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A
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.
14,
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3,
S
ept
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20
16,
pp.
11
83
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12928/
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©
20
16 U
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s A
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A
l
l
r
i
g
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t
s r
eser
ved
.
1.
I
n
tr
o
d
u
c
ti
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U
nder
w
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e
nv
i
r
onm
ent
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ar
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or
ex
pl
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o
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of
hi
g
h
f
r
equenc
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s
i
gna
l
s
pr
o
pag
at
i
o
n
[
1]
.
D
ue
t
o
t
he
und
er
w
at
er
ac
o
us
t
i
c
c
o
m
m
uni
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s
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g
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l
pr
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l
t
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nd f
as
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t
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t
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m
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s
l
o
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r
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agnet
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[
2]
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Mos
t
of
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m
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nt
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t
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s
and r
out
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n s
ui
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abl
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om
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i
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l
ar
g
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to
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end
de
l
a
y
s
[
3]
.
A
l
t
hou
gh
s
i
gni
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c
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t
ar
eas
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m
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gh
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U
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s
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on
of
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del
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om
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a
de
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In
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U
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pec
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s
f
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om
t
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r
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r
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net
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or
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4]
.
F
i
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s
t
l
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m
os
t
of
t
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t
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of
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or
nod
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ar
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de
pl
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d
r
a
n
dom
l
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t
ha
t
ar
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no
t
s
c
al
a
bl
e
f
or
ex
t
ens
i
o
n
of
under
w
at
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p
i
pe
l
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m
oni
t
or
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g c
ov
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ag
e.
S
ec
on
dl
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,
U
W
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equi
r
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s
pe
c
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al
dep
l
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or
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s
t
hat
as
s
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op
er
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es
pos
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t
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n
3D
d
y
n
am
i
c
under
w
at
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e
nv
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on
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.
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hi
r
dl
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,
s
ens
or
s
ar
e
l
i
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ear
l
y
de
pl
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t
o
m
ai
nt
ai
n
t
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l
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near
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l
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d
di
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but
ed
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net
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k
[
5]
t
hat
d
i
v
i
d
es
t
he
pi
pel
i
ne
l
e
ngt
h
i
nt
o
s
ub
-
z
on
es
and
r
anges
of
het
er
og
e
neous
s
ens
or
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
1
6
9
3
-
6
930
T
E
L
KO
M
NI
K
A
V
o
l.
14
,
N
o
.
3,
S
ept
em
ber
2016
:
11
83
–
1
191
1184
F
our
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om
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o t
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ar
der
s
.
B
es
i
d
es
,
i
t
c
a
n
al
s
o
f
unc
t
i
o
n
i
n
d
i
f
f
er
ent
k
i
nds
of
ot
her
l
i
n
ear
ap
pl
i
c
at
i
ons
un
der
m
an
y
i
m
por
t
ant
c
ons
t
r
ai
nt
s
.
2.
R
el
at
ed
W
o
r
k
I
t
i
s
har
d
t
o f
i
nd
an ar
t
i
c
l
e r
el
at
ed t
o
s
c
al
a
bl
e
nod
es
de
pl
o
y
m
ent
al
g
or
i
t
hm
t
hat
ef
f
i
c
i
ent
l
y
dep
l
o
y
s
het
er
oge
neo
us
t
y
p
es
of
nodes
i
n
or
d
er
t
o
c
o
v
er
t
he
l
ar
g
e
s
c
al
e
m
oni
t
or
i
ng
ar
e
a
of
t
he
under
w
at
er
pi
pel
i
n
e.
F
ur
t
h
er
,
i
n u
nder
w
at
er
en
v
i
r
o
n
m
ent
s
,
i
t
i
s
al
s
o
d
i
f
f
i
c
ul
t
t
o s
ep
ar
at
e
t
he
c
r
it
ic
a
l m
o
n
i
t
or
i
ng ar
e
as
an
d m
ai
nt
ai
n
i
ng
of
c
o
m
m
uni
c
at
i
o
n bet
w
ee
n t
he
nod
es
w
i
t
h hi
gh en
er
g
y
c
ons
t
r
ai
nt
,
c
om
m
on t
opol
o
g
y
c
ha
nges
a
nd no
des
f
ai
l
ur
es
.
F
or
s
uc
h t
y
pes
of
env
i
r
onm
ent
s
,
m
an
y
dep
l
o
y
m
ent
s
c
hem
es
hav
e
be
en
pr
op
os
ed
t
o
m
oni
t
or
t
he
under
w
at
er
pi
p
el
i
nes
.
A
m
ong
t
hes
e,
m
os
t
of
t
hem
need
s
pec
i
a
l
n
et
w
or
k
s
et
ups
l
i
k
e
aut
om
ot
i
v
e t
ool
s
/
r
o
bot
s
/
v
eh
i
c
l
es
a
nd
t
he
y
gener
al
l
y
ar
e
di
v
i
ded
i
n
d
i
f
f
er
ent
c
at
eg
or
i
es
[1
-
2
]
,
[
6]
.
D
ep
l
o
y
m
ent
S
c
hem
es
ar
e c
l
as
s
i
f
i
ed
as
t
hos
e t
ha
t
r
equ
i
r
e s
pec
i
al
net
w
or
k
s
et
ups
and ex
t
r
a aut
om
ot
i
v
e t
oo
l
s
[7
-
11]
an
d us
e
hom
ogenous
t
y
p
es
of
s
en
s
or
s
.
A
l
l
t
h
es
e pr
ot
oc
ol
s
r
equ
i
r
e ex
t
r
a
or
di
n
ar
y
s
y
s
t
e
m
and
m
ul
t
i
p
l
e
t
y
p
es
of
r
obot
s
/
A
U
V
s
e
qui
pped
w
i
t
h
s
pec
i
al
s
e
ns
or
m
ov
es
ov
er
t
h
e
p
i
pe
l
i
ne.
T
he
dr
a
w
bac
k
o
f
s
uc
h
k
i
nd
of
s
c
he
m
es
ar
e
t
hat
t
hes
e
ar
e
not
app
r
opr
i
at
e
f
or
l
on
g
t
er
m
and
l
ar
g
e
s
c
al
e
under
w
at
er
p
i
p
el
i
ne
m
oni
t
o
r
i
ng pr
oc
es
s
as
t
he
y
us
e
t
o
i
nc
r
eas
e c
os
t
and
de
l
a
y
.
S
ec
on
dl
y
,
c
ha
i
n
bas
e
d
de
p
l
o
y
m
ent
s
c
hem
es
m
os
t
l
y
i
n
v
o
l
v
es
ne
i
gh
bour
nod
es
l
o
c
at
i
on
d
e
t
a
ils
f
or
t
he
eac
h
s
e
ns
or
of
c
o
m
pl
et
e
net
w
or
k
.
F
or
t
he
s
ak
e
of
eas
e,
m
os
t
of
t
hes
e
t
y
pes
of
s
c
he
m
es
as
s
u
m
e t
hat
al
l
nodes
i
n t
he
net
w
or
k
al
r
ead
y
h
av
e det
ai
l
s
of
t
hei
r
o
w
n l
oc
at
i
on
and
des
t
i
n
at
i
on l
oc
at
i
on.
T
hes
e t
y
p
es
of
depl
o
y
m
ent
s
c
hem
es
[
18
-
20]
a
nd t
he
i
r
r
equ
i
r
e
m
ent
s
ar
e not
eas
y
t
o be
i
m
pl
em
ent
ed a
ppr
opr
i
at
e
l
y
i
n
und
er
w
at
er
as
ef
f
i
c
i
ent
nod
es
dep
l
o
y
m
ent
i
s
s
t
i
l
l
a
c
hal
l
eng
i
n
g t
as
k
i
n U
W
S
N
.
F
or
c
o
m
par
at
i
v
e a
na
l
y
s
i
s
per
s
pec
t
i
v
e,
a s
hor
t
s
um
m
ar
y
of
s
o
m
e
pi
p
el
i
nes
m
oni
t
or
i
ng
de
pl
o
y
m
ent
s
c
he
m
es
i
s
des
c
r
i
bed
i
n T
ab
l
e
1.
F
ur
t
h
er
,
p
i
p
el
i
n
es
m
oni
t
or
i
ng
i
s
hi
g
hl
y
i
m
por
t
ant
as
t
her
e i
s
a br
o
ad n
et
w
or
k
of
pi
pel
i
nes
c
ar
r
y
i
ng
oi
l
a
nd g
a
s
t
hat
pl
a
y
an
i
nt
e
gr
al
r
o
l
e
f
or
t
he
e
ner
g
y
m
anagem
ent
and
ec
onom
y
of
m
an
y
c
ou
nt
r
i
es
.
S
uc
h
a
s
N
i
ger
i
a
has
ar
oun
d 5,
000 k
i
l
om
et
r
es
o
i
l
pi
p
el
i
n
es
c
ons
i
s
t
i
ng
of
m
or
e t
han 4,
0
00 k
m
of
di
f
f
er
ent
pr
oduc
t
s
c
ar
r
y
i
ng p
i
p
el
i
nes
w
h
i
l
e t
h
e r
em
ai
ni
ng l
engt
h be
l
on
g
s
t
o c
r
ude
-
o
il p
ip
e
l
in
e
s
[
21
]
.
T
he av
er
ag
e
dept
h of
oc
eans
l
a
y
s
ar
o
und 2
.
5k
m
t
o 3
k
m
and pi
pel
i
nes
l
en
gt
h
i
s
m
or
e t
han 10
0 k
m
.
I
n
under
w
at
er
e
nv
i
r
onm
ent
,
ac
ous
t
i
c
c
om
m
uni
c
at
i
on
i
s
c
ons
i
der
ed
a
n
i
dea
l
b
ut
t
he
r
a
nge
of
under
w
at
er
s
e
ns
or
no
des
i
s
not
pr
ef
er
r
ed
m
or
e t
ha
n
1
k
m
.
H
ow
e
v
er
,
i
f
w
e
d
i
v
i
d
e t
he
p
i
pe
l
i
ne
l
en
gt
h
i
nt
o
s
ub
z
o
nes
of
10
00
m
et
er
eac
h,
t
he
n
l
es
s
n
um
ber
of
nodes
i
s
r
e
qu
i
r
ed
t
o
del
i
v
er
t
he
dat
a
p
ac
k
et
s
f
r
o
m
t
he
m
i
ddl
e
of
t
he
pi
pel
i
n
e
an
d
f
r
om
bot
t
om
t
o
t
he
s
ur
f
ac
e
at
di
f
f
er
ent
oc
ean
dept
hs
[
3]
.
