In
d
ia
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Dec
9
,
2
0
1
7
R
ev
i
s
ed
Feb
2
8
,
2
0
1
8
A
cc
ep
ted
Mar
1
8
,
2
0
1
8
W
irele
ss
M
u
lt
ime
d
ia
S
e
n
so
r
Ne
tw
o
rk
(
W
M
S
N)
is
e
m
b
e
d
d
e
d
w
it
h
larg
e
n
u
m
b
e
r
o
f
A
u
d
io
,
V
id
e
o
a
n
d
sc
a
lar
se
n
so
r
n
o
d
e
s
w
h
ich
c
a
n
a
b
le
to
re
tri
e
v
e
th
e
m
u
lt
i
m
e
d
ia
in
f
o
r
m
a
ti
o
n
f
ro
m
th
e
e
n
v
iro
n
m
e
n
t.
W
M
S
N
h
a
s
se
v
e
ra
l
c
h
a
ll
e
n
g
e
s
su
c
h
a
s
li
f
e
ti
m
e
o
f
th
e
n
e
tw
o
rk
,
M
e
m
o
r
y
re
q
u
irem
e
n
t,
Co
v
e
ra
g
e
,
Ba
n
d
w
id
th
a
n
d
Qo
S
m
e
tri
c
s.
He
n
c
e
se
lec
ti
o
n
o
f
ro
u
t
in
g
a
lg
o
rit
h
m
is
c
ru
c
ial
in
W
M
S
N.
A
g
a
in
in
terd
e
p
e
n
d
e
n
c
ies
o
f
th
e
p
ro
to
c
o
l
lay
e
r
c
a
n
n
o
t
b
e
n
e
g
lec
ted
to
im
p
ro
v
e
th
e
n
e
tw
o
rk
p
e
rf
o
rm
a
n
c
e
.
Clu
ste
rin
g
in
W
M
S
N
is
c
h
a
ll
e
n
g
in
g
tas
k
in
o
rd
e
r
to
in
c
r
e
a
se
n
e
t
w
o
rk
li
f
e
ti
m
e
a
n
d
to
im
p
ro
v
e
th
e
c
o
m
m
u
n
ica
ti
o
n
.
He
n
c
e
F
u
z
z
y
c
lu
ste
re
d
A
n
t
b
a
se
d
c
ro
ss
la
y
e
r
p
ro
to
c
o
l
(
F
CA
X
L
)
is
p
ro
p
o
se
d
.
In
t
h
is
p
a
p
e
r
p
e
rf
o
r
m
a
n
c
e
a
n
a
l
y
sis
o
f
a
n
t
b
a
se
d
c
ro
ss
la
y
e
r
o
p
ti
m
i
z
a
ti
o
n
p
ro
t
o
c
o
l
w
it
h
f
u
z
z
y
c
lu
ste
rin
g
b
a
s
e
d
o
n
n
u
m
b
e
r
o
f
n
o
d
e
s
a
n
d
p
a
c
k
e
t
siz
e
is
d
o
n
e
.
S
im
u
latio
n
re
su
lt
s
sh
o
w
s
th
a
t
F
u
z
z
y
c
lu
ste
re
d
a
n
t
b
a
se
d
c
ro
ss
lay
e
r
o
p
ti
m
iza
ti
o
n
p
ro
to
c
o
l
p
e
rf
o
rm
s
b
e
st
a
s
c
o
m
p
a
re
d
to
A
n
tS
e
n
se
Ne
t
ro
u
ti
n
g
p
ro
t
o
c
o
l,
C
ro
ss
la
y
e
r
r
o
u
ti
n
g
p
ro
t
o
c
o
l
a
n
d
A
n
t
b
a
se
d
c
ro
ss
lay
e
r
ro
u
ti
n
g
p
ro
t
o
c
o
l
in
term
s
o
f
Qo
S
p
a
ra
m
e
ters
su
c
h
a
s
Th
ro
u
g
h
p
u
t,
P
a
c
k
e
t
d
e
li
v
e
ry
ra
ti
o
a
n
d
d
e
lay
.
H
e
n
c
e
th
e
li
f
e
ti
m
e
o
f
th
e
n
e
tw
o
rk
in
c
re
a
se
s.
K
ey
w
o
r
d
s
:
W
MSN
Qo
S
FC
A
X
L
Al
l
rig
h
ts
re
se
rv
e
d
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Dip
aliP
ar
ag
A
d
h
y
ap
ak
,
Kar
p
ag
a
m
U
n
i
v
er
s
it
y
,
P
o
llach
i M
ain
R
o
ad
,
L
&
T
B
y
p
a
s
s
r
o
ad
J
u
n
ctio
n
,
E
ac
h
an
ar
i
P
o
s
t,
E
ac
h
an
ar
i,
C
o
i
m
b
ato
r
e,
T
am
il
n
ad
u
,
I
n
d
ia
-
6
4
1
0
2
1
.
E
m
ail:
ad
h
y
ap
ak
d
ee
p
a@
g
m
ail
.
co
m
1.
I
NT
RO
D
UCT
I
O
N
W
ir
eless
s
en
s
o
r
n
et
w
o
r
k
s
ar
e
co
m
p
r
is
ed
o
f
lar
g
e
n
u
m
b
er
o
f
s
ca
lar
s
en
s
o
r
n
o
d
es
w
h
ich
ca
n
s
en
s
e
p
h
y
s
ical
p
ar
a
m
eter
s
li
k
e
te
m
p
er
atu
r
e,
p
r
ess
u
r
e,
h
u
m
id
it
y
,
s
o
u
n
d
a
n
d
li
g
h
t
a
n
d
ca
n
e
x
ch
a
n
g
e
t
h
e
i
n
f
o
r
m
atio
n
.
A
d
v
an
ce
m
e
n
t
i
n
tec
h
n
o
lo
g
y
h
as
led
to
th
e
m
u
lti
m
ed
ia
s
e
n
s
o
r
n
o
d
es
w
h
ich
ar
e
ca
p
ab
le
o
f
s
e
n
s
i
n
g
a
u
d
io
as
w
ell
as
v
id
eo
d
ata.
T
h
ese
m
u
lti
m
ed
ia
d
e
v
ices
ar
e
e
m
b
ed
d
e
d
in
t
h
e
s
e
n
s
o
r
n
o
d
e.
S
u
c
h
t
y
p
e
o
f
n
e
t
w
o
r
k
s
is
ca
lled
as
w
ir
eles
s
m
u
lti
m
ed
ia
s
en
s
o
r
n
et
w
o
r
k
s
.
T
h
ese
n
et
wo
r
k
s
ca
n
s
e
n
s
e
a
n
d
tr
an
s
f
er
th
e
s
ca
lar
as
w
ell
a
s
m
u
lti
m
ed
ia
d
ata
i.
e.
im
a
g
e,
au
d
io
,
an
d
v
id
eo
s
tr
ea
m
s
i
n
r
ea
l
ti
m
e
as
w
ell
as
n
o
n
-
r
ea
l
ti
m
e
co
m
m
u
n
icat
io
n
.
T
h
ese
n
et
w
o
r
k
s
h
a
v
e
ad
d
itio
n
al
f
ea
t
u
r
es
lik
e
h
ig
h
b
a
n
d
w
i
d
th
r
eq
u
ir
e
m
en
t,
to
ler
ab
le
d
el
a
y
,
lo
w
j
itter
,
lo
w
p
ac
k
et
lo
s
s
w
h
ic
h
i
m
p
o
s
e
s
t
h
e
ad
d
itio
n
a
l
ch
a
llen
g
e
s
o
n
t
h
e
d
esi
g
n
er
.
