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u
it
th
at
is
class
if
ied
as
a
d
r
u
p
e
r
ath
er
th
an
a
r
ea
l
n
u
t.
Dr
ie
d
,
cu
r
e
d
,
a
n
d
f
r
esh
v
er
s
io
n
s
ar
e
co
m
m
er
cially
av
ailab
le.
I
n
I
n
d
ia,
c
o
m
m
er
cial
cu
ltiv
atio
n
o
f
t
h
e
ar
ec
a
n
u
t
h
as
b
ee
n
m
o
r
e
s
u
cc
e
s
s
f
u
l.
T
h
is
n
u
t
p
alm
f
alls
to
th
e
"Ar
ec
ac
ea
e"
class
an
d
th
e
"Ar
ec
a
L
"
g
en
u
s
.
Ker
ala,
Me
g
h
alay
a
Ass
am
,
T
am
il
Nad
u
,
an
d
Kar
n
atak
aa
r
e
am
o
n
g
t
h
e
s
tates
th
at
cu
ltiv
ate
th
e
Ar
ec
an
u
tc
r
o
p
.
Ar
ec
an
u
ts
m
ay
b
e
c
u
ltiv
ated
in
a
v
ar
iety
o
f
s
o
il
ty
p
es.
T
h
is
cr
o
p
,
o
n
th
e
o
th
e
r
h
an
d
,
d
o
es
b
est
o
n
well
-
d
r
ain
ed
s
o
ils
w
ith
p
len
ty
o
f
o
r
g
an
ic
m
atter
.
T
o
av
o
id
s
u
n
b
u
r
n
,
p
r
o
p
e
r
s
h
i
e
l
d
i
n
g
f
r
o
m
t
h
e
s
u
n
'
s
r
a
y
s
f
r
o
m
t
h
e
w
e
s
t
is
r
e
q
u
i
r
e
d
.
B
e
f
o
r
e
p
l
a
n
t
i
n
g
a
r
e
ca
n
u
t
s
e
e
d
l
i
n
g
s
,
f
as
t
-
g
r
o
w
i
n
g
s
h
a
d
e
t
r
e
es
s
h
o
u
l
d
b
e
p
la
n
t
e
d
o
n
t
h
e
s
o
u
t
h
e
r
n
a
n
d
w
es
t
e
r
n
s
i
d
es
.
T
h
is
p
al
m
n
u
t
t
r
e
e
is
s
u
s
c
e
p
t
i
b
l
e
t
o
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at
e
r
s
h
o
r
t
a
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e
s
a
n
d
s
h
o
u
l
d
o
n
l
y
b
e
c
u
l
t
i
v
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t
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d
i
n
a
r
e
a
s
wi
t
h
a
d
e
q
u
a
t
e
i
r
r
i
g
a
t
i
o
n
.
A
w
e
l
l
-
d
i
s
t
r
i
b
u
te
d
y
e
a
r
l
y
r
a
i
n
f
a
l
l
o
f
7
5
0
t
o
4
5
0
0
m
m
is
r
e
q
u
i
r
e
d
f
o
r
t
h
is
c
r
o
p
.
T
h
is
c
r
o
p
m
a
y
b
e
p
r
o
d
u
c
e
d
a
t
e
le
v
a
t
i
o
n
s
as
h
i
g
h
a
s
1
0
0
0
m
e
t
e
r
s
a
b
o
v
e
s
e
a
l
e
v
el
(
M
S
L
)
.
T
h
e
r
e
c
o
m
m
en
d
e
d
t
e
m
p
e
r
a
t
u
r
e
r
a
n
g
e
f
o
r
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t
s
g
r
o
w
t
h
a
n
d
y
i
e
l
d
i
s
1
0
°C
t
o
4
0
°
C
[
6
]
.
W
ir
eles
s
s
en
s
o
r
n
etwo
r
k
s
(
W
SN)
ar
e
a
co
m
m
o
n
u
s
e
o
f
in
f
o
r
m
atio
n
tech
n
o
lo
g
y
in
ag
r
icu
ltu
r
e,
ca
p
ab
le
o
f
m
o
n
ito
r
in
g
s
o
il
i
n
f
o
r
m
atio
n
in
th
e
r
eg
io
n
s
o
f
i
n
ter
est
an
d
en
co
u
r
ag
in
g
th
e
t
r
ad
itio
n
al
ir
r
ig
atio
n
s
y
s
tem
.
B
y
g
ath
er
in
g
d
ata
d
u
r
in
g
th
e
ag
r
icu
ltu
r
al
p
r
o
d
u
ctio
n
p
r
o
ce
s
s
,
it
ca
n
im
p
r
o
v
e
ir
r
i
g
atio
n
m
et
h
o
d
s
a
n
d
m
ak
e
ag
r
ic
u
ltu
r
e
s
m
ar
ter
[
7
]
.
W
SNs
ar
e
cr
itical
in
th
e
n
o
t
io
n
o
f
s
m
ar
t
ag
r
icu
lt
u
r
e
s
in
ce
th
ey
m
o
n
ito
r
a
n
d
g
ath
er
in
ter
est
d
ata
in
ag
r
ic
u
ltu
r
al
f
ield
s
f
o
r
u
s
e
in
n
u
m
er
o
u
s
ap
p
licatio
n
s
.
Sm
ar
t
ag
r
icu
ltu
r
e
m
a
k
es
s
ig
n
if
ican
t
ef
f
o
r
ts
to
r
ea
lize
p
r
ec
is
io
n
ir
r
ig
atio
n
,
f
er
tili
ze
r
s
,
an
d
p
esti
cid
es
b
ased
o
n
th
e
cr
o
p
d
ev
elo
p
m
en
t
m
o
d
el
a
n
d
W
SNs
in
ag
r
icu
ltu
r
e
to
r
ed
u
ce
wate
r
waste,
lo
w
s
o
il
f
er
tili
ty
,
f
er
tili
ze
r
ab
u
s
e,
an
d
illn
ess
es.
Sen
s
o
r
n
o
d
es
in
W
SNs
p
lan
ted
in
f
ie
ld
s
ar
e
ca
p
ab
le
o
f
r
eg
u
lar
l
y
r
e
lay
in
g
g
ath
er
e
d
s
o
il
in
f
o
r
m
ati
o
n
d
ata
to
th
e
s
in
k
n
o
d
e
th
r
o
u
g
h
wir
eless
co
m
m
u
n
icatio
n
[
8
]
.
W
SNs
ar
e
u
t
ilize
d
to
ca
p
tu
r
e
tem
p
er
atu
r
e,
h
u
m
id
ity
,
s
o
il
m
o
is
tu
r
e
co
n
ten
t,
an
d
win
d
s
p
ee
d
d
ata
in
an
ag
r
icu
ltu
r
al
ap
p
licatio
n
,
ac
co
r
d
in
g
to
th
e
au
th
o
r
s
.
Fo
r
cr
o
p
s
,
a
W
SNs
-
b
ased
I
o
T
ir
r
ig
atio
n
co
n
tr
o
l
s
y
s
tem
is
s
u
g
g
ested
to
m
an
ag
e
th
e
m
o
is
tu
r
e
co
n
ten
t
o
f
th
e
s
o
il
f
o
r
s
m
ar
t
f
ar
m
s
,
wh
ich
m
ay
s
u
cc
ess
f
u
lly
c
u
t
c
o
s
ts
an
d
b
o
o
s
t
ag
r
icu
ltu
r
al
o
u
t
p
u
t
[
9
]
.
Fig
u
r
e
1
s
h
o
ws
th
e
ty
p
ical
ar
ch
itectu
r
e
o
f
W
SN
b
ased
ag
r
icu
ltu
r
e
ar
ch
it
ec
tu
r
e
wh
er
e
th
e
d
ata
ar
e
s
en
s
ed
at
th
e
g
r
o
u
n
d
a
n
d
th
r
o
u
g
h
th
e
in
ter
n
et,
it
is
s
en
t to
th
e
in
ter
n
et
clo
u
d
wh
e
r
e
th
e
d
ata
ca
n
b
e
r
ea
d
an
d
an
al
y
ze
d
th
r
o
u
g
h
an
a
p
p
licatio
n
.
Fig
u
r
e
1.
T
y
p
ical
W
SN
ar
ch
itectu
r
e
f
o
r
p
r
ec
is
io
n
f
ar
m
in
g
W
SN
s
ar
e
co
n
s
tan
tly
i
n
d
a
n
g
er
o
f
f
au
lts
an
d
f
ailu
r
es
d
u
e
t
o
th
eir
r
eso
u
r
ce
-
co
n
s
tr
ain
ed
n
atu
r
e
an
d
u
n
iq
u
e
p
r
o
p
er
ties
.
T
h
e
r
ea
s
o
n
f
o
r
th
is
is
th
at
th
e
g
at
h
er
in
g
an
d
s
en
d
in
g
o
f
d
ata
co
n
s
u
m
e
th
e
m
ajo
r
ity
o
f
t
h
e
s
en
s
o
r
n
etwo
r
k
'
s
en
er
g
y
.