I
t
i
s
i
m
por
t
ant
t
o
be
no
t
ed
t
hat
t
he
per
f
or
m
anc
e
of
our
pr
ot
oc
ol
dep
ends
on
t
he
n
um
ber
and
t
y
p
es
of
s
ens
or
s
.
T
he
pr
opos
e
d
d
epl
o
y
m
e
nt
a
l
g
or
i
t
hm
s
uppor
t
e
as
i
l
y
het
er
og
eneo
us
t
y
pes
of
s
ens
or
s
but
i
f
w
e i
nc
r
eas
e t
he num
ber
of
s
ens
or
s
i
t
w
i
l
l
i
nc
r
eas
e t
he c
os
t
of
t
he
net
w
or
k
.
I
f
w
e
us
e hom
ogen
ous
t
y
pes
of
s
ens
or
s
i
n
t
ha
t
c
as
e t
he
ac
o
us
t
i
c
c
om
m
uni
c
at
i
ons
w
i
l
l
g
i
v
e s
up
por
t
u
p
t
o t
he r
ang
e of
5
k
m
;
but
i
t
i
s
not
des
i
r
ab
l
e as
l
on
g di
s
t
anc
e c
om
m
uni
c
at
i
on
s
ut
i
l
i
z
e m
or
e
ener
g
y
.
I
n
or
der
t
o c
o
v
er
m
ax
i
m
u
m
l
engt
h of
t
he p
i
pe
l
i
ne
w
i
t
h l
o
w
en
er
g
y
and m
or
e net
w
or
k
l
i
f
e
t
i
m
e,
w
e
ha
v
e
def
i
n
ed
t
he
di
f
f
er
ent
r
anges
of
ac
ous
t
i
c
c
o
m
m
uni
c
at
i
on
f
or
eac
h
t
y
pes
of
s
ens
o
r
v
ar
y
i
n
g f
r
o
m
200 m
et
er
t
o
m
or
e t
han 100
0 m
et
er
.
I
t
i
s
f
ound t
h
at
ac
o
us
t
i
c
c
om
m
uni
c
at
i
o
ns
w
or
k
bes
t
f
or
t
he s
hor
t
r
an
ge a
p
pl
i
c
a
t
i
o
ns
bec
a
us
e i
t
s
u
ppo
r
t
band
w
i
d
t
h of
20
-
3
0
K
H
z
[
22
-
24]
i
n
1 k
m
di
s
t
anc
e
.
A
l
t
h
oug
h,
i
n
s
pec
i
al
c
as
es
,
w
e
c
a
n
i
nc
r
eas
e
t
hi
s
r
an
ge
of
s
ens
or
s
[
25]
,
but
i
n
n
or
m
al
ac
ous
t
i
c
c
om
m
uni
c
at
i
on
i
t
i
s
s
ugg
es
t
ed
t
o
us
e t
h
e d
i
s
c
us
s
ed r
ang
es
of
s
ens
or
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
K
A
I
S
S
N
:
1
693
-
6
930
S
c
al
a
bl
e
H
e
t
er
og
ene
ous
N
odes
D
e
pl
oy
men
t
A
l
g
or
i
t
h
m f
or
…
(
Muh
amm
ad Z
ahi
d
A
bb
as
)
1185
T
abl
e 1.
S
h
or
t
s
um
m
ar
y
of
t
he
r
eq
ui
r
em
ent
s
an
d
l
i
m
i
t
at
i
ons
of
ex
i
s
t
i
ng
de
pl
o
y
m
en
t
s
c
hem
es
A
l
gor
i
t
hm
R
e
qui
r
e
m
e
nt
s
a
nd
L
i
m
i
t
a
t
i
ons
S
P
A
MMS
[
7]
i
)
R
obot
m
ov
es
i
n t
he
pi
pel
i
ne
t
o
c
ol
l
ec
t
da
t
a f
r
o
m
R
F
I
D
s
ens
or
s
depl
oy
ed at
t
he
i
nner
w
al
l
of
t
he
pi
pel
i
ne
f
or
t
he det
e
c
t
i
on
and r
epai
r
i
ng
of
def
e
c
t
ed pi
pel
i
ne p
l
ac
e
.
i
i
)
S
P
A
M
M
S
i
s
onl
y
s
ui
t
abl
e f
o
r
s
m
a
l
l
-
s
c
a
l
e
m
oni
t
or
i
ng and ha
v
e no an
y
depl
oy
m
ent
al
gor
i
t
h
m
.
PI
PEN
E
T
[
1
2]
i
)
S
pec
i
a
l
f
i
x
ed nodes
hav
i
ng s
t
a
t
i
c
addr
e
s
s
ar
e r
equi
r
ed equi
pped w
i
t
h ac
ous
t
i
c
pr
e
s
s
ur
e
s
ens
or
s
.
i
i
)
S
i
n
k
nodes
ar
e
depl
oy
e
d
onl
y
on
m
anhol
es
o
f
t
he
pi
pel
i
ne
s
o
i
t
i
s
di
f
f
i
c
ul
t
t
o
f
i
nd
t
he
ex
ac
t
l
eak
age pl
a
c
e.
S
ew
er
S
nor
t
[
13]
i
)
A
l
l
t
he
s
ens
or
s
dr
i
f
t
i
ns
i
de
t
he
s
ew
e
r
age pi
pel
i
nes
hav
e
s
pec
i
f
i
c
c
ov
er
age ar
ea.
i
i
)
T
he beac
ons
ar
e r
equi
r
ed t
o
as
s
i
gn nodes
addr
es
s
es
and i
nc
r
eas
e t
hei
r
r
es
pec
t
i
v
e
s
i
gnal
s
s
t
r
engt
h
.
iii)
I
t
w
or
k
s
onl
y
f
or
s
ew
er
age pi
p
e hav
i
ng f
l
ui
d f
l
ow
i
ng at
s
pec
i
f
i
c
s
peed but
not
s
ui
t
abl
e
f
or
UW
S
N.
T
r
i
opus
N
et
[
8]
i
)
I
t
needs
s
pe
c
i
al
nodes
depl
oy
m
ent
al
go
r
i
t
h
m
t
o r
el
eas
e
pool
o
f
r
o
bot
s
i
n
t
he
pi
pel
i
ne
.
i
i
)
I
t
i
s
not
s
ui
t
abl
e
f
or
l
ong r
ange
under
w
at
er
pi
pel
i
ne
m
oni
t
or
i
ng a
s
i
t
r
equi
r
es
s
pe
c
i
al
t
ool
s
and s
et
up
.
KAN
T
AR
O
[
9]
i
)
I
t
does
n'
t
r
equi
r
e node addr
e
s
s
as
i
t
c
ons
i
s
t
s
of
a f
u
l
l
y
aut
o
m
a
t
i
c
r
obot
hav
i
ng i
nt
el
l
i
gent
l
y
m
o
t
i
on
c
ont
r
ol
t
ool
i
n i
t
w
i
t
h a
s
c
an
ner
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c
a
m
er
a
t
hat
needs
t
o
m
ov
e i
ns
i
de
t
he p
i
pel
i
ne.
i
i
)
I
t
i
s
a
m
anual
w
ay
of
i
ns
pec
t
i
on
w
her
e
v
eh
i
c
l
e
m
ov
es
ov
er
pi
pe
and
i
t
c
an’
t
be
i
n
s
t
al
l
ed
i
n
UW
S
N.
S
CA
DA
[
1
4]
i
)
I
t
needs
s
pec
i
al
net
w
or
k
des
i
g
n and N
ode
-
I
D
s
w
her
e
al
l
c
l
i
ent
s
ar
e at
t
ac
hed t
o t
he
m
ai
n
t
er
m
i
nal
.
i
i
)
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hi
s
appr
oac
h i
nv
ol
v
es
m
or
e
m
anual
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oy
m
en
t
of
s
en
s
or
s
t
her
ef
or
e not
s
ui
t
abl
e f
or
UW
S
N.
S
W
AT
S
[
15]
I
t
r
equi
r
es
c
r
o
s
s
c
he
c
k
on
t
he
par
t
of
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he
nei
ghbour
i
ng
nodes
al
ong
t
he
t
r
aj
ec
t
or
y
of
t
he
f
l
ui
d
t
o v
al
i
dat
e
t
he nodes
.
I
t
i
nt
egr
at
e
s
S
C
A
D
A
and
as
s
um
e
s
t
he
s
t
a
t
i
c
a
ddr
es
s
i
ng
f
or
nodes
and
c
ont
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ol
uni
t
s
.
D
i
s
t
r
i
but
ed
t
opol
ogy
al
gor
i
t
h
m
[
5]
i
)
I
t
i
s
t
opol
ogy
di
s
c
ov
er
y
al
gor
i
t
hm
f
or
L
S
N
s
t
hat
r
equi
r
e
an
or
der
ed
l
i
s
t
o
f
t
he
nodes
addr
es
s
es
depl
oy
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he net
w
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hei
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at
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e geogr
aphi
c
a
l
p
os
i
t
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s
.
i
i
)
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t
w
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k
s
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y
f
or
s
a
m
e t
y
pes
o
f
s
en
s
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ot
c
apabl
e t
o handl
e het
er
ogeneous
s
ens
or
s
.
A
U
V
ba
s
ed
al
gor
i
t
h
m
[
1
0]
i
)
I
t
r
equi
r
es
aut
ono
m
ou
s
under
w
at
er
v
ehi
c
l
es
(
A
U
V
)
i
ns
i
de o
r
out
s
i
de of
t
he pi
pel
i
ne t
ha
t
c
oor
di
nat
e w
i
t
h ea
c
h ot
her
a
c
c
or
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o
t
he appl
i
c
at
i
on
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r
e
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ent
.
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i
)
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t
onl
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r
aj
e
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t
or
y
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he
A
U
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any
det
ai
l
s
abou
t
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pel
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ens
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depl
oy
m
ent
.
R
oad M
oni
t
or
i
ng
A
l
gor
i
t
h
m
[
16]
i
)
I
t
i
s
ba
s
ed on
t
he addr
es
s
es
an
d pl
ac
e
m
en
t
o
f
nodes
.