W
MSN
i
s
in
t
h
e
n
ee
d
o
f
o
n
ti
m
e
r
eliab
le
d
ata
d
eliv
er
y
to
ac
h
ie
v
e
Q
u
alit
y
o
f
Ser
v
ice.
M
u
lti
m
ed
ia
d
ata
is
d
ela
y
s
e
n
s
iti
v
e
[
1
]
an
d
s
en
s
i
tiv
e
to
p
ac
k
et
lo
s
s
also
w
h
ic
h
m
a
y
r
esu
lt i
n
j
itter
an
d
d
ec
r
ea
s
es th
e
th
r
o
u
g
h
p
u
t.
Selectio
n
o
f
r
o
u
ti
n
g
p
r
o
to
co
l
p
lay
s
a
n
i
m
p
o
r
tan
t
r
o
le
f
o
r
W
MSN
n
et
w
o
r
k
s
.
Ma
i
n
o
b
j
ec
tiv
e
o
f
t
h
e
r
o
u
tin
g
p
r
o
to
co
l
is
to
m
in
i
m
iz
e
th
e
e
n
d
to
en
d
d
ela
y
,
j
itter
an
d
to
in
cr
ea
s
e
th
e
p
ac
k
et
d
eli
v
er
y
r
atio
in
tu
r
n
to
in
cr
ea
s
e
t
h
e
th
r
o
u
g
h
p
u
t
a
tlo
w
en
er
g
y
co
s
t.
T
h
ese
n
et
w
o
r
k
s
ar
e
g
en
er
all
y
ev
e
n
t
b
ased
n
e
t
w
o
r
k
s
.
Fo
r
ev
e
n
t
b
ased
n
et
w
o
r
k
s
p
r
o
ac
tiv
e
ap
p
r
o
ac
h
is
u
s
ed
in
w
h
ic
h
ea
c
h
n
o
d
e
m
o
n
ito
r
s
its
n
ei
g
h
b
o
r
in
g
li
n
k
s
an
d
u
p
d
ate
ch
an
g
es
ac
co
r
d
in
g
l
y
[
1
]
.
Sen
s
o
r
n
o
d
esco
m
m
u
n
icate
w
it
h
ea
ch
o
th
er
to
d
etec
t
ev
e
n
ts
d
ep
en
d
in
g
o
n
t
h
e
ap
p
lica
tio
n
,
to
co
llect
an
d
p
r
o
ce
s
s
d
ata,
an
d
to
tr
an
s
m
it
th
e
s
en
s
ed
i
n
f
o
r
m
a
tio
n
to
t
h
e
b
ase
s
tatio
n
b
y
h
o
p
p
in
g
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lecE
n
g
&
C
o
m
p
Sci,
Vo
l.
10
,
No
.
1
,
A
p
r
il 2
0
1
8
:
2
9
5
–
301
296
th
e
d
ata
f
r
o
m
n
o
d
e
to
n
o
d
e
[
7
]
.
T
h
e
s
en
o
r
n
o
d
es
ar
e
eit
h
er
r
an
d
o
m
l
y
d
ep
lo
y
ed
o
r
ac
co
r
d
in
g
to
t
h
e
s
tati
s
tical
d
is
tr
ib
u
tio
n
.
W
ir
eles
s
m
u
liti
m
ed
ia
s
en
s
o
r
n
et
w
o
r
k
co
n
s
i
s
t
o
f
v
ar
io
u
s
s
en
s
o
r
n
o
d
es
t
h
at
ar
e
u
s
ed
to
tar
g
et
o
r
m
o
n
ito
r
f
o
r
est ar
ea
o
r
in
d
u
s
tr
i
al
ac
tiv
it
y
.
[
8
]
.
S
w
ar
m
b
ased
r
o
u
tin
g
p
r
o
to
co
ls
h
a
v
e
b
ee
n
u
s
ed
to
tac
k
le
ad
d
itio
n
al
c
h
alle
n
g
e
s
.
Mo
s
t
s
u
cc
e
s
s
f
u
l
an
d
f
a
m
o
u
s
s
w
ar
m
i
n
tell
ig
e
n
ce
i
s
th
e
a
n
t
co
lo
n
y
o
p
ti
m
izat
io
n
t
ec
h
n
iq
u
e
[
2
]
.
I
n
th
i
s
,
ar
ti
f
ici
al
an
t
s
ar
e
u
s
ed
to
f
i
n
d
th
e
m
o
s
t
e
f
f
icie
n
t
p
at
h
.
A
l
s
o
i
n
ter
d
ep
en
d
en
cies
o
f
th
e
p
r
o
to
co
l
lay
er
ca
n
n
o
t
b
e
n
eg
lecte
d
.
T
o
ex
p
lo
it
th
ese
i
n
ter
d
ep
en
d
en
cie
s
cr
o
s
s
la
y
er
in
g
p
r
in
cip
le
ca
n
b
e
e
m
p
lo
y
ed
alo
n
g
w
it
h
th
e
s
w
ar
m
in
telli
g
e
n
ce
.
T
h
ese
W
MSN
n
et
w
o
r
k
s
ar
e
h
av
in
g
h
ier
ar
ch
ical
s
tr
u
ct
u
r
e.
Hen
ce
to
o
p
ti
m
ize
t
h
e
cl
u
s
ter
i
n
g
p
r
o
ce
s
s
,
f
u
zz
y
i
s
t
h
e
o
n
e
o
f
th
e
b
est
s
o
l
u
tio
n
.
F
u
zz
y
b
a
s
ed
clu
s
ter
i
n
g
m
i
n
i
m
izes
d
ea
d
n
o
d
es,
s
av
es
t
h
e
co
s
t
o
f
cr
ea
tin
g
n
e
w
cl
u
s
ter
s
,
in
cr
ea
s
es t
h
e
r
esid
u
al
en
er
g
y
a
n
d
in
t
u
r
n
e
n
h
a
n
ce
s
t
h
e
n
e
t
w
o
r
k
lif
et
i
m
e.
I
n
th
i
s
p
ap
er
Fu
zz
y
cl
u
s
ter
e
d
an
t
b
ased
cr
o
s
s
la
y
er
p
r
o
to
co
l
is
p
r
o
p
o
s
ed
f
o
r
W
MS
N
w
h
ic
h
m
i
n
i
m
izes
e
n
d
to
en
d
d
ela
y
,
in
cr
ea
s
es
p
ac
k
et
d
eli
v
er
y
r
ati
o
an
d
th
r
o
u
g
h
p
u
t.
An
t
b
ased
r
o
u
tin
g
p
r
o
to
co
l
is
u
s
e
d
to
f
i
n
d
th
e
s
h
o
r
tes
t
p
ath
w
h
ile
t
h
e
p
r
io
r
it
y
b
ased
s
ch
e
d
u
lin
g
a
n
d
q
u
eu
i
n
g
m
in
i
m
ize
s
th
e
d
ela
y
.
Fu
zz
y
b
ased
clu
s
ter
i
n
g
m
i
n
i
m
izes c
o
s
t o
f
cr
ea
tin
g
n
e
w
clu
s
ter
s
w
h
i
ch
in
t
u
r
n
e
n
h
an
ce
s
th
e
n
et
w
o
r
k
li
f
eti
m
e.
