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Fo
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tech
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
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2
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8
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8708
I
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t J
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&
C
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p
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n
g
,
Vo
l.
9
,
No
.
3
,
J
u
n
e
201
9
:
2
1
3
1
-
2
1
4
0
2132
T
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ef
it
s
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u
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t
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d
es
ar
e
t
y
p
icall
y
d
is
tr
ib
u
ted
in
a
u
n
i
f
o
r
m
r
an
d
o
m
m
an
n
er
,
all
p
ar
titi
o
n
s
ar
e
al
m
o
s
t
ac
co
m
m
o
d
ati
n
g
th
e
s
a
m
e
n
u
m
b
er
o
f
s
en
s
o
r
n
o
d
es.
T
h
is
in
t
u
r
n
p
r
o
v
id
es
f
air
l
y
lo
ad
s
to
th
e
m
o
b
ile
ele
m
e
n
ts
i
n
ter
m
o
f
d
ata
b
u
f
f
er
in
g
an
d
p
o
w
er
co
n
s
u
m
p
tio
n
.
T
h
is
p
ap
er
is
o
r
g
an
ized
as
f
o
l
lo
w
s
.
T
h
e
li
ter
atu
r
e
r
e
v
ie
w
i
s
g
i
v
en
in
th
e
n
e
x
t
s
ec
tio
n
.
T
h
e
p
r
o
b
lem
s
tate
m
en
t
is
f
o
r
m
u
lated
i
n
S
ec
tio
n
3
.
I
n
Sectio
n
4
,
t
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
is
d
escr
ib
ed
.
T
h
e
p
er
f
o
r
m
a
n
ce
an
al
y
s
is
a
n
d
s
i
m
u
latio
n
r
es
u
lt
s
ar
e
d
is
cu
s
s
ed
i
n
Sectio
n
5
.
T
h
e
co
n
clu
s
io
n
is
d
r
a
w
n
i
n
Sect
i
o
n
6
.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
R
ec
en
t
l
y
,
u
s
in
g
m
u
ltip
le
m
o
b
ile
ele
m
e
n
ts
f
o
r
d
ata
g
at
h
er
in
g
i
n
W
SN
h
a
v
e
b
ec
a
m
e
a
n
i
m
p
o
r
tan
t
tr
en
d
in
liter
at
u
r
e,
as
i
t
p
r
o
v
id
ed
a
s
tr
aig
h
t
f
o
r
w
ar
d
ap
p
r
o
ac
h
to
i
m
p
r
o
v
e
th
e
n
et
w
o
r
k
s
ca
la
b
ilit
y
,
late
n
c
y
a
n
d
th
r
o
u
g
h
p
u
t
[
2
]
-
[
2
9
]
.
Fo
r
ex
am
p
le,
to
k
ee
p
a
w
a
y
f
r
o
m
t
h
e
d
ata
th
r
ash
i
n
g
d
u
e
to
b
u
f
f
er
s
p
r
ea
d
o
u
t,
au
th
o
r
in
[
4
]
p
r
o
p
o
s
ed
th
e
P
ar
titi
o
n
in
g
-
b
ased
Sc
h
ed
u
li
n
g
(
P
B
S)
alg
o
r
ith
m
to
p
r
o
g
r
a
m
th
e
ar
r
a
n
g
e
m
e
n
t
s
o
f
m
o
b
ile
ele
m
e
n
ts
in
a
s
e
n
s
o
r
s
et
o
f
co
n
n
ec
t
io
n
s
.
T
h
is
ap
p
r
o
ac
h
d
iv
id
es
t
h
e
r
elate
d
m
o
b
ile
ele
m
e
n
ts
in
to
t
w
o
s
u
b
-
p
r
o
b
lem
s
.
T
h
en
,
a
ll
n
o
d
es
ar
e
co
r
r
esp
o
n
d
in
g
l
y
d
i
v
id
ed
in
to
v
ar
io
u
s
p
ar
ts
w
it
h
i
n
a
g
r
o
u
p
,
an
d
t
h
en
t
h
e
s
ch
ed
u
lin
g
al
g
o
r
ith
m
atte
m
p
te
d
to
r
ed
u
ce
th
e
o
v
er
h
ea
d
o
f
m
o
v
in
g
b
ac
k
ac
r
o
s
s
t
h
e
d
is
ta
n
t
n
o
d
es.
Usi
n
g
MP
P
p
r
o
b
lem
f
o
r
th
e
m
o
b
ile
ele
m
en
ts
to
ex
te
n
d
t
h
e
li
f
e
s
p
an
o
f
W
SN
in
s
tead
o
f
u
s
in
g
th
e
s
in
g
le
p
ath
w
as
also
in
v
e
s
ti
g
ated
.
I
n
[
1
2
]
f
ix
ed
K
an
d
ad
ap
tiv
e
K
s
c
h
e
m
es
p
l
an
n
ed
n
u
m
er
o
u
s
p
ath
s
f
o
r
t
h
e
m
o
b
ile
ele
m
e
n
t.
T
h
ese
p
ath
s
w
er
e
d
esig
n
ed
in
o
r
d
er
t
o
m
ai
n
tai
n
s
tab
ili
t
y
o
n
en
er
g
y
u
s
e
f
o
r
s
ep
ar
ate
s
en
s
o
r
n
o
d
es.
As
a
r
esu
l
t
o
f
th
i
s
s
t
u
d
y
,
t
h
e
m
u
lti
-
p
at
h
ca
n
p
r
o
lo
n
g
th
e
l
if
e
ti
m
e
u
p
to
f
o
u
r
ti
m
es.
I
n
f
ac
t,
late
n
c
y
is
t
h
e
m
o
s
t
i
m
p
o
r
ta
n
t
i
s
s
u
e
w
h
en
co
n
ce
r
n
in
g
d
ata
co
llectio
n
w
it
h
m
u
lti
p
le
m
o
b
ile
ele
m
e
n
ts
[
7
]
-
[
2
9
]
.
I
n
f
ac
t,
d
ata
co
llectio
n
late
n
c
y
i
s
m
ai
n
l
y
i
n
f
lu
e
n
ce
d
b
y
t
h
e
s
p
ee
d
o
f
t
h
e
m
o
b
ile
e
le
m
e
n
t a
n
d
len
g
th
o
f
to
u
r
f
o
r
w
h
ich
th
e
m
o
b
ile
ele
m
en
t
w
ill
tr
av
er
s
e.
I
n
an
ea
r
lier
w
o
r
k
[
1
1
]
,
it
m
o
v
ed
to
o
v
er
co
m
e
t
h
i
s
p
r
o
b
lem
b
y
r
ed
u
ci
n
g
t
h
e
to
u
r
len
g
t
h
o
f
t
h
e
m
o
b
ile
e
n
tit
y
b
ased
o
n
w
h
et
h
er
th
e
b
ase
s
ta
t
io
n
(
B
S)
ca
n
m
o
v
e
th
r
o
u
g
h
t
h
e
n
et
w
o
r
k
s
o
r
n
o
t.
Ho
w
e
v
er
,
i
n
ca
s
e
w
h
e
n
t
h
e
B
S
ca
n
n
o
t
m
o
v
e,
it
id
en
t
if
ied
s
o
m
e
m
o
b
ile
ele
m
e
n
ts
(
ME
s
)
to
co
llect
d
ata
an
d
r
et
u
r
n
ed
it
to
th
e
B
S.
He
n
ce
,
t
h
r
e
e
d
if
f
er
en
t
p
r
o
ce
d
u
r
es
w
er
e
p
r
o
p
o
s
ed
f
o
cu
s
i
n
g
o
n
th
i
s
p
r
o
b
le
m
.
First
a
n
d
f
o
r
em
o
s
t
is
t
h
e
ar
ea
-
s
p
litt
i
n
g
al
g
o
r
ith
m
(
A
S
A
)
,
w
h
ich
d
i
v
id
es
th
e
n
et
w
o
r
k
s
in
to
v
ar
io
u
s
p
ar
ts
,
ea
ch
m
o
b
ile
en
tit
y
is
u
s
ed
f
o
r
g
at
h
er
in
g
d
ata
f
r
o
m
o
n
e
o
f
th
e
s
to
p
p
o
in
ts
.
