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[
1
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2
]
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[
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.
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[
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[
8
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A
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IJ
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h
e
clu
s
ter
h
ea
d
s
.
T
h
en
,
w
it
h
t
h
i
s
ap
p
r
o
ac
h
th
e
n
et
w
o
r
k
co
n
tai
n
s
t
w
o
t
y
p
es
o
f
th
e
n
o
d
es:
t
h
e
ex
c
lu
d
ed
an
d
n
o
t
e
x
clu
d
ed
.
T
h
e
n
e
w
en
er
g
y
to
t
a
l
o
f
t
h
e
n
et
w
o
r
k
i
s
i
n
tr
o
d
u
ce
d
,
w
h
ic
h
d
ep
en
d
o
n
th
e
n
u
m
b
er
o
f
e
x
clu
d
ed
n
o
d
es
an
d
n
u
m
b
er
o
f
clu
s
ter
s
.
T
h
is
en
er
g
y
is
n
o
n
li
n
ea
r
,
w
h
ic
h
r
eq
u
ir
es
ef
f
ic
ien
t
o
p
tim
izatio
n
.
T
h
e
m
a
th
e
m
ati
ca
l
an
al
y
s
is
o
cc
u
p
ies
a
lar
g
e
s
p
ac
e
o
f
m
e
m
o
r
y
a
n
d
p
r
o
ce
s
s
o
r
o
f
n
o
d
es
[
11
].
Ov
er
th
e
last
y
ea
r
s
,
t
h
e
n
e
w
al
g
o
r
ith
m
s
b
ased
o
n
th
e
b
e
h
av
io
r
o
f
s
w
ar
m
s
h
a
v
e
ap
p
ea
r
ed
to
s
o
lv
e
t
h
e
n
o
n
li
n
ea
r
p
r
o
b
lem
s
s
u
c
h
as
s
w
ar
m
o
p
tim
izatio
n
,
b
at
alg
o
r
it
h
m
,
f
ir
ef
l
y
al
g
o
r
ith
m
a
n
d
cu
c
k
o
o
s
ea
r
ch
[
12
].
B
et
w
ee
n
th
e
s
e
al
g
o
r
ith
m
s
,
f
ir
ef
l
y
alg
o
r
it
h
m
is
ab
le
i
n
tr
ea
t
m
en
t
o
f
o
p
ti
m
izatio
n
p
r
o
b
le
m
s
[
13
]
.
I
n
th
is
p
ap
er
,
w
e
ap
p
l
y
t
h
e
Fire
f
l
y
A
l
g
o
r
ith
m
to
f
i
n
d
th
e
o
p
ti
m
a
l
n
u
m
b
er
o
f
clu
s
ter
h
ea
d
an
d
t
h
e
o
p
tim
a
l
n
u
m
b
er
o
f
ex
clu
d
ed
n
o
d
es i
n
o
r
d
er
to
p
r
o
lo
n
g
t
h
e
n
et
w
o
r
k
li
f
eti
m
e.
T
h
e
r
est
o
f
t
h
e
p
ap
er
o
r
g
an
i
za
tio
n
i
s
d
o
n
e
a
s
f
o
llo
w
s
:
S
ec
tio
n
I
I
s
u
m
m
ar
ize
s
t
h
e
r
el
ated
w
o
r
k
.
T
h
e
p
r
o
b
lem
s
ta
te
m
e
n
t
an
d
p
r
o
p
o
s
ed
m
et
h
o
d
ar
e
p
r
o
v
id
ed
r
esp
ec
tiv
el
y
i
n
s
ec
tio
n
I
I
I
an
d
I
V.
T
h
e
s
y
s
te
m
m
o
d
el
i
s
an
a
l
y
ze
d
i
n
s
ec
tio
n
V.
T
h
e
Si
m
u
latio
n
r
es
u
lt
s
ar
e
ca
r
r
ied
o
u
t
in
s
ec
tio
n
VI
.
Fin
a
ll
y
w
e
co
n
cl
u
d
e
o
u
r
r
esear
ch
w
o
r
k
an
d
g
iv
e
s
o
m
e
p
er
s
p
ec
tiv
es i
n
s
ec
tio
n
VI
I
.
2.