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t
i
s
al
s
o b
as
ed on
t
he w
ay
of
dat
a
t
r
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m
i
s
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i
on t
hat
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a
k
es
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hi
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ec
hn
i
que m
or
e
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f
ec
t
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e
f
f
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c
i
en
t
f
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r
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N
.
i
i
)
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t
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s
onl
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ea
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i
bl
e f
or
ho
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ogen
eous
s
en
s
or
s
s
o het
er
ogeneous
t
y
pes
of
nodes
c
an’
t
be
depl
oy
ed.
S
R
J
A
l
gor
i
t
h
m
[
17]
i
)
I
t
needs
nei
ghbour
di
s
c
ov
er
y
t
ab
l
es
and dy
na
m
i
c
s
i
gnal
s
t
r
engt
h
s
t
o by
pas
s
f
ai
l
ur
e
nodes
.
i
i
)
R
ando
m
depl
oy
m
ent
m
odel
and
c
o
m
p
l
ex
r
out
i
ng t
abl
es
boos
t
del
a
y
i
n c
o
m
m
uni
c
at
i
on.
C
hai
n bas
ed
al
gor
i
t
h
m
[
1
8]
i
)
I
t
r
equi
r
es
a
l
l
t
he nodes
c
onnec
t
ed by
w
i
r
e
or
v
i
r
t
ual
l
y
bonded
i
n
a c
hai
n.
i
i
)
A
l
l
nodes
depl
oy
ed
i
n
a
c
hai
n
and
t
hey
gene
r
at
e
c
om
m
uni
c
a
t
i
on
ov
er
head
t
o
s
el
ec
t
f
or
w
ar
de
r
node and
k
eep
r
e
c
or
d
of
al
l
t
he nei
ghbour
nodes
.
3.
N
e
tw
o
r
k
A
r
c
h
i
te
c
tu
r
e
a
n
d
C
o
n
tr
i
b
u
ti
o
n
s
N
et
w
or
k
O
per
at
i
o
n C
ent
r
es
(
N
O
C
s
)
ar
e i
ns
t
al
l
ed o
n gr
ound
at
t
h
e bot
h en
ds
of
pi
pel
i
ne
c
ol
l
ec
t
i
ng
dat
a
f
r
om
t
he
pi
p
el
i
ne
s
ens
or
s
an
d
c
our
i
er
n
odes
.
T
he
pi
p
el
i
ne
s
e
ns
or
s
ar
e
dep
l
o
y
ed
l
i
n
ear
l
y
on
u
pper
s
ur
f
ac
e
of
t
he
pi
p
el
i
ne
.
N
odes
ne
ar
t
he
N
O
C
s
hav
e
a
c
l
os
er
di
s
t
anc
e
an
d
t
he
di
s
t
an
c
e
i
nc
r
eas
es
as
t
h
e nod
es
go
f
ar
f
r
o
m
N
O
C
s
.
T
he
nodes
pos
i
t
i
o
ns
ar
e as
s
i
gne
d
d
y
n
am
i
c
al
l
y
b
y
l
i
ne
ar
equ
a
t
i
ons
d
es
i
g
ned s
e
par
at
el
y
f
or
eac
h t
y
p
e of
nod
es
ac
c
or
di
ng
t
o t
h
e
l
en
gt
h
of
pi
p
el
i
ne
a
nd
e
ac
h
s
ens
or
r
ange.
T
he
f
our
t
y
p
es
of
nodes
ar
e
depl
o
y
ed
i
n
t
hi
s
net
w
or
k
i
.
e.
B
as
i
c
S
e
ns
i
ng
N
od
e (
B
S
N
)
,
D
at
a
R
e
l
a
y
N
o
de (
D
R
N
)
,
D
at
a D
ef
i
n
i
t
i
on
N
o
de (
D
D
N
)
a
nd
C
our
i
er
N
o
de (
C
N
)
;
B
S
N
h
as
a m
i
ni
m
u
m
r
ange
w
hi
l
e
C
N
t
h
e m
ax
i
m
u
m
.
N
odes
a
r
e de
pl
o
y
e
d
i
n
s
uc
h a w
a
y
t
h
at
t
he
y
c
ou
l
d c
ov
er
t
he m
ax
i
m
u
m
pi
pel
i
ne l
eng
t
h
w
i
t
h l
es
s
ut
i
l
i
z
at
i
o
n of
nodes
.
Mos
t
of
t
he
or
di
nar
y
n
odes
ar
e
anc
hor
ed
at
al
l
ot
t
ed
p
os
i
t
i
on
of
t
he
pi
pe
l
i
n
e
s
ur
f
ac
e
ex
c
ept
C
N
t
hat
i
s
m
obi
l
e
and
i
s
of
t
en
i
nt
r
oduc
e
d
i
n
net
w
or
k
b
y
us
i
ng
h
y
dr
aul
i
c
t
oo
l
.
T
he
c
our
i
er
no
des
ar
e
hel
pf
ul
t
o
ut
i
l
i
z
e t
he
bet
t
er
net
w
or
k
r
es
our
c
es
,
i
nc
r
ea
s
e t
he
r
el
i
ab
i
l
i
t
y
a
nd
m
i
ni
m
i
z
e t
he
de
l
a
y
.
T
hes
e
c
our
i
er
n
odes
c
an
c
ol
l
ec
t
da
t
a
pac
k
et
s
f
r
o
m
t
h
e
m
i
ddl
e
nod
es
be
i
n
g
f
ar
f
r
om
t
he
N
O
C
s
.
A
f
t
er
c
ol
l
ec
t
i
n
g t
h
e da
t
a,
t
h
e
y
del
i
v
er
t
h
es
e p
ac
k
et
s
di
r
ec
t
l
y
t
o t
he N
O
C
s
.
A
l
t
hou
gh s
om
e i
ns
pi
r
i
n
g di
s
t
r
i
but
e
d
t
op
ol
o
g
y
n
od
es
depl
o
y
m
en
t
s
c
hem
es
l
i
k
e
[5
]
,
[
26
-
27]
ex
i
s
t
i
n
l
i
t
er
a
t
ur
e
b
ut
t
h
ei
r
i
m
pl
em
ent
at
i
o
n
i
s
t
h
oug
ht
t
o
b
e
c
um
ber
s
o
m
e
i
n
un
der
w
at
er
l
on
g
r
ange
p
i
pe
l
i
ne
m
oni
t
or
i
n
g.
I
n
t
hi
s
pap
er
,
w
e
pr
opos
e
a
nov
e
l
dep
l
o
y
m
ent
a
l
gor
i
t
h
m
f
or
t
he
l
ong
r
ange
u
nder
w
at
er
p
i
pe
l
i
n
e
m
oni
t
or
i
ng.
B
e
i
ng
s
c
a
l
ab
l
e
a
nd
ef
f
i
c
i
ent
,
i
t
m
ak
es
us
e
o
f
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
1
6
9
3
-
6
930
T
E
L
KO
M
NI
K
A
V
o
l.
14
,
N
o
.
3,
S
ept
em
ber
2016
:
11
83
–
1
191
1186
het
er
o
gen
eous
t
y
p
es
of
s
ens
or
s
w
i
t
h m
ul
t
i
-
s
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nk
ar
c
hi
t
ec
t
ur
e.
B
e
i
ng
d
es
i
gn
ed
on
m
ul
t
i
-
si
n
k
ar
c
hi
t
ec
t
ur
e
,
t
he
pr
opos
e
d al
gor
i
t
hm
i
s
goi
ng t
o be he
l
pf
ul
i
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nc
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eas
i
ng
t
he m
oni
t
or
i
ng
c
ov
er
ag
e,
pac
k
et
del
i
v
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y
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at
i
o
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nd
m
i
ni
m
i
z
i
ng
t
he
d
el
a
y
bet
w
ee
n
nod
es
and
s
i
nk
s
.
T
he
c
our
i
er
nodes
dep
l
o
y
e
d as
s
ur
f
ac
e s
i
nk
s
ar
e equ
i
pp
ed
w
i
t
h
r
a
di
o
an
d ac
ous
t
i
c
m
odem
s
;
t
he
y
us
e r
a
di
o
f
r
equenc
y
t
o
c
om
m
uni
c
at
e
m
ut
ual
l
y
and
w
i
t
h
t
h
e
N
O
C
w
hi
l
e
u
nd
er
w
a
t
er
pi
p
el
i
ne
s
ens
or
s
hav
e
onl
y
ac
o
us
t
i
c
m
odem
s
t
o
c
om
m
uni
c
at
e
w
i
t
h
ot
h
er
s
en
s
or
of
s
a
m
e
or
di
f
f
er
ent
c
at
egor
y
.
T
hes
e
het
er
o
gen
eous
s
e
ns
or
no
d
es
ar
e d
ep
l
o
y
ed
ac
c
or
di
n
g
t
o L
S
N
t
hi
n
m
odel
[6
]
b
ut
t
he
y
ar
e
pl
ac
ed
at
s
pec
i
f
i
c
l
oc
at
i
on
ac
c
or
di
ng
t
o
d
epl
o
y
m
e
nt
a
l
g
or
i
t
hm
.
T
hes
e
nod
es
ar
e
de
pl
o
y
e
d
i
n
h
or
i
z
ont
al
di
r
ec
t
i
on a
l
on
g
w
i
t
h pi
pe
l
i
ne l
e
ngt
h,
t
he
y
c
an
’
t
m
ov
e f
r
eel
y
w
i
t
h t
h
e
w
at
er
c
u
r
r
ent
s
but
t
he
c
our
i
er
n
od
es
ha
v
e
v
er
t
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c
a
l
m
ov
em
ent
w
i
t
h
a s
pec
i
a
l
h
ar
d
w
ar
e
[
28]
.
B
y
f
o
l
l
o
w
i
ng t
hes
e p
at
t
er
ns
,
al
l
n
odes
ar
e dep
l
o
y
e
d i
n
on
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i
n
e s
t
ar
t
i
n
g f
r
o
m
t
he one c
or
ner
of
pi
pel
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ne
and en
di
n
g at
anot
her
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he depl
o
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ent
s
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our
i
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s
t
and f
l
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i
bl
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i
n
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e t
o be i
ns
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l
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y
p
l
ac
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of
t
he
pi
pel
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n
e,
at
an
y
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pt
h
l
e
v
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l
of
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ean,
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s
w
e
l
l
as
at
t
h
e
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ur
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ac
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l
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el
.