As
a
r
esu
lt,
th
e
m
ajo
r
it
y
o
f
th
e
s
o
lu
tio
n
s
p
r
o
p
o
s
ed
ce
n
ter
e
d
o
n
en
er
g
y
-
awa
r
e
co
m
p
u
tin
g
with
d
is
p
er
s
ed
d
at
a
co
llectin
g
.
C
lu
s
ter
in
g
is
an
o
th
er
ex
ten
s
iv
ely
u
s
ed
en
e
r
g
y
r
eser
v
atio
n
s
tr
ateg
y
in
W
SNs
.
E
ac
h
zo
n
e
ch
o
o
s
es
a
m
aster
n
o
d
e
(
clu
s
ter
h
ea
d
(
C
H)
)
to
g
ath
er
d
ata
f
r
o
m
all
n
o
d
es
an
d
tr
a
n
s
f
er
it
to
th
e
B
S.
C
H
o
n
ly
co
m
m
u
n
icate
s
with
th
e
B
S
-
m
an
ag
ed
n
etwo
r
k
to
p
o
lo
g
y
,
wh
ich
s
av
es
a
lo
t
o
f
en
er
g
y
.
Sen
s
o
r
n
o
d
es
in
W
SNs
ty
p
ica
lly
o
p
er
ate
in
a
co
n
tin
u
o
u
s
s
e
n
s
in
g
an
d
p
r
o
ce
s
s
in
g
m
o
d
e.
I
t
also
co
n
d
u
cts
d
ata
ag
g
r
eg
atio
n
an
d
f
o
r
war
d
in
g
o
f
d
etec
ted
d
ata,
lo
wer
in
g
n
o
d
e
en
er
g
y
co
n
s
u
m
p
tio
n
,
an
d
ex
te
n
d
in
g
n
etwo
r
k
life
.
Nu
m
er
o
u
s
tech
n
iq
u
es
h
av
e
b
e
en
d
ev
el
o
p
ed
to
r
e
d
u
ce
en
er
g
y
u
s
ag
e
a
n
d
e
x
ten
d
n
etwo
r
k
li
f
e.
T
h
e
m
ajo
r
ity
o
f
S
e
n
s
o
r
N
o
d
e
s
W
SN
G
a
t
ew
a
y
I
n
t
er
n
et
A
p
p
l
i
c
a
t
i
o
n
WS
N
In
tern
e
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
fficien
t d
a
ta
s
en
s
in
g
a
n
d
mo
n
ito
r
in
g
mo
d
el
fo
r
a
r
ec
a
n
u
t
…
(
N
ir
a
n
ja
n
Mu
r
th
y
C
h
a
n
d
r
a
s
h
ek
a
r
a
p
p
a
)
1551
th
ese
ap
p
r
o
ac
h
es
h
a
v
e
p
r
im
ar
i
ly
f
o
c
u
s
ed
o
n
e
n
er
g
y
d
is
s
ip
atio
n
.
Var
i
o
u
s
p
r
o
to
co
ls
p
r
o
v
id
e
d
if
f
er
e
n
t
s
tep
s
f
o
r
co
n
tr
o
llin
g
a
n
d
m
o
n
ito
r
i
n
g
n
et
wo
r
k
o
p
er
atio
n
s
[
1
0
]
,
[
1
1
]
.
A.
Mo
tiv
atio
n
an
d
co
n
tr
i
b
u
tio
n
o
f
r
esear
ch
wo
r
k
Far
m
in
g
is
co
n
s
id
er
ed
as
a
f
o
u
n
d
atio
n
o
f
an
y
n
atio
n
al
as
well
as
h
ar
m
o
n
io
u
s
s
o
ciety
an
d
f
o
r
th
e
p
ast
s
ev
er
al
y
ea
r
s
’
g
o
v
er
n
m
en
t
h
as
b
ee
n
f
o
cu
s
in
g
o
n
p
r
ec
is
io
n
f
a
r
m
in
g
;
m
o
r
eo
v
er
,
th
e
r
e
ar
e
v
a
r
io
u
s
ty
p
es
o
f
n
u
ts
p
r
o
d
u
ce
d
in
I
n
d
ia,
ar
ec
a
n
u
t
is
o
n
e
o
f
th
e
lar
g
est
p
r
o
d
u
c
tiv
ities
in
o
u
r
c
o
u
n
tr
y
.
Op
ti
m
u
m
av
ailab
ilit
y
o
f
n
u
tr
ien
ts
is
ess
en
tial
f
o
r
th
e
d
if
f
er
en
t
b
io
p
h
y
s
ical
p
r
o
ce
s
s
es
s
u
ch
as
p
lan
t
g
r
o
wth
,
s
ee
d
s
g
e
r
m
in
atio
n
,
n
u
tr
ie
n
t
cy
cle
an
d
also
to
s
u
s
tain
th
e
s
o
il
b
io
d
iv
e
r
s
ity
;
also
,
to
ac
h
ie
v
e
th
e
p
r
ec
is
io
n
f
a
r
m
in
g
en
v
i
r
o
n
m
en
tal
f
ac
to
r
lik
e
tem
p
er
atu
r
e
an
d
h
u
m
i
d
ity
n
e
ed
s
to
n
o
t
o
n
ly
s
en
s
ed
b
u
t
m
o
n
ito
r
an
d
g
en
e
r
ate
th
e
alar
m
as
well.
T
h
u
s,
m
o
tiv
ated
b
y
t
h
e
ap
p
licatio
n
an
d
co
m
m
e
r
cial
asp
ec
t,
th
is
r
esear
ch
wo
r
k
f
o
cu
s
es
n
o
n
d
e
s
ig
n
in
g
th
e
en
er
g
y
awa
r
e
E
DSM
m
o
d
el;
f
u
r
th
er
c
o
n
tr
ib
u
tio
n
o
f
th
e
r
esear
ch
wo
r
k
is
h
ig
h
lig
h
ted
th
r
o
u
g
h
th
e
p
o
in
ts
: i)
W
e
d
es
ig
n
an
d
d
ev
el
o
p
ef
f
icien
t
d
ata
s
en
s
in
g
an
d
m
o
n
ito
r
in
g
(
E
DSM
)
m
o
d
el
to
ac
h
iev
e
t
h
e
p
r
ec
is
io
n
f
ar
m
in
g
o
f
ar
ec
a
nut
;
ii)
E
DSM
co
m
p
r
is
es
f
o
u
r
d
is
tin
ctiv
estep
s
;
th
e
f
ir
s
t
s
t
ep
in
clu
d
es
th
e
g
ath
er
in
g
i
n
f
o
r
m
atio
n
ab
o
u
t
th
e
s
en
s
o
r
s
,
en
er
g
y
,
an
d
o
th
e
r
p
r
e
lim
in
ar
ies,
th
e
s
ec
o
n
d
s
tep
in
v
o
lv
es
th
e
s
en
s
in
g
o
f
d
at
a,
th
e
th
ir
d
s
tep
i
n
v
o
lv
es
th
e
m
o
n
ito
r
in
g
an
d
aler
t
g
en
e
r
atio
n
,
f
o
u
r
t
h
an
d
last
s
tep
in
clu
d
es
th
e
o
p
tim
izatio
n
o
f
p
a
ck
et
s
ize
alo
n
g
with
m
o
n
ito
r
in
g
an
d
aler
t
g
e
n
er
ati
o
n
;
iii)
E
DSM
m
in
im
izes
en
er
g
y
co
n
s
u
m
p
tio
n
a
n
d
m
o
n
ito
r
s
ess
en
tial
f
ac
to
r
s
s
u
ch
as
tem
p
er
at
u
r
e,
h
u
m
i
d
ity
,
an
d
NPK
v
alu
e
;
an
d
iv
)
C
o
m
p
ar
ativ
e
an
aly
s
is
is
ca
r
r
i
ed
o
u
t
to
p
r
o
v
e
th
e
m
o
d
el
ef
f
icien
c
y
an
d
E
DSM
o
u
tp
er
f
o
r
m
s
th
e
ex
is
tin
g
m
o
d
el
with
s
ig
n
if
ican
t im
p
r
o
v
is
atio
n
.
T
h
is
r
esear
ch
wo
r
k
is
o
r
g
an
i
ze
d
in
s
u
ch
a
way
th
at
th
e
s
ec
tio
n
1
s
tar
ts
with
th
e
b
ac
k
g
r
o
u
n
d
an
d
im
p
o
r
tan
ce
o
f
p
r
ec
is
io
n
f
ar
m
in
g
;
f
u
r
th
er
in
th
e
s
am
e
s
ec
tio
n
im
p
o
r
ta
n
ce
o
f
ar
ec
a
n
u
t
f
ar
m
i
n
g
an
d
th
e
r
eq
u
ir
em
e
n
t
f
o
r
p
r
ec
is
io
n
f
ar
m
in
g
is
d
is
cu
s
s
ed
.
