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,
it
u
s
e
s
th
e
co
n
ce
p
t
o
f
r
o
u
n
d
s
(
p
er
io
d
)
in
w
h
ic
h
n
o
d
es
ar
e
o
r
g
an
ized
in
to
cl
u
s
ter
s
an
d
u
s
e
s
cl
u
s
ter
h
ea
d
s
as
p
er
m
an
e
n
t
ac
t
iv
e
n
o
d
es
at
ea
ch
tu
r
n
.
T
h
is
p
r
o
to
co
l
th
er
ef
o
r
e
r
ed
u
ce
s
e
n
er
g
y
co
n
s
u
m
p
tio
n
[
23
]
.
I
n
f
ac
t,
s
ev
er
al
i
m
p
r
o
v
e
m
e
n
t
s
h
av
e
b
ee
n
m
ad
e
to
t
h
is
p
r
o
to
co
l
in
o
r
d
er
to
f
u
r
th
er
ex
te
n
d
t
h
e
li
f
eti
m
e
o
f
th
e
n
et
w
o
r
k
a
n
d
s
i
m
u
ltan
eo
u
s
l
y
s
en
d
a
m
ax
i
m
u
m
o
f
p
ac
k
e
ts
u
s
i
n
g
t
h
e
p
o
s
itio
n
o
f
th
e
cl
u
s
ter
h
ea
d
s
a
n
d
th
e
b
ase
s
tat
io
n
.
Fig
u
r
e
3
.
Hiea
r
ch
ical
a
r
ch
itect
u
r
e
o
f
a
w
ir
eless
s
en
s
o
r
n
et
wo
r
k
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
MG
-
lea
ch
:
a
n
en
h
a
n
ce
d
le
a
c
h
p
r
o
to
co
l fo
r
w
ir
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o
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etw
o
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k
(
Hich
a
m
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ld
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)
3141
2.
RE
L
AT
E
D
WO
RK
2
.
1
.
L
ea
ch
pro
t
o
c
o
l
T
h
e
L
E
AC
H
p
r
o
to
co
l a
s
s
u
m
e
s
th
e
eq
u
a
lit
y
o
f
t
h
e
r
esid
u
al
e
n
er
g
ie
s
o
f
t
h
e
s
e
n
s
o
r
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h
e
b
eg
in
n
i
n
g
o
f
th
e
o
p
er
atio
n
o
f
th
e
n
et
w
o
r
k
.
T
h
e
s
er
v
ice
lif
e
o
f
th
e
n
et
w
o
r
k
is
t
h
en
s
eg
m
e
n
ted
in
r
o
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n
d
s
ch
ar
ac
ter
ized
b
y
a
ch
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ice
o
f
C
H.
E
ac
h
c
y
cle
h
a
s
t
w
o
p
h
ases
:
t
h
e
s
et
-
u
p
p
h
ase
an
d
th
e
s
tead
y
s
tate
p
h
ase
.
T
h
e
s
et
-
up
p
h
ase
is
co
m
p
o
s
ed
o
f
t
h
r
ee
s
u
b
-
p
h
a
s
es
: a
n
n
o
u
n
ce
m
e
n
t,
o
r
g
an
izatio
n
o
f
th
e
g
r
o
u
p
an
d
f
i
n
all
y
p
lan
n
i
n
g
.
2
.
1
.
1
.
Anno
un
ce
m
ent
p
ha
s
e
B
ef
o
r
e
lau
n
c
h
in
g
t
h
is
p
h
a
s
e,
w
e
w
a
n
t
to
s
h
ed
li
g
h
t
o
n
C
H.
T
h
e
n
u
m
b
er
K
o
f
C
H
is
co
n
s
t
an
t
d
u
r
in
g
all
t
u
r
n
s
,
I
ts
e
s
ti
m
ated
o
p
ti
m
al
p
er
ce
n
tag
e
s
h
o
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ld
b
e
b
et
wee
n
5
%
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d
1
5
%
o
f
th
e
to
tal
n
u
m
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er
o
f
n
o
d
es,
o
th
er
w
is
e
it
w
il
l c
au
s
e
a
g
r
ea
t
d
is
s
ip
atio
n
o
f
e
n
er
g
y
i
n
th
e
n
e
t
w
o
r
k
.
I
n
f
ac
t,
i
f
t
h
e
n
u
m
b
er
o
f
C
H
i
s
v
er
y
h
i
g
h
,
w
e
w
ill
h
a
v
e
a
lar
g
e
n
u
m
b
er
o
f
C
H
n
o
d
es
d
ev
o
t
ed
to
v
er
y
ex
p
en
s
iv
e
tas
k
s
in
en
er
g
y
r
es
o
u
r
ce
s
.
Ho
w
ev
er
,
w
e
w
ill
h
av
e
co
n
s
id
er
ab
le
en
er
g
y
d
is
s
ip
at
io
n
i
n
t
h
e
n
et
w
o
r
k
.
Mo
r
eo
v
er
,
if
th
e
n
u
m
b
er
o
f
C
H
is
v
er
y
s
m
all,
th
e
y
w
il
l
m
a
n
ag
e
lar
g
e
g
r
o
u
p
s
.
As
a
r
esu
lt
,
th
e
y
w
il
l
q
u
ic
k
l
y
r
u
n
o
u
t
d
u
e
to
th
e
i
m
p
o
r
ta
n
t
t
ask
t
h
e
y
ar
e
s
u
p
p
o
s
ed
to
p
er
f
o
r
m
.
T
h
is
p
h
a
s
e
b
eg
i
n
s
w
it
h
t
h
e
an
n
o
u
n
ce
m
en
t
o
f
th
e
n
e
w
c
y
cle
b
y
t
h
e
lo
ca
l
d
ec
is
io
n
o
f
a
n
o
d
e
th
at
ca
n
b
ec
o
m
e
a
C
H
w
it
h
a
ce
r
tain
p
r
o
b
ab
ilit
y
P
i
(
t)
at
th
e
b
eg
in
n
i
n
g
o
f
th
e
c
y
cle
o
f
r
+
1
,
w
h
ich
b
e
g
in
s
at
ti
m
e
t.
E
ac
h
n
o
d
e
h
as a
r
an
d
o
m
n
u
m
b
er
b
et
w
ee
n
0
an
d
1
.
I
f
t
h
is
n
u
m
b
er
is
les
s
t
h
a
n
P
i
(
t)
,
th
e
n
o
d
e
w
il
l
b
ec
o
m
e
C
H
d
u
r
in
g
t
h
e
t
u
r
n
r
+
1
.
P
i
(
t)
is
ca
lcu
lated
as
a
f
u
n
ctio
n
o
f
K
an
d
t
h
e
tu
r
n
r
,
g
iv
e
n
b
y
f
o
r
m
u
la
(
1
)
,
w
h
er
e
N
is
th
e
to
tal
n
u
m
b
e
r
o
f
n
o
d
es
in
th
e
n
e
t
w
o
r
k
.