T
h
e
Net
w
o
r
k
s
i
m
u
lato
r
h
elp
s
th
e
d
ev
elo
p
er
to
c
r
ea
t
e
an
d
s
i
m
u
late
n
e
w
m
o
d
els
o
n
an
ar
b
itra
r
y
n
et
w
o
r
k
b
y
s
p
ec
i
f
y
in
g
b
o
th
th
e
b
eh
av
io
r
o
f
th
e
n
et
w
o
r
k
n
o
d
e
s
an
d
th
e
co
m
m
u
n
icatio
n
ch
an
n
els.
I
t
p
r
o
v
id
es
a
v
ir
tu
a
len
v
ir
o
n
m
e
n
t
f
o
r
an
a
s
s
o
r
tm
e
n
t
o
f
d
esira
b
le
f
ea
t
u
r
es
s
u
c
h
as
m
o
d
eli
n
g
a
n
et
w
o
r
k
b
ased
o
n
a
s
p
ec
i
f
i
c
cr
iter
ia
an
d
an
al
y
zi
n
g
i
ts
p
er
f
o
r
m
an
ce
u
n
d
er
d
if
f
er
e
n
t sce
n
ar
i
o
s
[
9
].
Hen
ce
to
s
i
m
u
late
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
Net
w
o
r
k
Si
m
u
lato
r
2
(
NS2
)
is
u
s
ed
.
T
h
e
r
em
ain
d
er
o
f
th
i
s
p
ap
er
is
o
r
g
an
ized
as
f
o
llo
w
s
.
I
n
s
ec
ti
o
n
I
I
s
o
m
e
r
elate
d
w
o
r
k
is
d
is
cu
s
s
ed
.
I
n
s
ec
tio
n
I
I
I
,
FC
A
X
L
-
R
o
u
ti
n
g
p
r
o
to
co
l
is
d
is
c
u
s
s
ed
.
Secti
o
n
I
V
d
is
c
u
s
s
es
ab
o
u
t
th
e
p
er
f
o
r
m
an
ce
o
f
t
h
e
p
r
o
p
o
s
ed
p
r
o
to
co
l.
2.
L
I
T
E
R
AT
U
RE
SU
RVE
Y
I
n
th
is
s
ec
tio
n
a
b
r
ief
s
u
r
v
e
y
o
f
W
MSN
an
d
its
r
o
u
tin
g
is
p
r
esen
ted
.
W
ir
eless
m
u
lti
m
e
d
ia
s
en
s
o
r
n
et
w
o
r
k
h
a
s
m
a
n
y
c
h
alle
n
g
e
s
.S
ev
er
al
ap
p
r
o
ac
h
es
h
av
e
b
ee
n
p
r
o
p
o
s
ed
t
o
o
p
ti
m
ize
th
e
Qo
S
p
ar
am
eter
s
.
C
r
o
s
s
la
y
er
Qo
S
r
o
u
ti
n
g
p
r
o
to
co
l
f
o
r
W
MSN
h
as
b
ee
n
p
r
o
p
o
s
ed
b
y
Z
ar
a
Ha
m
id
,
Fa
is
al
B
ash
ir
,
J
ae
Yo
u
n
g
P
y
u
n
.
T
h
is
p
r
o
to
co
l
h
as
ai
m
ed
at
p
r
o
v
id
in
g
s
o
f
t
e
n
d
to
en
d
d
ela
y
g
u
ar
an
tees.
E
v
a
lu
at
io
n
h
as
s
h
o
w
ed
th
a
t
it
p
r
o
v
id
es b
etter
d
elay
as c
o
m
p
ar
ed
to
m
i
n
i
m
u
m
r
o
u
ti
n
g
p
r
o
to
co
l [
1
]
.
L
u
is
C
o
b
o
,
A
lej
an
d
r
o
an
d
Sam
u
e
l
h
a
s
p
r
o
p
o
s
ed
Qo
S
r
o
u
tin
g
m
o
d
el
b
ased
o
n
tr
ad
itio
n
al
an
t
b
ased
alg
o
r
ith
m
.
An
tSe
n
s
eNe
t
p
r
o
to
co
l
h
as
b
ee
n
i
m
p
le
m
e
n
ted
.
T
h
is
alg
o
r
ith
m
h
a
s
b
e
tter
co
n
v
er
g
e
n
ce
a
n
d
it
p
r
o
v
id
es si
g
n
i
f
ican
tl
y
b
etter
Q
o
S f
o
r
m
u
ltip
le
t
y
p
es o
f
s
er
v
ic
es [
2
]
.
C
r
o
s
s
la
y
er
a
n
t
b
ased
r
o
u
tin
g
p
r
o
to
co
l
f
o
r
W
MSN
h
as
b
ee
n
p
r
o
p
o
s
ed
b
y
M.
A
b
az
ee
d
,
K.
Salee
m
,
S.
Z
u
b
air
an
d
N.
Fis
al
in
2
0
1
1
.
He
h
as
u
s
ed
m
o
d
i
f
ied
AC
O
t
ec
h
n
iq
u
e
to
en
h
a
n
ce
th
e
r
o
u
ti
n
g
e
f
f
ic
ien
c
y
.
T
h
is
i
m
p
r
o
v
ed
AC
O
h
as b
ee
n
u
s
ed
to
s
ea
r
ch
f
o
r
th
e
b
est p
at
h
to
s
atis
f
y
t
h
e
m
u
lt
i
m
ed
ia
tr
a
f
f
ic
r
eq
u
ir
e
m
e
n
ts
[
3
]
.
Fu
zz
y
b
ased
ap
p
r
o
ac
h
o
f
en
er
g
y
e
f
f
icie
n
t
h
ier
ar
ch
ical
cl
u
s
te
r
in
g
i
s
p
r
o
p
o
s
ed
b
y
G.
S.
M.
Va
m
s
i
an
d
Neh
aC
h
o
u
b
e
y
.
T
h
ey
h
av
e
o
p
ti
m
ized
th
e
cl
u
s
ter
i
n
g
p
r
o
ce
s
s
,
clu
s
ter
h
ea
d
elec
tio
n
,
an
d
d
ec
r
ea
s
ed
th
e
n
u
m
b
er
o
f
d
ea
d
n
o
d
es.
C
lu
s
ter
s
elec
t
io
n
is
r
a
n
d
o
m
i
n
n
at
u
r
e
an
d
w
ei
g
h
t
s
h
av
e
b
ee
n
ca
lcu
la
ted
b
ased
o
n
w
h
ic
h
clu
s
te
r
h
ea
d
elec
tio
n
is
d
o
n
e.
Hier
a
r
ch
ical
r
o
u
ti
n
g
h
as
b
ee
n
i
m
p
le
m
en
ted
u
s
i
n
g
f
u
zz
y
i
n
ter
f
er
en
ce
en
g
in
e.
B
y
ap
p
ly
i
n
g
th
i
s
m
e
th
o
d
th
e
r
es
id
u
al
en
er
g
y
a
n
d
n
et
w
o
r
k
li
f
eti
m
e
h
as
b
ee
n
i
n
cr
ea
s
ed
w
h
er
ea
s
th
e
co
s
t
o
f
cr
ea
tin
g
t
h
e
cl
u
s
ter
s
a
n
d
n
u
m
b
er
o
f
d
ea
d
n
o
d
es h
as b
ee
n
d
ec
r
ea
s
ed
[
4
]
.
Vik
asB
h
an
d
ar
ar
y
,
Am
ita
Ma
l
ik
a
n
d
San
j
a
y
Ku
m
ar
h
av
e
r
ev
ie
w
ed
t
h
e
r
o
u
ti
n
g
p
r
o
to
co
l
s
an
d
it
s
is
s
u
es
f
o
r
W
MSN.
