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d
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K
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w
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:
C
o
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p
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ativ
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W
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C
r
a
m
m
er
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(
C
R
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)
Dis
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Dis
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P
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izatio
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2
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In
stit
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te o
f
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n
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E
n
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n
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rin
g
a
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d
S
c
ien
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e
.
Al
l
rig
h
ts
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se
rv
e
d
.
C
o
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s
p
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ing
A
uth
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r
:
R
av
i
c
h
a
n
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J
an
ap
ati,
Dep
ar
t
m
en
t o
f
E
C
E
,
SR
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n
g
i
n
ee
r
in
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C
o
lle
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e,
W
ar
an
g
al,
I
n
d
ia.
E
m
ail: r
av
i_
ch
a
n
d
er
_
j
@
s
r
ec
w
ar
an
g
al.
ac
.
i
n
1.
I
NT
RO
D
UCT
I
O
N
W
SN
is
a
co
llectio
n
o
f
a
u
to
n
o
m
u
s
,
d
is
tr
ib
u
ted
d
ev
ic
es
w
h
ich
ar
e
co
o
p
er
ativ
e
y
s
en
d
t
h
eir
in
f
o
r
m
atio
n
t
h
r
o
u
g
h
t
h
e
n
et
w
o
r
k
to
t
h
e
ce
n
tr
al
n
o
d
e.
W
SN
ca
n
b
e
u
s
ed
i
n
cr
i
tical
a
p
p
licatio
n
s
o
f
tar
g
et
tr
ac
k
in
g
,
h
ea
lt
h
an
d
m
ilit
ar
y
ap
p
licatio
n
s
etc
.
[
1
]
.
I
n
in
d
o
o
r
en
v
ir
o
n
m
e
n
t
n
o
d
es
ar
e
d
ep
lo
y
ed
r
an
d
o
m
l
y
a
n
d
d
o
n
o
t
k
n
o
w
th
eir
p
o
s
itio
n
.
F
in
d
in
g
ex
ac
t
n
o
d
e
p
o
s
itio
n
is
k
n
o
w
n
as
l
o
ca
lizatio
n
.
GP
S
ca
n
b
e
u
s
ed
to
f
i
n
d
n
o
d
e
lo
ca
tio
n
s
,
d
u
e
to
n
o
is
e
a
n
d
m
u
ltip
at
h
e
f
f
ec
t
s
it d
o
es n
o
t
w
o
r
k
s
w
ell
i
n
in
d
o
o
r
en
v
ir
o
n
m
en
t [
2
]
.
L
o
ca
lizatio
n
al
g
o
r
ith
m
s
ca
n
b
e
u
s
ed
to
f
i
n
d
lo
ca
tio
n
o
f
n
o
d
es
u
s
i
n
g
an
c
h
o
r
n
o
d
es.
L
o
ca
lizatio
n
alg
o
r
ith
m
s
ca
n
b
e
cla
s
s
i
f
ied
i
n
to
t
w
o
t
y
p
es:
1
)
C
e
n
tr
alize
d
lo
ca
lizatio
n
al
g
o
r
ith
m
2
)
Dis
t
r
ib
u
ted
lo
ca
lizatio
n
alg
o
r
ith
m
.
I
n
ce
n
tr
alize
d
lo
ca
lizatio
n
al
g
o
r
ith
m
ce
n
tr
al
n
o
d
e
ca
lcu
lates
n
o
d
e
lo
ca
tio
n
a
n
d
p
ass
ed
to
o
th
er
n
o
d
es.
Dis
ad
v
a
n
ta
g
e
o
f
th
is
m
et
h
o
d
is
co
m
p
lex
it
y
is
m
o
r
e.
C
en
tr
alize
d
al
g
o
r
ith
m
s
ar
e
g
e
n
er
all
y
n
o
t
s
ca
lab
le
s
o
u
n
f
ea
s
ib
le
f
o
r
lar
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e
n
et
w
o
r
k
s
.
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n
d
i
s
tr
ib
u
ted
lo
ca
lizatio
n
alg
o
r
ith
m
s
ea
ch
n
o
d
e
co
m
p
u
t
es
its
lo
ca
tio
n
h
e
n
ce
co
m
p
le
x
it
y
is
r
ed
u
ce
d
.
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tr
ib
u
ted
alg
o
r
it
h
m
s
ar
e
s
ca
lab
le
s
o
f
it f
o
r
lar
g
e
n
e
t
w
o
r
k
s
[
3
]
.
No
d
es
w
it
h
k
n
o
w
n
p
o
s
itio
n
is
ter
m
ed
as
an
ch
o
r
n
o
d
es,
n
o
d
es
d
o
n
o
t
k
n
o
w
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h
eir
p
o
s
itio
n
is
k
n
o
wn
as
ag
e
n
t
n
o
d
es.