Fu
r
th
er
m
o
r
e,
s
en
s
in
g
tec
h
n
o
lo
g
y
b
ased
o
n
W
SN
is
d
is
cu
s
s
ed
an
d
th
e
s
ec
tio
n
1
en
d
s
with
th
e
m
o
tiv
atio
n
an
d
co
n
tr
ib
u
tio
n
o
f
t
h
e
r
esear
ch
ar
ticle.
I
n
th
e
s
ec
tio
n
2
,
s
ev
er
al
r
elate
d
wo
r
k
s
f
o
r
p
r
ec
is
io
n
f
ar
m
in
g
alo
n
g
with
s
en
s
in
g
tech
n
o
lo
g
ies
ar
e
r
ev
iewe
d
an
d
s
h
o
r
tco
m
in
g
s
o
f
th
e
s
am
e
ar
e
h
ig
h
lig
h
te
d
.
T
h
e
s
ec
tio
n
3
p
r
esen
ts
th
e
m
ath
em
atica
l
m
o
d
elin
g
o
f
th
e
p
r
o
p
o
s
ed
m
eth
o
d
o
lo
g
y
alo
n
g
with
th
e
alg
o
r
ith
m
;
th
e
f
u
r
t
h
er
m
o
d
el
is
ev
alu
at
ed
in
th
e
s
ec
tio
n
4
alo
n
g
with
a
p
er
f
o
r
m
an
c
e
co
m
p
ar
is
o
n
with
a
n
ex
is
tin
g
m
o
d
el.
2.
RE
L
AT
E
D
WO
RK
T
h
is
s
ec
tio
n
r
ev
iews
th
e
v
ar
i
o
u
s
ef
f
icien
t
s
en
s
in
g
m
ec
h
an
is
m
d
ev
elo
p
ed
;
i
n
g
e
n
er
al,
m
o
s
t
o
f
th
e
m
eth
o
d
s
h
a
d
a
n
ap
p
r
o
ac
h
o
f
clu
s
ter
in
g
an
d
r
o
u
tin
g
;
th
e
m
o
s
t
well
-
k
n
o
wn
clu
s
ter
in
g
r
o
u
tin
g
m
ec
h
a
n
is
m
f
o
r
W
SN
s
is
lo
w
-
en
er
g
y
ad
ap
tiv
e
clu
s
ter
in
g
h
ier
ar
ch
y
(
L
E
AC
H)
[
1
2
]
.
I
n
L
E
AC
H,
th
e
C
H
i
s
ch
o
s
en
d
e
p
en
d
i
n
g
o
n
th
e
cu
r
r
en
t
r
o
u
n
d
'
s
lik
elih
o
o
d
;
a
s
a
r
esu
lt,
C
H
s
elec
t
io
n
is
n
o
t
ev
en
ly
s
p
r
ea
d
,
r
esu
ltin
g
in
u
n
c
o
n
n
ec
ted
n
o
d
es.
Mu
ltih
o
p
-
L
E
AC
H
[
1
3
]
is
a
m
o
d
if
icatio
n
o
f
th
e
L
E
AC
H
p
r
o
to
co
l
th
at
allo
ws
f
o
r
m
u
lti
-
h
o
p
in
ter
-
clu
s
ter
an
d
i
n
tr
a
-
clu
s
ter
c
o
m
m
u
n
icatio
n
.
Sen
s
o
r
s
co
llect
d
ata
an
d
co
m
m
u
n
icate
it
t
o
C
Hs
b
ased
o
n
th
e
tim
eo
u
t
d
u
r
atio
n
;
f
o
r
war
d
in
g
v
ex
in
g
m
ess
ag
es
ca
n
lead
to
a
n
ev
er
-
e
n
d
in
g
u
s
e
o
f
el
ec
tr
icity
.
An
o
th
e
r
m
o
d
if
ied
ty
p
e
o
f
L
E
AC
H
is
th
e
Qu
ad
r
atu
r
e
-
L
E
AC
H
(
Q
-
L
E
AC
H)
[
1
4
]
;
Q
-
L
E
AC
H
h
as
b
ee
n
en
h
a
n
ce
d
f
o
r
b
o
th
p
o
wer
m
a
n
ag
em
en
t
an
d
im
p
r
o
v
e
d
s
er
v
ice,
n
o
n
eth
eless
,
all
L
E
AC
H
m
o
d
if
icatio
n
s
ar
e
b
ased
o
n
h
ier
ar
ch
ical
clu
s
ter
in
g
,
b
u
t
h
ie
r
ar
ch
y
is
n
o
t
t
h
e
b
est
ap
p
r
o
ac
h
in
W
SNs
.
Fo
r
a
b
etter
s
elec
t
io
n
o
f
C
H
b
ased
o
n
r
em
ain
in
g
e
n
er
g
y
,
h
y
b
r
id
L
E
AC
H
[
1
5
]
,
[
1
6
]
is
em
p
lo
y
e
d
wh
er
e
C
H
is
ch
o
s
en
b
etwe
en
h
ig
h
a
n
d
lo
w
en
er
g
y
lev
els
u
s
in
g
th
r
esh
o
ld
co
n
d
itio
n
s
f
o
r
ea
ch
iter
atio
n
.
PEGA
SIS
[
1
7
]
h
as
elim
in
ated
all
o
f
L
E
AC
H
'
s
f
law
s
.
Fo
r
a
lead
er
t
o
s
en
d
d
ata
t
o
B
S,
ju
s
t
two
m
ess
ag
es
will
b
e
n
ec
es
s
ar
y
in
s
tead
o
f
th
e
twen
ty
m
e
s
s
ag
es
n
ec
ess
ar
y
in
L
E
AC
H
f
o
r
co
m
p
lete
co
v
er
ag
e.
Ho
wev
er
,
u
n
d
e
r
th
is
m
eth
o
d
,
s
o
m
e
s
u
p
er
f
lu
o
u
s
an
d
b
u
lk
y
m
ess
ag
es c
ir
cu
late
in
th
e
n
etwo
r
k
,
r
esu
ltin
g
i
n
n
o
d
e
e
n
er
g
y
lev
els
b
ein
g
r
ed
u
ce
d
.
C
E
E
R
[
1
8
]
is
an
o
th
er
m
u
lti
-
h
o
p
co
m
m
u
n
icatio
n
ar
ch
itectu
r
e
t
h
at
m
ay
b
e
u
s
ed
f
o
r
b
o
th
C
Hs
an
d
B
S.
T
h
is
m
eth
o
d
r
u
n
s
i
n
r
o
u
n
d
s
,
wi
th
ea
ch
n
o
d
e
ca
lcu
latin
g
its
f
itn
ess
f
u
n
ctio
n
b
ased
o
n
d
is
tan
ce
,
r
esid
u
al
en
er
g
y
,
an
d
p
r
o
b
ab
ilit
y
.
B
ased
o
n
th
e
Ge
n
etic
alg
o
r
ith
m
,
B
S
ch
o
o
s
es
C
H.
T
h
is
tech
n
iq
u
e,
o
n
th
e
o
th
er
h
a
n
d
,
f
ails
to
m
an
ag
e
th
e
al
g
o
r
it
h
m
an
d
ch
o
o
s
e
th
e
o
p
tim
u
m
p
at
h
.
SEP
in
[
1
9
]
h
as
b
ee
n
d
e
v
elo
p
ed
t
o
b
alan
ce
en
er
g
y
u
s
ag
e
in
f
o
g
s
u
p
p
o
r
ted
W
SNs
.
C
H
Sis
ch
o
s
en
d
ep
e
n
d
in
g
o
n
th
e
r
em
ain
in
g
en
er
g
y
a
n
d
d
is
tan
ce
s
t
r
av
eled
u
s
in
g
C
Hs.
Fo
r
th
e
m
ain
an
d
s
ec
o
n
d
ar
y
C
H
elec
tio
n
p
r
o
ce
s
s
es,
a
th
r
esh
o
ld
is
d
ef
in
e
d
f
o
r
v
e
r
if
y
in
g
e
n
er
g
y
a
n
d
o
th
er
c
h
ar
ac
ter
is
tics
.
SEP
'
s
s
u
cc
es
s
o
r
is
th
e
p
r
o
lo
n
g
SEP
[
2
0
]
p
r
o
to
co
l.
On
th
e
GPS
in
ter
f
ac
e,
a
l
o
ca
tio
n
-
b
ased
p
r
o
to
co
l
s
u
ch
a
s
th
e
ME
C
N
[
2
1
]
is
u
s
ed
to
co
m
p
u
te
s
u
b
-
n
etwo
r
k
s
with
th
e
least
am
o
u
n
t
o
f
en
er
g
y
.
W
h
en
th
e
n
etwo
r
k
is
d
is
p
er
s
ed
an
d
i
m
p
e
d
i
m
e
n
t
s
a
r
is
e
b
e
tw
e
e
n
n
e
i
g
h
b
o
r
i
n
g
n
o
d
e
s
,
f
a
i
l
u
r
e
h
a
p
p
e
n
s
.