T
h
is
p
ap
er
p
r
esen
t
s
v
ar
io
u
s
ex
is
ti
n
g
r
o
u
t
in
g
s
tr
ateg
ie
s
i
n
W
MS
Ns
w
it
h
t
h
eir
ap
p
licatio
n
s
an
d
li
m
i
tatio
n
s
w
h
ich
lead
to
o
p
en
r
esear
ch
is
s
u
es,
d
etailed
class
i
f
icatio
n
an
d
co
m
p
ar
is
o
n
[
5
]
.
Al
m
al
k
a
w
i,
Z
ap
ata
an
d
Kar
a
k
i
h
as
p
r
o
p
o
s
ed
a
cr
o
s
s
la
y
er
b
ased
clu
s
ter
ed
m
u
lt
ip
ath
r
o
u
ti
n
g
w
it
h
Qo
S
a
w
ar
e
s
ch
ed
u
li
n
g
.
I
t
is
b
ased
o
n
clu
s
ter
ed
m
u
ltip
a
th
r
o
u
ti
n
g
p
r
o
to
co
l
an
d
ad
a
p
tiv
e
Qo
S
a
w
ar
e
s
ch
ed
u
lin
g
f
o
r
d
if
f
er
en
t
tr
af
f
ic
class
es.
He
h
as
ex
p
lo
ited
h
ier
ar
c
h
ical
s
tr
u
ct
u
r
e
o
f
p
o
w
er
f
u
l
clu
s
ter
h
ea
d
s
an
d
th
e
o
p
ti
m
ized
m
u
l
tip
le
p
ath
alo
n
g
w
it
h
t
h
e
ad
ap
ti
v
e
s
c
h
e
d
u
lin
g
to
s
u
p
p
o
r
t
r
eliab
le,
h
i
g
h
t
h
r
o
u
g
h
p
u
t
an
d
en
er
g
y
ef
f
icie
n
t
m
u
lti
m
ed
ia
tr
an
s
m
i
s
s
io
n
i
n
W
MSN
[
6
]
.
3.
M
E
T
H
O
DO
L
O
G
Y
W
MSN
n
et
w
o
r
k
is
cr
ea
ted
w
i
th
a
u
d
io
,
v
i
d
eo
an
d
te
m
p
er
at
u
r
e
s
e
n
s
o
r
s
.
T
h
is
n
e
t
w
o
r
k
is
h
eter
o
g
e
n
eo
u
s
i
n
n
at
u
r
e.
Netw
o
r
k
s
i
m
u
lato
r
2
is
u
s
ed
to
d
ev
elo
p
an
d
s
im
u
late
th
e
p
er
f
o
r
m
an
ce
o
f
t
h
e
FC
A
X
L
r
o
u
ti
n
g
p
r
o
to
co
l.
T
h
r
o
u
g
h
p
u
t,
j
itter
an
d
p
ac
k
et
d
eliv
er
y
r
atio
ar
e
u
s
ed
as
th
e
p
er
f
o
r
m
a
n
ce
m
ea
s
u
r
e
s
to
ev
alu
ate
t
h
e
p
er
f
o
r
m
a
n
ce
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lecE
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
A
n
t B
a
s
ed
C
r
o
s
s
La
ye
r
ed
Op
ti
miz
a
tio
n
P
r
o
to
co
l fo
r
W
MS
N
w
ith
F
u
z
z
y
C
lu
s
erin
g
(
Dip
a
liP
a
r
a
g
A
d
h
y
a
p
a
k
)
297
Net
w
o
r
k
P
ar
am
eter
s
to
s
i
m
u
l
ate
R
o
u
ti
n
g
Me
ch
a
n
is
m
ar
e
s
et
as
s
h
o
w
n
i
n
T
ab
le
1
.
T
h
ese
s
en
s
o
r
n
o
d
es
ar
e
e
m
b
ed
d
ed
w
it
h
d
at
a
p
ac
k
ets
ac
co
r
d
in
g
to
its
t
y
p
e.
T
h
e
m
ai
n
ai
m
o
f
th
e
d
e
s
ig
n
is
to
i
n
cr
ea
s
e
t
h
e
n
et
w
o
r
k
li
f
eti
m
e
an
d
to
o
p
ti
m
ize
th
e
Qo
S
p
ar
a
m
eter
s
.
H
en
ce
clu
s
ter
in
g
in
W
MSN
is
ch
allen
g
i
n
g
tas
k
.
C
lu
s
ter
i
n
g
is
d
o
n
e
b
y
ass
ig
n
i
n
g
ea
c
h
n
o
d
e
to
p
ar
ticu
lar
clu
s
ter
h
ea
d
.
T
h
is
clu
s
ter
h
ea
d
s
elec
tio
n
is
b
ased
o
n
f
o
llo
w
in
g
p
ar
a
m
eter
s
:
R
e
s
id
u
al
e
n
er
g
y
,
d
i
s
tan
ce
b
et
w
ee
n
b
ase
s
tat
io
n
a
n
d
s
i
n
k
,
Me
m
o
r
y
a
n
d
D
is
ta
n
ce
b
et
w
ee
n
t
w
o
cl
u
s
ter
s
.
T
h
is
p
r
o
ce
s
s
is
f
u
ll
y
d
is
tr
ib
u
ti
v
e.
I
n
th
e
p
r
o
p
o
s
ed
m
eth
o
d
,
f
u
zz
y
b
ased
clu
s
ter
i
n
g
is
u
s
ed
.
T
h
e
m
a
in
o
b
j
ec
tiv
e
o
f
th
is
m
et
h
o
d
is
to
clu
s
ter
th
e
n
o
d
es
in
h
ier
ar
ch
ical
w
a
y
a
n
d
to
d
ec
r
ea
s
e
th
e
n
u
m
b
er
o
f
d
ea
d
n
o
d
es.
T
ab
le
1
.
Netw
o
r
k
P
ar
a
m
eter
s
S
i
mu
l
a
t
o
r
N
e
t
w
o
r
k
S
i
mu
l
a
t
o
r
2
N
u
mb
e
r
o
f
N
o
d
e
s
R
a
n
d
o
m
T
o
p
o
l
o
g
y
G
r
i
d
I
n
t
e
r
f
a
c
e
Ty
p
e
P
h
y
/
W
i
r
e
l
e
ssP
h
y
M
A
C
Ty
p
e
8
0
2
.
1
1
Q
u
e
u
e
Ty
p
e
D
r
o
p
t
a
i
l
/
P
r
i
o
r
i
t
y
Q
u
e
u
e
Q
u
e
u
e
L
e
n
g
t
h
5
0
P
a
c
k
e
t
s
A
n
t
e
n
n
a
T
y
p
e
O
mn
i
A
n
t
e
n
n
a
P
r
o
p
a
g
a
t
i
o
n
T
y
p
e
Tw
o
r
a
y
G
r
o
u
n
d
R
o
u
t
i
n
g
P
r
o
t
o
c
o
l
A
O
D
V
T
r
a
n
sp
o
r
t
A
g
e
n
t
UDP
A
p
p
l
i
c
a
t
i
o
n
A
g
e
n
t
C
B
R
I
n
i
t
i
a
l
E
n
e
r
g
y
1
0
0
Jo
u
l
e
s
S
i
mu
l
a
t
i
o
n
T
i
me
5
0
se
c
o
n
d
s
On
ce
th
e
cl
u
s
ter
in
g
is
d
o
n
e
An
t
p
r
o
ce
d
u
r
e
is
in
v
o
k
ed
to
f
in
d
ac
ce
s
s
ib
le
p
ath
s
f
o
r
all
tr
af
f
i
c
w
h
ich
i
s
cr
ea
ted
b
y
t
h
e
n
et
w
o
r
k
to
m
ee
t
d
i
f
f
er
e
n
t
Qo
S
r
eq
u
ir
e
m
en
ts
.