I
n
t
h
is
lo
ca
liz
atio
n
p
r
o
ce
s
s
a
n
c
h
o
r
n
o
d
es
b
r
o
ad
ca
s
t
b
ea
co
n
s
i
g
n
a
l
a
n
d
esti
m
ate
lo
ca
tio
n
o
f
u
n
k
n
o
w
n
n
o
d
es
u
s
in
g
R
SS
.
All
th
e
a
n
ch
o
r
n
o
d
es
d
o
es
n
o
t
est
i
m
at
e
t
h
e
lo
ca
tio
n
o
f
n
o
d
es
with
h
i
g
h
ac
c
u
r
ac
y
.
Hen
ce
C
R
B
is
u
s
ed
to
s
elec
t
th
e
b
est
r
ef
er
en
ce
n
o
d
es
with
h
i
g
h
ac
cu
r
ac
y
.
Di
s
tr
ib
u
te
d
P
SO
lo
ca
lizatio
n
alg
o
r
ith
m
i
s
p
r
o
p
o
s
ed
to
f
i
n
d
ac
cu
r
ate
n
o
d
e
lo
ca
tio
n
.
P
r
o
p
o
s
ed
s
o
lu
tio
n
p
er
f
o
r
m
b
etter
i
n
co
m
p
ar
is
o
n
w
i
t
h
o
th
e
r
al
g
o
r
ith
m
s
li
k
e
P
SO,
R
L
S
al
g
o
r
ith
m
,
L
M
S
al
g
o
r
ith
m
an
d
GP
S
i
n
ter
m
s
o
f
p
o
s
itio
n
ac
c
u
r
ac
y
,
laten
c
y
an
d
co
m
p
lex
it
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2
0
8
8
-
8708
Lo
ca
liz
a
tio
n
o
f Co
o
p
era
tive
W
S
N
Usi
n
g
Dis
t
r
ib
u
ted
P
S
O
w
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(
R
a
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C
h
a
n
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er J
a
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p
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3095
Or
g
an
iza
tio
n
o
f
th
e
p
ap
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is
as
f
o
llo
w
s
,
Sectio
n
2
g
iv
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s
p
r
o
b
lem
s
tate
m
en
t,
p
r
o
p
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s
ed
C
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ativ
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D
is
tr
ib
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ted
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SO
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it
h
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p
ti
m
u
m
s
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f
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en
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s
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Sectio
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3
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m
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e
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al
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Sectio
n
4
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5
g
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s
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n
cl
u
s
io
n
.
2.
P
RO
B
L
E
M
ST
AT
E
M
E
NT
I
n
n
o
n
co
o
p
er
ativ
e
lo
ca
tio
n
es
ti
m
atio
n
a
n
ch
o
r
n
o
d
es f
in
d
lo
c
atio
n
o
f
ag
e
n
t
n
o
d
e.
A
g
e
n
t
n
o
d
es d
o
n
o
t
p
ar
ticip
ate
in
lo
ca
lizatio
n
p
r
o
ce
s
s
b
ec
au
s
e
o
f
co
m
m
u
n
ica
tio
n
d
o
es
n
o
t
ex
is
t
b
et
w
ee
n
ag
en
t
n
o
d
es.
Ma
in
d
is
ad
v
an
ta
g
e
o
f
t
h
i
s
m
et
h
o
d
is
th
at
m
o
r
e
an
ch
o
r
n
o
d
es
o
r
lo
n
g
d
is
tan
ce
tr
an
s
m
is
s
i
o
n
s
ar
e
r
eq
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ir
ed
.
C
o
o
p
er
ativ
e
lo
ca
lizati
o
n
m
et
h
o
d
g
et
th
e
lo
ca
tio
n
in
f
o
r
m
a
tio
n
f
r
o
m
an
c
h
o
r
n
o
d
es
a
n
d
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e
n
t
n
o
d
es,
h
e
n
ce
lo
n
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g
e
tr
an
s
m
is
s
io
n
s
ar
e
n
o
t r
eq
u
ir
ed
[
4
]
.
Fig
u
r
e
1
.
C
o
o
p
er
ativ
e
n
et
w
o
r
k
T
o
s
o
lv
e
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p
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le
m
o
f
d
if
f
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m
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eli
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ile
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ate
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.
Fig
u
r
e
1
s
h
o
w
s
t
h
e
m
a
n
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er
i
n
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h
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h
t
wo
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ased
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M2
ca
n
n
o
t
o
p
en
l
y
f
i
x
th
e
ir
lo
ca
tio
n
s
.
Mo
b
ile
n
o
d
e
M1
m
i
g
h
t
b
e
p
o
s
itio
n
ed
in
eit
h
er
i
n
ter
Sectio
n
o
f
I
1
o
r
I
2
w
h
er
ea
s
m
o
b
ile
n
o
d
e
M
2
m
ig
h
t
b
e
i
n
I
3
o
r
I
4
.