Seco
n
d
m
e
th
o
d
is
L
lo
y
d
’
s
b
ea
s
ed
al
g
o
r
ith
m
w
h
i
ch
d
ea
ls
w
it
h
s
e
n
s
o
r
n
et
w
o
r
k
s
th
at
ar
e
r
a
n
d
o
m
l
y
o
r
g
a
n
ized
.
T
h
ir
d
m
e
th
o
d
i
s
t
h
e
Gen
etic
b
ased
alg
o
r
ith
m
w
h
i
ch
is
co
n
s
id
er
ed
as
an
in
telli
g
en
t
al
g
o
r
ith
m
in
t
h
e
s
en
s
e
o
f
u
tili
zi
n
g
m
o
b
ile
ele
m
e
n
t to
u
r
o
p
ti
m
izat
io
n
s
c
h
e
m
es.
Oth
er
r
esear
c
h
,
s
u
ch
as
[
5
]
,
[
1
0
]
,
[
1
4
]
,
[
1
7
]
an
d
[
2
4
]
h
a
v
e
f
o
cu
s
ed
o
n
o
b
tain
in
g
o
p
ti
m
al
tr
aj
ec
to
r
ies
o
f
m
u
ltip
le
m
o
b
ile
ele
m
e
n
ts
.
Fo
r
ex
a
m
p
le,
i
n
[
2
4
]
th
e
k
-
tr
av
elli
n
g
s
ale
s
p
er
s
o
n
w
it
h
n
ei
g
h
b
o
r
(
k
-
T
SP
N)
is
in
tr
o
d
u
ce
d
.
I
n
th
i
s
m
et
h
o
d
,
ea
ch
m
o
b
ile
ele
m
en
t
w
h
ile
m
o
v
in
g
i
n
it
is
p
ath
ca
n
b
r
o
ad
ca
s
t
d
ata
to
t
h
e
s
in
k
i
n
its
ap
p
r
o
p
r
iate
p
o
s
itio
n
.
Mo
r
eo
v
er
,
a
s
tu
d
y
li
k
e
[
8
]
,
[
1
3
]
,
[
1
7
]
,
[
2
1
]
an
d
[
2
6
]
en
d
ea
v
o
u
r
ed
to
tack
le
th
e
la
ten
c
y
p
r
o
b
lem
w
h
ils
t
m
ai
n
tai
n
i
n
g
l
ess
p
o
w
er
co
n
s
u
m
p
tio
n
.
Fo
r
in
s
ta
n
ce
,
in
[
2
1
]
a
co
o
p
er
at
iv
e
d
ata
g
at
h
er
in
g
h
ier
ar
ch
y
s
ch
e
m
e
h
as
b
ee
n
p
r
o
p
o
s
ed
.
I
n
th
is
al
g
o
r
ith
m
,
t
wo
k
in
d
s
o
f
m
o
b
ile
ele
m
e
n
ts
wer
e
s
u
g
g
ested
.
Firs
t
o
n
e
ca
lled
m
o
b
ile
co
llecto
r
(
MC)
w
h
ic
h
u
s
ed
to
co
llect
d
ata
f
r
o
m
s
en
s
o
r
n
o
d
es.
T
h
e
o
th
er
o
n
e
is
ca
lled
m
o
b
ile
r
ela
y
(
M
R
)
w
h
ic
h
ca
te
g
o
r
ized
d
ata
f
r
o
m
v
ar
io
u
s
m
o
b
ile
co
llecto
r
s
an
d
tr
an
s
f
er
s
th
e
co
llected
d
ata
to
th
e
s
i
n
k
n
o
d
e.
Si
m
ilar
l
y
,
th
e
m
et
h
o
d
p
r
esen
ted
in
th
i
s
r
esea
r
ch
u
tili
ze
d
t
h
e
co
n
ce
p
t
o
f
th
e
m
o
b
ile
co
llecto
r
to
g
r
o
u
p
d
ata
f
r
o
m
n
o
d
es
an
d
tr
an
s
m
it
i
t
to
th
e
s
i
n
k
n
o
d
e
at
ap
p
r
o
p
r
iate
ti
m
e
an
d
lo
ca
tio
n
s
,
h
o
w
ev
er
w
i
th
o
u
t
b
ased
o
n
an
y
m
o
b
ile
r
ela
y
s
.
T
h
is
f
u
r
t
h
er
lead
s
to
d
ec
r
ea
s
e
th
e
co
s
t
o
f
n
e
t
w
o
r
k
o
v
er
h
ea
d
in
ad
d
itio
n
to
r
ed
u
cin
g
d
ata
g
at
h
er
in
g
late
n
c
y
.
On
t
h
e
o
th
er
h
a
n
d
,
au
t
h
o
r
s
i
n
[
6
]
,
[
7
]
,
[
1
1
]
,
[
1
5
]
,
[
1
6
]
an
d
[
2
5
]
r
elie
d
o
n
u
s
i
n
g
m
u
l
tip
le
m
o
b
il
e
ele
m
e
n
ts
in
s
tead
o
f
o
n
e
o
r
a
s
tat
ic
s
i
n
k
.
T
h
e
y
p
r
o
p
o
s
ed
alg
o
r
ith
m
s
f
o
r
w
h
ich
m
u
lt
ip
le
m
o
b
ile
ele
m
e
n
ts
u
s
ed
to
co
llect
d
ata
w
h
ile
m
o
v
i
n
g
th
r
o
u
g
h
p
r
escr
ib
ed
p
ath
s
.
Fo
r
ex
a
m
p
le,
a
u
t
h
o
r
s
in
[
6
]
s
u
g
g
ested
an
al
g
o
r
ith
m
w
h
ic
h
s
p
lits
t
h
e
n
et
w
o
r
k
i
n
to
tw
o
i
m
p
o
r
tan
t
ar
ea
s
.
T
h
e
f
ir
s
t
o
n
e
is
th
e
co
n
c
en
tr
ic
s
p
h
er
e
o
f
a
d
ep
lo
y
ed
r
eg
io
n
an
d
th
e
o
t
h
er
ar
ea
is
f
u
r
t
h
er
d
iv
id
ed
in
to
eig
h
t
s
u
b
-
ar
ea
s
.
T
h
e
m
o
b
ile
ele
m
e
n
ts
m
o
v
e
al
o
n
g
t
h
e
d
ia
m
e
ter
o
f
th
e
s
p
h
er
e
an
d
o
th
er
t
w
o
s
i
n
k
s
m
o
v
e
alo
n
g
t
h
e
ar
c
li
n
e
s
to
g
at
h
er
th
e
d
ata
p
ac
k
e
t
f
r
o
m
s
e
n
s
o
r
n
o
d
es.
I
t
is
d
e
m
o
n
s
t
r
ated
b
y
th
e
s
i
m
u
latio
n
r
es
u
lts
th
at
th
is
al
g
o
r
it
h
m
ef
f
icie
n
tl
y
m
o
d
if
ied
th
e
h
o
t
s
p
o
ts
tr
o
u
b
le
an
d
p
r
o
lo
n
g
ed
th
e
n
et
w
o
r
k
li
f
e
s
p
an
o
f
W
SN
s
.
I
n
co
n
tr
as
t,
in
t
h
is
r
esear
ch
t
h
e
n
et
w
o
r
k
is
r
ep
ea
ted
l
y
d
iv
id
ed
to
a
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8708
I
n
tellig
en
t fir
e
d
etec
tio
n
a
n
d
a
lert
s
ys
tem
u
s
in
g
la
b
V
I
E
W
(
F
a
kru
lr
a
d
z
i I
d
r
is
)
2133
n
u
m
b
er
o
f
h
o
r
izo
n
tal
a
n
d
v
er
tical
p
ar
titi
o
n
s
u
n
til
th
e
p
ath
len
g
th
an
d
co
m
m
u
n
icat
io
n
r
a
n
g
e
co
n
s
tr
ain
t
s
o
f
m
o
b
ile
ele
m
en
t
s
ar
e
s
at
is
f
ied
.