A
n
o
t
h
e
r
l
o
c
a
t
i
o
n
-
b
as
e
d
p
r
o
t
o
c
o
l
is
g
l
o
b
a
l
a
s
s
e
s
s
m
e
n
t
o
f
f
u
n
c
t
i
o
n
i
n
g
(
GAF
)
[
2
2
]
,
wh
ich
was
cr
ea
ted
f
o
r
Mo
b
ile
Ad
h
o
c
n
etwo
r
k
s
a
n
d
th
e
n
u
p
d
ate
d
f
o
r
W
SN
s
.
No
d
es
o
f
th
e
v
i
r
tu
al
g
r
id
co
m
m
u
n
icate
with
o
n
e
an
o
th
er
in
p
r
ed
e
f
in
ed
z
o
n
es.
W
h
en
SN
m
o
b
ilit
y
is
co
m
b
in
ed
with
d
y
n
a
m
ically
c
h
an
g
in
g
to
p
o
lo
g
ies,
th
e
s
y
s
te
m
ap
p
ea
r
s
to
b
e
u
n
r
eliab
le.
Ge
o
g
r
ap
h
ic
an
d
e
n
er
g
y
awa
r
e
r
o
u
tin
g
(
GE
AR
)
[
2
3
]
g
en
er
ates
g
eo
g
r
a
p
h
ic
d
ata,
wh
i
ch
is
th
en
u
tili
ze
d
to
p
ick
C
H.
GE
AR
i
s
u
s
ef
u
l
f
o
r
n
etwo
r
k
m
an
ag
e
m
en
t
in
g
en
e
r
al,
b
u
t
it
is
n
o
t
s
u
g
g
ested
f
o
r
lo
w
-
en
er
g
y
c
o
m
m
u
n
icatio
n
n
etwo
r
k
s
s
u
ch
as
W
SN
s
.
SP
I
N
[
2
4
]
is
a
d
ata
-
ce
n
tr
ic
en
er
g
y
c
o
n
s
er
v
atio
n
tec
h
n
iq
u
e
in
wh
er
e
ea
ch
n
o
d
e
ac
ts
as
a
B
S.
Du
p
licate
d
ata
p
ac
k
ets
ar
e
d
elete
d
b
ase
d
o
n
r
o
u
tin
g
n
e
g
o
tiatio
n
.
A
n
eg
o
tiati
o
n
m
ess
ag
e,
o
n
th
e
o
th
er
h
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ca
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es
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
3
,
Ma
r
ch
20
22
:
1
5
4
9
-
1
5
6
2
1552
n
etwo
r
k
co
n
g
esti
o
n
.
C
OUG
AR
[
2
5
]
,
a
d
ata
-
ce
n
tr
ic
s
tr
ateg
y
th
at
o
r
g
an
izes
th
e
n
etwo
r
k
in
a
d
is
tr
ib
u
ted
d
atab
ase
s
y
s
tem
,
is
an
o
th
er
v
er
s
io
n
.
Ab
s
tr
ac
t
q
u
er
y
p
r
o
ce
s
s
in
g
is
u
s
ed
at
th
e
n
et
wo
r
k
lay
er
f
o
r
d
ata
co
llectin
g
,
ag
g
r
e
g
atio
n
,
a
n
d
f
o
r
war
d
in
g
.
W
SNs
r
eq
u
ir
e
lo
wer
lay
er
r
u
les f
o
r
ag
g
r
eg
atio
n
a
n
d
d
ata
f
o
r
war
d
in
g
,
b
u
t
th
e
C
OUGA
R
o
p
er
ates
o
n
th
e
h
ig
h
er
lay
er
wh
er
e
m
o
r
e
en
er
g
y
is
g
ath
er
ed
.
Ot
h
er
s
y
s
tem
s
p
r
o
v
id
e
n
u
m
er
o
u
s
p
ar
am
eter
s
f
o
r
b
a
lan
ce
d
C
H
s
elec
tio
n
an
d
s
im
ilar
clu
s
ter
s
,
in
clu
d
in
g
en
e
r
g
y
,
d
is
tan
ce
[
2
4
]
,
co
v
er
ag
e,
an
d
c
o
n
v
e
r
g
en
ce
r
e
g
io
n
s
[
2
6
]
.
A
d
elay
an
d
e
n
er
g
y
awa
r
e
co
o
r
d
in
atio
n
p
r
o
to
co
l
(
DE
AC
P
)
in
[
1
6
]
h
as
b
ee
n
s
u
g
g
ested
as
an
en
er
g
y
-
ef
f
icien
t
r
o
u
tin
g
p
r
o
to
co
l.
Dr
o
p
p
in
g
ch
an
ce
is
r
ed
u
ce
d
wh
en
all
clu
s
ter
m
em
b
er
s
u
s
e
a
q
u
eu
e
o
v
er
f
l
o
wn
r
o
u
tin
g
s
ch
em
e
.
I
t
co
n
tr
o
l
s
th
e
d
is
s
ip
atio
n
o
f
en
e
r
g
y
ac
r
o
s
s
all
n
o
d
es.
T
h
e
C
H
s
elec
tio
n
h
as
b
ee
n
im
p
r
o
v
ed
,
an
d
th
e
e
n
tire
r
e
g
io
n
is
co
v
er
ed
with
co
m
p
lete
c
o
n
n
ec
ti
o
n
an
d
litt
le
en
er
g
y
u
s
e
.
Ac
c
o
r
d
i
n
g
t
o
a
s
l
e
e
p
i
n
g
s
ch
e
d
u
l
e
,
a
n
o
d
e'
s
r
a
d
i
o
m
o
d
u
l
e
i
s
s
wi
t
c
h
e
d
o
f
f
f
o
r
a
s
p
e
c
i
f
i
c
am
o
u
n
t
o
f
t
i
m
e
[
2
7
]
.
Pre
s
en
ts
a
f
u
ll st
u
d
y
o
f
r
o
u
tin
g
in
W
SNs
an
d
I
o
T
.
W
an
et
a
l.
[
2
8
]
p
r
esen
ted
th
e
r
ec
en
t
d
e
v
elo
p
m
e
n
t
o
b
s
er
v
ed
in
th
e
I
o
T
d
o
m
ai
n
wh
ich
m
ain
ly
f
o
c
u
s
ed
o
n
th
e
v
ar
io
u
s
s
en
s
in
g
m
ec
h
an
is
m
s
o
m
e
o
f
th
em
f
o
cu
s
ed
o
n
clu
s
ter
in
g
an
d
s
o
m
e
o
f
th
e
m
wer
e
clu
s
ter
h
ea
d
b
ased
.
An
o
th
er
s
tate
-
b
ased
s
y
s
tem
is
th
e
en
er
g
y
-
ef
f
icien
t
s
leep
s
c
h
ed
u
lin
g
m
ec
h
an
i
s
m
with
s
im
ilar
ity
m
ea
s
u
r
e
(
E
SS
M)
[
2
9
]
.
T
h
e
E
SS
M
m
eth
o
d
is
b
ased
o
n
s
wi
tch
in
g
a
n
o
d
e'
s
s
tatu
s
f
r
o
m
a
ctiv
e
to
s
leep
.
T
h
e
alg
o
r
ith
m
h
as
b
ee
n
d
esig
n
e
d
with
co
n
d
e
n
s
ed
s
en
s
o
r
d
ep
lo
y
m
en
t
in
m
in
d
,
m
ak
i
n
g
it
s
u
itab
le
f
o
r
cr
o
wd
e
d
W
SN
s
.
Ho
wev
er
,
with
a
d
is
tr
ib
u
ted
d
e
p
lo
y
m
e
n
t,
d
ata
co
r
r
elatio
n
will
b
e
lo
w,
an
d
t
h
e
n
etwo
r
k
wo
u
l
d
co
n
s
u
m
e
m
o
r
e
en
e
r
g
y
.
A
s
tate
-
b
ased
tech
n
iq
u
e
f
o
r
u
n
d
er
wate
r
ac
o
u
s
tic
s
en
s
o
r
n
etwo
r
k
s
is
an
ef
f
ec
tiv
e
s
ch
ed
u
lin
g
alg
o
r
ith
m
f
o
r
co
v
er
ag
e
co
n
tr
o
l
in
u
n
d
er
wate
r
ac
o
u
s
tic
s
en
s
o
r
n
etw
o
r
k
s
(
UASNs)
[
3
0
]
.
T
h
e
E
SAC
C
ac
tiv
e
-
s
leep
ap
p
r
o
ac
h
is
im
p
lem
en
ted
in
two
h
a
lv
es,
ea
ch
with
r
ed
u
n
d
an
t
n
o
d
es.
Fo
r
s
en
s
e,
a
m
em
etic
tech
n
iq
u
e
is
em
p
lo
y
ed
to
ac
tiv
ate
th
e
s
leep
s
tate,
wh
ile
ce
r
tain
n
o
d
es
will
b
e
in
an
ac
tiv
e
s
tate.