I
n
a
co
o
p
e
r
ativ
e
W
SN,
n
o
d
es
co
o
p
er
ated
w
it
h
ea
c
h
o
th
er
an
d
f
i
n
d
th
e
d
is
tan
ce
b
et
w
ee
n
th
e
m
.
T
h
is
d
i
s
tan
ce
in
f
o
r
m
at
io
n
is
u
s
e
f
u
l
to
f
i
n
d
lo
ca
tio
n
o
f
M1
is
in
I
1
an
d
M2
in
I
3
.
C
o
o
p
er
ativ
e
lo
ca
lizatio
n
n
ee
d
s
co
m
m
u
n
icatio
n
b
et
w
ee
n
t
h
e
m
o
b
ile
n
o
d
es
to
ass
is
t
th
e
m
to
aid
e
ac
h
o
th
er
.
I
n
t
h
e
e
x
a
m
p
le
o
f
Fi
g
u
r
e
1
th
at
co
u
ld
b
e
m
o
b
ile
n
o
d
e
M1
s
e
n
d
in
g
it
s
p
o
s
s
ib
le
p
o
s
it
io
n
co
o
r
d
in
ates
o
f
I
1
an
d
I
2
to
m
o
b
ile
n
o
d
e
M2
t
h
at
w
o
u
ld
th
e
n
b
e
ab
le
to
d
ete
r
m
in
e
its
p
o
s
i
tio
n
u
n
a
m
b
i
g
u
o
u
s
l
y
u
s
i
n
g
t
h
e
i
n
ter
d
is
tan
ce
o
f
th
e
t
w
o
m
o
b
ile
n
o
d
es.
T
h
e
p
o
s
itio
n
o
f
M2
s
h
o
u
ld
th
e
n
b
e
r
et
u
r
n
ed
to
M1
as
s
is
ti
n
g
it
to
as
w
ell
d
eter
m
in
e
it
s
p
o
s
itio
n
.
C
o
o
p
er
ativ
e
lo
ca
lizatio
n
ca
n
co
m
p
r
o
m
is
e
a
u
g
m
e
n
ted
ac
cu
r
ac
y
an
d
co
v
er
ag
e.
T
h
e
p
er
f
o
r
m
a
n
ce
o
f
p
o
s
itio
n
in
g
ac
cu
r
ac
y
ca
n
b
e
e
x
tr
e
m
e
l
y
e
n
h
a
n
ce
d
b
y
ex
c
h
a
n
g
in
g
p
o
s
itio
n
a
l
in
f
o
r
m
atio
n
b
et
w
ee
n
ag
en
ts
.
C
o
o
p
er
ativ
e
lo
ca
lizatio
n
m
eth
o
d
i
m
p
r
o
v
es
p
o
s
itio
n
i
n
g
ac
cu
r
ac
y
[
5
]
,
b
u
t
in
cr
ea
s
es
t
h
e
co
m
p
u
tatio
n
al
c
o
m
p
le
x
it
y
,
n
et
w
o
r
k
tr
af
f
ic
a
n
d
d
ela
y
.
So
m
e
o
f
t
h
e
p
o
s
i
tio
n
al
in
f
o
r
m
a
tio
n
m
a
y
also
b
e
d
estru
cti
v
e
a
s
s
o
m
e
d
ev
ices
h
av
e
p
o
o
r
est
i
m
ate
s
[
6
]
.
Hen
ce
,
a
b
ig
c
h
alle
n
g
e
i
s
to
s
elec
tio
n
a
n
d
r
ej
ec
tio
n
o
f
in
f
o
r
m
atio
n
f
r
o
m
n
o
d
es.
I
n
t
h
e
[
7
]
p
r
o
p
o
s
ed
to
u
s
e
t
h
e
li
n
k
s
w
h
ic
h
ar
e
t
h
e
clo
s
est
f
r
o
m
t
h
e
a
g
en
t
in
co
n
s
id
er
atio
n
.
Ho
w
e
v
er
,
th
e
clo
s
est
n
ei
g
h
b
o
r
s
m
a
y
n
o
t
co
r
r
esp
o
n
d
to
th
e
b
est
li
n
k
s
as
p
o
s
itio
n
i
n
g
also
d
ep
en
d
o
n
t
h
e
g
eo
m
etr
ic
co
n
f
ig
u
r
atio
n
o
f
th
e
ag
e
n
t
a
n
d
its
n
ei
g
h
b
o
r
s
.
So
s
elec
t
in
g
t
h
e
a
n
ch
o
r
n
o
d
es
to
d
eter
m
in
e
p
o
s
itio
n
o
f
n
o
d
e
is
a
b
ig
task
.