I
f
w
e
h
a
v
e
N
n
o
d
es
an
d
K
C
Hs,
th
e
n
it
w
i
ll
ta
k
e
N
/
K
r
o
u
n
d
s
d
u
r
i
n
g
w
h
ich
a
n
o
d
e
m
u
s
t
b
e
elec
ted
o
n
l
y
o
n
ce
as
m
u
c
h
as C
H
b
e
f
o
r
e
th
e
r
o
u
n
d
is
r
eset to
0
.
So
th
e
p
r
o
b
ab
ilit
y
o
f
b
ec
o
m
in
g
C
H
f
o
r
ea
ch
n
o
d
e
i
is
:
Pi
(
t
)
=
{
K
N
−
k
∗
(
r
mod
N
k
)
if
∶
Ci
(
t
)
=
1
1
∶
(
t
)
=
0
(
1
)
W
ith
C
i (
t)
: t
h
e
n
o
d
e
elig
ib
ili
t
y
to
b
e
C
H
at
ti
m
e
t
.
W
h
er
e
C
i
(
t)
is
eq
u
al
to
0
i
f
th
e
n
o
d
e
i
h
a
s
alr
ea
d
y
b
ee
n
C
H
d
u
r
in
g
o
n
e
o
f
t
h
e
p
r
ev
io
u
s
r
o
u
n
d
s
,
an
d
is
eq
u
al
to
1
o
th
er
w
is
e.
T
h
e
r
ef
o
r
e,
o
n
ly
n
o
d
es
t
h
at
h
a
v
e
n
o
t
y
et
b
ee
n
C
H
ar
e
li
k
el
y
to
h
a
v
e
s
u
f
f
icien
t
r
esid
u
al
en
er
g
y
r
elati
v
e
to
o
th
er
s
th
at
t
h
e
y
ca
n
b
e
s
elec
ted
.
F
ig
u
r
e.
4
p
r
esen
t t
h
e
p
r
o
to
co
l L
E
AC
H
f
lo
w
c
h
ar
t
:
Fig
u
r
e
4
.
L
E
A
C
H
p
r
o
to
co
l f
lo
w
c
h
ar
t
2
.
1
.
2
.
O
rg
a
niza
t
io
n pha
s
e
Af
ter
a
n
o
d
e
is
elec
ted
C
H,
it
m
u
s
t
i
n
f
o
r
m
t
h
e
o
th
er
s
e
n
s
o
r
n
o
d
es
o
f
its
n
e
w
r
a
n
k
i
n
t
h
e
cu
r
r
en
t
r
o
u
n
d
.
Fo
r
t
h
is
,
a
n
"
ADV"
w
ar
n
in
g
m
e
s
s
a
g
e
co
n
tain
in
g
th
e
id
e
n
ti
f
ier
o
f
t
h
e
C
H
i
s
b
r
o
ad
ca
s
t
to
all
o
t
h
er
n
o
d
es
u
s
in
g
t
h
e
C
SM
A
M
AC
p
r
o
to
co
l
to
av
o
id
co
llis
io
n
s
b
et
w
ee
n
t
h
e
C
Hs.
B
r
o
ad
ca
s
tin
g
en
s
u
r
e
s
th
a
t
al
l
n
o
d
es
h
av
e
r
ec
eiv
ed
t
h
e
m
e
s
s
ag
e.
Mo
r
eo
v
er
,
i
t
e
n
s
u
r
es
th
at
th
e
n
o
d
es
b
elo
n
g
to
t
h
e
C
H
th
a
t
r
eq
u
ir
es
t
h
e
m
i
n
i
m
u
m
e
n
er
g
y
f
o
r
co
m
m
u
n
icatio
n
.
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
.
4
,
A
u
g
u
s
t
201
9
:
3
1
3
9
-
3145
3142
T
h
e
d
ec
is
io
n
is
t
h
er
e
f
o
r
e
b
ased
o
n
th
e
a
m
p
lit
u
d
e
o
f
t
h
e
r
ec
e
iv
ed
s
i
g
n
alb
y
t
h
e
C
H
w
it
h
t
h
e
s
tr
o
n
g
e
s
t
s
ig
n
al,
t
h
at
is
to
s
a
y
t
h
e
n
ea
r
est
w
il
l
b
e
ch
o
s
en
.
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n
t
h
e
e
v
en
t
o
f
s
i
g
n
al
eq
u
alit
y
,
o
r
d
in
a
r
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n
o
d
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r
a
n
d
o
m
l
y
s
elec
t
th
eir
C
H.
E
ac
h
m
e
m
b
e
r
in
f
o
r
m
s
h
i
s
/
h
er
C
H
o
f
h
is
d
ec
is
io
n
.
On
ce
t
h
e
C
H
h
a
s
r
ec
eiv
ed
th
e
r
eq
u
est,
it sen
d
s
a
n
ac
k
n
o
w
led
g
m
e
n
t
m
es
s
ag
e
"
J
o
in
-
R
E
Q"
.
2
.
1
.
3
.
P
la
nn
ing
ph
a
s
e
Af
ter
g
r
o
u
p
f
o
r
m
at
io
n
,
ea
ch
C
H
ac
ts
a
s
a
lo
ca
l
co
m
m
a
n
d
ce
n
ter
to
co
o
r
d
in
ate
d
ata
tr
an
s
m
i
s
s
io
n
s
w
it
h
i
n
it
s
g
r
o
u
p
.
I
t
cr
ea
tes
a
T
DM
A
s
ch
ed
u
ler
an
d
ass
ig
n
s
e
ac
h
m
e
m
b
er
n
o
d
e
a
ti
m
e
s
lo
t
d
u
r
in
g
w
h
ic
h
it
ca
n
tr
an
s
m
it
i
ts
d
ata.
T
h
e
s
et
o
f
s
l
o
ts
ass
i
g
n
ed
to
th
e
n
o
d
es
o
f
a
g
r
o
u
p
is
ca
lled
f
r
a
m
e.
T
h
e
d
u
r
atio
n
o
f
ea
c
h
f
r
a
m
e
d
if
f
er
s
ac
co
r
d
in
g
to
t
h
e
n
u
m
b
er
o
f
m
e
m
b
er
s
o
f
t
h
e
g
r
o
u
p
.
I
n
ad
d
itio
n
,
to
m
i
n
i
m
ize
in
t
er
f
er
en
ce
b
et
w
ee
n
tr
an
s
m
is
s
io
n
s
i
n
ad
j
ac
en
t
g
r
o
u
p
s
,
ea
ch
C
H
r
an
d
o
m
l
y
ch
o
o
s
e
s
a
co
d
e
f
r
o
m
a
li
s
t o
f
C
DM
A
p
r
o
p
ag
atio
n
co
d
es.
I
t th
en
tr
a
n
s
m
it
s
it to
its
m
e
m
b
er
s
f
o
r
u
s
e
i
n
th
e
ir
tr
an
s
m
i
s
s
io
n
s
,
h
e
n
ce
t
h
e
n
e
x
t p
h
a
s
e
is
t
h
a
t o
f
tr
an
s
m
i
s
s
io
n
2
.
1
.
4
.