Du
r
in
g
n
etwo
r
k
ac
tiv
ities
,
t
h
e
d
r
o
wsy
n
o
d
es
ar
e
awa
k
en
ed
an
d
b
ec
o
m
e
Activ
e/L
iv
e.
T
h
e
in
tr
o
d
u
ctio
n
o
f
a
h
ar
v
esti
n
g
lay
er
in
W
SNs
h
as
b
ee
n
p
r
o
p
o
s
ed
in
A
m
eth
o
d
o
f
b
alan
ce
d
s
leep
s
ch
ed
u
lin
g
in
r
en
ewa
b
le
wir
eless
s
en
s
o
r
n
etwo
r
k
s
(
B
SS
R
)
[
3
1
]
.
Mo
r
eo
v
er
,
f
ew
r
ec
en
t
ap
p
r
o
a
ch
es
[
3
2
]
-
[
3
4
]
f
o
ll
o
ws
th
e
d
y
n
am
ic
ap
p
r
o
ac
h
o
f
th
e
s
en
s
in
g
m
ec
h
an
is
m
in
th
e
d
if
f
er
en
t
ar
ea
o
f
ag
r
ic
u
ltu
r
e
s
u
ch
as
wate
r
m
an
ag
em
en
t,
l
o
ca
tio
n
-
b
ased
lo
n
g
-
ter
m
m
o
n
ito
r
i
n
g
;
th
ese
ap
p
r
o
ac
h
d
o
es
p
r
o
v
id
e
th
e
s
o
lu
tio
n
to
an
y
p
r
o
b
lem
in
ag
r
icu
lt
u
r
e.
Ho
wev
er
,
it
is
o
b
s
er
v
ed
th
r
o
u
g
h
th
e
r
elate
d
wo
r
k
th
at
all
th
ese
m
ec
h
an
is
m
s
eith
er
f
o
cu
s
o
n
a
s
in
g
le
s
c
en
ar
io
o
r
t
h
ey
ar
e
n
o
t
ef
f
icien
t e
n
o
u
g
h
t
o
b
e
d
ep
lo
y
e
d
in
r
ea
l
-
tim
e.
3.
P
RO
P
O
SE
D
M
E
T
H
O
D
Op
tim
u
m
av
ailab
ilit
y
o
f
n
u
tr
i
en
ts
is
es
s
en
tial
f
o
r
th
e
d
if
f
er
en
t
b
io
p
h
y
s
ical
p
r
o
ce
s
s
es
s
u
c
h
as
p
lan
t
g
r
o
wth
,
s
ee
d
s
g
er
m
in
atio
n
,
a
n
d
n
u
tr
ien
t
cy
cle
an
d
also
to
s
u
s
tain
th
e
s
o
il
b
io
d
iv
er
s
ity
;
also
,
to
ac
h
iev
e
th
e
p
r
ec
is
io
n
f
a
r
m
in
g
en
v
ir
o
n
m
e
n
tal
f
ac
to
r
lik
e
t
em
p
e
r
atu
r
e
an
d
h
u
m
id
ity
n
ee
d
s
to
n
o
t
o
n
l
y
s
en
s
ed
b
u
t
m
o
n
ito
r
an
d
g
e
n
er
ate
th
e
alar
m
as
well.
T
h
u
s
,
co
n
s
id
er
in
g
t
h
e
ab
o
v
e
f
ac
to
r
,
i
n
th
is
s
ec
tio
n
,
we
d
esig
n
an
d
d
ev
elo
p
a
m
ath
em
atica
l
m
o
d
el
o
f
th
e
e
f
f
icien
t
d
ata
s
en
s
in
g
an
d
m
o
n
ito
r
in
g
(
E
DSM
)
m
ec
h
an
is
m
;
E
DSM
n
o
t
o
n
ly
s
en
s
es
th
e
d
ata
ef
f
icien
tly
b
u
t
also
m
o
n
ito
r
s
it
an
d
g
en
er
ates
aler
ts
if
it
ex
ce
ed
s
.
Mo
r
eo
v
e
r
,
E
DSM
co
m
p
r
is
es
s
ev
er
al
p
ar
ts
wh
ich
ar
e
d
ep
ict
ed
in
Fig
u
r
e
2
.
Fig
u
r
e
2
.
E
f
f
icien
t d
ata
s
en
s
in
g
an
d
m
o
n
ito
r
i
n
g
m
ec
h
an
is
m
3.
1
.
E
nerg
y
c
o
ns
um
ptio
n
L
et’
s
co
n
s
id
er
a
s
en
s
o
r
y
f
ield
th
at
h
as
lim
ited
e
n
er
g
y
s
in
ce
it
is
co
n
s
id
er
ed
b
atter
y
-
b
ase
d
,
th
u
s
th
e
n
etwo
r
k
life
tim
e
in
te
r
m
s
o
f
e
n
er
g
y
ca
n
b
e
g
iv
en
as:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
fficien
t d
a
ta
s
en
s
in
g
a
n
d
mo
n
ito
r
in
g
mo
d
el
fo
r
a
r
ec
a
n
u
t
…
(
N
ir
a
n
ja
n
Mu
r
th
y
C
h
a
n
d
r
a
s
h
ek
a
r
a
p
p
a
)
1553
=
(
)
(
)
(
1
)
f
u
r
th
er
m
o
r
e
,
t
h
e
is
s
u
e
o
f
d
ata
g
ath
er
in
g
ca
n
b
e
d
ef
in
e
d
as
(
2
)
:
(
,
)
≤
(
2
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wh
er
e
=
{
1
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2
…
.
}
an
d
=
1
,
2
,
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.
.
,
;
in
ab
o
v
e
two
eq
u
atio
n
is
m
ax
im
u
m
th
r
esh
o
ld
b
it
th
at
is
tr
an
s
m
itted
o
r
r
ec
eiv
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in
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r
tain
tim
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in
d
icate
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th
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en
er
g
y
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s
t
to
tr
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s
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it
o
r
r
e
ce
iv
e
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e
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in
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-
b
it
d
ata
an
d
in
d
icate
s
th
e
m
ea
s
u
r
e
d
ata
with
in
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icatin
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to
tal
co
n
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tr
ain
ts
an
d
as
th
e
n
u
m
b
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o
f
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am
p
les.
T
h
e
(
3
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as
(
3
)
:
=
(
,
,
)
(
3
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with
s
u
b
jecte
d
to
:
{
{
(
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(
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,
(
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}
}
(
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in
d
icate
s
th
e
o
p
tim
izin
g
th
e
u
p
d
atin
g
tim
e
wh
ile
c
o
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ata,
(
)
in
d
icate
s
th
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f
u
n
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tim
ize
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e
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ata
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in
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icate
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izatio
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f
u
n
cti
o
n
o
f
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e
tr
an
s
m
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s
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s
u
e.
Fu
r
th
er
m
o
r
e,
t
h
r
o
u
g
h
th
e
an
al
y
s
is
o
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a
v
ar
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is
tin
g
m
o
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f
s
m
ar
t
f
ar
m
i
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it
was
o
b
s
er
v
ed
th
at
f
a
u
lty
d
ata
tr
a
n
s
m
is
s
io
n
lead
s
to
h
i
g
h
en
er
g
y
co
n
s
u
m
p
tio
n
an
d
av
o
id
an
ce
o
f
s
am
e
ca
n
r
esu
lt
in
o
p
tim
izatio
n
o
f
e
n
er
g
y
,
also
it
was
n
o
ted
th
at
f
au
lty
d
at
a
d
etec
tio
n
an
d
tr
a
n
s
m
is
s
io
n
ca
n
b
e
co
m
p
u
ted
in
v
alid
atio
n
s
tep
an
d
ca
n
b
e
c
o
m
p
u
ted
th
r
o
u
g
h
e
q
u
atio
n
.
ℎ
(
)
=
(
)
+
(
)
+
ℎ
(
)
(
4
)
I
n
th
e
eq
u
atio
n
,
ℎ
(
)
in
d
icate
s
t
h
e
en
e
r
g
y
r
e
q
u
ir
ed
to
g
ath
e
r
d
ata
f
r
o
m
ad
jace
n
t
n
o
d
es,
d
en
o
tes
cu
r
r
en
t
tim
e
an
d
in
d
icate
s
th
e
d
ata
to
b
e
r
ea
d
;
Fu
r
th
er
,
th
e
eq
u
atio
n
ca
n
b
e
r
e
-
wr
itten
as
(
5
)
:
ℎ
(
)
=
∑
(
(
)
+
(
×
)
+
=
1
ℎ
(
)
)
(
5
)
is
th
e
d
ata
s
ize
o
f
th
e
tr
an
s
m
itted
p
ac
k
et;
Fu
r
th
er
,
th
e
e
n
e
r
g
y
r
eq
u
ir
ed
to
r
ec
eiv
e
th
e
d
ata
f
r
o
m
th
e
n
ea
r
est n
eig
h
b
o
r
n
o
d
e
ca
n
b
e
i
n
d
icate
d
as
ℎ
an
d
co
m
p
u
ted
th
r
o
u
g
h
t
h
e
eq
u
atio
n
.