Her
e
ea
c
h
s
e
n
s
o
r
n
o
d
e
w
ai
ts
f
o
r
th
e
an
n
o
u
n
ce
m
e
n
t
f
r
o
m
t
h
e
b
ase
s
tatio
n
.
O
n
ce
t
h
e
a
n
n
o
u
n
ce
m
e
n
t
i
s
r
ec
eiv
ed
f
r
o
m
th
e
b
ase
s
t
atio
n
t
h
en
it
lo
o
k
s
f
o
r
th
e
r
o
u
te
to
th
e
b
ase
s
tatio
n
.
I
f
r
o
u
te
is
n
o
t
av
ailab
le
th
en
F
AN
T
s
ar
e
r
elea
s
ed
in
o
r
d
er
to
f
in
d
th
e
p
at
h
w
it
h
m
es
s
ag
e
to
its
n
eig
h
b
o
r
.
T
h
is
m
e
s
s
a
g
e
is
s
e
n
t
to
th
e
b
ase
s
tatio
n
t
h
r
o
u
g
h
t
h
e
in
ter
m
ed
iate
n
o
d
es.
I
n
r
esp
o
n
s
e
,
b
ase
s
tatio
n
r
elea
s
e
s
B
A
NT
m
e
s
s
a
g
e
o
n
r
ev
er
s
e
r
o
u
te.
T
h
u
s
i
n
ter
m
ed
iate
n
o
d
es
cr
ea
te
th
e
r
o
u
te
v
i
a
an
t
n
o
d
es.
B
ase
s
tatio
n
co
n
ti
n
u
o
u
s
l
y
r
elea
s
es
a
n
t
s
til
l
t
h
e
m
ax
i
m
u
m
a
n
t
r
elea
s
e
co
u
n
t
r
ea
ch
es.
E
ac
h
n
o
d
e
m
ai
n
tai
n
s
m
ai
n
te
n
an
ce
ti
m
er
,
an
d
c
h
ec
k
s
f
o
r
tr
af
f
ic
lo
ad
,
if
i
t
r
ea
ch
e
s
t
h
e
t
h
r
es
h
o
ld
th
en
it
s
e
n
d
M
A
NT
m
es
s
ag
e
w
it
h
p
h
er
o
m
o
n
e
v
a
lu
e.
Fro
m
th
e
in
ter
f
ac
e
q
u
e
u
e,
MA
C
la
y
er
a
n
d
L
i
n
k
la
y
er
p
a
ck
et
s
er
v
ice
ti
m
e
i
s
esti
m
ated
.
T
_
P
S
T
=
T
_
n
et
+
T
_
q
u
eu
e
+
T
_
m
ac
+
T
_
tr
an
s
;
Sen
s
o
r
d
ata
is
o
r
ig
i
n
ated
f
r
o
m
v
ar
io
u
s
t
y
p
e
s
o
f
n
o
d
es.
T
h
is
d
ata
is
au
d
io
,
v
id
eo
an
d
s
c
alar
t
y
p
e.
Hen
ce
s
ch
ed
u
li
n
g
is
d
o
n
e
ac
c
o
r
d
in
g
to
t
h
e
p
r
io
r
ities
.
Vid
eo
d
ata
h
a
v
e
h
i
g
h
e
s
t
p
r
io
r
it
y
w
h
ile
s
ca
lar
d
ata
h
a
s
lo
w
es
t
p
r
io
r
ity
.
Dr
o
p
tr
ail
ty
p
e
q
u
eu
in
g
is
u
s
ed
.
Fo
r
ea
ch
C
H,
class
i
f
ier
ch
ec
k
s
f
o
r
th
e
t
y
p
e
o
f
th
e
p
ac
k
et
an
d
th
en
s
en
t to
ap
p
r
o
p
r
iate
q
u
eu
e.
Sch
ed
u
ler
o
r
g
an
izes t
h
ese
p
a
ck
ets ac
co
r
d
in
g
to
th
e
le
v
el
o
f
p
r
io
r
ity
.
W
h
en
No
d
e
w
an
t
s
to
co
m
m
u
n
icate
w
it
h
s
i
n
k
it,
i
t se
n
d
s
th
e
i
n
f
o
r
m
atio
n
to
t
h
e
C
H.
T
h
en
C
H
ch
ec
k
s
its
r
o
u
tin
g
tab
le
to
f
in
d
th
e
ap
p
r
o
p
r
iate
s
h
o
r
test
p
ath
b
ased
f
r
o
m
t
h
e
p
h
er
o
m
o
n
e
tab
le.
On
ce
th
e
r
o
u
te
is
d
is
co
v
er
ed
,
d
ata
is
s
en
t
to
t
h
e
s
in
k
.
An
tSe
n
s
eNe
t
a
lg
o
r
it
h
m
is
u
s
ed
to
d
is
co
v
er
t
h
e
p
at
h
.
T
h
r
ee
p
h
ases
ar
e
d
ef
in
ed
f
o
r
t
h
is
p
r
o
to
co
l:
Fo
r
w
ar
d
a
n
t
P
h
a
s
e,
B
ac
k
w
ar
d
a
n
t
p
h
ase
an
d
r
o
u
te
m
ai
n
te
n
an
c
e
p
h
ase.
I
n
f
o
r
w
ar
d
an
t
p
h
ase
F
A
NT
S
ar
e
g
en
er
a
ted
to
s
ea
r
ch
th
e
p
ath
to
w
ar
d
s
th
e
s
i
n
k
.
F
A
NT
S
ca
r
r
y
t
h
e
in
f
o
r
m
atio
n
ab
o
u
t
r
esid
u
al
en
er
g
y
o
f
th
e
n
o
d
es
an
d
m
e
m
o
r
y
p
ac
k
et
lo
s
s
a
n
d
q
u
eu
in
g
d
ela
y
.
T
h
ese
v
al
u
es
ar
e
u
s
ed
as
Qo
S
m
etr
ics to
d
is
co
v
er
t
h
e
p
ath
.
W
h
en
a
f
o
r
w
ar
d
an
t
r
ea
c
h
es
t
o
th
e
s
i
n
k
,
it
e
v
al
u
ates
t
h
e
s
u
i
tab
le
p
ath
an
d
B
ANT
s
ar
e
g
en
er
ated
i
n
re
s
p
o
n
s
e.
T
h
ese
B
ANT
S
ca
r
r
ies
th
e
in
f
o
r
m
at
io
n
o
f
th
e
co
r
r
esp
o
n
d
in
g
F
A
NT
s
ab
o
u
t
t
h
e
i
n
ter
m
ed
iate
n
o
d
es
an
d
ar
e
s
e
n
t
o
v
er
t
h
e
s
a
m
e
p
ath
a
s
F
ANT
.
I
n
r
ev
er
s
e
j
o
u
r
n
e
y
p
h
er
o
m
o
n
e
v
alu
e
s
o
f
i
n
t
er
m
ed
iate
C
Hs
ar
e
u
p
d
ated
.
W
h
en
B
ANT
r
ea
ch
es
t
h
e
co
r
r
esp
o
n
d
in
g
s
o
u
r
ce
n
o
d
e
B
A
NT
S
ar
e
t
h
r
as
h
ed
an
d
d
ata
is
s
e
n
t
o
v
er
t
h
e
s
elec
ted
p
ath
.