T
h
e
n
u
m
b
er
o
f
n
et
w
o
r
k
p
ar
ti
tio
n
s
i
s
t
h
er
ef
o
r
e
v
ar
ia
n
t
a
n
d
in
d
ep
en
d
en
t
o
n
t
h
e
n
u
m
b
er
an
d
lo
ca
tio
n
s
o
f
s
e
n
s
o
r
n
o
d
es.
3.
P
RO
B
L
E
M
F
O
R
M
UL
AT
I
O
N
C
o
n
s
id
er
th
at
a
W
SN
co
n
s
i
s
ts
o
f
s
e
n
s
o
r
n
o
d
es
t
h
at
ar
e
u
n
i
f
o
r
m
l
y
a
n
d
r
an
d
o
m
l
y
d
is
tr
ib
u
te
d
w
it
h
i
n
an
ar
ea
o
f
m
eter
s
s
q
u
ar
e
an
d
m
o
b
ile
ele
m
e
n
ts
u
s
ed
to
co
ll
ec
t
d
ata.
Su
p
p
o
s
in
g
th
at
all
s
en
s
o
r
n
o
d
e
s
ar
e
u
s
i
n
g
s
tatic
tr
an
s
m
is
s
io
n
p
o
w
er
,
i.e
.
s
a
m
e
le
v
el
o
f
tr
a
n
s
m
is
s
io
n
p
o
w
er
an
d
m
o
b
ile
ele
m
en
ts
ar
e
m
o
v
ed
o
n
p
r
ed
ef
in
ed
p
ath
s
at
a
f
i
x
ed
s
p
ee
d
.
I
n
ea
ch
d
ata
g
at
h
er
in
g
r
o
u
n
d
,
m
o
b
ile
ele
m
en
t
s
ar
e
r
eq
u
ir
ed
to
tr
av
er
s
e
its
p
ath
w
h
ils
t
co
llec
tin
g
d
ata
f
r
o
m
n
o
d
es
an
d
t
h
en
u
p
lo
ad
th
e
c
o
llected
d
ata
in
to
th
e
s
i
n
k
n
o
d
e.
T
h
e
s
in
k
n
o
d
e
i
s
s
u
p
p
o
s
ed
to
b
e
m
o
u
n
ted
at
th
e
o
r
ig
in
p
o
in
t o
f
t
h
e
s
e
n
s
o
r
f
ie
l
d
.
As
m
en
tio
n
ed
i
n
th
e
in
tr
o
d
u
ctio
n
s
ec
tio
n
,
d
ata
g
at
h
er
in
g
ta
s
k
w
it
h
m
u
ltip
le
m
o
b
ile
ele
m
e
n
t
s
r
eq
u
ir
es
th
e
s
ati
s
f
ac
tio
n
o
f
t
h
e
f
o
llo
w
in
g
co
n
d
itio
n
s
:
a.
C
o
v
er
in
g
all
s
en
s
o
r
n
o
d
es in
t
h
e
n
et
w
o
r
k
f
ield
.
b.
Satis
f
y
in
g
p
ath
le
n
g
th
co
n
s
tr
ai
n
t o
f
t
h
e
m
o
b
ile
ele
m
en
t,
s
u
c
h
th
at
≤
(
1
)
w
h
er
e
is
to
tal
p
ath
len
g
t
h
o
f
th
e
m
o
b
ile
ele
m
e
n
t
an
d
is
p
ath
len
g
th
co
n
s
tr
ain
t.
T
h
e
f
o
llo
w
in
g
tab
le
r
ep
r
esen
ts
all
m
ath
e
m
a
t
ical
n
o
tatio
n
s
u
s
ed
in
t
h
i
s
p
ap
er
.
4.
T
H
E
P
RO
P
O
SE
D
M
E
T
H
O
D
I
n
t
h
is
s
ec
tio
n
,
t
h
e
C
o
llab
o
r
a
tiv
e
Da
ta
C
o
llectio
n
A
l
g
o
r
ith
m
(
C
DC
A
)
is
d
i
s
cu
s
s
ed
.
T
h
e
alg
o
r
it
h
m
atte
m
p
ts
to
r
ed
u
ce
th
e
n
et
w
o
r
k
late
n
c
y
w
h
ils
t
m
ai
n
tai
n
i
n
g
th
e
lea
s
t
n
u
m
b
er
o
f
m
o
b
ile
el
e
m
en
ts
.
T
h
e
m
ai
n
id
ea
b
eh
in
d
t
h
e
C
D
C
A
i
s
to
,
as
n
ec
e
s
s
ar
y
,
d
i
v
id
e
t
h
e
n
e
t
w
o
r
k
f
ield
i
n
to
a
n
u
m
b
er
o
f
p
ar
titi
o
n
s
,
f
o
r
ea
c
h
p
ar
titi
o
n
a
m
o
b
ile
ele
m
e
n
t
is
allo
ca
ted
.
T
h
e
n
u
m
b
er
o
f
m
o
b
ile
elem
e
n
t
s
th
at
is
r
eq
u
ir
ed
to
co
v
er
all
s
en
s
o
r
n
o
d
es,
i.e
.
s
atis
f
y
in
g
t
h
e
r
eq
u
ir
e
m
e
n
t
o
f
co
n
d
itio
n
(
1
)
,
is
eq
u
iv
ale
n
tl
y
t
h
e
s
a
m
e
n
u
m
b
er
o
f
p
ar
titi
o
n
s
in
th
e
h
o
r
izo
n
ta
l d
ir
ec
tio
n
w
h
ic
h
is
g
i
v
e
n
as,
=
⌈
3
(
−
)
⌉
(
2
)
w
h
er
e
r
is
th
e
co
m
m
u
n
icatio
n
r
an
g
e
o
f
th
e
m
o
b
ile
ele
m
en
t
an
d
τ
r
ep
r
esen
t
t
h
e
d
ef
icien
c
y
o
f
th
e
co
m
m
u
n
icatio
n
r
an
g
e
o
f
m
o
b
ile
ele
m
en
ts
a
s
a
r
es
u
lt
o
f
e
n
v
ir
o
n
m
en
tal
co
n
d
it
io
n
s
,
s
u
ch
as
n
o
is
e,
o
b
s
tacle
s
an
d
in
ter
f
er
e
n
ce
[
3
0
]
.
T
h
e
v
al
u
e
o
f
τ
s
h
o
u
ld
b
e
c
h
o
s
e
n
ca
r
ef
u
ll
y
i
n
o
r
d
er
to
en
s
u
r
e
t
h
at
ev
e
r
y
s
e
n
s
o
r
n
o
d
e
w
ill
b
e
co
v
er
ed
w
it
h
in
th
e
co
m
m
u
n
icatio
n
r
an
g
e
o
f
at
lea
s
t
o
n
e
m
o
b
ile
ele
m
e
n
t.
I
t
i
s
also
w
o
r
th
m
en
tio
n
i
n
g
th
a
t
E
q
u
atio
n
(
2
)
is
co
m
p
u
ted
s
u
c
h
th
a
t
in
ad
d
itio
n
to
co
v
er
i
n
g
all
s
en
s
o
r
n
o
d
es,
ev
er
y
m
o
b
i
le
ele
m
e
n
t
is
al
s
o
co
n
n
ec
ted
to
its
d
ir
ec
t
n
ei
g
h
b
o
r
o
f
m
o
b
ile
ele
m
e
n
t
s
.
T
h
is
t
h
o
u
g
h
t
is
i
m
p
o
r
tan
t
s
i
n
ce
it
a
llo
w
s
co
o
p
er
atio
n
b
et
w
ee
n
m
o
b
ile
e
le
m
e
n
t
s
i
n
a
s
en
s
e
t
h
at
d
is
ta
n
t
m
o
b
ile
ele
m
en
ts
ca
n
b
y
p
a
s
s
i
ts
d
ata
to
t
h
e
s
in
k
n
o
d
e
w
ith
o
u
t
th
e
n
ee
d
to
m
a
k
e
d
ir
ec
t c
o
n
tac
t
w
i
th
it.
A
cc
o
r
d
in
g
to
th
e
n
et
w
o
r
k
p
ar
t
itio
n
s
d
ef
i
n
ed
in
(
2
)
,
th
e
m
o
b
ile
ele
m
e
n
t
s
h
o
u
ld
m
o
v
e
alo
n
g
t
h
e
r
ec
ta
n
g
u
lar
p
ath
ar
r
an
g
ed
o
n
t
h
e
m
i
d
d
le
o
f
t
h
e
n
et
w
o
r
k
ar
ea
.