ℎ
(
)
=
∑
(
×
)
=
1
(
6
)
in
d
icate
s
r
ec
eiv
ed
d
ata
s
ize
a
n
d
is
a
p
ar
am
eter
f
o
r
th
e
en
er
g
y
r
eq
u
ir
e
d
to
r
ec
eiv
e
th
e
u
n
it b
it a
n
d
in
d
icate
s
n
ea
r
est n
eig
h
b
o
r
n
o
d
es.
=
(
∑
=
1
×
)
+
(
∑
=
1
×
)
(
7
)
I
n
th
e
eq
u
atio
n
s
,
an
d
in
d
ic
ates
th
e
n
u
m
b
er
o
f
r
ea
d
s
an
d
wr
ite
b
its
;
an
d
in
d
icate
s
th
e
en
er
g
y
r
eq
u
ir
e
d
to
r
ea
d
an
d
wr
ite
th
e
d
ata.
Fu
r
th
er
,
en
er
g
y
co
n
s
u
m
p
tio
n
wh
ile
o
p
tim
izatio
n
s
tep
is
d
en
o
ted
as
−
ℎ
an
d
f
o
r
m
u
late
d
th
r
o
u
g
h
th
e
eq
u
atio
n
wh
er
e
1
,
2
an
d
3
ar
e
co
n
s
id
er
e
d
as
th
e
f
o
r
war
d
e
d
s
am
p
le
d
ata
.
ℎ
ℎ
=
(
∑
1
(
)
1
=
1
)
+
(
∑
2
(
)
2
=
1
)
+
(
∑
3
(
)
3
=
1
)
(
8
)
I
n
th
e
eq
u
atio
n
,
3
is
(
9
)
:
1
=
(
ℎ
×
)
(
9
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
3
,
Ma
r
ch
20
22
:
1
5
4
9
-
1
5
6
2
1554
wh
er
e
2
in
d
icate
s
th
e
d
ata
s
en
t f
r
o
m
s
en
s
o
r
n
o
d
e
to
th
e
clu
s
te
r
h
ea
d
; th
u
s
en
er
g
y
co
n
s
u
m
p
ti
o
n
f
o
r
th
e
p
ar
am
2
is
co
m
p
u
ted
as
(
1
0
)
:
2
=
(
1
×
(
1
−
ℎ
ℎ
)
)
(
1
0
)
in
th
e
eq
u
atio
n
,
ℎ
an
d
ℎ
in
d
icate
s
th
e
len
g
th
p
ar
am
eter
.
Fu
r
th
e
r
en
er
g
y
co
n
s
u
m
p
tio
n
f
o
r
3
is
g
iv
en
as
(
1
1
)
:
3
=
2
+
(
ℎ
×
)
(
1
1
)
to
tal
en
er
g
y
c
o
n
s
u
m
p
tio
n
is
(
1
2
)
.
=
ℎ
ℎ
+
ℎ
ℎ
(
1
2
)
3
.
2
.
E
f
f
icient
da
t
a
s
ens
ing
a
nd
m
o
nito
ring
I
n
th
is
s
ec
tio
n
,
we
d
ev
el
o
p
ef
f
icien
t
r
ea
l
-
tim
e
d
ata
c
o
llectio
n
;
o
p
tim
a
l
d
ata
c
o
llectio
n
co
m
p
r
is
es
d
if
f
er
en
t
s
tep
s
;
th
e
f
ir
s
t
s
tep
in
clu
d
es
th
e
s
en
s
in
g
d
ev
ice
co
n
d
itio
n
,
th
e
s
ec
o
n
d
s
tep
in
clu
d
e
s
u
p
d
atin
g
th
e
d
ata
s
tr
ateg
y
,
th
e
th
ir
d
s
tep
in
clu
d
e
s
d
ata
v
alid
atio
n
,
an
d
th
e
f
o
u
r
th
s
tep
in
clu
d
es
th
e
s
en
s
ed
d
ata
o
p
tim
izatio
n
T
h
e
te
r
m
s
en
s
in
g
d
ev
ice
r
ef
er
s
to
a
d
ev
ice
th
at
co
llects d
ata
f
r
o
m
v
ar
io
u
s
s
en
s
o
r
s
an
d
ca
lcu
late
s
h
o
w
m
u
ch
en
er
g
y
is
co
n
s
u
m
ed
wh
ile
s
en
s
in
g
an
d
s
en
d
in
g
d
ata.
L
ater
u
p
d
ates
im
p
ly
th
at
d
ata
is
r
etu
r
n
ed
to
th
e
u
s
er
f
o
r
f
u
r
th
e
r
an
aly
s
is
,
th
at
th
e
d
ata
is
th
en
v
er
if
i
ed
to
s
ee
if
it
is
v
alid
o
r
i
n
co
r
r
ec
t,
an
d
th
at
th
e
n
ex
t
p
r
o
ce
d
u
r
e
is
to
r
ec
eiv
e
id
ea
l
d
ata
th
at
is
s
im
p
le
to
v
er
if
y
a
n
d
u
p
d
ate.
I
n
d
if
f
er
en
t
s
tag
es
o
f
o
b
tain
in
g
d
ata,
all
p
o
s
s
ib
le
s
tep
s
ar
e
s
h
o
wn
b
elo
w.
3
.
2
.
1
.
O
bta
ini
ng
t
he
s
ens
o
r
no
de
info
rm
a
t
i
o
n
T
h
is
Alg
o
r
ith
m
1
d
ea
ls
m
ain
l
y
with
th
e
p
h
y
s
ical
s
en
s
in
g
d
ev
ice
co
n
d
itio
n
as
s
en
s
ed
d
at
a
q
u
ality
in
th
is
s
tep
,
at
f
ir
s
t,
th
e
p
r
ed
icti
o
n
m
o
d
el
is
f
o
r
m
u
lated
an
d
c
o
m
p
u
ted
an
d
a
th
r
esh
o
ld
is
d
ef
in
ed
to
c
h
ec
k
th
e
d
ata
v
alid
atio
n
wh
ile
c
o
llectin
g
th
e
d
ata,
later
s
in
g
le
d
ata
ar
e
tr
an
s
m
itted
.
T
h
r
esh
o
l
d
p
r
e
d
ic
tio
n
alg
o
r
ith
m
:
Alg
o
r
ith
m
1
.
Alg
o
r
ith
m
to
g
at
h
er
in
g
in
f
o
r
m
atio
n
r
e
g
ar
d
in
g
t
h
e
s
en
s
o
r
[
]
×
∈
×
,
,
,
∁
,
t
e
p
1
S
t
a
r
t
t
e
p
2
=
×
[
]
=
×
[
]
3
=
,
(
,
)
where
∈
1
×
4
For k=1 to x do
′
(
)
=
_
(
,
)
_
(
)
=
(
′
(
)
−
(
)
)
5
End for loop
6
∁
=
max
(
)
7
×
[
]
8
×
[
]
9
×
[
−
1
]
=
×
[
]
p
r
ed
ictio
n
m
o
d
el
r
e
f
er
en
ce
is
co
m
p
u
ted
th
r
o
u
g
h
t
h
e
(
1
3
)
.
=
(
×
)
−
1
×
×
(
1
3
)
I
n
th
e
eq
u
atio
n
in
d
icate
s
th
e
d
ep
en
d
e
n
ce
s
en
s
o
r
an
d
in
d
icate
s
th
e
in
d
ep
e
n
d
en
t
s
en
s
o
r
wh
er
e
is
co
m
p
u
ted
th
r
o
u
g
h
=
×
[
]
an
d
o
th
er
s
en
s
o
r
s
ar
e
in
d
icate
d
as
×
[
]
wh
er
e
=
1
,
,
×
1
.
Pre
d
icted
s
en
s
o
r
v
alu
e
f
u
n
ctio
n
is
d
en
o
ted
th
r
o
u
g
h
′
(
)
an
d
f
o
r
m
u
lated
th
r
o
u
g
h
t
h
e
(
1
4
)
:
′
(
)
=
+
×
(
)
+
⋯
×
(
)
(
1
4
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
fficien
t d
a
ta
s
en
s
in
g
a
n
d
mo
n
ito
r
in
g
mo
d
el
fo
r
a
r
ec
a
n
u
t
…
(
N
ir
a
n
ja
n
Mu
r
th
y
C
h
a
n
d
r
a
s
h
ek
a
r
a
p
p
a
)
1555
wh
er
e
=
1
an
d
=
1
wh
ich
f
u
r
th
er
in
d
icate
s
co
llected
s
am
p
les.