D
ue
t
o
t
he
har
s
h un
der
w
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r
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ur
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s
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t
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s
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eas
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oni
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om
e ar
ea of
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n
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o
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s
um
e t
hat
an
y
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our
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ode
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ea
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ne,
i
t
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o
ul
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om
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k
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ea
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ur
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ac
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c
or
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o t
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r
onm
ent
c
on
di
t
i
o
ns
a
nd
und
er
w
at
er
pi
pe
l
i
ne r
equ
i
r
em
ent
s
,
t
he
c
ont
r
i
bu
t
i
ons
of
t
h
i
s
dep
l
o
y
m
ent
a
l
g
or
i
t
hm
ar
e a
s
f
ol
l
o
w
s
.
1.
S
cal
ab
l
e
d
ep
l
o
y
m
en
t
o
f
sen
so
r
s:
T
he
pr
opos
ed
al
g
or
i
t
hm
i
s
s
c
al
abl
e
i
n
per
f
or
m
anc
e;
i
t
d
ep
l
o
y
s
het
er
oge
neo
us
s
ens
or
s
ha
v
i
n
g no
an
y
r
es
t
r
i
c
t
i
on
of
net
w
or
k
s
i
z
e.
2.
D
e
s
i
g
n
i
n
g
o
f d
y
n
a
m
i
c
l
i
n
e
a
r
e
q
u
a
ti
o
n
s
:
E
ac
h t
y
p
e of
node ob
t
ai
ns
i
t
s
pos
i
t
i
on
d
y
n
am
i
c
al
l
y
b
y
us
i
ng
of
l
i
near
e
qua
t
i
o
ns
s
pec
i
f
i
e
d
t
o di
f
f
er
ent
i
at
e t
he t
y
p
es
o
f
s
ens
or
,
s
i
n
k
addr
es
s
and m
ai
nt
a
i
n d
i
s
t
anc
e.
T
her
e i
s
no n
eed of
an
y
s
t
at
i
c
or
m
anual
no
d
es
depl
o
y
m
e
nt
pr
oc
edur
e.
3.
M
a
x
i
m
i
z
i
n
g
o
f
m
o
n
i
to
r
i
n
g
c
o
v
e
r
a
g
e
:
I
t
pr
ov
i
des
ef
f
i
c
i
ent
m
oni
t
or
i
ng
c
ov
er
age
f
or
t
he
l
o
ng r
a
ng
e p
i
p
el
i
ne
b
y
us
i
ng
d
i
f
f
er
ent
t
y
p
es
of
s
en
s
or
s
,
r
anges
and
b
y
pas
s
i
n
g t
h
e
dam
aged
nodes
.
4.
R
o
b
u
s
tn
e
s
s
:
I
t
i
s
r
obus
t
as
i
t
c
an
b
e
eas
i
l
y
ad
o
pt
ed
i
n
a
n
y
net
w
or
k
s
i
z
e
;
i
t
ac
c
o
m
m
odat
es
ne
w
n
od
es
,
dam
aged no
des
or
r
ep
l
ac
i
ng t
h
e ne
t
w
or
k
nodes
w
i
t
ho
ut
m
a
k
i
ng an
y
s
er
i
ous
ef
f
ec
t
on
t
h
e r
es
t
of
net
w
or
k
.
4.
P
r
o
p
o
s
e
d
N
o
d
e
s
D
e
p
l
o
y
m
e
n
t A
l
g
o
r
i
th
m
A
f
t
er
a
br
oad
l
i
t
er
a
t
ur
e
r
ev
i
e
w
,
i
t
i
s
r
e
v
e
al
ed
t
hat
U
W
S
N
nodes
d
epl
o
y
m
e
nt
i
s
a
c
hal
l
eng
i
n
g t
as
k
i
nc
l
u
di
n
g t
he l
oc
al
i
z
at
i
on
of
under
w
at
er
s
ens
or
no
des
[
4]
.
F
or
t
h
i
s
pur
pos
e,
t
he
al
g
or
i
t
hm
c
o
m
pl
et
es
i
t
s
t
as
k
i
n t
hr
ee
phas
es
.
I
n
t
he
fi
r
s
t p
h
a
s
e
,
i
t
s
et
s
t
he
r
an
ges
of
het
er
o
gen
eous
t
y
p
es
of
s
e
ns
or
s
and
c
al
c
u
l
at
es
t
h
e r
e
qui
r
e
d t
ot
a
l
n
um
ber
of
nod
es
ac
c
or
di
n
g t
o
t
ot
a
l
l
eng
t
h
of
t
he
pi
p
el
i
n
e.
I
n
t
he
seco
n
d
p
h
ase,
i
t
s
et
s
t
he
f
r
equenc
y
a
nd
t
y
p
e
s
of
nei
g
hbo
ur
nodes
.
I
n t
he
th
i
r
d
p
h
a
s
e
,
al
l
n
odes
ar
e as
s
i
g
ned
s
pec
i
f
i
c
l
oc
at
i
on
on t
he
pi
pel
i
ne
s
ur
f
ac
e
ac
c
or
di
ng
t
o t
he f
unc
t
i
on
of
t
he
i
r
l
i
ne
ar
equ
at
i
ons
i
n d
e
pl
o
y
m
ent
al
gor
i
t
hm
.
4.
1.
T
y
p
es o
f
S
en
so
r
s an
d
H
i
er
ar
ch
i
cal
N
et
w
o
r
k M
o
d
el
W
e
hav
e
pr
op
os
ed
a
h
i
er
a
r
c
hi
c
al
net
w
or
k
m
odel
of
L
S
N
f
or
t
h
e
d
ep
l
o
y
m
ent
of
pi
pe
l
i
ne
nodes
.
T
he
r
el
i
ab
i
l
i
t
y
ana
l
y
s
i
s
of
di
f
f
er
ent
k
i
nds
of
LS
N
net
w
or
k
ar
c
hi
t
ec
t
ur
e
[
2
9]
pr
ec
eded
t
he
des
i
g
ni
n
g
of
t
hi
s
m
odel
.
LS
N
i
s
c
ons
i
der
ed
an
i
d
eal
n
et
w
or
k
f
or
t
he
pi
p
el
i
ne
m
oni
t
or
i
n
g
app
l
i
c
at
i
on
h
av
i
n
g
s
pec
i
f
i
c
t
y
p
es
of
nodes
de
pl
o
y
m
ent
t
opol
ogi
es
.
I
n
t
hi
s
r
egar
d
,
di
f
f
er
ent
t
y
pes
of
LS
N
nodes
d
epl
o
y
m
e
nt
m
odel
s
ex
i
s
t
l
i
k
e t
hi
n,
t
h
i
c
k
and v
er
y
t
h
i
c
k
t
hat
ar
e
m
os
t
l
y
us
e
d i
n f
l
at
net
w
or
k
m
odel
s
and
a
ppl
i
c
at
i
o
ns
[
6]
.
T
he
hi
er
ar
c
hi
c
al
net
w
or
k
m
odel
ad
v
ant
age
s
ov
er
t
he f
l
at
net
w
or
k
m
odel
s
ar
e m
ul
t
i
p
l
e i
.
e.
t
he
hi
er
ar
c
hi
c
al
net
w
o
r
k
has
t
he ab
i
l
i
t
y
t
o d
ev
el
op
m
or
e r
el
i
a
bl
e
and r
o
bus
t
m
odel
[5
-
6]
.
I
t
p
r
ov
i
des
h
el
p
t
o
di
s
t
r
i
but
e
t
h
e net
w
or
k
t
opol
og
y
,
d
i
v
i
d
e
and c
o
nt
r
ol
t
he
t
r
af
f
i
c
l
oad,
a
nd
ov
er
c
om
e
t
he
net
w
or
k
f
ai
l
ur
es
bas
ed o
n d
i
f
f
er
ent
t
y
p
es
of
a
t
t
ac
k
s
,
nodes
f
ai
l
ur
es
,
a
nd b
at
t
er
y
ex
h
a
us
t
i
on
.
T
hes
e k
i
nds
of
net
w
or
k
al
s
o s
up
por
t
r
o
ut
i
ng
pr
ot
oc
o
l
s
t
o
c
o
m
m
uni
c
at
e
q
ui
c
k
l
y
,
r
e
du
c
e
l
at
enc
y
,
as
s
i
gn
aut
ono
m
ous
r
egi
ons
,
and
c
ont
r
o
l
net
w
or
k
f
ai
l
ur
es
ef
f
i
c
i
ent
l
y
.
I
n
t
hi
s
m
odel
,
t
h
e f
ol
l
o
w
i
n
g f
our
t
y
pes
of
no
des
ar
e d
i
s
c
us
s
ed.
A
l
l
of
t
h
es
e no
des
ar
e
dep
l
o
y
ed
l
i
ne
ar
l
y
on
t
h
e
p
i
pel
i
ne
s
ur
f
ac
e.
F
i
g
ur
e
1
pr
es
ent
s
he
t
er
og
ene
ous
t
y
p
e
s
of
t
he
no
des
hav
i
n
g u
ni
q
ue f
unc
t
i
ons
t
o ac
c
om
pl
i
s
h s
uc
h as
ba
s
i
c
s
ens
i
ng
an
d d
at
a c
o
l
l
ec
t
i
on
,
pac
k
et
f
or
w
ar
di
ng
and
dat
a d
i
s
s
em
i
nat
i
on t
o t
h
e s
i
nk
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
K
A
I
S
S
N
:
1
693
-
6
930
S
c
al
a
bl
e
H
e
t
er
og
ene
ous
N
odes
D
e
pl
oy
men
t
A
l
g
or
i
t
h
m f
or
…
(
Muh
amm
ad Z
ahi
d
A
bb
as
)
1187
B
asi
c
S
en
s
i
n
g
N
o
d
es (
B
S
N
s
)
:
T
hes
e ar
e t
he m
os
t
c
o
m
m
on nodes
i
n
o
ur
ne
t
w
or
k
dep
l
o
y
ed
on t
he p
i
p
el
i
ne
.
T
hei
r
m
ai
n t
as
k
i
s
t
o s
ens
e t
he
pi
pel
i
n
es
s
t
at
us
l
i
k
e an
y
l
e
ak
age,
c
or
r
os
i
on,
e
t
c
.
an
d
f
or
w
ar
d
t
hat
dat
a
t
o
t
he
c
l
os
es
t
d
at
a r
e
l
a
y
n
ode,
da
t
a
d
i
s
s
e
m
i
nat
i
on
nod
e,
and c
o
ur
i
er
n
ode
or
d
i
r
ec
t
l
y
t
o s
i
nk
.