T
ra
ns
m
is
s
io
n p
ha
s
e
I
n
t
h
is
s
ec
o
n
d
p
h
ase,
th
e
d
ata
tr
an
s
f
er
w
ill
tak
e
p
lace
to
th
e
B
S.
Us
in
g
th
e
T
DM
A
s
ch
ed
u
ler
,
m
e
m
b
er
s
e
m
it
t
h
eir
ca
p
tu
r
ed
d
ata
d
u
r
in
g
t
h
eir
o
w
n
s
lo
ts
.
T
h
is
allo
w
s
t
h
e
m
to
tu
r
n
o
f
f
t
h
eir
co
m
m
u
n
icat
io
n
in
ter
f
ac
e
s
o
u
ts
id
e
o
f
th
eir
s
lo
t
s
to
s
av
e
t
h
eir
e
n
er
g
y
.
T
h
ese
d
ata
ar
e
th
e
n
a
g
g
r
eg
ated
b
y
t
h
e
C
Hs
t
h
at
m
er
g
e
an
d
co
m
p
r
ess
t
h
e
m
,
a
n
d
s
en
d
th
e
f
in
al
r
es
u
lt
to
Si
n
k
.
Af
ter
a
p
r
ed
eter
m
in
ed
ti
m
e,
t
h
e
n
et
w
o
r
k
w
i
ll
m
o
v
e
to
a
n
e
w
r
o
u
n
d
.
T
h
is
p
r
o
ce
s
s
is
r
ep
ea
ted
u
n
til
all
n
o
d
es
in
th
e
n
et
w
o
r
k
ar
e
elec
ted
C
H
o
n
ce
,
all
th
r
o
u
g
h
th
e
p
r
ev
io
u
s
r
o
u
n
d
s
.
I
n
th
is
ca
s
e,
t
h
e
r
o
u
n
d
is
r
ese
t to
0
.
I
n
th
is
w
o
r
k
,
w
e
i
m
p
le
m
e
n
t
an
en
er
g
y
m
o
d
el
th
at
co
v
er
s
b
o
th
tr
an
s
m
i
s
s
io
n
a
n
d
r
ec
ep
tio
n
co
m
m
u
n
icatio
n
s
.
T
h
is
is
a
r
a
d
io
m
o
d
el
u
s
ed
in
t
h
e
s
i
m
u
l
atio
n
o
f
t
h
e
L
E
AC
H
a
n
d
M
G
-
E
AC
H
p
r
o
to
co
ls
s
h
o
w
n
i
n
f
o
r
m
u
las (
2
)
,
(
3
)
an
d
(
4
)
.
T
h
u
s
,
to
tr
a
n
s
m
it a
m
e
s
s
a
g
e
o
f
s
ize
S (
b
its
)
o
v
er
a
d
i
s
ta
n
ce
D
(
m
eter
s
)
,
t
h
e
tr
an
s
m
itter
co
n
s
u
m
e
s
:
ET
x
=
{
S
∗
E
e
lec
+
S
∗
E
el
∗
D
²
;
D
<
D
th
r
e
s
h
o
ld
S
∗
E
e
lec
+
S
∗
E
el
∗
D
4
;
D
≥
D
th
r
e
s
h
o
ld
(
2
)
D
th
r
e
s
h
o
ld
=
√
Ee
l
Em
c
(
3
)
W
ith
: E
elec
=5
0
*
1
0
-
9
J
,
E
e
l=9
.
6
7
*
1
0
-
1
2
J
,
E
m
c=
1
.
3
*
1
0
-
1
5
J
D
t
hr
es
ho
l
d
≈
86
T
h
e
en
er
g
y
co
n
s
u
m
ed
at
t
h
e
r
ec
ep
tio
n
lev
el
i
s
ca
lcu
lated
as
f
o
llo
w
s
:
E
Rx
=
S
∗
E
el
ec
(
4
)
Am
o
n
g
t
h
e
d
i
s
ad
v
a
n
tag
e
s
o
f
L
E
AC
H
p
r
o
to
co
l
is
t
h
e
r
ed
u
ct
io
n
o
f
t
h
e
e
n
er
g
y
o
f
t
h
e
n
o
d
es,
th
is
d
ec
r
ea
s
e
is
d
u
e
to
t
h
e
u
s
e
o
f
a
s
i
n
g
le
j
u
m
p
co
m
m
u
n
icatio
n
in
s
tead
o
f
a
m
u
l
ti
-
h
o
p
co
m
m
u
n
icat
io
n
.
E
v
en
if
th
e
li
f
eti
m
e
o
f
th
e
n
et
w
o
r
k
is
m
o
r
e
t
h
an
o
t
h
er
p
r
o
to
co
ls
s
u
c
h
as
p
lan
e
m
u
ltip
at
h
r
o
u
tin
g
,
it
s
til
l
h
a
s
s
o
m
e
d
r
a
w
b
ac
k
s
.
T
h
e
clu
s
te
r
-
h
ea
d
co
m
m
u
n
icate
s
d
ir
ec
tl
y
w
it
h
th
e
s
i
n
k
w
h
ich
ca
u
s
es
s
o
m
e
p
r
o
b
le
m
s
.
Firstl
y
,
i
f
t
h
e
s
i
n
k
i
s
f
ar
f
r
o
m
t
h
e
cl
u
s
ter
-
h
ea
d
,
it
w
ill
b
e
i
m
p
o
s
s
ib
le
to
co
m
m
u
n
icate
w
it
h
i
t.
Seco
n
d
l
y
,
e
v
en
i
f
th
e
s
in
k
i
s
r
ea
ch
ab
le
b
y
t
h
e
c
lu
s
ter
-
h
ea
d
,
th
e
n
ec
es
s
ar
y
e
n
e
r
g
y
to
tr
a
n
s
m
it
d
ata
w
ill
b
e
v
er
y
h
i
g
h
.
T
h
u
s
,
th
e
en
er
g
y
co
n
s
u
m
p
tio
n
o
f
t
h
e
n
et
w
o
r
k
w
i
ll in
cr
ea
s
e.
T
h
er
ef
o
r
e,
th
e
li
f
ti
m
e
o
f
t
h
e
n
et
w
o
r
k
w
ill
b
e
af
f
ec
ted
.
3.
P
RO
P
O
SE
D
P
RO
T
O
CO
L
Ou
r
co
n
tr
ib
u
tio
n
,
i
n
t
h
i
s
p
ap
er
,
is
an
i
m
p
r
o
v
ed
L
ea
ch
p
r
o
to
co
l
ca
lled
MG
-
L
E
A
C
H
[
1
]
.
I
n
f
ac
t,
I
n
MG
-
L
E
A
C
H,
d
ep
lo
y
ed
n
o
d
es
ar
e
d
iv
id
ed
in
to
S
u
b
Gr
o
u
p
s
(
G1
….
Gk
)
d
ep
en
d
i
n
g
u
p
o
n
th
eir
lo
ca
tio
n
s
.