R
o
u
te
m
a
in
te
n
a
n
ce
p
h
ase
d
ea
ls
w
it
h
co
n
g
esti
o
n
an
d
lo
s
t
lin
k
p
r
o
b
lem
s
.
Her
e
MA
NT
s
ar
e
g
en
er
ated
w
h
ic
h
is
s
et
ac
co
r
d
in
g
to
th
e
tr
af
f
ic
lo
ad
o
n
th
e
li
n
k
.
I
n
th
i
s
,
Hello
m
e
s
s
a
g
es
ar
e
s
en
t
o
v
er
t
h
e
l
in
k
p
er
io
d
ically
i
n
o
r
d
er
to
ch
ec
k
th
e
co
n
n
ec
t
iv
i
t
y
o
f
n
o
d
es.
O
n
ce
t
h
e
r
o
u
te
is
d
i
s
co
v
er
ed
d
ata
p
ac
k
ets
ar
e
s
e
n
t
o
v
er
th
e
r
o
u
te
f
o
llo
w
i
n
g
th
e
m
ax
i
m
u
m
p
h
er
o
m
o
n
e
v
a
lu
e.
M
u
lti p
ath
tr
a
n
s
m
i
s
s
io
n
is
u
s
ed
i
n
W
MSN.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lecE
n
g
&
C
o
m
p
Sci,
Vo
l.
10
,
No
.
1
,
A
p
r
il 2
0
1
8
:
2
9
5
–
301
298
4.
RE
SU
L
T
S
I
n
th
is
p
ap
er
p
er
f
o
r
m
a
n
ce
o
f
f
o
u
r
d
if
f
er
en
t
alg
o
r
ith
m
s
i
s
ev
a
lu
ated
f
o
r
d
if
f
er
e
n
t
s
ce
n
ar
io
u
s
in
g
NS2
.
Fo
r
all
s
i
m
u
latio
n
s
,
1
0
1
n
o
d
e
s
ar
e
d
is
tr
ib
u
ted
in
g
r
id
o
f
5
0
0
m
X
5
0
0
m
ar
ea
.
No
d
es
ar
e
h
eter
o
g
en
eo
u
s
i
n
n
atu
r
e
i.e
.
a
u
d
io
,
v
id
eo
an
d
s
c
alar
n
o
d
es
ar
e
u
s
ed
.
S
i
m
u
latio
n
p
ar
a
m
eter
s
ar
e
s
et
as
s
h
o
w
n
in
tab
le
n
o
.
1
.
A
l
l
s
i
m
u
lat
io
n
s
ar
e
r
u
n
f
o
r
5
0
S
ec
o
n
d
s
.
F
u
zz
y
cl
u
s
ter
ed
a
n
t
b
ased
cr
o
s
s
la
y
er
ed
p
r
o
to
co
l
is
e
v
alu
a
ted
ag
a
in
s
t
An
tSe
n
s
e
Net,
C
r
o
s
s
la
y
er
ed
An
tSe
n
s
e
Net,
an
d
C
r
o
s
s
la
y
e
r
ed
r
o
u
tin
g
p
r
o
to
co
l
o
n
th
e
b
asis
o
f
e
n
d
to
en
d
d
elay
,
p
ac
k
et
d
eliv
er
y
r
ati
o
an
d
th
r
o
u
g
h
p
u
t.
Net
w
o
r
k
is
m
o
d
er
ately
lo
ad
ed
.
T
w
o
t
y
p
e
s
o
f
d
ata
tr
af
f
ic
s
w
er
e
g
en
er
ated
as
s
ca
lar
d
ata
an
d
m
u
lti
m
ed
ia
d
ata.
Mu
lti
m
ed
ia
tr
af
f
ic
h
a
s
h
i
g
h
er
p
r
io
r
ity
th
an
th
e
s
ca
lar
d
ata
tr
af
f
ic.
Fo
llo
w
in
g
p
ar
a
m
eter
s
ar
e
ev
alu
ated
:
P
ac
k
et
Deliv
er
y
R
atio
:
P
DR
is
th
e
r
atio
o
f
s
u
cc
es
s
f
u
ll
y
d
eliv
er
ed
p
ac
k
et
at
th
e
d
esti
n
ati
o
n
to
th
e
to
tal
n
u
m
b
er
o
f
p
ac
k
et
s
s
en
t f
r
o
m
s
o
u
r
ce
to
d
esti
n
a
tio
n
.
T
h
r
o
u
g
h
p
u
t:
T
h
r
o
u
g
h
p
u
t
i
s
d
ef
i
n
ed
as
t
h
e
n
u
m
b
er
o
f
p
ac
k
ets
p
er
s
ec
o
n
d
r
ec
eiv
ed
at
t
h
e
s
in
k
n
o
d
e
i.e
.
at
d
esti
n
atio
n
.
Fro
m
t
h
e
F
i
g
u
r
e
1
it
is
o
b
s
er
v
ed
th
at
a
s
P
DR
o
f
Fu
zz
y
cl
u
s
t
er
ed
an
t
b
ased
X
L
W
MS
N
lie
s
b
et
w
ee
n
6
5
%
to
9
8
%
w
h
ic
h
i
s
h
ig
h
er
th
an
o
th
er
t
h
r
ee
p
r
o
to
co
ls
.
I
t
is
also
i
s
s
ee
n
t
h
at
P
DR
o
f
a
n
t
b
ased
XL
W
MS
N
an
d
X
L
W
MSN
is
n
o
t
les
s
t
h
an
4
5
%.
As
t
h
e
n
u
m
b
er
o
f
n
o
d
es
i
n
cr
ea
s
e
s
,
P
DR
al
s
o
i
n
cr
ea
s
es
d
u
e
to
th
e
d
ec
r
ea
s
e
in
th
e
n
u
m
b
er
o
f
h
o
l
es
.
As a
r
esu
l
t
th
r
o
u
g
h
p
u
t i
n
cr
ea
s
es.
T
h
is
ca
n
b
e
o
b
s
er
v
ed
f
r
o
m
F
ig
u
r
e
2.
Fig
u
r
e
1
.
No
.
o
f
No
d
es
v
s
P
ac
k
et
Deli
v
er
y
R
atio
Fig
u
r
e
2.
No
.
o
f
No
d
es
vs
T
h
r
o
u
g
h
p
u
t
I
f
p
ac
k
et
s
ize
o
f
t
h
e
d
ata
is
c
h
an
g
ed
t
h
en
FC
AXL
,
C
r
o
s
s
l
a
y
er
p
r
o
to
co
l
an
d
A
n
t
b
ased
cr
o
s
s
la
y
e
r
p
r
o
to
co
l h
as a
p
p
r
o
x
i
m
atel
y
s
a
m
e
P
DR
.
B
u
t s
till
FC
AX
L
W
MSN
p
er
f
o
r
m
a
n
ce
i
s
s
li
g
h
tl
y
i
m
p
r
o
v
ed
as
s
ee
n
i
n
F
ig
u
r
e
3.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lecE
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
A
n
t B
a
s
ed
C
r
o
s
s
La
ye
r
ed
Op
ti
miz
a
tio
n
P
r
o
to
co
l fo
r
W
MS
N
w
ith
F
u
z
z
y
C
lu
s
erin
g
(
Dip
a
liP
a
r
a
g
A
d
h
y
a
p
a
k
)
299
Fig
u
r
e
3
.
P
ac
k
etsi
ze
v
s
p
ac
k
et
Deliv
er
y
R
atio
Fig
u
r
e
4
.