D
at
a R
el
ay
N
o
d
es
(
DRN
s
)
:
T
hes
e n
odes
f
unc
t
i
on
a
s
i
nt
er
m
edi
at
e n
odes
t
hat
gat
h
er
dat
a f
r
om
B
S
N
s
and f
or
w
ar
d i
t
t
o t
h
e c
l
os
es
t
D
D
N
,
C
N
or
N
O
C
.
T
hei
r
m
ai
n r
ol
e i
s
i
n r
out
i
ng t
h
e
dat
a t
o
w
ar
d t
he N
O
C
at
t
h
e s
hor
t
es
t
pat
h an
d i
n
l
es
s
del
a
y
.
T
he d
i
s
t
anc
e b
et
w
e
e
n t
hes
e n
odes
i
s
det
er
m
i
ne
d b
y
c
om
par
i
ng t
he
ne
i
gh
bour
nod
es
ad
dr
es
s
es
.
D
at
a D
i
s
sem
i
n
at
i
o
n
N
o
d
es (
D
D
N
s
)
:
T
hes
e no
des
per
f
or
m
t
he f
unc
t
i
on of
de
l
i
v
er
i
n
g
t
he c
ol
l
ec
t
e
d dat
a t
o t
h
e N
O
C
.
T
he t
ec
hnol
o
g
y
us
ed t
o t
r
ans
f
er
t
he dat
a f
r
om
t
he
s
e nodes
t
o t
h
e
N
O
C
i
s
v
ar
i
e
d
s
uc
h
as
us
age
of
und
er
w
at
er
v
eh
i
c
l
es
.
T
hi
s
i
m
pl
i
es
t
hat
eac
h
of
t
h
e
D
D
N
nod
es
hav
e a
hi
gher
c
om
m
uni
c
at
i
on c
ap
abi
l
i
t
y
.
Co
u
r
i
e
r
No
d
e
s
(
CNs
)
:
T
hes
e ar
e t
he
hi
g
her
f
r
eque
nc
y
no
des
i
n t
he n
et
w
or
k
.
T
hei
r
obj
ec
t
i
v
e
i
s
t
o
c
ol
l
ec
t
dat
a
f
r
om
nodes
bei
n
g
f
ar
f
r
o
m
t
he
N
O
C
b
y
es
t
ab
l
i
s
h
i
n
g
s
ec
ondar
y
p
at
h.
A
f
t
er
dat
a
c
ol
l
ec
t
i
on,
t
he
y
d
i
r
ec
t
l
y
f
or
w
ar
d t
h
i
s
da
t
a t
o t
he N
O
C
b
y
us
i
n
g R
F
c
om
m
uni
c
at
i
o
n.
F
i
gur
e 1.
H
et
er
o
gen
eous
t
y
pes
of
s
ens
or
s
F
i
gur
e 2
.
A
h
i
er
ar
c
hi
c
a
l
r
e
p
r
es
ent
at
i
on
of
het
er
o
gen
eous
t
y
p
es
of
no
des
i
n
pr
op
os
ed
net
w
or
k
m
odel
F
i
gur
e 2 pr
es
e
nt
s
t
he hi
er
ar
c
hi
c
al
r
el
at
i
ons
h
i
p bet
w
e
en t
he v
ar
i
o
us
t
y
pes
of
no
des
i
n
t
he pr
o
pos
ed
s
e
ns
or
net
w
or
k
.
B
S
N
s
c
ons
i
s
t
of
s
ens
i
ng
t
oo
l
s
l
i
k
e
pr
es
s
ur
e
s
ens
i
ng
i
n
or
d
er
t
o
per
f
or
m
t
he bas
i
c
s
ens
i
ng
pr
oc
es
s
;
m
ul
t
i
p
l
e
B
S
N
s
f
or
w
ar
d t
he
i
r
dat
a t
o t
he n
ear
es
t
D
R
N
an
d
s
i
m
i
l
ar
l
y
,
D
R
N
s
t
r
ans
f
er
t
h
ei
r
d
at
a
t
o
t
he
near
es
t
D
D
N
nod
;
f
i
na
l
l
y
,
al
l
D
D
N
s
t
r
a
ns
m
i
t
t
he
i
r
da
t
a
t
o t
he N
O
C
di
r
ec
t
l
y
or
v
i
a C
N
.
B
S
N
s
,
D
R
N
s
,
a
nd
D
D
N
s
ar
e equ
i
p
ped
w
i
t
h
bat
t
er
i
es
an
d
ac
ous
t
i
c
an
t
en
nas
f
or
under
w
at
er
c
om
m
uni
c
at
i
o
n.
B
S
N
s
,
D
R
N
s
,
an
d
D
D
N
s
ar
e l
o
gi
c
a
l
l
y
c
hai
n
ed
w
i
t
h
eac
h
ot
h
er
and
us
ed
f
or
des
i
gni
ng
of
i
n
t
egr
at
e
d ac
ous
t
i
c
s
ens
or
n
et
w
or
k
[
30]
. In
t
hi
s
c
as
e,
t
he
nod
es
ar
e e
qui
ppe
d
w
i
t
h r
ec
har
ge
ab
l
e
bat
t
er
i
es
t
hat
c
a
n be r
ec
har
ge
d f
r
o
m
a
w
i
r
e.
I
n a
dd
i
t
i
on,
t
he ac
ous
t
i
c
c
o
m
m
uni
c
at
i
on
i
s
us
ed t
o s
end t
h
e dat
a t
o t
h
e nex
t
hop n
ei
g
hbo
ur
ei
t
h
er
t
o
w
ar
ds
t
he s
i
nk
no
de or
t
h
e C
N
.
I
n
t
h
i
s
s
c
e
nar
i
o,
N
O
C
c
an
be
i
ns
t
a
l
l
ed o
n t
he
bo
at
s
t
andi
ng i
n w
at
er
or
pl
ac
ed
on gr
ound n
ear
t
he c
oas
t
a
l
ar
ea.
A
l
l
s
i
n
k
s
and c
our
i
er
node ar
e a
l
s
o
equ
i
pp
ed
w
i
t
h
R
F
an
t
en
nas
t
o c
oor
d
i
na
t
e
w
i
t
h
N
O
C
at
hi
g
h s
pee
d.
4.
2.
P
r
o
p
o
s
e
d
N
e
tw
o
r
k
T
o
p
o
l
o
g
y
T
he pr
opos
ed
net
w
or
k
t
opo
l
og
y
i
n t
hi
s
r
es
ear
c
h
i
s
s
ho
w
n
i
n F
i
g
ur
e 3
.
F
i
gur
e 3.
N
et
w
or
k
t
opo
l
og
y
di
a
gr
am
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
1
6
9
3
-
6
930
T
E
L
KO
M
NI
K
A
V
o
l.
14
,
N
o
.
3,
S
ept
em
ber
2016
:
11
83
–
1
191
1188
4.
3.
N
o
d
e
s
D
e
p
l
o
y
m
e
n
t
A
l
g
o
r
i
th
m
I
n
p
u
t:
1.
H
et
er
og
en
eous
t
y
p
es
of
pi
p
el
i
nes
S
ens
or
s
w
i
t
h d
i
f
f
er
ent
c
om
m
uni
c
at
i
on r
an
ges
2.
S
et
f
r
equ
enc
y
and
t
y
p
es
of
nei
ghb
or
no
des
3.
T
ot
al
P
i
pe
l
i
ne
l
en
gt
h
P
r
o
c
ess:
A
l
g
o
r
i
th
m
S
te
p
s
D
e
s
c
r
i
p
ti
o
n
s
1.
If
i
=
1 t
hen
L/
N
*
1
=
2
50
M
/
/
i
=
1
1
st
BSN
node
nu
mber
2.
{
i
=
2 t
he
n L/
N
*
2 =
500
M
/
/
i
=
2 2
n
d
BSN
node
nu
mber
3.
i
=
k
t
h
en
L/
N
*
k
=
(
L
N
∗
i
)
=
1
}
/
/ i
-
k
=
t
ot
al
B
S
N
nodes
dep
l
oy
m
ent
f
or
mu
l
a
4.
El
s
e
If
I
<
1
&
j
=
1 t
hen
L/
N
*
10
*
1
=
250
0
M
/
/
j
=
1
1
st
D
R
N
n
ode
numb
er
5.
{
i
<
1
&
j
=
2
t
hen
L/
N
*
10*
2
=
500
0
M
//
j
=
2
2
n
d
DRN
node
nu
mber
6.
i
<
1
&
j
=
r
t
h
en
L
/
N
*
10*
r
=
(
L
N
∗
1
0
∗
j
)
=
1
}
//
j
-
r
=
T
ot
al
D
R
N
nodes
dep
l
oy
m
ent
s
er
i
es
f
o
r
mul
a
7.
El
s
e
If
I
<
1
&
j
<
1
&
p
=
1
t
hen
L/
N
*
5
0*
1
=
250
0
M
/
/
p=
1
1
st
DDN
node
nu
mber
8.
{
i
<1
&
j
=
2
&
p=
2 t
hen
L/
N
*
5
0*
2
=
50
00
M
9.
i
<
1
&
j
=
r
&
p
=
t
t
hen
L/
N
*
50
*
t
=
(
L
N
∗
5
0
∗
p
)
=
1
}
//p
-
t
= T
o
t
a
l
D
D
N
no
des
d
epl
oy
me
nt
f
or
mul
a
10.
El
s
e
If
I
<
1
&
j
<
1
&
p<
1
&
m
=
1
t
h
en
L/
N
*
22
5*
1
=
1
2500
M
/
/
m
=
1
1
st
C
N
no
de n
um
ber
11.
{
i
<
1
&
j
<
1 &
p
<
1
&
m
=
2 t
h
en L/
N
*
2
25*
2
=
25
00
00
M
12.
i
<
1
&
j
<
1
&
p
<
1 &
m
=
q
t
h
en L/
N
*
22
5*
q =
(
L
N
∗
2
2
5
∗
m
)
=
1
}
//m
-
q =
T
ot
al
C
N
no
des
de
pl
oy
men
t
f
or
m
ul
a
13.
E
n
d
I
F
14.
T
o
ta
l
c
o
v
e
r
a
g
e
fo
r
m
u
l
a
/
e
q
u
a
ti
o
n
=
s
te
p
3
+
s
te
p
6
+
s
te
p
9
+
s
te
p
1
2
//
add
al
l
f
or
m
ul
as
15.