Nu
m
b
er
o
f
g
r
o
u
p
s
ar
e
m
a
in
l
y
d
ep
en
d
s
u
p
o
n
No
d
e
d
en
s
it
y
.
T
h
ese
g
r
o
u
p
s
ar
e
cr
ea
ted
b
y
t
h
e
B
ase
-
Stat
io
n
at
th
e
ti
m
e
o
f
d
ep
lo
y
m
e
n
t
a
n
d
af
ter
ev
er
y
“
x
”
r
o
u
n
d
s
.
T
h
is
i
s
a
n
ad
d
itio
n
al
s
tep
u
s
ed
i
n
o
u
r
p
r
o
p
o
s
ed
alg
o
r
ith
m
b
ef
o
r
e
s
et
u
p
p
h
ase
an
d
s
tead
y
s
tate
p
h
ase
a
n
d
k
n
o
w
n
as
Set
b
u
i
ld
in
g
p
h
ase.
MG
-
L
E
AC
H
co
n
s
i
s
ts
o
f
th
r
ee
s
tep
s
,
t
h
e
b
u
ild
p
h
a
s
e
i
s
u
s
ed
a
t d
ep
lo
y
m
e
n
t ti
m
e
a
n
d
af
ter
ea
ch
"
x
"
r
o
u
n
d
s
p
er
B
S,
an
d
t
h
e
r
e
m
ain
in
g
t
w
o
ar
e
th
e
s
a
m
e
as t
h
o
s
e
u
s
ed
in
L
E
AC
H
s
u
ch
a
s
th
e
I
n
s
talla
tio
n
P
h
asean
d
s
tead
y
s
tate
p
h
a
s
e.
A
t
t
h
e
b
eg
in
n
i
n
g
o
f
s
et
u
p
p
h
ase,
ea
c
h
n
o
d
e
c
h
o
s
e
a
r
an
d
o
m
n
u
m
b
er
f
r
o
m
‘
ze
r
o
’
to
‘
o
n
e
’
a
n
d
co
m
p
ar
es it
to
a
t
h
r
esh
o
ld
P
i(
T
)
,
w
h
ic
h
is
ca
lc
u
lated
as
f
o
ll
o
w
:
Pi
(
t
)
=
{
K
N
−
k
∗
(
r
mo
d
N
k
)
x
[
]
2
if
∶
Ci
(
t
)
=
1
1
∶
(
t
)
=
0
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
MG
-
lea
ch
:
a
n
en
h
a
n
ce
d
le
a
c
h
p
r
o
to
co
l fo
r
w
ir
eless
s
en
s
o
r
n
etw
o
r
k
(
Hich
a
m
Ou
ld
z
ir
a
)
3143
W
h
er
e
K
is
th
e
d
esire
d
p
er
ce
n
tag
e
o
f
C
Hs,
r
is
th
e
cu
r
r
e
n
t
r
o
u
n
d
,
C
i(
t)
is
th
e
s
et
o
f
n
o
d
e
s
th
at
h
a
v
e
n
o
t
b
ec
o
m
e
C
H
i
n
last
N
k
r
o
u
n
d
s
,
[
Ei
Es
]
²
is
th
e
n
o
d
e’
s
en
er
g
y
d
ev
id
ed
b
y
in
i
tial
en
er
g
y
to
s
ele
ct
th
e
n
o
d
e
h
av
i
n
g
h
i
g
h
est le
v
el
o
f
r
es
id
u
a
l e
n
er
g
y
.
A
t
t
h
e
ti
m
e
o
f
r
an
d
o
m
n
o
d
e
d
ep
lo
y
m
e
n
ts
,
ea
ch
n
o
d
e
is
eq
u
i
p
p
ed
w
it
h
a
GP
S
m
o
d
u
le
th
a
t
s
en
d
s
t
h
e
lo
ca
tio
n
in
f
o
r
m
at
io
n
o
f
th
at
n
o
d
e
d
ir
ec
tly
to
t
h
e
B
S.
T
h
e
B
S
w
ill
u
s
e
t
h
e
i
n
f
o
r
m
atio
n
p
r
o
v
id
ed
f
o
r
ea
ch
p
h
a
s
e
o
f
co
n
s
tr
u
ctio
n
o
f
t
h
e
s
e
t.
As i
t h
as b
ee
n
d
o
n
e
o
n
l
y
o
n
c
e
a
n
d
th
er
ef
o
r
e
it d
o
es n
o
t c
o
n
s
u
m
e
to
o
m
u
ch
e
n
er
g
y
.
Set
u
p
p
h
ase
an
d
s
tead
y
s
tate
p
h
ase
is
s
a
m
e
as
u
s
ed
in
L
E
AC
H
an
d
w
o
r
k
s
in
e
v
er
y
g
r
o
u
p
s
ep
ar
atel
y
.
T
h
ese
g
r
o
u
p
s
d
o
n
o
t
w
o
r
k
s
i
m
u
lta
n
eo
u
s
l
y
b
u
t o
n
al
ter
n
ate
b
asis
e.
g
.
o
n
e
at
a
ti
m
e
a
s
p
er
s
et
d
u
t
y
c
y
cle
b
y
B
S.
I
f
Net
w
o
r
k
co
m
p
r
is
ed
b
y
Su
b
Gr
o
u
p
G1
is
w
o
r
k
in
g
No
d
es
o
f
S
u
b
Gr
o
u
p
G2
w
ill
b
e
in
s
l
ee
p
s
tate.
T
h
e
d
u
t
y
c
y
cle
is
s
et
b
y
B
S
at
t
h
e
ti
m
e
o
f
Se
tb
u
ild
i
n
g
p
h
ase.
Mi
n
i
m
u
m
g
r
o
u
p
o
f
n
o
d
es
co
n
s
t
r
u
ct
at
th
e
t
i
m
e
o
f
d
ep
lo
y
m
en
t i
s
t
w
o
b
u
t
m
ai
n
l
y
d
ep
en
d
s
u
p
o
n
n
o
d
e
d
en
s
it
y
i
n
th
e
en
t
ir
e
n
et
w
o
r
k
.
W
e
h
av
e
s
i
m
u
lated
t
h
e
MG
-
L
E
A
C
H
an
d
f
in
d
it
m
u
ch
m
o
r
e
e
f
f
icie
n
t
t
h
an
L
E
AC
H.
W
e
h
av
e
ch
ec
k
ed
t
h
e
p
er
f
o
r
m
a
n
ce
b
y
t
ak
in
g
d
i
f
f
er
e
n
t
i
n
itial
e
n
er
g
y
o
f
d
ep
lo
y
ed
n
o
d
es
al
s
o
w
it
h
d
if
f
er
en
t
v
al
u
e
o
f
p
.
MG
-
L
E
AC
H
i
s
p
er
f
o
r
m
ed
m
u
ch
b
ett
er
t
h
a
n
L
E
AC
H
a
s
i
n
cr
ea
s
ed
Net
w
o
r
k
li
f
eti
m
e
co
n
s
id
er
ab
ly
.