T
h
e
C
r
a
m
er
R
ao
b
o
u
n
d
(
C
R
B
)
u
s
ed
to
d
is
ca
r
d
v
ain
lin
k
s
[
8
]
.
R
ath
er
th
an
d
ep
en
d
o
n
p
r
o
x
i
m
i
t
y
as
a
cr
iter
io
n
,
[
9
]
p
r
o
p
o
s
ed
to
u
s
e
a
p
r
eset
n
u
m
b
er
o
f
li
n
k
s
t
h
a
t
g
i
v
e
lo
w
e
s
t
C
R
B
.
I
n
[
1
0
-
1
1
]
th
e
au
t
h
o
r
s
p
r
o
p
o
s
ed
to
u
s
e
th
e
C
R
B
to
s
elec
t
t
h
o
s
e
an
c
h
o
r
s
t
h
at
w
o
u
ld
g
i
v
e
th
e
b
est
p
o
s
itio
n
in
g
ac
cu
r
ac
y
.
Dis
tr
ib
u
ted
P
SO lo
ca
lizatio
n
al
g
o
r
ith
m
is
p
r
o
p
o
s
ed
to
f
in
d
a
cc
u
r
ate
n
o
d
e
lo
ca
tio
n
.
3.
CO
O
P
E
RAT
I
VE
DIS
T
RIB
U
T
E
D
P
SO
L
O
CA
L
I
Z
AT
I
O
N
USI
N
G
O
P
T
I
M
UM
RE
F
E
RE
N
CE
S
P
r
o
p
o
s
ed
s
o
lu
tio
n
co
n
s
is
t
s
o
f
t
w
o
p
ar
ts
1
.
Se
lectio
n
o
f
o
p
ti
m
u
m
r
ef
er
e
n
ce
s
2
.
Dis
tr
ib
u
ted
P
SO
lo
ca
lizatio
n
.
Sectio
n
3
.
1
ex
p
l
ain
s
o
p
ti
m
u
m
s
e
lectio
n
o
f
r
e
f
er
en
ce
s
,
Sectio
n
3
.
2
ex
p
lai
n
s
C
DP
SO
w
it
h
C
R
B
lo
ca
lizatio
n
alg
o
r
it
h
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
6
,
No
.
6
,
Dec
em
b
er
2
0
1
6
:
3
09
4
–
3
10
2
3096
3
.
1
.
O
pti
m
u
m
Se
le
ct
io
n o
f
Ref
er
enc
es us
ing
CRB
I
n
co
o
p
er
ativ
e
W
SN
ev
er
y
n
o
d
e
co
m
m
u
n
icate
d
w
ith
all
o
th
er
n
o
d
es.
E
v
er
y
n
o
d
e
in
v
o
l
v
ed
in
th
e
p
r
o
ce
s
s
o
f
e
s
ti
m
atio
n
.
Her
e
C
R
L
B
is
ca
lcu
lated
to
es
ti
m
ate
th
e
s
et
o
f
n
o
d
es
w
h
ic
h
g
i
v
e
s
lo
w
er
b
o
u
n
d
,
leas
t
lo
ca
lizatio
n
er
r
o
r
[
1
2
]
.
I
n
th
is
p
r
o
ce
s
s
u
n
k
n
o
w
n
n
o
d
es
in
i
tiates
th
e
lo
ca
lizatio
n
p
r
o
ce
s
s
an
d
ag
en
ts
i
n
th
e
co
m
m
u
n
icatio
n
r
an
g
e
r
esp
o
n
d
s
to
th
a
t
p
r
o
ce
s
s
b
y
e
s
ti
m
ati
n
g
th
e
l
o
ca
tio
n
s
.
A
l
l
t
h
e
n
o
d
es
d
o
n
o
t
g
i
v
e
ac
c
u
r
ate
lo
ca
tio
n
d
u
e
to
n
o
is
e.
So
s
elec
tio
n
o
f
n
o
d
es
w
h
ic
h
g
iv
e
s
ac
cu
r
ate
lo
ca
tio
n
s
is
i
m
p
o
r
tan
t
c
r
iter
ia.
I
n
th
is
p
ap
er
C
R
B
is
u
s
ed
to
s
elec
t t
h
e
n
o
d
es
w
h
ic
h
g
iv
e
s
lo
w
er
b
o
u
n
d
,
m
i
n
i
m
u
m
v
ar
ian
ce
o
f
er
r
o
r
[
1
3
]
.
W
e
p
r
o
p
o
s
e
to
u
s
e
th
e
C
R
B
o
n
lo
ca
lizatio
n
er
r
o
r
f
o
r
th
e
s
elec
tio
n
.