Fu
r
th
er
m
o
r
e
,
to
co
m
p
u
te
th
e
th
r
esh
o
ld
,
er
r
o
r
am
o
n
g
th
e
g
iv
en
an
d
p
r
e
d
icted
d
ata
is
co
m
p
u
ted
,
a
f
u
r
th
er
th
r
esh
o
ld
v
alu
e
is
co
m
p
u
ted
th
r
o
u
g
h
ch
o
o
s
in
g
th
e
m
a
x
i
m
u
m
v
al
u
e
o
f
ap
p
r
o
x
im
atio
n
er
r
o
r
f
o
r
t
h
e
g
iv
e
n
v
alu
e
o
f
an
d
er
r
o
r
is
f
o
r
m
u
lated
as
(
1
5
)
.
_
(
)
=
|
′
(
)
−
′
(
)
|
,
1
×
(
1
5
)
3
.
2
.
2
.
E
f
f
icient
da
t
a
s
ens
ing
a
nd
m
o
nito
ring
I
n
th
is
s
u
b
-
s
tep
A
lg
o
r
it
h
m
2
,
d
ata
ar
e
e
f
f
icien
tly
s
en
s
ed
;
f
u
r
th
er
,
t
h
is
p
ar
ticu
lar
s
tep
also
lo
o
k
s
f
o
r
th
e
d
ev
ic
e
co
n
d
itio
n
in
ter
m
s
o
f
en
er
g
y
,
m
ea
s
u
r
i
n
g
ca
p
ac
ity
to
av
o
id
th
e
in
ac
c
u
r
ate
d
ata
s
en
s
in
g
;
m
o
r
eo
v
er
,
s
en
s
in
g
ca
p
ac
ity
is
co
m
p
u
ted
;
s
en
s
in
g
ca
p
ac
ity
d
ef
in
ed
as th
e
m
ea
s
u
r
e
o
f
th
e
ac
ce
p
tan
ce
o
f
r
ea
d
in
g
s
ac
h
iev
e
d
th
r
o
u
g
h
:
=
(
1
−
(
+
)
×
100
(
1
6
)
in
th
e
eq
u
atio
n,
in
d
icate
s
th
e
d
etec
ted
er
r
o
r
an
d
in
d
icate
s
th
e
co
r
r
ec
tl
y
m
ea
s
u
r
ed
d
ata
(
16
)
co
m
p
u
tes
th
e
n
etwo
r
k
r
eliab
ilit
y
:
Alg
o
r
ith
m
2
.
Alg
o
r
ith
m
f
o
r
e
f
f
icien
t d
ata
s
en
s
in
g
,
,
∈
1
×
3
Step1:
Start
Step2:
(
<
)
(
1
)
=
1
Else;
(
1
)
=
0
Step3:
(
≥
)
(
2
)
=
1
Else;
(
2
)
=
0
Step4:
(
≥
)
(
2
)
=
1
Else;
(
2
)
=
0
to
av
o
id
th
e
tr
an
s
m
is
s
io
n
o
f
in
co
r
r
ec
t
d
ata
an
d
en
h
a
n
ce
th
e
d
etec
tio
n
ac
cu
r
ac
y
;
we
in
tr
o
d
u
ce
s
ev
er
al
p
ar
am
eter
s
wh
ich
co
n
tr
ib
u
te
to
th
e
ev
en
t
d
etec
tio
n
an
d
d
etec
tio
n
ac
cu
r
ac
y
.
Mo
r
eo
v
er
,
th
e
er
r
o
r
lies
b
ec
au
s
e
o
f
v
ar
i
o
u
s
er
r
o
r
s
d
is
cu
s
s
ed
b
elo
w.
3
.
2
.
3
.
M
o
nito
ring
a
nd
a
lert
g
ener
a
t
io
n
I
n
th
is
s
tep
,
th
e
d
etec
tio
n
er
r
o
r
r
ate
is
co
m
p
u
ted
an
d
f
u
r
th
er
m
o
n
ito
r
e
d
,
an
d
an
ale
r
t
is
g
e
n
er
ated
if
f
o
u
n
d
an
y
f
au
lty
d
ata.
Aler
t
Gen
er
atio
n
:
I
n
A
lg
o
r
ith
m
3
,
th
is
ty
p
e
o
f
e
r
r
o
r
,
th
e
ale
r
t
is
g
en
e
r
ated
i
f
th
e
r
a
n
g
e
e
x
ce
ed
s
;
f
o
r
in
s
tan
ce
,
in
th
is
ca
s
e,
th
e
tem
p
er
atu
r
e
v
alu
e
r
an
g
es
f
r
o
m
2
5
to
3
0
;
h
en
ce
if
it
ex
ce
ed
s
th
en
it
g
e
n
e
r
ates
th
e
aler
t,
it
is
d
en
o
ted
as
.
-
T
y
p
e
1
e
r
r
o
r
: I
n
th
is
ty
p
e
o
f
e
r
r
o
r
,
alth
o
u
g
h
th
er
e
is
a
f
alse a
l
ar
m
p
r
esen
ted
as tr
u
e
an
d
d
en
o
ted
as
-
T
y
p
e
2
er
r
o
r
:
I
n
th
is
ty
p
e
o
f
er
r
o
r
,
alth
o
u
g
h
th
e
m
o
d
el
d
et
ec
ts
th
e
co
r
r
ec
tly
it
is
d
etec
ted
as
f
au
lty
an
d
d
e
n
o
ted
as
ℤ
Mo
r
eo
v
er
,
in
o
u
r
ca
s
e,
we
co
n
s
id
er
th
e
(
)
as
a
f
au
lty
if
it
i
s
m
o
r
e
th
an
th
e
th
r
esh
o
ld
v
alu
e,
o
th
er
wis
e
it
i
s
co
n
s
id
er
ed
as th
e
n
o
r
m
al
.
3
.
3
.
O
pti
m
iza
t
io
n
o
f
pa
c
k
et
t
ra
ns
m
is
s
io
n
T
h
e
m
ain
aim
o
f
p
ac
k
et
tr
a
n
s
m
is
s
io
n
o
p
tim
izatio
n
A
lg
o
r
ith
m
4
is
to
o
p
tim
ize
th
e
en
e
r
g
y
;
to
ac
h
iev
e
th
e
o
p
tim
izatio
n
,
w
e
in
tr
o
d
u
c
e
a
p
ar
am
eter
f
u
n
ctio
n
d
en
o
t
ed
as
wh
ich
co
m
p
u
tes
th
e
r
elativ
e
d
if
f
er
en
ce
a
m
o
n
g
th
e
cu
r
r
en
tl
y
s
en
s
ed
d
ata
an
d
last
d
ata
tr
a
n
s
m
itted
:
=
[
(
[
]
−
[
−
1
]
)
(
[
]
+
[
−
1
]
∗
0
.
5
)
−
1
]
(
1
7
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
3
,
Ma
r
ch
20
22
:
1
5
4
9
-
1
5
6
2
1556
w
h
er
e
=
1
,
2
.
.
,
an
d
in
d
icate
s
th
e
to
tal
n
u
m
b
er
o
f
s
en
s
o
r
s
.
Mo
r
eo
v
er
,
r
ec
en
t
s
en
s
ed
d
ata
is
d
en
o
ted
as
̂
×
[
]
an
d
last
d
ata
tr
a
n
s
m
itted
is
d
en
o
ted
as
̂
×
[
−
1
]
an
d
p
ac
k
et
tr
a
n
s
m
is
s
io
n
is
ca
r
r
ied
o
u
t
t
h
r
o
u
g
h
th
e
alg
o
r
ith
m
,
if
th
e
s
en
s
ed
d
a
ta
r
em
ain
s
th
e
s
am
e
th
en
p
r
o
c
ee
d
,
els
e
ch
ec
k
th
e
v
alid
atio
n
i
n
th
e
last
s
tep
.
Alg
o
r
ith
m
3
.
Alg
o
r
ith
m
f
o
r
o
p
tim
al
d
ata
m
o
to
r
in
g
an
d
d
etec
t
io
n
er
r
o
r
r
ate
c
o
m
p
u
tatio
n
(
)
,
,
∁
,
_
,
Step1:
Start
Step2:
(
(
)
>
(
)
<
)
=
1
=
1
do
(
)
=
(
(
)
−
(
)
)
End for
Step3:
(
{
}
=
=
)
=
1
:
(
{
}
>
)
ℤ
=
1
:
_
(
)
=
(
′
(
)
−
(
)
)
′
(
)
=
(
,
(
)
)
Step4
(
(
_
(
)
>
∁
)
)
ℎ
′
(
)
=
(
,
(
)
)
_
(
)
=
(
′
(
)
−
(
)
)
Step5:
(
_
(
)
>
∁
)
=
1
(
4
)
(
3
)
(
3
)
(
2
)
Step6:
=
(
,
,
ℤ
)
Alg
o
r
ith
m
4
.
Alg
o
r
ith
m
f
o
r
o
p
tim
izin
g
th
e
d
ata
tr
a
n
s
m
is
s
io
n
,
[
]
Step1:
Start
Step2:
Compute maximum number of bits using
(
8
)
Step3:
Compute relative difference using
(
9
)
Step4:
Fo
r
j
=
1
to
o
do
(
(
)
≥
0
)
(
)
=
2
(
(
×
)
−
1
)
:
(
)
=
0
[
]
=
(
(
)
×
2
(
(
×
)
−
1
)
)
Step5:
[
]
=
[
]
Step6:
[
]
ℎ
Step7:
̂
×
[
]
=
(
,
×
[
−
1
]
)
Step8:
×
[
−
1
]
=
̂
×
[
]
3
.