Ac
co
r
d
in
g
l
y
,
th
e
p
ath
len
g
th
o
f
th
e
m
o
b
ile
ele
m
e
n
t c
an
b
e
co
m
p
u
ted
as
=
2
(
−
(
−
)
)
(
3
)
Fig
u
r
e
1
s
h
o
w
s
th
e
s
ce
n
ar
io
o
f
co
m
p
u
ti
n
g
th
e
p
ath
o
f
th
e
m
o
b
ile
elem
e
n
t
in
t
h
e
h
o
r
izo
n
ta
l
d
ir
ec
tio
n
.
Ho
w
e
v
er
,
th
e
co
m
p
u
ted
p
ath
m
a
y
n
o
t
m
ee
t th
e
p
at
h
co
n
s
tr
ain
t
g
iv
e
n
i
n
(
1
)
.
I
n
th
is
ca
s
e,
t
h
e
n
et
w
o
r
k
is
f
u
r
th
er
d
iv
id
ed
in
th
e
v
er
tical
d
ir
ec
tio
n
.
I
t
is
clea
r
f
r
o
m
Fi
g
u
r
e
2
th
at
th
e
r
eq
u
ir
ed
n
u
m
b
er
o
f
p
ar
titi
o
n
s
in
t
h
e
v
er
tica
l
di
r
ec
tio
n
is
o
b
tain
ed
as
=
⌈
+
2
−
(
−
)
⌉
(
4
)
T
h
er
ef
o
r
e,
th
e
m
o
b
ile
ele
m
e
n
t
w
ill
m
o
v
e
h
o
r
izo
n
tall
y
alo
n
g
th
e
p
ath
,
w
h
er
e
=
2
(
1
−
(
−
)
)
(
5
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
3
,
J
u
n
e
201
9
:
2
1
3
1
-
2
1
4
0
2134
T
h
e
o
v
er
all
n
u
m
b
er
o
f
m
o
b
ile
ele
m
e
n
ts
t
h
at
s
at
is
f
ies t
h
e
ab
o
v
e
m
e
n
tio
n
ed
co
n
d
itio
n
s
,
i
s
g
i
v
en
a
s
=
×
(
6
)
Si
m
i
lar
l
y
,
t
h
e
to
tal
p
ath
le
n
g
t
h
o
f
a
s
in
g
le
m
o
b
ile
ele
m
e
n
t is
co
m
p
u
ted
as
=
×
(
7
)
T
h
e
C
DC
A
ca
n
b
e
b
r
ief
l
y
d
es
cr
ib
ed
in
th
e
f
o
llo
w
i
n
g
t
h
r
ee
p
h
ase
s
.
4
.
1
.
P
ha
s
e
1
I
n
th
i
s
p
h
ase,
th
e
t
w
o
co
n
d
iti
o
n
s
(
i.e
.
co
v
er
in
g
all
s
e
n
s
o
r
n
o
d
es
in
th
e
n
et
w
o
r
k
f
ield
an
d
s
atis
f
y
i
n
g
th
e
p
at
h
co
n
s
tr
ai
n
t)
ar
e
ac
h
ie
v
ed
.
I
n
th
i
s
p
h
ase,
to
s
p
ec
i
f
y
th
e
n
u
m
b
er
o
f
m
o
b
ile
ele
m
e
n
ts
t
h
at
i
s
u
s
ed
to
co
llect
d
ata
f
r
o
m
all
s
en
s
o
r
n
o
d
es,
th
e
n
e
t
w
o
r
k
f
ield
is
d
i
v
id
ed
h
o
r
izo
n
tall
y
in
to
s
u
b
-
ar
ea
s
,
f
o
r
ea
ch
s
u
b
-
ar
ea
a
m
o
b
ile
ele
m
en
t
is
a
s
s
ig
n
ed
.
F
ig
u
r
e
1
illu
s
tr
ates
an
e
x
a
m
p
le
o
f
u
s
i
n
g
t
h
r
ee
m
o
b
ile
ele
m
e
n
ts
to
co
v
er
all
t
h
e
s
en
s
o
r
n
o
d
es
in
th
e
f
ield
.
Ho
w
e
v
er
,
w
h
e
n
th
e
p
ath
le
n
g
t
h
o
f
a
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u
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Fig
u
r
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2
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T
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et
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en
t
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its
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h
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=
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(
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
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&
C
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m
p
E
n
g
I
SS
N:
2088
-
8708
I
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ates
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(
a)
(
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Fig
u
r
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3
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Mo
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t
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3
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t
s
tar
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g
d
at
a
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d
eliv
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Fig
u
r
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4
illu
s
tr
ates th
e
f
lo
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ch
ar
t o
f
th
e
C
DC
A
alg
o
r
ith
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
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&
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Fig
u
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5.
RE
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(
AS
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[
8
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.
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a
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t
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llect
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t r
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r
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r
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all
s
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ar
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m
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h
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.
1
.
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m
ber
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m
o
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ile
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m
ent
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As
m
en
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k
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h
t
h
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m
i
n
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m
u
m
n
u
m
b
er
o
f
m
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m
en
t
s
.
T
o
th
is
en
d
,
th
e
n
u
m
b
er
o
f
m
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ele
m
en
t
s
u
s
ed
f
o
r
th
e
t
w
o
alg
o
r
ith
m
s
,
C
DC
A
an
d
A
S
A,
as
a
f
u
n
ctio
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o
f
i
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cr
ea
s
i
n
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n
et
w
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n
d
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s
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Pha
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C
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8708
I
n
tellig
en
t fir
e
d
etec
tio
n
a
n
d
a
lert
s
ys
tem
u
s
in
g
la
b
V
I
E
W
(
F
a
kru
lr
a
d
z
i I
d
r
is
)
2137
Fig
u
r
e
5
(
a)
an
d
Fig
u
r
e
5
(
b
)
,
r
e
s
p
ec
tiv
el
y
.
I
n
Fi
g
u
r
e
5
(
a)
,
th
e
n
u
m
b
er
o
f
m
o
b
ile
ele
m
e
n
ts
i
s
r
ap
id
ly
g
r
o
w
i
n
g
as
th
e
n
et
w
o
r
k
ar
ea
en
lar
g
ed
.
T
h
e
C
DC
A
alg
o
r
it
h
m
,
in
co
n
tr
as
t,
s
h
o
w
s
a
s
li
g
h
t
ch
a
n
g
e
o
f
t
h
e
n
u
m
b
er
o
f
m
o
b
ile
ele
m
e
n
ts
w
h
ich
led
to
r
ed
u
ce
th
e
n
et
w
o
r
k
co
s
t
s
i
g
n
i
f
ica
n
tl
y
.
Si
m
ilar
l
y
,
i
n
Fi
g
u
r
e
5
(
b
)
,
th
e
C
D
C
A
a
lg
o
r
it
h
m
r
eq
u
ir
ed
less
n
u
m
b
er
o
f
m
o
b
il
e
ele
m
en
ts
i
n
co
m
p
ar
is
o
n
w
i
th
th
e
A
S
A
,
p
ar
ticu
lar
l
y
at
s
h
o
r
t p
ath
co
n
s
tr
ai
n
t.
(
a)
(
b
)
Fig
u
r
e
5
.
T
h
e
n
u
m
b
er
o
f
m
o
b
i
le
ele
m
e
n
ts
as a
f
u
n
ctio
n
o
f
(
a
)
in
cr
ea
s
in
g
n
et
w
o
r
k
ar
ea
s
,
an
d
(
b
)
in
cr
ea
s
in
g
p
ath
co
n
s
tr
ain
ts
o
f
m
o
b
ile
ele
m
en
ts
5
.
2.
L
o
a
d ba
la
ncing
o
n m
o
b
ile
ele
m
ent
T
h
e
lo
ad
b
alan
cin
g
o
f
m
u
ltip
l
e
m
o
b
ile
ele
m
e
n
t
s
is
o
n
e
o
f
i
m
p
o
r
ta
n
t c
o
n
s
id
er
atio
n
w
h
en
d
esig
n
in
g
a
n
ef
f
icien
t
d
ata
g
at
h
er
in
g
al
g
o
r
i
th
m
.