W
e
ca
n
u
s
e
th
is
p
r
o
p
o
s
ed
alg
o
r
ith
m
w
it
h
an
y
v
ar
ian
t
b
ased
o
n
L
E
AC
H
in
w
h
ich
s
et
t
h
r
esh
o
ld
h
as
b
e
en
m
o
d
i
f
ied
eith
er
b
y
ad
d
r
ess
i
n
g
th
e
s
h
o
r
tco
m
i
n
g
s
in
t
h
e
f
o
r
m
o
f
co
n
s
id
er
in
g
r
e
s
id
u
al
e
n
er
g
y
a
s
w
ell
a
s
o
t
h
er
p
ar
am
eter
s
.
4.
SI
M
UL
AT
I
O
N
S AN
D
R
E
S
UL
T
S
I
n
th
i
s
s
ec
tio
n
,
w
e
ar
e
g
o
in
g
t
o
u
s
e
a
s
i
m
u
latio
n
to
ev
alu
a
te
an
d
an
al
y
ze
o
u
r
p
r
o
to
co
l.
W
e
s
i
m
u
late
MG
-
L
E
AC
H
alo
n
g
w
it
h
L
E
AC
H
al
g
o
r
ith
m
i
n
M
A
T
L
A
B
to
s
et
u
p
a
co
m
p
ar
ativ
e
a
n
al
y
s
is
b
o
th
f
o
r
L
E
A
C
H
an
d
MG
-
L
E
A
C
H.
F
o
r
t
h
e
e
x
p
er
im
e
n
t,
th
e
r
an
d
o
m
n
e
t
w
o
r
k
o
f
3
0
0
No
d
es
is
u
s
ed
.
T
h
e
B
ase
-
Statio
n
w
a
s
p
lace
d
in
ce
n
tr
e
L
o
ca
tio
n
w
i
t
h
d
i
m
e
n
s
io
n
(
x
=1
0
0
,
y
=1
0
0
)
.
T
h
e
b
an
d
w
id
th
o
f
t
h
e
ch
a
n
n
el
w
a
s
s
et
to
1
Mb
p
s
.
E
ac
h
d
ata
m
es
s
a
g
e
w
a
s
4
0
0
0
b
y
tes
lo
n
g
w
i
th
h
ea
d
er
p
ac
k
et
w
h
ich
is
2
5
b
y
tes
lo
n
g
.
T
h
e
r
ad
io
elec
tr
o
n
ics
en
er
g
y
w
a
s
s
et
to
5
0
n
J
/b
it
a
n
d
th
e
r
ad
io
tr
an
s
m
itter
e
n
er
g
y
E
j
s
Set
t0
1
0
0
p
J
/
b
it/
m
²
f
o
r
d
is
tan
ce
s
les
s
t
h
a
n
8
7
m
a
n
d
0
.
0
0
1
3
p
J
/b
it/m
4
f
o
r
d
is
tan
ce
s
g
r
ea
ter
th
a
n
8
7
m
.
T
h
e
en
er
g
y
f
o
r
p
er
f
o
r
m
in
g
C
o
m
p
u
tat
io
n
s
to
ag
g
r
e
g
ate
d
ata
w
a
s
s
e
t
to
5
n
J
/b
it/s
i
g
n
al.
I
n
o
r
d
er
to
g
et
i
m
p
r
o
v
ed
an
d
q
u
ite
ac
c
u
r
at
e
co
m
m
en
t
s
o
f
th
e
alg
o
r
ith
m
,
w
e
e
s
tab
lis
h
t
h
e
s
a
m
e
s
i
m
u
latio
n
s
ce
n
e
3
0
ti
m
es
an
d
th
e
ta
k
e
n
r
es
u
lt
i
s
t
h
e
av
e
r
ag
e
o
f
t
h
e
co
n
ta
i
n
o
u
tp
u
ts
.
Fo
r
en
er
g
y
m
o
d
el,
we
ass
u
m
e
t
h
at
ea
c
h
n
o
d
e
b
eg
i
n
s
w
it
h
eq
u
al
en
er
g
y
a
n
d
an
u
n
li
m
ited
a
m
o
u
n
t
o
f
d
ata
to
s
en
d
to
th
e
b
ase
s
ta
tio
n
.
On
ce
a
n
o
d
e
r
u
n
s
o
u
t
o
f
e
n
er
g
y
,
co
n
s
id
er
ed
as
d
ea
d
n
o
d
e
an
d
ca
n
n
o
lo
n
g
e
r
tr
an
s
m
it
o
r
r
ec
eiv
e
d
ata.
T
h
e
v
alv
e
o
f
x
u
s
ed
in
s
et
b
u
ild
i
n
g
p
h
ase
is
tak
e
n
as
2
0
.
I
n
itial
en
er
g
y
f
o
r
e
ac
h
n
o
d
e
u
s
ed
i
n
s
i
m
u
latio
n
is
s
e
t
to
0
.
5
J
o
u
le,
w
h
ile
th
e
e
x
p
er
i
m
e
n
t
is
r
ep
ea
ted
w
it
h
2
J
o
u
le
b
o
th
f
o
r
L
E
A
C
H
an
d
p
r
o
p
o
s
ed
MG
-
L
E
AC
H.
T
h
e
m
ai
n
o
b
j
ec
tiv
e
o
f
MG
-
L
E
AC
H
is
to
p
r
o
lo
n
g
t
h
e
n
et
w
o
r
k
li
f
e
ti
m
e
b
y
u
t
ilizi
n
g
r
ed
u
n
d
an
t n
o
d
es
d
ep
lo
y
ed
i
n
W
SN.
As
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
i
s
b
ased
u
p
o
n
t
h
e
f
r
a
m
e
w
o
r
k
o
f
L
E
AC
H
s
o
th
e
tea
m
r
o
u
n
d
is
u
s
ed
f
o
r
ea
ch
o
f
t
h
e
co
n
s
ec
u
tiv
e
p
er
io
d
s
i
n
w
h
ich
th
e
s
e
n
s
o
r
n
o
d
es
p
er
f
o
r
m
:
a
p
r
ed
ef
in
ed
co
n
s
tan
t
w
o
r
k
.
Fo
r
ex
a
m
p
le,
i
n
ea
ch
r
o
u
n
d
,
e
v
er
y
s
e
n
s
o
r
n
o
d
e
f
o
r
w
ar
d
s
4
0
0
0
b
its
o
f
d
ata
t
o
its
cl
u
s
ter
-
h
ea
d
.
W
e
p
r
o
v
id
e
a
s
u
m
m
ar
y
ch
ar
t
w
h
ic
h
illu
s
tr
ates
t
h
e
v
al
u
es
o
f
FND(
First
No
d
e
Dies)
HND
(
Half
No
d
e
Dies)
an
d
L
ND
(
L
as
t N
o
d
e
Dies)
m
etr
ics v
i
s
u
al
l
y
.
Fig
u
r
e
5
ill
u
s
tr
ates
th
e
s
i
m
u
latio
n
r
esu
lt
t
h
at
d
e
m
o
n
s
tr
a
te
r
elativ
e
b
e
h
av
io
r
o
f
b
o
t
h
d
is
cu
s
s
ed
alg
o
r
ith
m
s
w
i
th
p
ar
a
m
eter
s
v
alu
es
n
=3
0
0
,
p
=
0
.