RE
L
AT
E
D
WO
RK
Ov
er
t
h
e
last
y
ea
r
s
,
t
h
e
r
esear
ch
er
s
lo
ca
ted
t
h
eir
id
ea
s
ar
o
u
n
d
th
e
cl
u
s
ter
ed
h
eter
o
g
en
eo
u
s
W
SN
w
it
h
th
e
g
o
al
to
p
r
o
lo
n
g
th
e
li
f
eti
m
e
o
f
th
e
s
e
tin
y
n
o
d
es.
Q.
L
i
et
al.
h
av
e
p
r
o
p
o
s
ed
Dis
tr
ib
u
ted
E
n
er
g
y
E
f
f
icie
n
t
C
lu
s
ter
i
n
g
P
r
o
to
co
l
(
DE
E
C
)
[
8
]
,
w
h
ic
h
s
elec
ts
th
e
cl
u
s
ter
h
ea
d
b
y
a
n
e
w
v
al
u
e
o
f
p
r
o
b
ab
ilit
y
w
itc
h
d
ep
en
d
o
n
th
e
e
n
er
g
y
r
esid
u
al
o
f
ea
c
h
n
o
d
e
an
d
a
v
er
ag
e
e
n
er
g
y
o
f
t
h
e
n
et
w
o
r
k
.
T
h
e
y
ap
p
lied
th
eir
id
ea
s
i
n
m
u
lt
i
-
lev
el
an
d
t
w
o
le
v
el
en
er
g
y
h
et
er
o
g
en
eo
u
s
s
ch
e
m
e
s
.
P
ar
u
l
Sain
i
et
al.
i
n
T
h
r
es
h
o
ld
Dis
tr
ib
u
ted
E
n
er
g
y
E
f
f
ic
ien
t
C
l
u
s
ter
i
n
g
[
9
]
p
r
o
p
o
s
e
a
n
ew
f
o
r
m
o
f
th
r
e
s
h
o
ld
th
a
t
ea
c
h
n
o
d
e
d
ec
id
es
to
b
ec
o
m
e
a
cl
u
s
ter
h
ea
d
i
n
t
h
e
c
u
r
r
en
t
r
o
u
n
d
b
ased
o
n
t
h
e
r
atio
o
f
r
esid
u
al
en
er
g
y
an
d
a
v
er
ag
e
e
n
er
g
y
o
f
th
at
r
o
u
n
d
in
r
esp
ec
t
to
t
h
e
o
p
tim
u
m
n
u
m
b
er
o
f
cl
u
s
ter
h
ea
d
s
.
Un
f
o
r
tu
n
a
tel
y
b
o
th
p
r
o
to
co
ls
d
o
n
o
t ta
k
e
i
n
to
ac
co
u
n
t
th
e
n
o
d
es
th
at
clo
s
est
to
th
e
b
ase
s
tat
io
n
,
w
h
ic
h
co
n
s
u
m
e
m
o
r
e
en
er
g
y
b
y
f
o
r
m
i
n
g
th
eir
cl
u
s
ter
s
.
B
.
m
o
s
ta
f
a
et
al.
in
I
m
p
r
o
v
i
n
g
T
h
r
esh
o
ld
Dis
tr
ib
u
tio
n
E
n
er
g
y
E
f
f
icie
n
t
C
lu
s
ter
in
g
A
l
g
o
r
ith
m
f
o
r
h
eter
o
g
e
n
eo
u
s
W
SN
[
10
]
,
p
r
o
p
o
s
ed
a
n
e
w
tec
h
n
i
q
u
e
to
f
in
d
s
o
lu
tio
n
to
th
is
p
r
o
b
le
m
b
y
eli
m
i
n
ati
n
g
th
e
clo
s
est
n
o
d
es
to
th
e
b
ase
s
tati
o
n
f
r
o
m
th
e
elec
t
io
n
p
r
o
ce
s
s
.
T
h
ese
n
o
d
es
co
m
m
u
n
icate
d
ir
ec
tl
y
w
it
h
th
e
b
ase
s
tatio
n
w
h
ich
ca
u
s
es
lo
s
s
en
e
r
g
y
if
t
h
eir
n
u
m
b
er
b
ec
o
m
es
lar
g
er
.