B
y
a
ttai
n
in
g
th
i
s
g
o
al,
t
h
e
n
et
w
o
r
k
late
n
c
y
w
ill
b
e
r
ed
u
ce
d
i
n
ad
d
itio
n
to
b
etter
u
s
a
g
e
o
f
t
h
e
m
o
b
ile
ele
m
en
t
r
eso
u
r
ce
s
s
u
c
h
as
p
o
w
er
an
d
b
u
f
f
er
s
ize.
T
h
e
m
o
s
t
co
m
m
o
n
f
ac
to
r
u
s
ed
to
m
ea
s
u
r
e
t
h
i
s
cr
iter
io
n
is
t
h
e
Var
iatio
n
C
o
e
f
f
icien
t
(
V
C
)
.
VC
is
d
ef
i
n
ed
a
s
t
h
e
p
er
c
en
tag
e
o
f
s
ta
n
d
ar
d
d
ev
iatio
n
o
f
to
u
r
le
n
g
t
h
s
o
f
al
l
m
o
b
ile
e
le
m
e
n
t
s
a
n
d
t
h
eir
m
e
an
v
al
u
e
[
6
]
.
I
n
o
u
r
ca
s
e,
i
n
t
h
e
C
D
C
A
a
lg
o
r
it
h
m
all
m
o
b
ile
ele
m
e
n
ts
w
ill
tr
av
er
s
e
id
e
n
tical
p
at
h
le
n
g
t
h
s
an
d
t
h
er
ef
o
r
e
t
h
e
V
C
w
i
ll
b
e
al
m
o
s
t
ze
r
o
.
Fo
r
a
f
air
n
e
s
s
a
n
d
co
n
s
i
s
te
n
t
c
o
m
p
ar
is
o
n
,
t
h
e
VC
is
co
m
p
u
t
ed
b
ased
o
n
th
e
n
u
m
b
er
o
f
s
e
n
s
o
r
n
o
d
es
as
s
i
g
n
ed
to
ea
ch
m
o
b
ile
ele
m
e
n
t,
w
h
ic
h
ca
n
b
e
w
r
itte
n
as:
%
1
0
0
1
%
1
1
M
i
i
M
i
i
N
M
VC
(
1
1
)
w
h
er
e
σ
i
is
th
e
s
tan
d
ar
d
d
ev
iatio
n
o
f
th
e
n
u
m
b
er
o
f
s
en
s
o
r
n
o
d
es
b
elo
n
g
in
g
to
m
o
b
ile
elem
en
t
i
,
an
d
is
th
e
to
tal
n
u
m
b
er
o
f
m
o
b
ile
el
e
m
en
ts
.
No
te
th
at
t
h
e
lo
w
er
t
h
e
v
ar
iatio
n
co
ef
f
icie
n
t
(
VC
)
,
th
e
b
etter
th
e
lo
a
d
b
alan
ce
f
o
r
ea
c
h
m
o
b
ile
e
le
m
en
t.
Fi
g
u
r
e
6
(
a)
illu
s
tr
ates
t
h
e
f
o
r
C
D
C
A
a
n
d
A
S
A
al
g
o
r
ith
m
s
,
at
v
ar
y
i
n
g
n
et
w
o
r
k
ar
ea
s
.
T
h
e
o
f
th
e
t
w
o
al
g
o
r
ith
m
s
is
al
m
o
s
t
s
i
m
il
ar
at
s
m
all
n
et
w
o
r
k
ar
ea
s
.
De
s
p
ite
t
h
is
,
a
s
t
h
e
n
et
w
o
r
k
ar
ea
i
n
cr
ea
s
e
s
,
t
h
e
p
er
f
o
r
m
an
ce
g
ap
b
et
w
ee
n
t
h
e
t
wo
alg
o
r
ith
m
s
is
e
x
p
an
d
ed
.
T
h
is
r
esu
lt
i
s
ap
p
ar
en
t
s
in
ce
th
e
C
DC
A
alg
o
r
it
h
m
d
e
m
o
n
s
tr
ates
a
co
n
s
is
te
n
t
in
cr
ea
s
e
in
th
e
,
w
h
er
ea
s
th
is
v
al
u
e
f
o
r
th
e
A
S
A
alg
o
r
ith
m
r
ap
id
l
y
i
n
cr
ea
s
es.
F
ig
u
r
e
6
(
b
)
s
h
o
w
s
th
e
as
a
f
u
n
ctio
n
o
f
in
cr
ea
s
i
n
g
d
en
s
it
y
o
f
s
e
n
s
o
r
n
o
d
es.
Su
r
p
r
is
i
n
g
l
y
,
t
h
e
o
f
th
e
C
D
C
A
al
g
o
r
ith
m
d
ec
r
ea
s
e
s
as
t
h
e
n
u
m
b
er
o
f
s
en
s
o
r
n
o
d
es
i
n
cr
ea
s
es,
w
h
er
ea
s
t
h
is
v
alu
e
is
s
u
b
s
ta
n
tia
ll
y
in
cr
ea
s
e
d
f
o
r
A
S
A
alg
o
r
it
h
m
.
T
h
is
e
m
p
h
asizes
th
e
e
f
f
icie
n
c
y
o
f
u
s
i
n
g
C
D
C
A
al
g
o
r
ith
m
f
o
r
d
en
s
e
s
en
s
o
r
n
et
w
o
r
k
s
.
Si
m
ilar
l
y
,
Fig
u
r
e
6
(
c)
s
h
o
w
s
th
e
o
b
tain
ed
b
y
t
h
e
t
w
o
al
g
o
r
ith
m
s
.
T
h
e
lo
ad
b
alan
ce
is
i
m
p
r
o
v
ed
f
o
r
b
o
th
alg
o
r
ith
m
s
,
b
u
t
th
e
C
D
C
A
al
g
o
r
ith
m
h
as
lo
w
er
p
er
ce
n
tag
e
th
a
n
AS
A
o
v
er
th
e
en
t
ir
e
r
an
g
e
o
f
p
ath
co
n
s
tr
ain
t.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
3
,
J
u
n
e
201
9
:
2
1
3
1
-
2
1
4
0
2138
(
a)
(
b
)
(
c)
Fig
u
r
e
6
.
Var
iatio
n
C
o
ef
f
icie
n
t (
VC
)
as a
f
u
n
ct
io
n
o
f
(
a)
I
n
cr
ea
s
in
g
Net
w
o
r
k
A
r
ea
,
(
b
)
I
n
cr
ea
s
in
g
N
u
m
b
er
o
f
Se
n
s
o
r
No
d
es,
(
c)
I
n
cr
ea
s
in
g
P
ath
C
o
n
s
tr
ai
n
t
s
5
.
3
.
Net
wo
rk
l
a
t
ency
L
ate
n
c
y
ca
n
b
e
d
ef
in
ed
as
th
e
d
u
r
atio
n
o
f
ti
m
e
r
eq
u
ir
ed
to
c
o
m
p
lete
o
n
e
r
o
u
n
d
o
f
d
ata
g
ath
er
in
g
b
y
m
o
b
ile
ele
m
e
n
ts
.
As
m
e
n
tio
n
ed
b
ef
o
r
e,
th
e
in
cr
ea
s
in
g
o
f
m
o
b
ile
ele
m
e
n
ts
lead
s
to
d
ec
r
ea
s
e
th
e
n
et
w
o
r
k
laten
c
y
[
8
]
.
Fig
u
r
e
7
i
n
v
e
s
ti
g
ates
th
e
i
m
p
ac
t
o
f
n
et
w
o
r
k
ar
ea
s
,
n
u
m
b
er
o
f
n
o
d
es
an
d
th
e
p
ath
co
n
s
tr
ain
t
o
n
t
h
e
n
et
w
o
r
k
laten
c
y
f
o
r
b
o
th
a
lg
o
r
i
th
m
s
.