If
m
or
e
B
S
N
no
des
adde
d i
n L
S
N
N
et
w
or
k
16.
R
e
peat
s
t
ep
1
-
3
17.
E
ls
e
If
mor
e D
R
N
n
o
des
ad
ded
i
n
LS
N
N
et
w
or
k
18.
R
e
peat
s
t
ep
4
-
6
19.
E
ls
e
If
m
or
e D
D
N
no
des
ad
ded
i
n
LS
N
N
et
w
or
k
20.
R
e
peat
s
t
ep
7
-
9
21.
E
ls
e
If
m
or
e C
N
no
de
s
adde
d i
n L
S
N
N
et
w
or
k
22.
R
e
peat
s
t
ep
10
-
12
23.
U
p
d
a
te
to
ta
l
c
o
v
e
r
a
g
e
fo
r
m
u
l
a
o
f
c
o
m
p
l
e
te
n
e
tw
o
r
k
b
y
r
e
p
e
a
ti
n
g
s
te
p
14
24.
El
s
e
a
l
l
het
er
oge
neo
us
nod
es
ar
e d
ep
l
oy
ed
at
pr
o
per
pl
ac
e of
t
h
e p
i
pe
l
i
ne
25.
E
n
d
I
F
“
S
t
op
n
odes
de
pl
oy
m
ent
pr
oc
es
s
”
O
u
tp
u
t:
T
ot
al
pi
p
el
i
ne l
en
gt
h i
s
c
ov
er
e
d and al
l
het
er
oge
neo
us
t
y
pes
of
node
s
hav
e
as
s
i
gne
d s
pec
i
f
i
c
l
oc
at
i
on
o
n t
he
pi
pe
l
i
n
e
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
K
A
I
S
S
N
:
1
693
-
6
930
S
c
al
a
bl
e
H
e
t
er
og
ene
ous
N
odes
D
e
pl
oy
men
t
A
l
g
or
i
t
h
m f
or
…
(
Muh
amm
ad Z
ahi
d
A
bb
as
)
1189
5.
P
e
r
f
o
r
m
an
c
e M
et
r
i
cs
W
e
us
ed
m
oni
t
or
i
ng c
o
v
er
a
ge,
t
y
pes
of
s
ens
or
s
an
d r
a
nges
of
s
ens
or
s
as
t
he m
et
r
i
c
s
i
n
or
der
t
o
c
hec
k
t
he
per
f
or
m
anc
e
of
t
he
pr
op
os
ed
d
ep
l
o
y
m
ent
al
g
or
i
t
hm
.
Moni
t
or
i
ng
c
ov
er
age
is
bas
ed o
n nod
es
dep
l
o
y
m
e
nt
equ
at
i
ons
di
s
c
us
s
ed
i
n a
l
gor
i
t
hm
and l
en
gt
hs
of
di
f
f
er
ent
p
i
pe
l
i
nes
.
T
y
pe
of
s
ens
or
i
s
def
i
n
ed
as
het
er
oge
ne
i
t
y
na
t
ur
e
of
a
s
ens
or
.
R
a
nge
of
s
ens
o
r
i
s
def
i
n
ed
as
t
he br
o
adc
as
t
d
om
ai
n of
t
he eac
h t
y
p
e of
s
ens
or
.
T
opol
o
g
y
di
s
t
r
i
but
i
on
per
c
ent
ag
e i
s
c
al
c
u
l
at
ed
b
y
di
v
i
di
ng
t
he
t
ot
al
pi
pe
l
i
n
e l
engt
h
and
r
ang
es
of
d
i
f
f
er
ent
t
y
p
es
of
s
ens
or
s
es
p
ec
i
al
l
y
i
n t
he
pr
es
enc
e of
c
our
i
er
no
de.
5.
1.
R
esu
l
t
s
an
d
D
i
s
cu
ssi
o
n
s
N
o
d
e
d
e
p
l
o
y
m
e
n
t a
n
d
c
o
v
e
r
a
g
e
:
W
e us
ed di
f
f
er
ent
n
um
ber
of
nodes
and
p
i
pe
l
i
nes
l
en
gt
hs
i
n
or
der
t
o t
es
t
o
ur
al
gor
i
t
hm
;
F
i
gur
e 4 ex
p
l
ai
ns
t
he h
et
er
o
gen
eous
t
y
p
es
of
nod
es
dep
l
o
y
m
ent
f
r
equenc
i
es
i
n di
f
f
er
ent
l
engt
hs
of
t
he pi
pe
l
i
n
es
.
F
i
gur
e 5 s
ho
w
s
t
h
at
t
ot
al
n
um
ber
of
het
er
o
gen
eous
nod
e
s
ar
e
v
ar
i
ed
ac
c
or
di
ng t
o t
hei
r
app
l
i
c
at
i
on
r
eq
ui
r
em
ent
w
h
i
l
e t
ot
al
num
ber
of
hom
ogeneo
us
no
des
ar
e
al
w
a
y
s
d
ep
l
o
y
ed
at
f
i
x
ed
r
at
i
o
l
i
k
e
i
n
A
l
m
a
z
y
a
d
m
odel
[
4]
.
T
he
dr
a
w
bac
k
of
hom
ogeneou
s
nodes
dep
l
o
y
m
ent
i
s
t
h
a
t
i
t
i
s
ex
p
ens
i
v
e
ut
i
l
i
z
i
ng
m
or
e r
es
our
c
e
s
and
f
ac
i
ng
hi
gher
l
a
t
enc
y
due
t
o
us
age
of
s
a
m
e
r
ange
s
ens
or
s
.
T
he
pr
opo
s
ed
al
gor
i
t
h
m
di
s
t
r
i
b
ut
es
t
he
net
w
or
k
t
opol
o
g
y
i
n
t
o s
e
gm
ent
s
ac
c
or
di
n
g t
o
h
i
er
ar
c
hi
c
a
l
net
w
or
k
m
odel
and
r
anges
of
t
he
s
ens
or
s
.
F
i
gur
e
6
hi
ghl
i
g
ht
s
t
he
c
o
m
par
i
s
on
of
pr
opos
ed
al
gor
i
t
hm
nodes
dep
l
o
y
m
ent
f
r
equ
enc
y
s
ho
w
i
ng
l
o
w
er
f
r
equ
enc
y
i
n
o
n
e
s
egm
ent
t
h
an
t
he
R
O
ut
i
ng
pr
ot
oc
o
l
f
or
Li
n
ear
S
t
r
uc
t
ur
es
(
R
O
LS
)
[
3
1]
.
T
he
pr
opos
e
d
a
l
gor
i
t
hm
ut
i
l
i
z
ed
het
er
oge
neo
us
t
y
p
es
of
s
ens
or
s
hav
i
n
g di
f
f
er
ent
br
oadc
as
t
r
anges
s
ho
w
n i
n F
i
gur
e 7.
F
or
ex
a
m
pl
e,
t
he t
ot
a
l
pi
p
e
l
i
ne l
e
ngt
h
i
s
c
ons
i
der
e
d
as
100
0M
and
eac
h
B
S
N
no
de
c
o
v
er
s
1
0
0M
l
en
gt
h,
eac
h
D
R
N
c
o
v
e
r
s
250M,
eac
h
D
D
N
c
ov
er
s
400
M
w
hi
l
e
C
N
c
ov
er
s
hal
f
l
engt
h of
t
he
pi
p
el
i
n
e s
ho
w
i
ng
bet
t
er
m
oni
t
or
i
n
g
c
ov
er
ag
e.
N
e
tw
o
r
k
T
o
p
o
l
o
g
y
D
i
s
t
r
i
b
u
ti
o
n
:
I
m
ad
pr
opos
ed
a
d
i
s
t
r
i
bu
t
ed
t
op
ol
o
g
y
nodes
dep
l
o
y
m
ent
m
odel
[
5]
f
or
p
i
pe
l
i
nes
m
oni
t
or
i
n
g;
i
t
r
e
qu
i
r
es
t
o
m
ai
nt
a
i
n
a
nd
u
pdat
e
t
he t
w
o
l
i
s
t
s
r
egul
ar
l
y
c
aus
i
ng
i
nc
r
e
as
e i
n t
h
e
w
or
k
l
oad
an
d c
om
put
at
i
o
na
l
o
v
er
h
ead
o
n s
ens
or
s
.
T
hi
s
k
i
nd of
di
s
t
r
i
b
ut
e
d t
opo
l
og
y
di
s
c
o
v
er
y
does
not
l
ook
f
eas
i
bl
e
f
or
m
oni
t
or
i
ng
of
l
ong
r
an
ge
und
er
w
at
er
pi
p
el
i
ne.
T
he
pr
opos
e
d
a
l
g
or
i
t
hm
c
ons
i
der
i
ng
t
h
i
s
i
s
s
u
e
di
s
t
r
i
but
ed
t
he
n
et
w
or
k
i
n
t
o
hi
er
ar
c
hi
c
a
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gur
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odes
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f
r
equenc
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n
di
f
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p
el
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i
gur
e 5
.
H
et
er
o
gen
eous
v
s
H
om
ogeneous
nodes
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l
o
y
m
ent
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
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6
9
3
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6
930
T
E
L
KO
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NI
K
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14
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3,
S
ept
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2016
:
11
83
–
1
191
1190
F
i
gur
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N
odes
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d br
o
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ange
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d t
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6
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s
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W
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op
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abl
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es
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l
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m
ent
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gor
i
t
hm
bas
ed on m
at
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m
at
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c
al
equa
t
i
o
ns
an
d h
et
er
o
gen
e
ous
t
y
p
es
of
s
ens
or
s
.
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v
e
l
t
y
of
t
hi
s
dep
l
o
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m
ent
i
s
i
t
s
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f
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c
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ag
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f
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ent
l
e
ngt
hs
of
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he p
i
p
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nes
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t
ha
s
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nt
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d d
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s
t
r
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bu
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op
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g
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m
odel
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n
w
hi
c
h t
o
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e
ngt
h
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s
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v
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d
ed i
nt
o s
egm
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s
.
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hi
s
appr
oac
h i
s
r
obus
t
enou
gh f
or
t
he
add
i
t
i
on of
ne
w
nod
es
;
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i
des
,
i
t
i
s
s
c
al
ab
l
e
as
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el
l
f
or
an
y
s
i
z
e
of
net
w
or
k
i
n
w
h
i
c
h ne
w
n
odes
get
t
he
i
r
r
el
at
i
v
e p
os
i
t
i
ons
.