4
.
O
pti
m
i
za
t
io
n
o
f
pa
c
k
et
s
ize
I
n
th
is
s
tep
,
th
e
m
ain
in
ten
tio
n
is
to
m
in
im
ize
th
e
s
ize
o
f
th
e
d
ata
p
ac
k
ets
wh
ich
f
u
r
th
er
o
p
tim
izes
th
e
en
er
g
y
a
n
d
s
en
s
in
g
v
u
ln
e
r
ab
ilit
ies;
m
o
r
eo
v
er
,
in
o
r
d
er
to
o
p
tim
ize
th
e
p
ac
k
ets
a
p
ar
am
eter
d
en
o
ted
as
|
|
wh
ich
r
ep
r
esen
ts
th
e
n
u
m
b
e
r
o
f
b
its
r
eq
u
i
r
ed
f
o
r
tr
a
n
s
m
is
s
i
o
n
;
th
u
s
,
we
co
m
p
u
te
t
h
e
m
a
x
im
u
m
n
u
m
b
er
o
f
b
its
th
r
o
u
g
h
th
e
(
1
8
)
.
=
[
2
(
(
1
×
)
)
]
+
1
(
1
8
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
E
fficien
t d
a
ta
s
en
s
in
g
a
n
d
mo
n
ito
r
in
g
mo
d
el
fo
r
a
r
ec
a
n
u
t
…
(
N
ir
a
n
ja
n
Mu
r
th
y
C
h
a
n
d
r
a
s
h
ek
a
r
a
p
p
a
)
1557
Fu
r
th
er
,
we
co
m
p
u
te
th
e
r
elativ
e
d
if
f
er
e
n
ce
th
r
o
u
g
h
th
e
(
1
9
)
:
=
+
1
(
1
9
)
co
n
s
id
er
in
g
t
h
e
ab
o
v
e
r
elativ
e
d
if
f
er
en
ce
,
p
o
s
itiv
e
an
d
n
eg
ati
v
e
ca
n
b
e
m
an
ag
e
d
th
r
o
u
g
h
(
2
0
)
.
=
[
2
(
(
×
)
−
1
)
ℎ
0
ℎ
(
2
0
)
Fu
r
th
er
m
o
r
e
,
s
en
s
ed
d
ata
is
r
e
p
r
esen
ted
th
r
o
u
g
h
th
e
[
]
an
d
f
o
r
m
u
lated
th
r
o
u
g
h
th
e
(
2
1
)
.
[
]
=
∑
+
|
|
×
=
1
2
(
(
×
)
−
1
)
(
2
1
)
Fu
r
th
er
,
we
co
m
p
u
te
th
e
ap
p
r
o
x
im
ated
d
ata
t
h
r
o
u
g
h
th
e
(
2
2
)
at
g
iv
en
tim
e
.
̂
×
[
]
=
×
[
−
1
]
+
(
(
×
×
10
−
2
)
×
̂
×
[
−
1
]
)
(
2
2
)
Mo
r
eo
v
er
,
th
e
ab
o
v
e
-
p
r
esen
te
d
alg
o
r
ith
m
is
f
o
r
th
e
en
d
-
to
-
en
d
im
p
lem
e
n
tatio
n
o
f
E
DSM
wh
ich
is
ca
r
r
ie
d
in
to
d
if
f
e
r
en
t
s
tag
es.
On
ce
th
e
s
en
s
in
g
m
ec
h
a
n
is
m
is
d
esig
n
ed
,
ev
alu
atio
n
is
ca
r
r
ie
d
o
u
t
in
th
e
n
e
x
t
s
ec
tio
n
o
f
th
e
r
esear
ch
.
4.
P
E
RF
O
RM
A
NCE
E
VA
L
U
AT
I
O
N
I
n
g
en
er
al
co
s
t
o
f
ar
ec
a
n
u
t
c
u
ltiv
atio
n
d
o
es
n
o
t
m
ak
e
lu
cr
a
tiv
e
p
r
o
p
o
s
itio
n
;
h
o
we
v
er
s
m
ar
t
f
ar
m
in
g
ca
n
lead
th
e
in
d
u
s
tr
y
to
b
e
p
r
o
f
itab
le
an
d
q
u
ality
-
b
ased
v
e
n
tu
r
e;
th
u
s
,
th
is
r
esear
ch
wo
r
k
p
r
o
p
o
s
es
E
DSM
m
ec
h
an
is
m
wh
ich
ef
f
icien
tly
s
en
s
e
th
e
d
ata
an
d
m
o
n
i
to
r
s
f
o
r
th
e
f
alse
d
ata
g
en
er
atio
n
.
Mo
r
eo
v
er
,
E
DSM
is
d
esig
n
ed
u
s
in
g
th
e
s
h
ar
p
as
a
p
r
o
g
r
a
m
m
in
g
lan
g
u
ag
e
o
n
p
r
o
g
r
am
m
in
g
t
o
o
l
o
f
v
is
u
al
s
tu
d
io
2
0
1
7
;
f
u
r
th
e
r
th
e
s
y
s
tem
co
n
f
ig
u
r
atio
n
i
n
clu
d
es
th
e
8
GB
o
f
R
AM
p
ac
k
ed
with
2
GB
o
f
Nv
id
iag
r
ap
h
ics
o
n
win
d
o
ws
1
0
a
s
o
p
er
atin
g
s
y
s
tem
.
E
DSM
is
s
im
u
lated
th
r
o
u
g
h
s
en
s
o
r
ia
s
im
u
lato
r
,
f
u
r
th
e
r
d
etails
o
f
p
r
o
p
o
s
ed
m
o
d
el
ar
e
g
iv
en
th
r
o
u
g
h
T
ab
le
1
.
T
ab
le
1
.
Sy
s
tem
p
a
ra
m
e
ter
S
y
st
e
m
p
a
r
a
m
e
t
e
r
V
a
l
u
e
S
e
n
s
o
r
n
o
d
e
c
o
n
s
i
d
e
r
e
d
1
0
0
S
e
n
s
o
r
f
i
e
l
d
s
i
z
e
5
0
x
5
0
m
S
e
n
s
o
r
s
Te
mp
e
r
a
t
u
r
e
I
n
i
t
i
a
l
E
n
e
r
g
y
0
.
0
5
j
Tr
a
n
sm
i
ssi
o
n
r
a
n
g
e
15
m
S
e
n
s
i
n
g
r
a
n
g
e
8
m
N
o
d
e
f
a
i
l
u
r
e
p
r
o
b
a
b
i
l
i
t
y
0
.
1
-
0
.
5
4
.
1
.
Aler
t
g
ener
a
t
io
n
At
f
ir
s
t,
we
co
llect
t
h
e
d
ata
i.e
.
,
r
aw
d
ata
o
f
tem
p
er
atu
r
e
an
d
s
et
th
e
m
i
n
im
u
m
tem
p
er
atu
r
e
as
2
5
an
d
m
ax
im
u
m
tem
p
er
atu
r
e
as
3
0
wh
ich
is
id
ea
l
f
o
r
th
e
ar
ec
a
n
u
t;
f
u
r
t
h
er
t
h
e
d
ata
p
r
o
ce
s
s
ed
is
d
ep
icted
in
th
e
b
elo
w
f
ig
u
r
e.
I
n
Fig
u
r
e
3
,
y
-
a
x
is
p
r
esen
ts
th
e
tem
p
er
atu
r
e
an
d
x
-
ax
is
p
r
esen
ts
th
e
n
u
m
b
er
o
f
r
o
u
n
d
s
o
v
er
th
e
g
iv
en
tim
e;
m
o
r
eo
v
er
,
in
g
r
a
p
h
we
o
b
s
er
v
e
s
o
m
e
lo
w
an
d
h
ig
h
tem
p
er
atu
r
e
wh
ich
s
u
g
g
ests
th
at
wh
en
ev
er
tem
p
er
atu
r
e
ex
ce
e
d
s
m
ax
im
u
m
v
alu
e
o
f
3
0
th
e
n
it
g
en
er
at
es
th
e
aler
t
an
d
f
u
r
th
er
s
u
itab
le
s
tep
s
ar
e
tak
en
.
C
o
n
s
id
er
th
e
g
r
ap
h
b
elo
w,
wh
ich
h
as
an
x
-
a
x
is
an
d
a
y
-
ax
is
.
T
h
e
tem
p
er
atu
r
e
r
a
n
g
e
is
r
ep
r
esen
ted
o
n
th
e
x
-
ax
is
,
an
d
th
e
n
u
m
b
er
o
f
n
o
d
es
d
ee
m
ed
to
s
en
s
e
d
ata
f
r
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