T
o
f
in
d
t
h
e
l
i
m
it
o
f
t
h
ese
n
o
d
es,
it
m
u
s
t
o
p
tim
ize
t
h
e
to
tal
o
f
en
er
g
y
c
o
n
s
u
m
p
tio
n
w
h
ic
h
ca
n
d
o
b
y
t
h
e
m
at
h
e
m
atica
l a
n
al
y
tic
s
b
u
t
o
cc
u
p
y
m
u
ch
s
p
ac
e
o
f
m
e
m
o
r
y
an
d
p
r
o
ce
s
s
i
n
g
.
3.
P
RO
B
L
E
M
ST
AT
E
M
E
NT
I
n
th
i
s
p
ap
er
,
w
e
co
n
s
id
er
a
s
et
o
f
n
o
d
es,
w
h
ic
h
ar
e
u
n
i
f
o
r
m
l
y
d
ep
lo
y
ed
r
an
d
o
m
l
y
i
n
an
ar
ea
to
m
o
n
ito
r
in
g
ce
r
tain
e
v
e
n
ts
,
as sh
o
w
n
i
n
Fi
g
u
r
e
1
.
Fig
u
r
e
1
.
T
h
r
o
u
g
h
th
e
cl
u
s
ter
i
n
g
p
r
o
ce
s
s
,
all
n
o
d
es
m
u
s
t
f
o
r
m
clu
s
ter
s
e
v
en
t
h
o
s
e
w
h
o
ar
e
clo
s
est to
th
e
b
ase
s
tatio
n
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
-
AI
I
SS
N:
2252
-
8938
F
ir
efly
A
lg
o
r
ith
m
S
o
lu
tio
n
to
I
mp
r
o
vin
g
Th
r
esh
o
ld
Dis
tr
ib
u
ted
.
.
.
(
B
a
g
h
o
u
r
i Mo
s
ta
fa
)
93
Fu
r
t
h
er
m
o
r
e,
in
t
h
is
p
ap
er
w
e
co
n
s
id
er
a
clu
s
ter
-
b
ased
to
p
o
lo
g
y
i
n
w
h
i
c
h
ea
ch
C
H
r
o
u
te
s
in
ev
er
y
ti
m
e
t
h
e
d
ata
r
ec
eiv
ed
f
r
o
m
t
h
e
m
e
m
b
er
n
o
d
es
to
th
e
b
ase
s
tatio
n
.
Ge
n
er
all
y
,
m
a
n
y
s
ea
r
ch
er
s
ap
p
lied
th
e
d
y
n
a
m
ic
al
g
o
r
ith
m
f
o
r
C
H
el
ec
tio
n
in
w
h
ic
h
b
ased
o
n
th
e
p
r
o
b
ab
ilit
y
o
f
a
n
o
d
e
to
b
ec
o
m
e
a
cl
u
s
ter
h
ea
d
.
I
n
a
ce
r
tain
ti
m
e,
th
is
m
e
th
o
d
ca
n
in
tr
o
d
u
ce
s
a
lo
s
s
o
f
en
er
g
y
ca
u
s
ed
b
y
clo
s
est
n
o
d
es
wh
ich
co
n
s
u
m
e
m
o
r
e
en
er
g
y
s
i
n
ce
th
e
y
s
e
n
d
th
e
d
ata
to
w
ar
d
s
th
eir
clu
s
ter
h
ea
d
.
T
o
s
o
lv
e
th
is
p
r
o
b
lem
,
th
e
a
u
th
o
r
s
in
[
1
0
]
,
p
r
o
p
o
s
e
to
eli
m
in
a
tio
n
o
f
t
h
ese
n
o
t
f
r
o
m
th
e
C
H
elec
tio
n
.
Ho
w
ev
er
,
th
e
in
cr
ea
s
e
o
f
t
h
ese
n
o
tes
d
is
s
ip
ates
th
e
e
n
er
g
y
to
tal
o
f
th
e
n
et
w
o
r
k
b
ec
au
s
e
t
h
e
d
ir
ec
t c
o
m
m
u
n
icatio
n
i
n
cr
e
ases
as
w
ell.
4.