1
an
d
E
0
=
0
.
5
J
.
I
t
d
em
o
n
s
tr
ates
Ali
v
e
N
o
d
es
th
at
is
ta
k
e
n
a
t
y
-
a
x
i
s
f
o
r
d
if
f
er
en
t
ti
m
e
s
ta
m
p
s
(
R
o
u
n
d
s
)
t
h
at
i
s
ta
k
e
n
o
n
x
-
a
x
is
.
Fi
g
u
r
e
6
a
n
d
Fi
g
u
r
e
7
ill
u
s
tr
ate
s
t
h
e
P
icto
g
r
ap
h
ic
r
ep
r
esen
tatio
n
o
f
C
o
m
p
ar
a
tiv
e
An
al
y
s
is
o
f
L
E
AC
H
a
n
d
.
MG
-
L
E
AC
H
f
o
r
d
is
tr
ib
u
tio
n
o
f
t
h
e
aliv
e
s
en
s
o
r
n
o
d
es
w
it
h
r
esp
ec
t
to
t
h
e
n
u
m
b
er
o
f
r
o
u
n
d
s
f
o
r
ea
ch
al
g
o
r
ith
m
w
h
e
n
th
e
d
ef
i
n
e
p
ar
a
m
eter
s
s
et
to
n
=3
0
0
,
p
=
0
.
0
5
,
E
0
=
0
.
5
J
an
d
n
=3
0
0
,
p
=
0
.
0
5
,
E
0
=
2
J
r
esp
e
ctiv
el
y
.
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
.
4
,
A
u
g
u
s
t
201
9
:
3
1
3
9
-
3145
3144
Fig
u
r
e
5.
Gr
ap
h
ical
r
ep
r
esen
ta
tio
n
o
f
s
i
m
u
latio
n
r
esu
lt
s
w
h
e
n
p
ar
a
m
eter
s
v
al
u
e
s
ar
e
s
et
to
n
=3
0
0
,
p
=
0
.
1
an
d
E
0
=0
.
5
J
Fig
u
r
e
6.
P
icto
g
r
ap
h
ic
o
f
s
i
m
u
latio
n
d
ata
f
o
r
co
m
p
ar
ati
v
e
an
al
y
s
is
o
f
L
E
AC
H
an
d
MG
-
L
E
A
C
H
w
h
e
n
n
=3
0
0
,
p
=
0
.
0
5
,
E
0
=0
.
5
J
Fig
u
r
e
7
.
P
icto
g
r
ap
h
ic
o
f
s
i
m
u
latio
n
d
ata
f
o
r
co
m
p
ar
ativ
e
a
n
al
y
s
i
s
o
f
L
E
AC
H
an
d
MG
-
L
E
AC
H
w
h
en
n
=3
0
0
,
p
=
0
.
0
5
,
E
0
=
2
J
5.
CO
NCLU
SI
O
N
I
n
th
i
s
p
ap
er
,
af
ter
co
n
d
u
ctin
g
a
r
esear
ch
o
n
L
E
AC
H
p
r
o
to
co
l,
we
ca
m
e
u
p
w
it
h
an
i
m
p
r
o
v
ed
p
r
o
to
co
l
ca
lled
MG
-
L
E
A
C
H.
I
n
f
ac
t,
t
h
e
k
e
y
o
b
j
ec
ti
v
e
o
f
p
r
o
p
o
s
ed
th
is
p
r
o
to
co
l
is
to
p
r
o
lo
n
g
th
e
li
f
eti
m
e
o
f
th
e
w
ir
e
less
s
e
n
s
o
r
n
et
w
o
r
k
b
y
u
tili
zi
n
g
t
h
e
co
r
r
elate
d
n
a
tu
r
e
o
f
d
ata
i
n
s
id
e
t
h
e
cl
u
s
te
r
s
.
MG
-
L
E
AC
H
is
b
ased
u
p
o
n
th
e
f
r
a
m
e
w
o
r
k
o
f
L
E
A
C
H
p
r
o
to
co
l
s
o
w
e
al
s
o
illu
s
tr
ated
in
d
etail
t
h
e
s
h
o
r
tc
o
m
in
g
as
s
o
ciate
d
w
it
h
it,
in
ad
d
itio
n
t
h
e
p
er
f
o
r
m
an
ce
an
a
l
y
s
is
o
f
L
E
AC
H
h
as
b
ee
n
p
er
f
o
r
m
ed
.
I
t
also
co
v
er
s
co
m
p
ar
ativ
e
an
al
y
s
is
o
f
en
er
g
y
e
f
f
icie
n
t M
AC
an
d
R
o
u
ti
n
g
p
r
o
to
co
ls
u
s
e
d
in
W
ir
eless
Se
n
s
o
r
Net
w
o
r
k
.
W
e
h
av
e
i
m
p
le
m
en
ted
o
u
r
b
asic
id
ea
u
p
o
n
th
e
f
r
a
m
e
w
o
r
k
o
f
L
E
AC
H
p
r
o
to
co
l
an
d
c
o
m
p
ar
at
iv
e
p
er
f
o
r
m
a
n
ce
a
n
al
y
s
i
s
h
as
al
s
o
b
ee
n
p
er
f
o
r
m
ed
b
o
th
f
o
r
M
G
-
L
E
AC
H
a
n
d
L
E
AC
H
p
r
o
t
o
co
l.
T
h
e
p
r
o
p
o
s
e
d
r
o
u
tin
g
alg
o
r
it
h
m
h
a
s
b
ee
n
s
i
m
u
lated
u
s
in
g
M
A
T
L
A
B
to
v
er
if
y
t
h
e
e
f
f
icien
c
y
i
n
en
h
a
n
ci
n
g
n
et
w
o
r
k
li
f
e
ti
m
e.
A
cr
itical
e
v
alu
a
tio
n
o
f
r
o
u
t
in
g
al
g
o
r
ith
m
i
s
co
n
d
u
cted
t
o
d
eter
m
i
n
e
th
e
r
elev
a
n
ce
a
n
d
ap
p
licab
ilit
y
in
in
cr
ea
s
i
n
g
n
e
t
w
o
r
k
li
f
e
ti
m
e.
Si
m
u
la
tio
n
r
e
s
u
lt
s
co
n
f
ir
m
e
d
th
at
it
h
a
s
p
er
f
o
r
m
ed
b
etter
th
a
n
L
E
A
C
H
an
d
en
h
a
n
ce
d
n
et
w
o
r
k
lif
e
ti
m
e.
T
h
e
f
u
t
u
r
e
r
esear
ch
i
s
n
ee
d
ed
o
n
t
h
e
s
ec
u
r
it
y
o
f
th
is
i
m
p
r
o
v
ed
p
r
o
to
co
l.