E
v
er
y
ag
e
n
t
n
o
d
e
co
m
p
ar
e
s
its
lo
ca
lizatio
n
ac
c
u
r
ac
y
w
i
th
al
l
o
th
er
a
g
en
t
s
u
s
i
n
g
a
v
ailab
l
e
g
lo
b
al
k
n
o
w
led
g
e.
T
h
is
m
eth
o
d
is
k
n
o
w
n
a
s
g
lo
b
al
-
cr
lb
alg
o
r
it
h
m
.
T
h
is
al
g
o
r
ith
m
s
e
lects o
p
ti
m
al
s
u
b
s
ets
ac
co
r
d
in
g
to
th
e
f
o
llo
w
i
n
g
E
q
u
atio
n
s
1
an
d
2
.
(
)
(
)
(
1
)
∑
∑
∑
(
)
(
2
)
(
)
n
p
=p
ath
lo
s
s
ex
p
o
n
e
n
t
σ
dB
=
s
tan
d
ar
d
d
ev
iatio
n
o
f
t
h
e
r
ec
eiv
ed
s
ig
n
al
s
tr
e
n
g
th
.
=D
is
ta
n
ce
b
et
w
ee
n
a
n
ch
o
r
an
d
ag
en
t.
3
.
2
.
Co
o
pera
t
iv
e
Dis
t
ributiv
e
P
a
rt
icle
Sw
a
rm
O
pti
m
iza
t
io
n (
CDP
SO
)
P
SO
is
a
s
w
ar
m
i
n
tel
lig
e
n
c
e
alg
o
r
ith
m
,
w
o
r
k
s
o
n
s
o
ci
al
b
eh
av
io
r
o
f
b
ir
d
s
an
d
a
s
ch
o
o
l
o
f
f
is
h
es
[
1
4
-
1
5
]
.
I
t
g
iv
es
a
s
e
t
o
f
s
o
lu
tio
n
s
ca
lled
as
p
ar
ticles.P
SO
alg
o
r
ith
m
co
m
p
le
x
it
y
is
les
s
h
e
n
c
e
i
m
p
lan
tatio
n
i
s
e
as
y
w
ith
g
o
o
d
c
o
n
v
er
g
e
n
ce
[
1
6
-
1
7
]
w
h
ich
i
s
v
iab
le
f
o
r
lo
ca
lizatio
n
o
f
W
SN.
Fo
r
i
m
p
r
o
v
e
m
en
t
in
th
e
ef
f
icie
n
c
y
a
n
d
ac
cu
r
ac
y
o
f
P
SO
-
b
ased
lo
ca
lizatio
n
m
et
h
o
d
s
ar
e
u
s
e
d
,
d
is
tr
ib
u
ted
P
SO
alg
o
r
ith
m
is
p
r
o
p
o
s
ed
b
ased
o
n
th
e
p
r
o
b
ab
ilis
tic
d
is
tr
ib
u
ti
o
n
o
f
r
an
g
in
g
er
r
o
r
.
P
r
o
p
o
s
e
d
o
b
j
ec
tiv
e
f
u
n
ctio
n
ev
alu
a
tes
t
h
e
f
it
n
es
s
o
f
p
ar
ticles.
I
t
atte
m
p
ts
to
lo
ca
lize
m
o
r
e
u
n
k
n
o
w
n
n
o
d
es
i
n
a
h
ig
h
ac
c
u
r
ate
s
ea
r
ch
s
p
ac
e
[
1
8
]
.
T
h
e
u
p
d
ated
p
a
r
ticle’
s
p
o
s
itio
n
ca
n
b
e
m
at
h
e
m
a
ticall
y
m
o
d
elled
ac
co
r
d
in
g
t
h
e
f
o
llo
w
i
n
g
E
q
u
atio
n
s
s
3
an
d
4
.
V
i
k+
1
=
w
V
i
k
+ c
1
r
1
(p
best
-
x
i
k
)
+
c
2
r
2
(g
best
-
x
i
k
)
(
3
)
Xi
k+
1
=
Xi
k
+V
i
k+
1
(
4
)
w
h
er
e
v
i
k
,
X
i
k
ar
e
v
elo
cit
y
a
n
d
cu
r
r
en
t
p
o
s
itio
n
o
f
n
o
d
e
i
at
iter
atio
n
k
,
C
l
a
n
d
C
2
ar
e
ac
ce
ler
atio
n
co
n
s
ta
n
ts
,
r
l
an
d
r
2
ar
e
r
an
d
o
m
n
u
m
b
er
s
u
n
i
f
o
r
m
l
y
d
is
tr
ib
u
ted
in
(
0
,
1
)
,
an
d
w
is
t
h
e
i
n
er
tia
w
e
ig
h
t
to
co
n
tr
o
l
th
e
s
co
p
e
o
f
th
e
s
ea
r
c
h
.