A
n i
m
por
t
ant
as
p
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t
of
t
hi
s
al
g
or
i
t
hm
i
s
t
hat
i
t
i
s
d
y
nam
i
c
i
n nat
ur
e.
I
t
dev
el
ops
m
at
he
m
at
i
c
al
equ
a
t
i
o
ns
f
or
het
er
ogene
ous
t
y
pes
of
nodes
depl
o
y
m
ent
a
nd
c
al
c
ul
at
es
t
hei
r
p
os
i
t
i
on r
e
l
at
i
v
e t
o t
he
t
ot
al
p
i
p
el
i
ne
l
en
gt
h.
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os
t
i
m
por
t
ant
l
y
,
i
t
he
l
ps
t
o m
i
ni
m
i
z
e t
h
e i
s
s
ue
of
del
a
y
i
n f
i
n
di
n
g a d
am
a
ge or
l
e
ak
age pos
i
t
i
o
n of
under
w
at
er
p
i
pe
l
i
ne.
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hi
s
al
g
or
i
t
hm
gi
v
es
s
uppor
t
i
n
det
ec
t
i
n
g t
he
d
ef
ec
t
ed pos
i
t
i
on
of
pi
p
el
i
n
e an
d as
w
el
l
as
pr
o
v
es
hel
pf
ul
i
n t
he
add
i
t
i
on or
r
epl
ac
em
ent
of
nodes
.
F
ur
t
her
,
t
he pr
o
pos
ed de
pl
o
y
m
en
t
m
odel
m
i
ni
m
i
z
es
t
he
c
o
m
put
at
i
ona
l
o
v
er
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ads
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us
ual
l
y
u
nder
w
at
er
ac
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us
t
i
c
c
om
m
uni
c
at
i
o
n s
u
pp
or
t
s
ex
t
r
e
m
el
y
l
o
w
dat
a
r
at
es
.
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ur
t
her
m
or
e,
t
hi
s
al
gor
i
t
hm
i
s
f
l
ex
i
bl
e en
oug
h t
o
be
us
ed f
or
t
he
l
on
g t
er
m
pi
p
el
i
ne
m
oni
t
or
i
ng
app
l
i
c
a
t
i
ons
.
Mor
e
ov
er
,
i
t
s
u
ppor
t
s
t
he c
o
v
er
a
ge
of
l
o
ng
r
ang
e
pi
p
el
i
nes
w
i
t
h
l
es
s
num
ber
o
f
nodes
hav
i
ng no an
y
l
i
m
i
t
at
i
on
of
net
w
or
k
s
i
z
e.
I
n f
ut
ur
e,
w
e pl
an t
o i
nt
egr
at
e
t
hi
s
d
y
n
am
i
c
depl
o
y
m
e
nt
a
l
gor
i
t
hm
w
i
t
h d
y
n
am
i
c
addr
es
s
i
ng
bas
ed
r
out
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n
g pr
o
t
o
c
ol
s
i
n
or
d
er
t
o
i
n
v
es
t
i
gat
e
i
t
s
r
e
l
at
i
v
e p
er
f
or
m
anc
e.
R
ef
er
en
ces
[1
]
M
ur
ad
M
,
et
al
.
A
S
ur
v
e
y
on
C
ur
r
ent
U
n
der
w
at
e
r
A
c
o
us
t
i
c
S
e
ns
or
N
e
t
w
or
k
A
ppl
i
c
at
i
on
s
.
201
5
.
[2
]
Va
rs
h
n
e
y
S,
C
Ku
m
a
r,
A
S
w
ar
oop.
Li
n
ear
s
en
s
or
net
w
or
k
s
:
A
ppl
i
c
at
i
on
s
,
i
s
s
ue
s
a
nd
m
aj
or
r
es
ear
c
h
t
r
end
s
.
I
n
C
om
put
i
ng,
C
om
m
uni
c
at
i
o
n
&
A
ut
o
m
at
i
on
(
I
C
C
C
A
)
,
2015
I
nt
er
nat
i
on
al
C
o
nf
er
enc
e
o
n
.
2015
.
[3
]
O
w
oj
ai
y
e
G
,
Y
S
un.
F
oc
a
l
de
s
i
gn
i
s
s
ue
s
af
f
e
c
t
i
n
g
t
he
de
pl
oy
m
ent
of
w
i
r
el
e
s
s
s
ens
or
ne
t
w
or
k
s
f
or
pi
pe
l
i
ne
m
o
ni
t
or
i
ng
.
A
d H
o
c
N
et
w
or
k
s
.
20
13;
11
(
3)
:
123
7
-
12
53.
[4
]
A
l
m
az
y
ad A
S
, e
t
a
l
.
A
P
r
opo
s
ed S
c
al
a
bl
e D
es
i
gn a
nd S
i
m
u
l
at
i
on
of
W
i
r
e
l
es
s
S
e
ns
or
N
et
w
or
k
-
B
as
e
d
Long
-
D
is
t
an
c
e
W
at
e
r
P
i
p
el
i
n
e
Leak
age M
oni
t
or
i
ng S
y
s
t
em
.
S
ens
or
s
.
2
014;
14
(
2)
:
35
57
-
35
77
.
[5
]
J
aw
har
I
,
N
M
oham
ed,
L
Z
hang.
A
d
i
s
t
r
i
but
ed
t
op
ol
o
gy
di
s
c
ov
er
y
al
gor
i
t
hm
f
or
l
i
n
e
ar
s
en
s
or
net
w
or
k
s
. I
n
C
om
m
u
ni
c
at
i
o
ns
i
n C
hi
na
(
I
C
C
C
)
,
20
12 1
s
t
I
E
E
E
I
nt
er
n
at
i
o
nal
C
onf
er
enc
e on
.
2012
.
[6
]
J
aw
har
I
,
N
M
oham
ed,
D
P
Ag
ra
w
a
l
.
Li
n
ear
w
i
r
el
e
s
s
s
ens
or
net
w
or
k
s
:
C
l
as
s
i
f
i
c
at
i
o
n a
nd
a
ppl
i
c
at
i
on
s
.
J
our
n
al
o
f
N
et
w
or
k
an
d C
om
p
ut
er
A
pp
l
i
c
at
i
ons
.
20
11;
34
(
5)
:
1671
-
1
682.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KO
M
NI
K
A
I
S
S
N
:
1
693
-
6
930
S
c
al
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e
H
e
t
er
og
ene
ous
N
odes
D
e
pl
oy
men
t
A
l
g
or
i
t
h
m f
or
…
(
Muh
amm
ad Z
ahi
d
A
bb
as
)
1191
[7
]
K
i
m
JH
,
e
t a
l
.
SPAM
M
S:
a
s
e
n
s
o
r
-
b
as
e
d p
i
pe
l
i
ne
au
t
onom
o
us
m
on
i
t
or
i
ng a
nd m
ai
nt
en
an
c
e
s
yst
e
m
.
i
n
C
om
m
uni
c
at
i
on S
y
s
t
em
s
an
d N
et
w
or
k
s
(
C
O
M
S
N
E
T
S
)
,
2010 S
ec
o
nd I
nt
er
nat
i
on
al
C
onf
e
r
enc
e o
n.
2010.
[8
]
L
a
i
TTT
, e
t a
l
.
T
r
i
op
us
N
et
:
aut
om
at
i
ng
w
i
r
e
l
e
s
s
s
en
s
or
net
w
or
k
dep
l
oy
m
e
nt
an
d
r
ep
l
ac
em
ent
i
n
pi
pe
l
i
ne m
on
i
t
or
i
ng
. I
n
P
r
o
c
ee
di
ng
s
of
t
he 1
1t
h i
nt
er
n
at
i
o
nal
c
onf
er
en
c
e on I
n
f
or
m
at
i
o
n P
r
o
c
es
s
i
n
g i
n
S
ens
or
N
et
w
or
k
s
.
A
C
M.
2012
.
[9
]
N
as
s
i
r
aei
A
A
,
e
t
a
l
.
A
N
ew
A
ppr
oac
h
t
o
t
he
S
ew
er
P
i
pe
I
n
s
pec
t
i
on:
F
u
l
l
y
A
ut
on
om
ous
M
obi
l
e
R
ob
ot
"
KAN
T
AR
O
"
.
I
n
I
EEE I
n
d
u
s
t
ri
a
l
El
e
c
t
ro
n
i
c
s
,
I
EC
O
N
2
0
0
6
-
32
n
d A
nnu
al
C
on
f
er
en
c
e
on
.
2006
.
[
10]
J
aw
har
I
, e
t a
l
.
A
n ef
f
i
c
i
ent
f
r
a
m
ew
or
k
f
or
aut
onom
ou
s
un
de
r
w
at
er
v
e
hi
c
l
e e
x
t
en
ded
s
en
s
o
r
net
w
or
k
s
f
or
pi
p
el
i
n
e m
oni
t
or
i
ng
.
I
n R
obot
i
c
an
d S
ens
or
s
E
n
v
i
r
o
n
m
ent
s
(
R
O
S
E
)
,
2013 I
E
E
E
I
nt
er
nat
i
on
al
S
y
m
pos
i
um
on.
2013
.
[
11]
Y
i
nhui
X
,
et
al
.
A
R
eal
-
t
i
m
e
SAR
Ec
h
o
Si
m
u
l
a
t
or
B
as
ed on F
P
G
A
and P
ar
a
l
l
e
l
C
om
put
i
n
g
.
T
E
LK
O
M
N
I
K
A
(
T
el
ec
om
m
uni
c
at
i
on
C
om
put
i
ng E
l
ec
t
r
oni
c
s
a
nd C
ont
r
ol
)
.
2015
;
13
(
3)
:
8
06
-
812.
[
12]
S
t
oi
an
ov
I
, e
t a
l
.
P
I
P
E
N
E
T
:
A
w
i
r
el
es
s
s
en
s
or
n
et
w
or
k
f
or
pi
pe
l
i
ne m
on
i
t
or
i
ng
. I
n
I
n
f
o
r
m
a
t
ion
P
r
oc
e
s
s
i
ng i
n S
en
s
or
N
et
w
or
k
s
,
20
07.
I
P
S
N
200
7.
6t
h I
nt
er
n
at
i
on
al
S
y
m
p
os
i
um
on.
200
7.
[
13]
Ki
m
J
, e
t
a
l
.