P
ac
k
et
s
ize
v
s
T
h
r
o
u
g
h
p
u
t
E
n
d
to
en
d
d
ela
y
is
t
h
et
i
m
e
d
if
f
er
en
ce
b
et
w
ee
n
th
e
p
ac
k
et
g
en
er
atio
n
ti
m
e
an
d
t
h
e
ti
m
e
w
h
e
n
it
is
r
ec
eiv
ed
at
th
e
s
i
n
k
n
o
d
e.
As
s
ee
n
i
n
F
ig
u
r
e
5
if
th
e
n
u
m
b
er
o
f
n
o
d
es
in
cr
ea
s
e
s
,
en
d
to
en
d
d
elay
d
ec
r
ea
s
es
an
d
is
m
u
c
h
les
s
er
th
an
th
e
o
th
er
t
h
r
ee
al
g
o
r
ith
m
s
f
o
r
F
C
A
X
L
p
r
o
to
co
l.
T
h
is
is
b
ec
au
s
e
a
s
t
h
e
n
u
m
b
er
o
f
n
o
d
es
i
n
cr
ea
s
e
s
d
is
tan
ce
b
et
w
ee
n
s
in
k
a
n
d
s
o
u
r
ce
ca
n
b
e
co
v
er
ed
w
it
h
m
i
n
i
m
u
m
h
o
p
s
a
n
d
as
t
h
e
m
u
ltip
ath
r
o
u
ti
n
g
i
s
e
m
p
lo
y
ed
d
ea
d
lin
k
d
ela
y
ca
n
b
e
m
in
i
m
ized
.
A
ls
o
p
r
io
r
itriz
ed
s
ch
ed
u
li
n
g
al
g
o
r
ith
m
is
em
p
lo
y
ed
w
h
ic
h
r
esu
lt
s
in
d
ec
r
eses
i
n
d
ela
y
.
Fig
u
r
e
5
.
Nu
m
b
er
o
f
No
d
es v
s
Dela
y
E
v
en
i
f
t
h
e
p
ac
k
et
s
ize
in
cr
ea
s
es
th
e
d
ela
y
r
e
m
ain
s
m
in
i
m
u
m
co
m
p
ar
ed
to
o
th
er
t
h
r
ee
alg
o
r
ith
m
s
a
s
s
h
o
w
n
in
F
ig
u
r
e
6.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lecE
n
g
&
C
o
m
p
Sci,
Vo
l.
10
,
No
.
1
,
A
p
r
il 2
0
1
8
:
2
9
5
–
301
300
Fig
u
r
e
6
.
P
ac
k
etsi
ze
v
s
Dela
y
5.
CO
NCLU
SI
O
N
W
MSN
is
th
e
n
e
t
w
o
r
k
o
f
h
e
te
r
o
g
en
eo
u
s
s
en
s
o
r
s
.
I
t
h
as
m
a
n
y
c
h
alle
n
g
es
s
u
c
h
as
Qo
S
o
p
tim
izatio
n
,
b
an
d
w
id
t
h
,
p
o
w
er
,
co
v
er
ag
e
an
d
lif
eti
m
e.
I
n
t
h
is
p
ap
er
,
f
u
zz
y
clu
s
ter
ed
An
t
b
ased
C
r
o
s
s
la
y
er
p
r
o
to
co
l
is
p
r
o
p
o
s
ed
.
Her
e
d
u
e
to
f
u
zz
y
clu
s
ter
i
n
g
d
ea
d
n
o
d
e
s
ar
e
m
i
n
i
m
ized
w
h
ic
h
in
cr
ea
s
e
s
th
r
o
u
g
h
p
u
t
an
d
in
tu
r
n
in
cr
ea
s
es
t
h
e
n
et
w
o
r
k
li
f
eti
m
e
.
C
r
o
s
s
la
y
er
i
n
g
e
x
p
lo
its
i
n
ter
d
ep
en
d
en
cies
o
f
t
h
e
p
r
o
to
co
l
l
a
y
er
w
h
ic
h
lead
s
to
in
cr
ea
s
e
in
li
f
eti
m
e
o
f
t
h
e
n
et
w
o
r
k
a
n
d
an
t
b
ased
r
o
u
tin
g
alg
o
r
it
h
m
h
elp
s
to
f
i
n
d
s
h
o
r
test
p
ath
w
h
ic
h
m
i
n
i
m
izes
t
h
e
e
n
d
to
en
d
d
el
a
y
.
C
o
m
b
i
n
ed
e
f
f
ec
t
o
f
all
o
f
th
ese
m
et
h
o
d
s
ca
n
b
e
o
b
s
er
v
ed
f
r
o
m
t
h
e
r
esu
lts
s
h
o
w
n
.
T
h
u
s
f
r
o
m
t
h
e
s
i
m
u
l
a
tio
n
r
es
u
lt
s
it
is
o
b
s
er
v
ed
t
h
a
t
F
u
zz
y
clu
s
ter
ed
An
t
b
ased
cr
o
s
s
la
y
er
r
o
u
ti
n
g
p
r
o
to
co
l
h
as
b
etter
p
er
f
o
r
m
a
n
ce
co
m
p
ar
ed
to
o
th
er
th
r
ee
al
g
o
r
ith
m
s
i
n
ter
m
s
o
f
en
d
to
e
n
d
d
ela
y
,
th
r
o
u
g
h
p
u
t
an
d
p
ac
k
et
d
eliv
er
y
r
atio
.
RE
F
E
R
E
NC
E
S
[1
]
Zara
Ha
m
id
,
F
a
isa
l
Ba
sh
ir
a
n
d
Ja
e
Yo
u
n
g
P
y
u
n
,
“
Cro
ss
lay
e
r
Qo
S
ro
u
ti
n
g
p
ro
t
o
c
o
l
f
o
r
m
u
lt
im
e
d
ia
c
o
m
m
u
n
ica
ti
o
n
i
n
se
n
so
r
n
e
tw
o
rk
s”
,
IEE
E
,
p
p
4
9
8
-
5
0
2
,
2
0
1
2
.
[2
]
L
u
is
Co
b
o
,
A
leja
n
d
ro
Qu
i
n
tero
,
S
a
m
u
e
l
P
ierre
,
“
A
n
t
b
a
se
d
ro
u
ti
n
g
f
o
r
w
irele
ss
m
u
lt
ime
d
ia
se
n
so
r
n
e
tw
o
rk
s
u
sin
g
m
u
lt
ip
le Qo
S
m
e
tri
c
s”
,
El
se
v
ier
.
Co
mp
u
ter
Ne
tw
o
rk
s
.
5
4
p
p
2
9
9
1
-
3
0
1
0
,
m
a
y
2
0
1
0
.
[3
]
M
.
A
b
a
z
e
e
d
,
K.
S
a
lee
m
,
S
.
Zu
b
a
ir,
N.
F
isa
l,
“
CA
RM
P
:
Cr
o
ss
lay
e
r
b
a
se
d
p
r
o
to
c
o
l
f
o
r
w
irele
ss
se
n
so
r
m
u
lt
im
e
d
ia
se
n
so
r
n
e
tw
o
rk
”
,
S
p
rin
g
e
r
,
p
p
1
,
2
0
1
1
.
[4
]
G
S
M
V
a
m
si,
Ne
h
a
Ch
o
u
b
e
y
,
“
A
f
u
z
z
y
b
a
se
d
a
p
p
ro
a
c
h
o
f
e
n
e
rg
y
e
ff
icie
n
t
h
iera
rc
h
ica
l
c
lu
ste
rin
g
m
e
th
o
d
in
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
”
,
IJ
S
R
,
p
p
3
0
0
1
-
3
0
0
6
,
Ju
n
e
1
5
.