Fig
u
r
e
7
(
a)
s
h
o
w
s
a
g
r
ad
u
al
i
n
cr
ea
s
e
o
f
t
h
e
n
et
w
o
r
k
laten
c
y
f
o
r
th
e
t
w
o
alg
o
r
ith
m
s
as
th
e
n
et
w
o
r
k
ar
e
a
is
e
n
lar
g
ed
w
it
h
s
u
p
er
io
r
it
y
t
o
th
e
C
DC
A
al
g
o
r
ith
m
.
Mo
r
e
o
v
er
,
in
Fi
g
u
r
e
7
(
b
)
th
e
laten
c
y
is
n
o
t
c
h
an
g
ed
w
i
t
h
th
e
i
n
cr
ea
s
in
g
n
u
m
b
er
o
f
s
en
s
o
r
n
o
d
es
f
o
r
th
e
C
D
C
A
.
T
h
is
is
n
o
t
th
e
ca
s
e
f
o
r
th
e
A
S
A
alg
o
r
it
h
m
,
in
w
h
ic
h
t
h
e
n
e
t
w
o
r
k
late
n
c
y
is
s
li
g
h
t
l
y
in
cr
ea
s
ed
as
a
f
u
n
ct
io
n
o
f
in
cr
ea
s
in
g
t
h
e
n
u
m
b
er
o
f
s
en
s
o
r
n
o
d
es.
T
h
is
is
d
u
e
to
th
e
f
ac
t
t
h
at
t
h
e
A
S
A
al
g
o
r
ith
m
u
s
ed
th
e
T
r
av
el
Sales
-
Ma
n
(
T
S
P
)
alg
o
r
ith
m
to
f
i
n
d
th
e
p
ath
s
o
f
m
o
b
ile
ele
m
e
n
ts
.
On
th
e
o
t
h
er
h
a
n
d
,
alth
o
u
g
h
l
o
n
g
p
ath
s
o
f
m
o
b
ile
ele
m
e
n
ts
g
en
er
all
y
y
ie
ld
to
r
ed
u
ce
th
e
n
u
m
b
er
o
f
m
o
b
ile
ele
m
en
ts
,
t
h
e
n
et
w
o
r
k
laten
c
y
i
s
i
n
cr
ea
s
ed
.
T
h
is
tr
en
d
is
s
h
o
w
n
i
n
Fig
u
r
e
7
(
c)
.
I
n
t
h
is
r
eg
ar
d
,
th
e
A
S
A
alg
o
r
ith
m
ex
h
ib
ited
an
al
m
o
s
t
co
n
s
tan
t
laten
c
y
.
Nev
er
t
h
ele
s
s
,
th
e
C
DC
A
al
g
o
r
ith
m
ac
co
m
p
lis
h
ed
th
e
d
ata
g
ath
er
i
n
g
w
it
h
lo
w
er
late
n
c
y
o
v
er
th
e
en
tire
r
an
g
e
o
f
th
e
p
ath
co
n
s
tr
ain
ts
.
I
n
th
is
f
i
g
u
r
e,
at
lo
w
p
at
h
co
n
s
tr
ain
ts
,
t
h
e
C
D
C
A
r
ed
u
ce
s
th
e
n
et
w
o
r
k
late
n
c
y
s
u
b
s
tan
t
i
all
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8708
I
n
tellig
en
t fir
e
d
etec
tio
n
a
n
d
a
lert
s
ys
tem
u
s
in
g
la
b
V
I
E
W
(
F
a
kru
lr
a
d
z
i I
d
r
is
)
2139
(
a)
(
b
)
(
c)
Fig
u
r
e
7
.
Net
w
o
r
k
la
ten
c
y
as a
f
u
n
ctio
n
o
f
(
a)
in
cr
ea
s
i
n
g
n
et
w
o
r
k
ar
ea
,
(
b
)
in
cr
ea
s
in
g
n
u
m
b
er
o
f
s
e
n
s
o
r
n
o
d
es,
(
c)
in
cr
ea
s
in
g
p
ath
c
o
n
s
tr
ain
ts
6.
CO
NCLUS
I
O
N
I
n
t
h
is
p
ap
er
a
n
e
w
d
ata
g
at
h
e
r
in
g
tech
n
iq
u
e
i
n
W
SN
b
ased
o
n
u
s
i
n
g
m
o
r
e
t
h
a
n
o
n
e
m
o
b
il
e
ele
m
e
n
t,
r
ef
er
r
ed
to
as
co
llab
o
r
ativ
e
d
a
ta
co
llectio
n
alg
o
r
ith
m
(
C
DC
A
)
,
w
a
s
p
r
o
p
o
s
ed
.
T
h
e
m
ai
n
o
b
j
ec
tiv
e
b
eh
in
d
th
e
C
DC
A
i
s
to
r
ed
u
ce
d
ata
g
ath
er
in
g
late
n
c
y
w
h
ic
h
i
n
tu
r
n
l
ea
d
s
to
in
cr
ea
s
e
th
e
n
et
w
o
r
k
th
r
o
u
g
h
p
u
t
a
n
d
to
d
ec
r
ea
s
e
t
h
e
n
u
m
b
er
o
f
m
o
b
ile
ele
m
e
n
ts
u
s
ed
f
o
r
th
i
s
ta
s
k
.
Si
m
u
latio
n
r
es
u
lts
s
h
o
w
e
d
th
at
th
e
C
D
C
A
ex
h
ib
ited
s
u
p
er
io
r
p
er
f
o
r
m
a
n
c
e
in
co
m
p
ar
is
o
n
w
it
h
t
h
e
AS
A
a
lg
o
r
it
h
m
i
n
ter
m
o
f
lo
ad
b
alan
ci
n
g
,
n
u
m
b
er
o
f
m
o
b
ile
ele
m
e
n
t
s
an
d
n
et
w
o
r
k
laten
c
y
.
I
n
f
u
tu
r
e
w
o
r
k
,
as
ea
c
h
m
o
b
i
le
ele
m
e
n
t
is
d
esi
g
n
ed
to
co
l
lect
d
ata
f
r
o
m
lar
g
e
n
u
m
b
er
o
f
s
en
s
o
r
n
o
d
es,
th
e
b
u
f
f
er
s
ize
li
m
itati
o
n
co
u
ld
b
e
co
n
s
id
er
ed
.
I
n
ad
d
itio
n
,
it
w
o
u
ld
b
e
w
o
r
th
w
h
ile
to
s
tu
d
y
t
h
e
w
a
y
o
f
d
eliv
er
in
g
d
ata
t
h
r
o
u
g
h
m
o
b
il
e
ele
m
e
n
ts
to
th
e
s
i
n
k
n
o
d
e.
I
t
w
o
u
ld
also
b
e
u
s
e
f
u
l
to
f
u
r
th
er
s
tu
d
y
th
e
p
o
w
er
r
ec
h
ar
g
i
n
g
c
y
cles o
f
th
e
m
o
b
il
e
ele
m
en
ts
f
r
o
m
te
m
p
o
r
al
an
d
s
p
aial
p
er
s
p
ec
tiv
e.
RE
F
E
R
E
NC
E
S
[1
]
W
.
B.
He
in
z
e
l
m
a
n
,
e
t
a
l
.
,
“
A
n
a
p
p
li
c
a
ti
o
n
-
sp
e
c
if
ic
p
ro
to
c
o
l
a
rc
h
it
e
c
tu
re
f
o
r
w
irele
ss
m
i
c
ro
se
n
so
r
n
e
tw
o
rk
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
W
ire
les
s Co
mm
u
n
ica
ti
o
n
s
,
v
ol
/i
ss
u
e
:
1
(4
),
p
p
.
6
6
0
-
6
7
0
,
2
0
0
2
.
[2
]
K.
Da
n
tu
,
e
t
a
l
.
,
“
R
o
b
o
m
o
te:
En
a
b
li
n
g
m
o
b
il
it
y
in
se
n
so
r
n
e
tw
o
rk
s
,
”
In
fo
rm
a
ti
o
n
Pr
o
c
e
ss
in
g
in
S
e
n
so
r
Ne
two
rk
s,
IPS
N,
F
o
u
rt
h
I
n
ter
n
a
t
io
n
a
l
S
y
mp
o
siu
m
,
p
p
.
4
0
4
-
4
0
9
,
2
0
0
5
.
[3
]
J.
W
a
n
g
,
e
t
a
l
.