P
RO
P
O
SE
D
M
E
T
H
O
D
T
h
is
ar
ticle
p
r
o
p
o
s
es
to
i
m
p
r
o
v
e
T
h
r
esh
o
ld
C
l
u
s
ter
i
n
g
D
is
tr
ib
u
ted
E
n
er
g
y
ef
f
icie
n
t
u
s
i
n
g
th
e
f
ir
ef
l
y
alg
o
r
ith
m
ca
ll
ed
(
FT
DE
E
C
)
in
o
r
d
er
to
in
cr
ea
s
e
th
e
s
tab
le
r
eg
io
n
a
n
d
d
ec
r
ea
s
e
th
e
u
n
s
tab
l
e
r
eg
io
n
.
I
n
[
5
]
,
th
e
au
th
o
r
s
a
m
elio
r
ate
t
h
is
p
r
o
to
c
o
l
b
y
eli
m
i
n
atio
n
o
f
t
h
e
clo
s
e
s
t
n
o
d
es
to
t
h
e
b
ase
s
tat
io
n
t
h
e
elec
tio
n
p
r
o
ce
s
s
.
T
h
ey
in
tr
o
d
u
ce
d
t
h
e
n
e
w
to
tal
en
er
g
y
co
n
s
u
m
p
tio
n
w
h
ic
h
d
ep
en
d
s
n
o
t o
n
l
y
o
n
th
e
n
u
m
b
er
o
f
cl
u
s
ter
h
ea
d
b
u
t
o
n
th
e
ex
c
lu
d
ed
n
o
d
es
as
w
el
l.
T
o
o
p
tim
ize
t
h
i
s
en
er
g
y
,
t
h
e
e
m
p
ir
ical
m
et
h
o
d
is
p
r
o
p
o
s
ed
,
w
h
ich
h
a
s
m
a
n
y
d
is
ad
v
an
ta
g
es
s
u
c
h
a
s
m
i
n
i
m
u
m
e
n
er
g
y
v
al
u
e
i
s
to
b
e
d
eter
m
in
ed
b
y
t
h
e
li
n
ea
r
d
er
iv
atio
n
a
n
d
t
h
e
v
al
u
es
o
f
th
e
clo
s
e
s
t
n
o
d
es
ar
e
ch
o
s
e
n
ar
b
itra
r
ily
.
I
f
t
h
e
v
a
lu
e
s
o
f
th
ese
n
o
d
es
b
ec
o
m
e
lar
g
er
,
t
h
e
n
et
w
o
r
k
g
r
ad
u
all
y
s
tar
t
lo
s
i
n
g
it
s
e
n
er
g
y
a
s
t
h
e
y
s
en
d
t
h
e
d
ata
d
ir
ec
tl
y
to
th
e
b
ase
s
tatio
n
.
A
ll
th
is
i
s
d
u
e
to
t
h
e
n
o
n
-
d
eter
m
in
at
io
n
o
f
t
h
e
m
ax
i
m
u
m
v
al
u
e
o
f
th
e
ex
cl
u
d
ed
n
o
d
e
s
.
T
o
s
o
lv
e
th
e
s
e
p
r
o
b
le
m
s
,
we
p
r
o
p
o
s
e
to
u
s
e
t
h
e
n
o
n
li
n
ea
r
o
p
ti
m
izat
io
n
o
f
t
h
e
en
er
g
y
co
n
s
u
m
p
tio
n
i
n
t
h
e
o
r
d
er
to
f
u
n
d
th
e
o
p
ti
m
a
l
v
a
lu
es
o
f
n
u
m
b
er
o
f
clu
s
ter
h
ea
d
s
a
n
d
n
u
m
b
er
o
f
e
x
clu
d
e
s
n
o
d
es.
T
h
e
an
al
y
tica
l
m
et
h
o
d
s
ar
e
u
n
f
a
v
o
r
ab
l
e
b
ec
au
s
e
t
h
e
d
ev
ices
ar
e
li
m
ited
i
n
th
e
p
r
o
ce
s
s
in
g
an
d
m
e
m
o
r
y
ca
p
ac
it
y
.
I
n
t
h
is
f
e
w
last
y
ea
r
s
,
th
e
n
at
u
r
e
in
s
p
ir
ed
o
p
tim
izatio
n
alg
o
r
ith
m
s
ar
e
p
r
ese
n
ted
.