[5
]
V
ik
a
sBh
a
n
d
a
ry
,
Am
it
a
M
a
li
k
,
S
a
n
jay
Ku
m
a
r,
“
Ro
u
ti
n
g
I
w
irele
ss
m
u
lt
i
m
e
d
ia se
n
so
r
n
e
t
w
o
rk
s:
A
s
u
r
v
e
y
o
f
e
x
i
stin
g
p
ro
t
o
c
o
ls
a
n
d
o
p
e
n
re
se
a
rc
h
c
h
a
ll
e
n
g
e
s”
,
Hin
d
a
wi
P
u
b
li
c
a
ti
o
n
s
,
2
0
1
6
.
[6
]
Isla
m
T
.
A
l
m
a
lk
a
w
i,
M
a
n
e
l
Za
p
a
ta,
a
n
d
Ja
m
a
l
N.
A
l
-
K
a
ra
k
i,
“
A
c
ro
ss
la
y
e
r
b
a
se
d
c
lu
ste
re
d
m
u
lt
ip
a
th
ro
u
ti
n
g
w
it
h
Qo
S
a
w
a
re
sc
h
e
d
u
li
n
g
f
o
r
w
irele
s
s m
u
lt
i
m
e
d
ia se
n
so
r
n
e
t
w
o
rk
s”
,
IJ
DS
N
,
p
p
1
-
1
1
,
V
o
l
u
m
e
2
0
1
2
.
[7
]
T
a
m
i
z
h
a
ra
si,
A
.
,
S
e
lv
a
th
a
i,
J.J.,
Ka
v
iP
riy
a
,
A
.
,
M
a
a
rli
n
,
R.
,
H
a
rin
e
th
a
,
M
.
,
“
En
e
rg
y
a
wa
re
h
e
u
risti
c
a
p
p
r
o
a
c
h
f
o
rc
lu
ste
r
h
e
a
d
se
lec
ti
o
n
in
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s”
Bu
ll
e
ti
n
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
In
fo
r
ma
ti
c
s
,
V
o
l.
6
,
Iss
u
e
1
,
2
0
1
7
,
p
p
.
7
0
-
75.
[8
]
S
a
in
i,
R
.
K.,
Rit
ik
a
,
V
ij
a
y
,
S
.
,
“
Da
ta f
lo
w
in
w
irel
e
ss
se
n
so
r
n
e
tw
o
rk
p
ro
to
c
o
l
sta
c
k
b
y
u
sin
g
b
e
ll
m
a
n
-
f
o
rd
ro
u
t
in
g
a
lg
o
rit
h
m
”
,
Bu
ll
e
ti
n
o
f
E
lec
trica
l
En
g
i
n
e
e
rin
g
a
n
d
I
n
fo
rm
a
ti
c
s
,
V
o
l
.
6
,
Iss
u
e
1
,
2
0
1
7
,
p
p
.
8
1
-
8
7
.
[9
]
T
o
o
r,
A
.
S
.
,
Ja
in
,
A
.
K.,
“
A
su
rv
e
y
o
n
w
irele
ss
n
e
tw
o
rk
s
im
u
lato
rs”
,
Bu
ll
e
ti
n
o
f
E
lec
trica
l
En
g
in
e
e
rin
g
a
n
d
In
fo
rm
a
t
ics
,
Vo
l.
6
,
Iss
u
e
1
,
2
0
1
7
,
p
p
.
6
2
-
6
9
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
De
e
p
a
li
P
a
ra
g
A
d
h
y
a
p
a
k
,
M
.
E.
(El
e
c
tro
n
ics
:
Dig
it
a
l
S
y
ste
m
s)
a
n
d
w
o
rk
in
g
a
s
A
s
sista
n
t
P
r
o
f
e
ss
o
r
in
P
ES
’s
M
o
d
e
rn
Co
ll
e
g
e
o
f
En
g
in
e
e
rin
g
,
P
u
n
e
,
M
a
h
a
ra
sh
tra,
In
d
ia.
Re
se
a
rc
h
in
tere
sts
a
re
in
c
o
m
m
u
n
ica
ti
o
n
a
n
d
w
irele
ss
m
u
lt
im
e
d
ia
se
n
so
r
n
e
tw
o
rk
.
P
o
sta
l
A
d
d
re
ss
:
H.
No
.
4
5
4
,
Ka
n
a
k
a
d
it
y
a
P
ra
sa
d
,
A
b
h
in
a
v
Na
g
a
r,
Eas
t
S
a
n
g
a
v
i,
P
u
n
e
–
4
1
1
0
2
7
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lecE
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
A
n
t B
a
s
ed
C
r
o
s
s
La
ye
r
ed
Op
ti
miz
a
tio
n
P
r
o
to
co
l fo
r
W
MS
N
w
ith
F
u
z
z
y
C
lu
s
erin
g
(
Dip
a
liP
a
r
a
g
A
d
h
y
a
p
a
k
)
301
S
rid
h
a
ra
n
B
h
a
v
a
n
i
is
P
h
.
D.
a
n
d
w
o
rk
in
g
a
s
P
ro
f
e
ss
o
r
&
He
a
d
o
f
El
e
c
tro
n
ics
&
Co
m
m
u
n
ica
ti
o
n
En
g
in
e
e
ri
n
g
De
p
a
rtme
n
t
in
Ka
rp
a
g
a
m
A
c
a
d
e
m
y
o
f
Hig
h
e
r
Ed
u
c
a
ti
o
n
,
Co
im
b
a
to
re
,
T
a
m
il
n
a
d
u
,
In
d
ia.
Re
se
a
rc
h
in
tere
sts
a
re
in
i
m
a
g
e
p
ro
c
e
ss
in
g
,
e
m
b
e
d
d
e
d
s
y
ste
m
s,
V
L
S
I
a
n
d
w
irele
ss
n
e
tw
o
rk
s.
P
o
sta
l
A
d
d
re
ss
:
P
o
ll
a
c
h
i
M
a
in
Ro
a
d
,
L
&
T
B
y
P
a
ss
Ro
a
d
J
u
n
c
ti
o
n
Eac
h
a
n
a
ri
P
o
st,
Eac
h
a
n
a
ri
,
Co
im
b
a
to
re
,
T
a
m
il
Na
d
u
6
4
1
0
2
1
.
A
p
a
rn
a
P
ra
d
e
e
p
L
a
tu
rk
a
r,
M
.
E.
(E
lec
tro
n
ics
)
a
n
d
w
o
rk
in
g
a
s
A
ss
ist
a
n
t
P
r
o
f
e
ss
o
r
in
P
E
S
’s
M
o
d
e
rn
Co
ll
e
g
e
o
f
En
g
in
e
e
rin
g
,
P
u
n
e
,
M
a
h
a
ra
sh
tra,
In
d
ia.
Re
se
a
rc
h
in
tere
sts
a
re
in
c
o
m
m
u
n
ica
ti
o
n
a
n
d
w
irele
ss
se
n
so
r
n
e
tw
o
rk
.
P
o
st
a
l
A
d
d
re
ss
:
F
lat
No
.
3
0
1
,
A
V
A
L
ON
,
S
,
No
.
1
8
/
1
,
1
9
,
2
0
/
3
,
Ne
a
r
F
ire
Brig
a
d
e
,
S
u
n
Cit
y
Ro
a
d
,
O
ff
S
in
h
g
a
d
R
o
a
d
,
W
a
d
g
a
o
n
Bu
d
r
u
k
,
P
u
n
e
–
4
1
1
0
5
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.