,
“
M
u
lt
i
p
le
m
o
b
il
e
sin
k
-
b
a
se
d
ro
u
t
in
g
a
lg
o
rit
h
m
s
f
o
r
d
a
ta
d
isse
m
in
a
ti
o
n
in
w
irele
ss
s
e
n
so
r
n
e
tw
o
rk
s
,
”
c
o
n
c
u
rr
e
n
c
y
a
n
d
c
o
mp
u
ta
ti
o
n
:
p
r
a
c
ti
c
e
a
n
d
e
x
p
e
rie
n
c
e
,
W
il
e
y
On
li
n
e
L
ib
ra
ry
,
v
ol
/i
ss
u
e
:
27
(
10
)
,
p
p
.
2
6
5
6
-
2
6
6
7
,
2
0
1
5
.
[4
]
Y
.
G
u
,
e
t
a
l
.
,
“
P
a
rti
ti
o
n
in
g
Ba
se
d
M
o
b
i
le
El
e
m
e
n
t
S
c
h
e
d
u
l
in
g
i
n
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s
,
”
Pr
o
c
.
o
f
S
ECON
,
S
a
n
ta
C
la
ra
,
U.S
.
,
p
p
.
3
8
6
-
3
9
5
,
2
0
0
5
.
[5
]
B.
Yu
a
n
,
e
t
a
l
.
,
“
On
th
e
o
p
ti
m
a
l
ro
b
o
t
r
o
u
ti
n
g
p
ro
b
lem
in
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
,
”
IEE
E
T
ra
n
s.
Kn
o
wl
.
Da
ta
En
g
.
,
v
ol
/i
ss
u
e
:
1
9
(9
),
p
p
.
1
2
5
2
-
1
2
6
1
,
2
0
0
7
.
[6
]
G
.
X
in
g
,
e
t
a
l
.
,
“
Re
n
d
e
z
v
o
u
s
p
lan
n
i
n
g
in
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
w
it
h
m
o
b
il
e
e
le
m
e
n
ts
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
M
o
b
il
e
Co
m
p
u
ti
n
g
,
v
ol
/i
ss
u
e
:
7
(
1
2
),
p
p
.
1
4
3
0
-
1
4
4
3
,
2
0
0
8
.
[7
]
D.
Zh
u
,
e
t
a
l
.
,
“
M
u
lt
i
-
p
a
th
P
lan
n
i
n
g
f
o
r
M
o
b
il
e
El
e
m
e
n
t
to
P
r
o
lo
n
g
t
h
e
L
if
e
ti
m
e
o
f
Wi
re
les
s
S
e
n
so
r
Ne
tw
o
rk
s,”
2
0
0
9
1
5
t
h
IEE
E
I
n
t
e
rn
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Em
b
e
d
d
e
d
a
n
d
Rea
l
-
T
ime
Co
mp
u
ti
n
g
S
y
ste
ms
a
n
d
Ap
p
li
c
a
ti
o
n
s
,
Beiji
n
g
,
p
p
.
4
1
-
50
,
2
0
0
9
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
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lec
&
C
o
m
p
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,
Vo
l.
9
,
No
.
3
,
J
u
n
e
201
9
:
2
1
3
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1
4
0
2140
[8
]
E.
C.
H.
Ng
a
i,
e
t
a
l
.
,
“
A
n
A
d
a
p
ti
v
e
De
la
y
-
M
in
im
ize
d
Ro
u
te
De
sig
n
f
o
r
W
irele
ss
S
e
n
so
r
–
A
c
tu
a
to
r
Ne
tw
o
rk
s,”
IEE
E
T
ra
n
s
a
c
ti
o
n
s o
n
Veh
ic
u
la
r
T
e
c
h
n
o
lo
g
y
,
v
ol
/i
ss
u
e
:
58
(
9
)
,
p
p
.
5
0
8
3
-
5
0
9
4
,
2
0
0
9
.
[9
]
S
.
G
a
o
a
n
d
H.
Zh
a
n
g
,
“
En
e
rg
y
Eff
icie
n
t
P
a
th
-
c
o
n
stra
in
e
d
S
i
n
k
Na
v
ig
a
ti
o
n
in
De
la
y
-
g
u
a
ra
n
tee
d
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s
,
”
J
o
u
rn
a
l
o
f
Ne
tw
o
rk
s
,
v
ol
/i
ss
u
e
:
5
(
6
),
p
p
.
6
58
-
6
6
5
,
2
0
1
0
.
[1
0
]
S
.
G
a
o
,
e
t
a
l
.
,
“
Eff
icie
n
t
Da
ta
Co
ll
e
c
ti
o
n
i
n
W
irele
ss
S
e
n
so
r
Ne
two
rk
s
w
it
h
P
a
th
-
Co
n
stra
i
n
e
d
M
o
b
i
le
S
in
k
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
M
o
b
i
le Co
mp
u
ti
n
g
,
v
ol
/i
ss
u
e
:
1
0
(
5
),
p
p
.
5
9
2
-
6
0
8
,
2
0
1
1
.
[1
1
]
L
.
He
,
e
t
a
l
.
,
“
A
n
a
l
y
sis
o
n
d
a
ta
c
o
ll
e
c
ti
o
n
w
it
h
m
u
lt
ip
le
m
o
b
il
e
e
le
m
e
n
ts
in
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
,
”
Glo
b
a
l
T
e
lec
o
mm
u
n
ica
ti
o
n
s C
o
n
fer
e
n
c
e
(
GLOBE
COM
2
0
1
1
),
I
EE
E,
p
p
.
1
-
5
,
2
0
1
1
.
[1
2
]
W
.
K
w
o
n
g
a
n
d
Y
.
X
u
,
“
P
a
th
p
lan
n
in
g
a
lg
o
rit
h
m
f
o
r
sp
a
c
e
m
a
n
ip
u
l
a
to
r
w
it
h
a
m
in
i
m
u
m
e
n
e
rg
y
d
e
m
a
n
d
,
”
R
o
b
o
ti
c
s
a
n
d
Bi
o
mime
ti
c
s (
ROBI
O) 2
0
1
2
I
EE
E
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
,
p
p
.
1
5
5
6
-
1
5
6
3
,
2
0
1
2
.
[1
3
]
X
.
Xu
,
e
t
a
l
.
,
“
A
De
la
y
-
E
ff
ici
e
n
t
A
lg
o
rit
h
m
f
o
r
Da
ta
A
g
g
re
g
a
ti
o
n
in
M
u
lt
i
h
o
p
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s
,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Pa
r
a
ll
e
l
Distri
b
u
ted
S
y
ste
ms
,
v
ol
/i
ss
u
e
:
2
2
(
1
),
p
p
.
1
6
3
-
1
7
5
,
2
0
1
1
.
[1
4
]
G
.
X
in
g
,
e
t
a
l
.
,
“
Eff
icie
n
t
re
n
d
e
z
v
o
u
s
a
lg
o
rit
h
m
s
f
o
r
m
o
b
il
it
y
-
e
n
a
b
led
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
M
o
b
i
le Co
mp
u
ti
n
g
,
v
ol
/i
ss
u
e
:
1
1
(
1
),
p
p
.
4
7
-
6
0
,
2
0
1
2
.
[1
5
]
L
.
H
e
,
e
t
a
l
.
,
“
A
P
ro
g
re
ss
iv
e
A
p
p
ro
a
c
h
to
Re
d
u
c
i
n
g
Da
ta
Co
ll
e
c
t
io
n
L
a
ten
c
y
in
W
irele
s
s
S
e
n
so
r
Ne
tw
o
rk
s
w
it
h
M
o
b
i
le E
lem
e
n
ts
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s O
n
M
o
b
il
e
Co
m
p
u
ti
n
g
,
v
ol
/i
ss
u
e
:
1
2
(
7
),
p
p
.
1
3
0
8
-
1
3
2
0
,
2
0
1
3
.
[1
6
]
M
.
M
a
,
e
t
a
l
.
,
“
T
o
u
r
P
lan
n
i
n
g
f
o
r
M
o
b
il
e
Da
ta
-
G
a
th
e
rin
g
M
e
c
h
a
n
ism
s
in
W
irele
s
s
S
e
n
so
r
Ne
tw
o
rk
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Veh
icu
la
r T
e
c
h
n
o
lo
g
y
,
v
ol
/i
ss
u
e
:
6
2
(4
),
p
p
.