On
e
o
f
f
a
m
o
u
s
b
io
-
i
n
s
p
ir
ed
o
p
ti
m
izatio
n
al
g
o
r
ith
m
t
h
at
w
ill
b
e
u
s
ed
m
ain
l
y
i
n
t
h
is
p
ap
er
is
th
e
Fire
f
l
y
alg
o
r
it
h
m
.
5.
SYST
E
M
M
O
DE
L
5
.
1
.
Net
w
o
rk
M
o
del
T
h
is
s
ec
tio
n
d
escr
ib
es t
h
e
n
et
w
o
r
k
m
o
d
el
an
d
o
th
er
b
asic a
s
s
u
m
p
tio
n
s
:
1.
N
s
e
n
s
o
r
s
ar
e
u
n
i
f
o
r
m
l
y
d
is
t
r
ib
u
ted
w
ith
in
a
s
q
u
ar
e
f
ie
ld
o
f
ar
ea
.
T
h
e
B
ase
Statio
n
i
s
p
o
s
itio
n
ed
at
t
h
e
ce
n
ter
o
f
th
e
s
q
u
ar
e
r
eg
io
n
.
T
h
e
n
u
m
b
er
o
f
s
e
n
s
o
r
n
o
d
es
N
to
b
e
d
e
p
lo
y
ed
d
ep
en
d
s
s
p
ec
if
icall
y
o
n
t
h
e
ap
p
licatio
n
.
2.
A
ll
n
o
d
es
ar
e
d
ep
lo
y
ed
r
a
n
d
o
m
l
y
a
n
d
ca
n
f
al
l
i
n
t
h
e
o
n
e
o
f
t
w
o
t
y
p
es
o
f
r
e
g
io
n
s
w
h
ic
h
ca
n
b
e
d
ef
i
n
ed
b
y
th
e
th
r
e
s
h
o
ld
d
is
ta
n
ce
f
r
o
m
th
e
b
ase
s
tatio
n
.
3.
I
n
th
is
ca
s
e
w
e
d
ef
i
n
e
t
w
o
t
y
p
es
o
f
n
o
d
es,
E
x
clu
d
ed
an
d
n
o
t
E
x
clu
d
ed
n
o
d
es.
T
h
e
E
x
clu
d
e
d
ar
e
th
e
n
o
d
es
th
at
n
o
t e
n
ter
in
t
h
e
cl
u
s
ter
i
n
g
p
r
o
ce
s
s
b
ec
au
s
e
th
er
e
ar
e
clo
s
ed
to
th
e
b
ase
s
tatio
n
an
d
t
h
e
o
th
er
ar
e
f
ar
.
4.
A
ll
s
en
s
o
r
s
ar
e
h
eter
o
g
e
n
eo
u
s
,
i.e
.
,
th
e
y
n
o
t
h
av
e
t
h
e
s
a
m
e
ca
p
ac
ities
.
A
ll
th
e
s
en
s
o
r
n
o
d
es
h
a
v
e
a
p
ar
ticu
lar
id
en
ti
f
ier
(
I
D)
allo
ca
ted
to
th
e
m
.
E
a
ch
cl
u
s
ter
h
ea
d
co
o
r
d
in
ates th
e
M
AC
an
d
r
o
u
t
in
g
o
f
p
ac
k
e
ts
w
ith
in
t
h
eir
cl
u
s
ter
s
in
F
ig
u
r
e
2
.
Fig
u
r
e
2
.
W
ir
eless
Sen
s
o
r
Netw
o
r
k
m
o
d
el
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
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8938
IJ
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AI
Vo
l.
6
,
No
.
3
,
Sep
tem
b
er
2
0
1
7
:
9
1
–
99
94
5
.
2
.
Ra
dio
E
nerg
y
M
o
del
T
h
is
s
tu
d
y
ass
u
m
es
a
s
i
m
p
le
m
o
d
el
f
o
r
th
e
r
ad
io
h
ar
d
w
ar
e
w
h
er
e
th
e
tr
a
n
s
m
itter
d
is
s
ip
ates
en
er
g
y
f
o
r
r
u
n
n
i
n
g
t
h
e
r
ad
io
elec
tr
o
n
ics
to
tr
an
s
m
it
an
d
a
m
p
li
f
y
t
h
e
s
i
g
n
als,
a
n
d
t
h
e
r
ec
e
iv
er
r
u
n
s
t
h
e
r
ad
io
elec
tr
o
n
ics
f
o
r
r
ec
ep
tio
n
o
f
s
ig
n
als
[
7
]
.