Us
u
al
l
y
w
i
s
s
e
t
to
lin
ea
r
l
y
d
ec
r
ea
s
e
w
it
h
t
h
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2
0
8
8
-
8708
Lo
ca
liz
a
tio
n
o
f Co
o
p
era
tive
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n
g
Dis
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r
ib
u
ted
P
S
O
w
ith
….
(
R
a
vi
C
h
a
n
d
er J
a
n
a
p
a
ti)
3101
R
L
S
a
n
d
GP
S
alg
o
r
ith
m
i
n
t
er
m
s
o
f
p
o
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tio
n
ac
c
u
r
ac
y
,
C
DF,
co
m
p
lex
it
y
a
n
d
MSE
.
Fr
o
m
th
e
co
m
p
ar
is
o
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esu
lt
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it is
o
b
s
er
v
ed
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a
t p
r
o
p
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d
p
er
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m
s
b
etter
t
h
an
o
t
h
er
alg
o
r
ith
m
s
.
ACK
NO
WL
E
D
G
E
M
E
NT
S
T
h
e
au
th
o
r
s
w
o
u
ld
lik
e
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k
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o
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led
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h
e
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a
n
cial
s
u
p
p
o
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h
e
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n
i
v
er
s
it
y
Gr
a
n
t
c
o
m
m
i
s
s
io
n
,
I
n
d
ia
[
Fil
e
No
:
MRP
-
6
2
3
3
/1
5
(
SERO/UG
C
)
]
to
ca
r
r
y
o
u
t
th
e
p
r
esen
t
r
esear
ch
.
T
h
e
au
th
o
r
s
also
ac
k
n
o
w
led
g
e
th
e
Ma
n
ag
e
m
e
n
t
a
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d
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r
in
cip
al
o
f
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R
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n
g
in
ee
r
i
n
g
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o
ll
eg
e,
W
ar
an
g
al
f
o
r
th
e
ir
co
n
tin
u
o
u
s
s
u
p
p
o
r
t
b
y
p
r
o
v
id
in
g
all
th
e
n
ec
es
s
ar
y
f
a
cilities
.
W
e
g
r
ate
f
u
ll
y
th
a
n
k
s
to
P
r
o
f
ess
o
r
s
o
f
E
C
E
Dep
ar
t
m
en
t
an
d
R
esear
ch
&
De
v
elo
p
m
e
n
t Cel
l,
J
NT
U,
A
n
an
tap
u
r
f
o
r
u
s
ef
u
l d
is
c
u
s
s
io
n
&
s
u
g
g
e
s
tio
n
s
f
o
r
th
is
r
esear
ch
w
o
r
k.
RE
F
E
R
E
NC
E
S
[1
]
D.
Ch
a
n
d
iras
e
k
a
ra
n
a
n
d
T
.
Ja
y
a
b
a
ra
th
i
,
“
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s
No
d
e
L
o
c
a
li
z
a
ti
o
n
-
A
P
e
rf
o
rm
a
n
c
e
Co
m
p
a
riso
n
o
f
S
h
u
f
f
l
e
d
F
ro
g
L
e
a
p
in
g
a
n
d
F
i
re
f
l
y
A
lg
o
rit
h
m
in
L
a
b
V
IEW
,”
T
EL
KOM
NIKA
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
,
v
o
l/
issu
e
:
1
4
(
3
)
,
p
p
.
5
1
6
–
5
2
4
,
2
0
1
5
.
[2
]
W
.
Ju
n
sh
e
n
g
,
“
De
sig
n
a
n
d
A
p
p
l
i
c
a
ti
o
n
o
f
Itera
ti
v
e
M
o
n
te
Ca
rlo
L
o
c
a
li
z
a
ti
o
n
f
o
r
M
o
b
i
le
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s
Ba
se
d
o
n
M
CL
,”
T
EL
KOM
NIKA
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
,
v
o
l/
iss
u
e
:
1
2
(
3
),
p
p
.
2
0
7
9
-
2
0
8
7
,
2
0
1
4
.
[3
]
S
iv
ieri
A
.
,
e
t
a
l.
,
“
B
u
il
d
in
g
In
ter
n
e
t
o
f
T
h
in
g
s so
f
t
w
a
re
w
it
h
EL
Io
T
,”
Co
mp
u
ter
Co
mm
u
n
ica
ti
o
n
s
,
2
0
1
6
.
[4
]
L
v
T
.
,
e
t
a
l.
,
“
S
p
a
c
e
-
ti
m
e
h
iera
r
c
h
ica
l
-
g
ra
p
h
b
a
se
d
c
o
o
p
e
ra
ti
v
e
lo
c
a
li
z
a
t
io
n
i
n
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
,”
S
ig
n
a
l
Pro
c
e
ss
in
g
,
IE
EE
T
r
a
n
sa
c
ti
o
n
s
,
v
o
l
/i
ss
u
e
:
6
4
(
2
)
,
p
p
.