ACK
NO
WL
E
D
G
E
M
E
NT
S
T
h
e
au
th
o
r
s
ar
e
v
er
y
m
u
c
h
t
h
an
k
f
u
l
to
th
e
u
n
a
n
i
m
o
u
s
r
e
v
ie
w
er
s
o
f
th
e
p
ap
er
an
d
ed
ito
r
s
o
f
th
e
j
o
u
r
n
al
f
o
r
th
eir
co
n
s
tr
u
cti
v
e
a
n
d
h
elp
f
u
l c
o
m
m
e
n
t
s
th
at
i
m
p
r
o
v
ed
th
e
q
u
alit
y
o
f
t
h
e
p
ap
er
.
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
MG
-
lea
ch
:
a
n
en
h
a
n
ce
d
le
a
c
h
p
r
o
to
co
l fo
r
w
ir
eless
s
en
s
o
r
n
etw
o
r
k
(
Hich
a
m
Ou
ld
z
ir
a
)
3145
RE
F
E
R
E
NC
E
S
[1
]
S
.
Du
tt
,
G
.
Ka
u
r,
a
n
d
S
.
A
g
ra
w
a
l,
“
En
e
rg
y
E
ff
icie
n
t
S
e
c
to
r
-
Ba
se
d
Clu
ste
ri
n
g
P
r
o
t
o
c
o
l
f
o
r
He
tero
g
e
n
e
o
u
s
W
S
N,”
in
Pr
o
c
e
e
d
in
g
s
o
f
2
n
d
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
C
o
mm
u
n
ic
a
t
io
n
,
Co
m
p
u
ti
n
g
a
n
d
Ne
two
rk
in
g
,
v
o
l.
4
6
,
C.
R
.
Krish
n
a
,
M
.
Du
tt
a
,
a
n
d
R.
Ku
m
a
r,
Ed
s.
S
in
g
a
p
o
re
:
S
p
rin
g
e
r
S
i
n
g
a
p
o
re
,
p
p
.
1
1
7
–
1
2
5
,
2
0
1
9
.
[2
]
C.
Zh
a
n
,
Y.
Ze
n
g
,
a
n
d
R.
Z
h
a
n
g
,
“
En
e
rg
y
-
Eff
ici
e
n
t
Da
ta
Co
ll
e
c
ti
o
n
i
n
UA
V
E
n
a
b
led
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
,
”
IEE
E
W
ire
les
s Co
mm
u
n
ica
t
io
n
s
L
e
tt
e
rs
,
v
o
l.
7
,
n
o
.
3
,
p
p
.
3
2
8
–
3
3
1
,
Ju
n
.
2
0
1
8
.
[3
]
D.
Ca
c
c
iag
r
a
n
o
,
R.
Cu
lm
o
n
e
,
M
.
M
ich
e
letti
,
a
n
d
L
.
M
o
sta
rd
a
,
“
En
e
rg
y
-
Eff
ici
e
n
t
Clu
ste
rin
g
f
o
r
W
irele
ss
S
e
n
so
r
De
v
ice
s
in
In
tern
e
t
o
f
T
h
in
g
s,”
in
P
e
rf
o
rm
a
b
il
it
y
in
In
tern
e
t
o
f
T
h
in
g
s,
F
.
A
l
-
T
u
r
j
m
a
n
,
Ed
.
Ch
a
m
:
S
p
rin
g
e
r
In
tern
a
ti
o
n
a
l
P
u
b
l
ish
i
n
g
,
p
p
.
5
9
–
80
,
2
0
1
9
.
[4
]
G
.
X
u
,
W
.
S
h
e
n
,
a
n
d
X
.
W
a
n
g
,
“
A
p
p
li
c
a
ti
o
n
s
o
f
W
irele
ss
S
e
n
so
r
Ne
t
w
o
rk
s
in
M
a
rin
e
En
v
iro
n
m
e
n
t
M
o
n
i
to
ri
n
g
:
A
S
u
rv
e
y
,
”
S
e
n
so
rs
,
v
o
l.
1
4
,
n
o
.
9
,
p
p
.
1
6
9
3
2
–
1
6
9
5
4
,
S
e
p
.
2
0
1
4
.
[5
]
M
.
S
u
d
h
e
e
r,
“
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
f
o
r
Disa
ste
r
M
o
n
it
o
ri
n
g
,
”
in
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s:
A
p
p
li
c
a
ti
o
n
-
Ce
n
tri
c
De
sig
n
,
Y.
K.
T
a
n
,
E
d
.
I
n
T
e
c
h
,
2
0
1
0
.
[6
]
S
.
Be
ra
,
S
.
M
isra
,
S
.
K.
Ro
y
,
a
n
d
M
.
S
.
O
b
a
id
a
t,
“
S
o
f
t
-
W
S
N:
S
o
f
t
w
a
r
e
-
De
f
in
e
d
W
S
N
M
a
n
a
g
e
m
e
n
t
S
y
ste
m
f
o
r
Io
T
A
p
p
li
c
a
ti
o
n
s,”
IEE
E
S
y
ste
ms
J
o
u
rn
a
l
,
v
o
l.
1
2
,
n
o
.
3
,
p
p
.
2
0
7
4
–
2
0
8
1
,
S
e
p
.
2
0
1
8
.
[7
]
M
.
P
a
ra
m
e
s
w
a
ri
a
n
d
M
.
B.
M
o
se
s,
“
On
li
n
e
m
e
a
su
re
m
e
n
t
o
f
w
a
t
e
r
q
u
a
li
ty
a
n
d
re
p
o
rti
n
g
sy
ste
m
u
sin
g
p
ro
m
in
e
n
t
ru
le
c
o
n
tro
ll
e
r
b
a
se
d
o
n
a
q
u
a
c
a
re
-
IOT
,
”
De
sig
n
Au
to
ma
ti
o
n
f
o
r
Emb
e
d
d
e
d
S
y
ste
ms
,
v
o
l.
2
2
,
n
o
.
1
–
2
,
p
p
.
2
5
–
4
4
,
Ju
n
.
2
0
1
8
.
[8
]
H.
Na
v
a
rro
-
He
ll
ín
,
R.
T
o
rre
s
-
S
á
n
c
h
e
z
,
F
.
S
o
to
-
V
a
ll
e
s,
C.
A
lb
a
lad
e
jo
-
P
é
re
z
,
J.
A
.
L
ó
p
e
z
-
Riq
u
e
lm
e
,
a
n
d
R.
Do
m
in
g
o
-
M
ig
u
e
l,
“
A
w
irele
ss
se
n
so
rs
a
rc
h
it
e
c
tu
re
f
o
r
e
f
f
icie
n
t
irri
g
a
ti
o
n
w
a
ter
m
a
n
a
g
e
m
e
n
t,
”
Ag
ri
c
u
lt
u
ra
l
W
a
ter
M
a
n
a
g
e
me
n
t
,
v
o
l.
1
5
1
,
p
p
.
6
4
–
7
4
,
M
a
r.
2
0
1
5
.
[9
]
D.
Jia
n
g
,
Z.
Xu
,
a
n
d
Z.