1
4
7
2
-
148
3,
2
0
1
3
.
[1
7
]
D.
Kim
,
e
t
a
l
.
,
“
M
in
im
u
m
Late
n
c
y
M
u
lt
ip
le
Da
ta
M
UL
E
T
ra
je
c
to
ry
P
lan
n
in
g
i
n
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
M
o
b
i
le Co
mp
u
ti
n
g
,
v
ol
/i
ss
u
e
:
1
3
(
4
),
p
p
.
8
3
8
-
8
5
1
,
2
0
1
4
.
[1
8
]
J
.
S
.
He
,
e
t
a
l
.
,
“
Co
n
str
u
c
ti
n
g
L
o
a
d
-
Ba
lan
c
e
d
Da
ta
A
g
g
re
g
a
ti
o
n
Tree
s
in
P
ro
b
a
b
il
isti
c
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Pa
r
a
ll
e
l
a
n
d
Distri
b
u
te
d
S
y
ste
ms
,
v
ol
/i
ss
u
e
:
2
5
(
7
),
p
p
.
1
6
8
1
-
1
6
9
0
,
2
0
1
4
.
[1
9
]
D.
G
o
n
g
a
n
d
Y.
Ya
n
g
,
“
L
o
w
-
l
a
ten
c
y
S
INR
-
b
a
se
d
d
a
ta
g
a
th
e
rin
g
in
w
ir
e
les
s
se
n
so
r
n
e
tw
o
rk
s
,
”
IEE
E
T
ra
n
s.
W
ire
les
s Co
mm
u
n
.,
v
ol
/i
ss
u
e
:
1
3
(
6
),
p
p
.
3
2
0
7
-
3
2
2
,
2
0
1
4
.
[2
0
]
H.
L
in
a
n
d
H.
Üs
tert,
“
Ex
a
c
t
a
n
d
h
e
u
risti
c
a
lg
o
rit
h
m
s
f
o
r
d
a
ta
-
g
a
th
e
rin
g
c
lu
ste
r
b
a
se
d
w
irele
ss
s
e
n
so
r
n
e
tw
o
rk
d
e
sig
n
p
ro
b
lem
,
”
IEE
E/
ACM
T
ra
n
sa
c
ti
o
n
s o
n
Ne
two
rk
i
n
g
,
v
ol
/i
ss
u
e
:
2
2
(
3
),
p
p
.
9
0
3
-
9
1
6
,
2
0
1
4
.
[2
1
]
D.
V
.
L
e
,
e
t
a
l
.,
“
HiCo
D
G
:
A
h
iera
rc
h
ica
l
d
a
ta
-
g
a
th
e
rin
g
s
c
h
e
m
e
u
sin
g
c
o
o
p
e
ra
ti
v
e
m
u
lt
ip
le
m
o
b
il
e
e
le
m
e
n
ts
,
”
S
e
n
so
rs
,
v
ol
/
issu
e
:
1
4
(1
2
),
p
p
.
2
4
2
7
8
-
2
4
3
0
4
,
2
0
1
4
.
[2
2
]
M
.
Z
h
a
o
,
e
t
a
l
.,
“
M
o
b
il
e
Da
ta
G
a
th
e
rin
g
w
it
h
L
o
a
d
Ba
lan
c
e
d
Clu
ste
rin
g
a
n
d
Du
a
l
Da
ta
Up
l
o
a
d
in
g
i
n
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s O
n
M
o
b
il
e
Co
m
p
u
ti
n
g
,
v
ol
/i
ss
u
e
:
1
4
(
4
),
p
p
.
7
7
0
-
7
8
5
,
2
0
1
5
.
[2
3
]
Y.
Ya
o
,
e
t
a
l
.
,
“
ED
AL
:
A
n
e
n
e
rg
y
-
e
f
f
i
c
ien
t,
d
e
la
y
-
a
w
a
r
e
,
a
n
d
li
f
e
ti
m
e
-
ba
lan
c
in
g
d
a
ta
c
o
ll
e
c
ti
o
n
p
r
o
to
c
o
l
f
o
r
h
e
tero
g
e
n
e
o
u
s
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
,
”
IEE
E/
ACM
T
ra
n
sa
c
ti
o
n
s
o
n
Ne
two
rk
in
g
,
v
ol
/i
ss
u
e
:
2
3
(
3
),
p
p
.
8
1
0
-
8
2
3
,
2
0
1
5
.
[2
4
]
C
.
F
.
Ch
e
n
g
a
n
d
C
.
F
.
Yu
,
“
Da
ta G
a
th
e
rin
g
in
W
irel
e
ss
S
e
n
so
r
Ne
t
w
o
rk
s:
A Co
m
b
in
e
T
S
P
Re
d
u
c
e
Ap
p
r
o
a
c
h
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Veh
icu
la
r T
e
c
h
n
o
lo
g
y
,
v
ol
/i
ss
u
e
:
6
5
(4
),
2
3
0
9
-
2
3
2
4
,
2
0
1
6
.
[2
5
]
D.
Kim
,
e
t
a
l
.
,
“
M
in
im
izin
g
d
a
ta
c
o
ll
e
c
ti
o
n
late
n
c
y
in
w
irele
ss
s
e
n
so
r
n
e
tw
o
rk
w
it
h
m
u
lt
ip
le
m
o
b
il
e
e
lem
e
n
ts,”
2
0
1
2
p
ro
c
e
e
d
in
g
INFOCOM
,
IEE
E,
p
p
.
5
0
4
-
5
1
2
,
2
0
1
2
.
[2
6
]
J
.
He
,
e
t
a
l
.
,
“
De
lay
M
in
im
iza
ti
o
n
f
o
r
Da
ta
Diss
e
m
in
a
ti
o
n
in
L
a
rg
e
-
S
c
a
le
V
AN
ET
s
w
it
h
Bu
se
s
a
n
d
T
a
x
is,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
M
o
b
i
le Co
mp
u
ti
n
g
,
v
o
l.
1
5
,
p
p
.
1
9
3
9
-
1
9
5
0
,
2
0
1
6
.
[2
7
]
D
.
G
o
sa
in
a
n
d
I
.
S
n
ig
d
h
,
“
P
e
rf
o
rm
a
n
c
e
Co
m
p
a
riso
n
o
f
Ro
u
ti
n
g
P
ro
to
c
o
ls
in
Bi
p
a
rti
te
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
,
v
ol
/
issu
e
:
5
(6
)
,
p
p
.
1
4
1
7
-
1
4
2
3
,
2
0
1
5
.
[2
8
]
S
.
Um
a
r,
e
t
a
l
.
,
“
T
re
e
Ba
se
d
En
e
rg
y
Ba
lan
c
in
g
Ro
u
ti
n
g
P
ro
to
c
o
l
b
y
S
e
l
f
O
rg
a
n
izin
g
in
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s,”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
,
v
ol
/
issu
e
:
5
(
6
)
,
p
p
.
1
4
8
6
-
1
4
9
1
,
2
0
1
5
.
[2
9
]
K
.
N
.
Qu
re
sh
i,
e
t
a
l
.
,
“
G
e
o
g
ra
p
h
ica
l
F
o
rw
a
rd
in
g
M
e
th
o
d
s
in
V
e
h
icu
lar
A
d
h
o
c
Ne
tw
o
rk
s,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
,
v
ol
/i
ss
u
e
:
5
(6
),
p
p
.
1
4
0
7
-
1
4
1
6
,
2
0
1
5
.
[3
0
]
M
.
F
.
Isk
a
n
d
e
r
a
n
d
Z
.
Y
u
n
,
“
P
r
o
p
a
g
a
ti
o
n
p
re
d
ictio
n
m
o
d
e
ls
f
o
r
w
irele
ss
c
o
m
m
u
n
ica
ti
o
n
s
y
ste
m
s,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
M
icr
o
wa
v
e
T
h
e
o
ry
a
n
d
T
e
c
h
n
i
q
u
e
s
,
v
ol
/i
ss
u
e
:
50
(
3
)
,
p
p
.
6
6
2
-
6
7
3
,
2
0
0
2
.
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