S
ew
er
S
n
or
t
:
A
dr
i
f
t
i
n
g
s
e
ns
or
f
or
i
n
-
s
i
t
u
s
ew
er
gas
m
oni
t
or
i
ng
.
I
n
S
ens
or
,
M
es
h
an
d
A
d
H
oc
C
om
m
un
i
c
at
i
on
s
an
d N
et
w
or
k
s
,
2009
.
S
E
C
O
N
'
09.
6t
h
A
nnual
I
E
E
E
C
o
m
m
u
ni
c
at
i
o
ns
S
oc
i
et
y
C
onf
er
en
c
e o
n
.
2009
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[
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M
ille
r
B
,
D
R
o
we
.
A
s
ur
v
ey
S
C
A
D
A
of
and c
r
i
t
i
c
al
i
nf
r
a
s
t
r
u
c
t
ur
e i
n
c
i
de
nt
s
. I
n
P
r
oc
e
edi
ngs
of
t
he 1s
t
A
nnual
c
o
nf
er
e
nc
e
on R
es
e
ar
c
h i
n i
n
f
or
m
at
i
o
n t
e
c
hn
ol
o
gy
.
AC
M
.
2012
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[
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Y
oon
S
,
et
al
.
S
W
A
T
S
:
W
i
r
e
l
e
s
s
s
en
s
or
ne
t
w
or
k
s
f
or
s
t
ea
m
f
l
ood
a
nd
w
at
er
f
l
o
od
p
i
pel
i
ne m
oni
t
or
i
ng
.
Ne
t
wo
r
k
,
I
EEE.
2
0
1
1
;
25
(1
):
5
0
-
56.
[
16]
S
un X
, e
t a
l
.
A
new
r
out
i
ng a
l
gor
i
t
hm
f
or
l
i
ne
ar
w
i
r
el
e
s
s
s
e
ns
or
ne
t
w
or
k
s
. I
n
P
er
v
as
i
v
e C
om
put
i
n
g
and A
p
pl
i
c
at
i
on
s
(
I
C
P
C
A
)
,
20
1
1 6t
h I
nt
er
nat
i
ona
l
C
onf
er
en
c
e
on.
2
011.
[
17]
J
aw
har
I
,
et
al
.
A
n E
f
f
i
c
i
ent
F
r
am
ew
or
k
and N
e
t
w
or
k
i
ng
P
r
ot
oc
o
l
f
or
Li
near
W
i
r
el
es
s
S
ens
o
r
N
et
w
or
k
s
.
A
dh
oc
&
S
ens
or
W
i
r
el
es
s
N
et
w
o
r
k
s
.
20
09;
7
.
[
18]
Sh
o
k
ri
R
,
N
Y
az
dani
,
A
K
h
ons
a
r
i
.
C
hai
n
ba
s
ed a
non
y
m
ous
r
out
i
n
g f
or
w
i
r
el
e
s
s
ad
hoc
ne
t
w
or
k
s
. I
n
P
r
oc
ee
di
n
gs
o
f
t
h
e 4t
h
I
E
E
E
C
ons
u
m
er
C
o
m
m
uni
c
at
i
on
s
an
d
N
et
w
or
k
i
ng C
o
nf
er
e
nc
e
(
C
C
N
C
)
.
2007
.
[
19]
C
hen
C
W
,
Y
W
a
ng.
C
hai
n
-
T
y
pe
W
i
r
el
e
s
s
S
e
ns
or
N
et
w
or
k
f
or
M
oni
t
or
i
ng
Long
R
ang
e
I
nf
r
as
t
r
u
c
t
ur
es
:
A
r
c
hi
t
ec
t
ur
e an
d P
r
ot
o
c
ol
s
∗
.
I
nt
er
nat
i
on
al
J
our
n
al
of
D
i
s
t
r
i
b
ut
ed S
e
ns
or
N
e
t
w
or
k
s
.
20
08
;
4
(4
):
2
8
7
-
314.
[
20]
F
er
nan
dez
J
D,
AE
F
er
nan
d
ez
.
S
C
A
D
A
s
y
s
t
em
s
:
v
ul
ne
r
abi
l
i
t
i
e
s
and r
e
m
e
di
at
i
on.
J
our
nal
of
C
om
put
i
ng S
c
i
enc
es
i
n C
ol
l
eg
es
.
2
005;
20
(
4)
:
16
0
-
16
8.
[
21]
Ta
r
i
q
A
K
,
A
T
Z
i
y
ad,
A
O
A
bdul
l
a
h.
W
i
r
e
l
e
s
s
s
en
s
or
net
w
or
k
s
f
or
l
ea
k
ag
e
det
e
c
t
i
on
i
n
u
nder
gr
o
und
p
i
p
el
i
n
es
:
a
s
ur
v
ey
p
aper
.
P
r
o
c
edi
a C
om
put
er
S
c
i
en
c
e.
2
01
3;
21
:
491
-
498.
[
22]
B
u
t
ku
s J,
L
Ja
ke
v
i
č
i
u
s,
O
T
u
mšy
s.
A
n ac
ou
s
t
i
c
m
et
h
od of
det
er
m
i
nat
i
on of
l
e
ak
age c
oo
r
di
nat
es
i
n
gas
pi
pe
l
i
n
es
.
A
r
ch
i
ve
s o
f
A
co
u
st
i
cs
.
201
4;
23
(
4)
:
533
-
5
40.
[
23]
Li
ngy
a M
, e
t a
l
.
A
c
ous
t
i
c
p
r
opaga
t
i
o
n
c
har
ac
t
er
i
s
t
i
c
s
,
p
os
i
t
i
on m
oni
t
or
i
n
g and l
oc
at
i
ng of
ga
s
t
r
ans
m
i
s
s
i
on p
i
pe
l
i
n
e l
e
ak
a
ge
.
N
at
ur
al
G
as
I
ndu
s
t
r
y
.
20
10;
11
:
23.
[
24]
M
ahf
ur
dz
A
,
e
t
a
l
.,
D
i
s
t
i
ngu
i
s
h
S
ea
T
ur
t
l
e
a
nd
F
i
s
h
U
s
i
ng
S
ound
T
ec
hni
que
i
n
D
es
i
gni
n
g
A
c
o
us
t
i
c
D
et
er
r
ent
D
ev
i
c
e
.
T
EL
KO
M
N
I
KA
(
T
el
ec
om
m
uni
c
at
i
on
C
o
m
put
i
ng
E
l
e
c
t
r
on
i
c
s
a
nd C
o
n
t
r
ol
)
.
2015
;
13
(
4)
:
1305
-
131
1.
[
25]
A
k
y
ild
iz
I
F
, D
P
om
pi
l
i
,
T
M
el
odi
a.
U
nd
er
w
at
er
ac
o
us
t
i
c
s
en
s
o
r
net
w
or
k
s
:
r
es
e
ar
c
h c
h
al
l
eng
e
s
.
A
d
H
oc
Ne
t
wo
r
k
s
.
20
05;
3
(3
):
2
5
7
-
27
9.
[
26]
W
ang
P
,
C
L
i
,
J
Z
hen
g.
D
is
t
r
ibu
t
e
d
mi
n
i
mu
m
-
c
os
t
c
l
us
t
er
i
n
g
pr
ot
o
c
ol
f
or
u
nder
w
at
er
s
en
s
or
net
w
or
k
s
(
UW
S
Ns
)
.
I
n
C
o
m
m
uni
c
at
i
on
s
,
2007.
I
C
C
'
07.
I
E
E
E
I
nt
er
n
at
i
o
nal
C
on
f
er
e
nc
e
on.
2007
.
[
27]
D
om
i
n
go M
C
,
R
Pri
o
r.
A
di
s
t
r
i
but
e
d c
l
us
t
er
i
n
g s
c
hem
e
f
or
under
w
at
er
w
i
r
e
l
es
s
s
en
s
or
n
et
w
or
k
s
. I
n
P
er
s
on
al
,
I
nd
o
or
a
nd
M
obi
l
e
R
adi
o
C
o
m
m
uni
c
at
i
on
s
,
2
007
.
P
I
M
R
C
2007.
I
E
E
E
1
8t
h
I
nt
er
nat
i
ona
l
S
y
m
pos
i
um
on.
2007
.
[
28]
A
ya
z M
,
A
A
bdul
l
ah.
H
op
-
by
-
ho
p
dy
nam
i
c
addr
es
s
i
n
g
bas
e
d
(
H
2
-
D
A
B
)
r
out
i
ng
p
r
ot
oc
ol
f
or
under
w
at
er
w
i
r
el
es
s
s
e
ns
or
n
et
w
or
k
s
. I
n
I
nf
or
m
at
i
o
n
and M
ul
t
i
m
edi
a
T
ec
h
nol
ogy
,
200
9
.
I
C
I
M
T
'
09.
I
nt
er
na
t
i
o
nal
C
o
nf
er
e
nc
e on.
2
009.
[
29]
M
oham
ed N
,
e
t a
l
.
R
e
l
i
a
bi
l
i
t
y
A
nal
y
s
i
s
of
Li
n
ear
W
i
r
el
es
s
S
ens
or
N
et
w
or
k
s
. I
n
N
et
w
or
k
C
om
put
i
n
g
and A
p
pl
i
c
at
i
on
s
(
N
C
A
)
,
20
13
12t
h I
E
E
E
I
nt
er
nat
i
ona
l
S
y
m
p
os
i
u
m
o
n.
2
013.
[
30]
M
oham
ed N
,
et
a
l
.
S
e
ns
or
net
w
or
k
ar
c
hi
t
ec
t
ur
es
f
or
m
oni
t
or
i
ng un
der
w
at
er
pi
p
el
i
nes
.
Se
n
s
o
rs
.
2
011
;
11
(
11)
:
107
38
-
1
0764
.
[
31]
J
aw
har
I,
e
t
a
l
.
A
r
ou
t
i
ng pr
ot
oc
ol
and addr
e
s
s
i
ng s
c
hem
e
f
or
oi
l
,
ga
s
,
an
d
w
at
er
p
i
pe
l
i
n
e m
oni
t
or
i
ng
us
i
n
g
w
i
r
el
e
s
s
s
en
s
or
net
w
or
k
s
.
I
n
W
i
r
el
es
s
and
O
pt
i
c
al
C
om
m
un
i
c
at
i
o
ns
N
et
w
or
k
s
,
20
08
.
W
O
C
N
'
08.
5
t
h I
F
I
P
I
nt
er
nat
i
on
al
C
onf
er
en
c
e o
n.
2
008
.
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