3
2
2
-
34
,
2
0
1
6
.
[5
]
Ra
m
a
sa
m
y
D
.
,
e
t
a
l.
,
“
Co
m
p
re
s
si
v
e
p
a
ra
m
e
ter
e
sti
m
a
ti
o
n
in
AWG
N
,”
S
ig
n
a
l
Pro
c
e
ss
in
g
,
IEE
E
T
ra
n
sa
c
ti
o
n
s
,
v
o
l/
issu
e
:
6
2
(8
)
,
p
p
.
2
0
1
2
-
27
,
2
0
1
4
.
[6
]
Ya
n
g
G
.
,
e
t
a
l.
,
“
T
h
ro
u
g
h
p
u
t
o
p
ti
m
iza
ti
o
n
f
o
r
m
a
ss
i
v
e
M
IM
O
s
y
ste
m
s
p
o
w
e
re
d
b
y
w
irel
e
ss
e
n
e
rg
y
tran
s
f
e
r
,”
S
e
lec
ted
Are
a
s in
Co
mm
u
n
ica
ti
o
n
s,
IEE
E
J
o
u
rn
a
l
,
v
o
l
/i
ss
u
e
:
3
3
(
8
)
,
p
p
.
1
6
4
0
-
50
,
2
0
1
5
.
[7
]
A
.
Co
n
ti
,
e
t
a
l
.
,
“
Ne
tw
o
rk
e
x
p
e
r
im
e
n
tatio
n
f
o
r
c
o
o
p
e
ra
ti
v
e
lo
c
a
li
z
a
ti
o
n
,
”
IEE
E
J
.
S
e
l.
Are
a
s
C
o
m
mu
n
,
v
ol
/
issu
e
:
30
(
2
),
pp
.
4
6
7
-
4
7
5
,
2
0
1
2
.
[8
]
E.
Ga
rc
ia,
e
t
a
l.
,
“
On
th
e
trad
e
-
o
ff
b
e
t
we
e
n
a
c
c
u
ra
c
y
a
n
d
d
e
la
y
in
c
o
o
p
e
ra
ti
v
e
UW
B
n
a
v
ig
a
ti
o
n
,
”
i
n
p
ro
c
.
In
t.
c
o
n
f.
W
ire
les
s Co
mm
u
n
ica
ti
o
n
s a
n
d
Ne
two
rk
in
g
,
S
h
a
n
g
h
a
i,
p
p
.
1
6
0
3
-
1
6
0
8
,
2
0
1
3
.
[9
]
G
a
r
c
ia
G
.
E
.
,
e
t
a
l.
,
“
On
th
e
trad
e
-
o
ff
b
e
t
w
e
e
n
a
c
c
u
ra
c
y
a
n
d
d
e
lay
in
c
o
o
p
e
ra
ti
v
e
U
W
B
lo
c
a
li
z
a
ti
o
n
:
P
e
rf
o
rm
a
n
c
e
b
o
u
n
d
s
a
n
d
sc
a
li
n
g
law
s
,”
W
i
re
le
ss
Co
mm
u
n
ica
ti
o
n
s,
IEE
E
T
ra
n
sa
c
ti
o
n
s
,
v
o
l
/i
ss
u
e
:
1
3
(
8
)
,
p
p
.
4
5
7
4
-
85
,
2
0
1
4
.
[1
0
]
Da
s
K
.
a
n
d
Wy
m
e
e
rsc
h
H.
,
“
Ce
n
so
rin
g
f
o
r
b
a
y
e
si
a
n
c
o
o
p
e
ra
ti
v
e
p
o
siti
o
n
in
g
i
n
d
e
n
se
w
irele
s
s
n
e
two
rk
s
,”
S
e
lec
ted
Are
a
s
in
C
o
mm
u
n
ic
a
ti
o
n
s,
IE
EE
J
o
u
rn
a
l
,
v
o
l/
issu
e
:
3
0
(9
)
,
p
p
.
1
8
3
5
-
42
,
2
0
1
2
.
[1
1
]
S
a
v
ic
V
.
a
n
d
Zaz
o
S
.
,
“
Co
o
p
e
ra
ti
v
e
lo
c
a
li
z
a
ti
o
n
in
m
o
b
il
e
n
e
tw
o
rk
s
u
sin
g
n
o
n
p
a
ra
m
e
tri
c
v
a
r
ian
ts
o
f
b
e
li
e
f
p
ro
p
a
g
a
ti
o
n
,”
A
d
Ho
c
Ne
two
rk
s
,
v
o
l/
issu
e
:
1
1
(1
)
,
p
p
.