L
v
,
“
A
m
u
lt
ica
st
d
e
li
v
e
ry
a
p
p
ro
a
c
h
w
it
h
m
in
im
u
m
e
n
e
r
g
y
c
o
n
su
m
p
ti
o
n
f
o
r
w
irele
ss
m
u
lt
i
-
h
o
p
n
e
tw
o
rk
s,”
T
e
lec
o
mm
u
n
ica
ti
o
n
S
y
ste
ms
,
v
o
l.
6
2
,
n
o
.
4
,
p
p
.
7
7
1
–
7
8
2
,
A
u
g
.
2
0
1
6
.
[1
0
]
H.
Ya
n
h
u
a
a
n
d
X
.
Zh
a
n
g
,
“
A
g
g
r
e
g
a
ti
o
n
T
re
e
Ba
se
d
Da
ta
Ag
g
re
g
a
ti
o
n
A
lg
o
rit
h
m
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
O
n
li
n
e
E
n
g
i
n
e
e
rin
g
(
iJO
E)
,
v
o
l.
1
2
,
n
o
.
0
6
,
p
.
1
0
,
Ju
n
.
2
0
1
6
.
[1
1
]
G
.
Ha
n
,
Y.
Do
n
g
,
H.
G
u
o
,
L
.
S
h
u
,
a
n
d
D.
W
u
,
“
Cro
ss
-
lay
e
r
o
p
t
im
iz
e
d
ro
u
t
in
g
in
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
w
it
h
d
u
ty
c
y
c
l
e
a
n
d
e
n
e
rg
y
h
a
rv
e
stin
g
:
Op
ti
m
ize
d
g
e
o
g
ra
p
h
ic
n
o
d
e
-
d
isjo
i
n
t
m
u
lt
ip
a
th
ro
u
ti
n
g
a
lg
o
ri
th
m
,
”
W
ire
l
e
ss
Co
mm
u
n
ica
ti
o
n
s a
n
d
M
o
b
il
e
C
o
mp
u
ti
n
g
,
v
o
l
.
1
5
,
n
o
.
1
6
,
p
p
.
1
9
5
7
–
1
9
8
1
,
No
v
.
2
0
1
5
.
[1
2
]
H.
Ja
d
id
o
les
lam
y
,
“
A
Hi
e
ra
rc
h
ic
a
l
In
tru
si
o
n
De
tec
ti
o
n
A
rc
h
it
e
c
tu
re
f
o
r
W
ir
e
les
s
S
e
n
so
r
Ne
t
w
o
rk
s,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Ne
two
rk
S
e
c
u
rity &
Its
Ap
p
li
c
a
ti
o
n
s,
v
o
l.
3
,
n
o
.
5
,
p
p
.
1
3
1
–
1
5
4
,
S
e
p
.
2
0
1
1
.
[1
3
]
M
.
Ha
m
m
o
u
d
e
h
a
n
d
R.
Ne
wm
a
n
,
“
A
d
a
p
ti
v
e
ro
u
ti
n
g
in
w
irele
ss
s
e
n
so
r
n
e
tw
o
rk
s:
Qo
S
o
p
ti
m
isa
ti
o
n
f
o
r
e
n
h
a
n
c
e
d
a
p
p
li
c
a
ti
o
n
p
e
rf
o
r
m
a
n
c
e
,
”
In
fo
rm
a
ti
o
n
F
u
sio
n
,
v
o
l
.
2
2
,
p
p
.
3
–
1
5
,
M
a
r.
2
0
1
5
.
[1
4
]
E.
F
a
d
e
l
e
t
a
l.
,
“
A
su
rv
e
y
o
n
w
ire
les
s
se
n
so
r
n
e
tw
o
rk
s
f
o
r
s
m
a
rt
g
ri
d
,
”
Co
mp
u
ter
Co
mm
u
n
ica
ti
o
n
s
,
v
o
l.
7
1
,
p
p
.
2
2
–
3
3
,
N
o
v
.
2
0
1
5
.
[1
5
]
S
.
P
e
n
g
a
n
d
C.
P
.
L
o
w
,
“
En
e
r
g
y
n
e
u
tral
d
irec
ted
d
if
f
u
sio
n
f
o
r
e
n
e
rg
y
h
a
rv
e
stin
g
w
irele
s
s
se
n
so
r
n
e
tw
o
rk
s,”
Co
mp
u
ter
C
o
mm
u
n
ica
ti
o
n
s,
v
o
l.
6
3
,
p
p
.
4
0
–
5
2
,
Ju
n
.
2
0
1
5
.
[1
6
]
De
p
a
rtme
n
t
o
f
Co
m
p
u
ter
S
c
ien
c
e
&
En
g
in
e
e
rin
g
,
M
.
M
.
Un
iv
e
rsit
y
,
S
a
d
o
p
u
r
,
Am
b
a
la,
In
d
ia,
J.
G
ro
v
e
r,
M
.
S
h
a
rm
a
,
a
n
d
S
.
S
h
ik
h
a
,
“
Re
li
a
b
le
S
P
IN
i
n
W
irele
ss
S
e
n
so
r
Ne
t
w
o
rk
:
A
R
e
v
ie
w
,
”
IOS
R
J
o
u
rn
a
l
o
f
Co
mp
u
ter
En
g
i
n
e
e
rin
g
,
v
o
l.
1
6
,
n
o
.
6
,
p
p
.
7
9
–
8
3
,
2
0
1
4
.
[1
7
]
A
.
N.
P
a
tel,
P
.
N.
Ji
,
J.
P
.
Ju
e
,
a
n
d
T
.
W
a
n
g
,
“
A
n
a
tu
ra
ll
y
-
in
sp
ired
a
lg
o
rit
h
m
f
o
r
Ro
u
ti
n
g
,
W
a
v
e
len
g
th
a
ss
ig
n
m
e
n
t,
a
n
d
S
p
e
c
tru
m
A
ll
o
c
a
ti
o
n
in
f
lex
i
b
le
g
rid
W
DM
n
e
t
w
o
rk
s,”
in
2
0
1
2
IEE
E
Glo
b
e
c
o
m
W
o
rk
sh
o
p
s,
A
n
a
h
e
i
m
,
C
A
,
USA
,
p
p
.
3
4
0
–
3
4
5
,
2
0
1
2
.
[1
8
]
R.
A
.
Ro
se
li
n
e
a
n
d
P
.
S
u
m
a
th
i,
“
L
o
c
a
l
c
lu
ste
rin
g
a
n
d
th
re
sh
o
l
d
se
n
siti
v
e
ro
u
ti
n
g
a
lg
o
rit
h
m
f
o
r
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s,”
in
2
0
1
2
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
De
v
ice
s,
Circ
u
it
s
a
n
d
S
y
ste
ms
(
ICDCS
)
,
Co
im
b
a
to
re
,
p
p
.
3
6
5
–
3
6
9
,
2
0
1
2
.
[1
9
]
W
.
B.
He
in
z
e
l
m
a
n
,
A
.
P
.
Ch
a
n
d
ra
k
a
s
a
n
,
a
n
d
H.
Ba
lak
rish
n
a
n
,
“
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
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