1
3
8
-
50
,
2
0
1
3
.
[1
2
]
L
v
T
.
,
e
t
a
l.
,
“
S
p
a
c
e
-
ti
m
e
h
iera
r
c
h
ica
l
-
g
ra
p
h
b
a
se
d
c
o
o
p
e
ra
ti
v
e
lo
c
a
li
z
a
t
io
n
i
n
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
,”
S
ig
n
a
l
Pro
c
e
ss
in
g
,
IE
EE
T
r
a
n
sa
c
ti
o
n
s
,
v
o
l/
issu
e
:
6
4
(
2
)
,
p
p
.
3
2
2
-
34
,
2
0
1
6
.
[1
3
]
G
rib
b
e
n
J
.
a
n
d
Bo
u
k
e
rc
h
e
A
.
,
“
Lo
c
a
ti
o
n
e
rro
r
e
stim
a
ti
o
n
in
w
irele
ss
a
d
h
o
c
n
e
tw
o
rk
s
,”
Ad
Ho
c
Ne
t
wo
rk
s
,
v
o
l.
13
,
p
p
.
5
0
4
-
15
,
2
0
1
4
.
[1
4
]
M
a
'
su
m
M
.
A
.
,
e
t
a
l.
,
“
A
u
to
m
a
t
ic
fe
tal
h
e
a
d
a
p
p
ro
x
ima
ti
o
n
u
sin
g
P
a
rti
c
le
S
w
a
r
m
Op
ti
m
iza
ti
o
n
b
a
se
d
Ga
u
ss
ian
El
li
p
ti
c
a
l
P
a
th
,”
i
n
2
0
1
5
In
ter
n
a
ti
o
n
a
l
S
y
mp
o
si
u
m
o
n
M
icr
o
-
Na
n
o
M
e
c
h
a
tro
n
ics
a
n
d
Hu
ma
n
S
c
ie
n
c
e
(
M
HS
)
,
p
p
.
1
-
6
,
2
0
1
5
.
[1
5
]
M
iras
w
a
n
K
.
J
.
a
n
d
M
a
u
li
d
e
v
i
N
.
U.
,
“
P
a
rti
c
le
sw
a
r
m
o
p
ti
m
iz
a
ti
o
n
a
n
d
f
u
z
z
y
lo
g
ic
c
o
n
tro
l
in
g
a
s
lea
k
a
g
e
d
e
tec
to
r
m
o
b
il
e
ro
b
o
t
,”
i
n
2
0
1
5
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
A
u
to
m
a
ti
o
n
,
C
o
g
n
it
ive
S
c
ien
c
e
,
Op
ti
c
s,
M
icr
o
El
e
c
tro
-
M
e
c
h
a
n
ica
l
S
y
ste
m,
a
n
d
I
n
fo
rm
a
t
io
n
T
e
c
h
n
o
lo
g
y
(
ICACOM
IT
)
,
p
p
.
1
5
0
-
1
5
5
,
2
0
1
5
.
[1
6
]
Esm
in
A
.
A
.
,
e
t
a
l.
,
“
A
re
v
ie
w
o
n
p
a
rti
c
le
sw
a
r
m
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
a
n
d
it
s
v
a
rian
ts
t
o
c
lu
ste
rin
g
h
ig
h
-
d
im
e
n
sio
n
a
l
d
a
ta
,”
Arti
f
icia
l
I
n
tel
li
g
e
n
c
e
Rev
iew
,
v
o
l/
issu
e
:
4
4
(
1
)
,
p
p
.
23
-
45
,
2
0
1
5
.
[1
7
]
L
iu
J
.
,
e
t
a
l.
,
“
A
Co
o
p
e
ra
ti
v
e
Ev
o
lu
ti
o
n
f
o
r
Qo
S
-
d
riv
e
n
Io
T
S
e
rv
ice
Co
m
p
o
siti
o
n
,”
Au
t
o
ma
t
i
k
a
‒
J
o
u
r
n
a
l
f
o
r
Co
n
tro
l,
M
e
a
su
re
me
n
t,
El
e
c
tro
n
i
c
s,
Co
mp
u
t
in
g
a
n
d
Co
mm
u
n
ica
ti
o
n
s
,
v
o
l
/i
ss
u
e
:
5
4
(
4
)
,
2
0
1
3
.
[1
8
]
Ya
o
Y
.
a
n
d
Jia
n
g
N.
,
“
Distrib
u
t
e
d
w
irele
ss
s
e
n
so
r
n
e
tw
o
rk
lo
c
a
li
z
a
ti
o
n
b
a
se
d
o
n
w
e
ig
h
ted
se
a
r
c
h
,”
Co
mp
u
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Evaluation Warning : The document was created with Spire.PDF for Python.
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Evaluation Warning : The document was created with Spire.PDF for Python.