Mu
ltip
at
h
f
ad
i
n
g
m
o
d
el
(
p
o
w
er
lo
s
s
)
f
o
r
lar
g
e
d
is
tan
ce
tr
an
s
m
is
s
io
n
s
an
d
t
h
e
f
r
ee
s
p
ac
e
m
o
d
el
(
p
o
w
er
lo
s
s
)
f
o
r
p
r
o
x
i
m
al
tr
a
n
s
m
i
s
s
io
n
s
ar
e
co
n
s
id
er
ed
.
T
h
u
s
t
o
tr
an
s
m
it a
m
ess
a
g
e
o
v
er
a
d
is
t
an
ce
,
th
e
r
ad
io
ex
p
en
d
s
:
(
)
(
)
(
)
(
1
)
(
)
(
2
)
(
)
{
(
3
)
W
h
er
e
d
o
is
th
e
d
is
tan
ce
t
h
r
es
h
o
ld
f
o
r
s
w
ap
p
in
g
a
m
p
li
f
icati
o
n
m
o
d
els,
w
h
ich
ca
n
b
e
ca
lcu
lated
as
:
√
(
4
)
T
o
r
ec
eiv
e
a
m
e
s
s
a
g
e
th
e
r
ec
e
iv
er
ex
p
en
d
s
:
(
)
(
5
)
T
o
ag
g
r
eg
ate
d
ata
s
ig
n
als o
f
le
n
g
t
h
,
th
e
en
er
g
y
co
n
s
u
m
p
tio
n
w
a
s
ca
lcu
la
ted
as
:
(
)
(
6
)
5
.
3
.
E
nerg
y
Co
ns
u
m
ptio
n
B
asin
g
o
n
th
e
n
et
w
o
r
k
m
o
d
el
d
escr
ib
ed
ab
o
v
e,
th
e
en
er
g
y
c
o
n
s
u
m
p
tio
n
is
eq
u
al
to
:
(
)
(
7
)
W
h
er
e
s
is
th
e
n
u
m
b
er
o
f
t
h
e
ex
clu
d
ed
n
o
d
es
an
d
N
is
n
u
m
b
er
o
f
t
h
e
n
o
d
es.
T
h
is
en
e
r
g
y
ca
n
b
e
ex
p
lain
ed
as
f
o
llo
w
:
*
+
(
)
[
(
)
(
)
]
(
)
*
+
(
8
)
W
h
er
e
c
d
en
o
ti
n
g
t
h
e
n
u
m
b
er
o
f
t
h
e
c
lu
s
ter
s
.
T
h
e
g
r
ap
h
ical
r
ep
r
esen
ta
tio
n
o
f
t
h
is
e
n
er
g
y
in
t
h
e
ca
s
e
th
at
is
illu
s
tr
ated
in
Fi
g
u
r
e
3
.
Fig
u
r
e
3
.
Var
iatio
n
o
f
en
er
g
y
co
n
s
u
m
p
tio
n
f
o
r
d
if
f
er
en
t
v
al
u
es o
f
n
u
m
b
er
o
f
e
x
cl
u
d
ed
n
o
d
es a
n
d
n
u
m
b
er
o
f
clu
s
ter
s
0
5
10
15
20
0
5
10
4
5
6
7
8
9
10
N
u
m
b
e
r
o
f
c
l
u
s
t
e
r
s
X
:
7
.
2
7
Y
:
1
0
Z
:
4
.
8
3
8
N
u
m
b
e
r
o
f
e
x
c
l
u
d
e
d
n
o
d
e
s
E
n
e
r
g
y
c
o
n
s
u
m
p
t
i
o
n
(
J
)
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
-
AI
I
SS
N:
2252
-
8938
F
ir
efly
A
lg
o
r
ith
m
S
o
lu
tio
n
to
I
mp
r
o
vin
g
Th
r
esh
o
ld
Dis
tr
ib
u
ted
.
.
.
(
B
a
g
h
o
u
r
i Mo
s
ta
fa
)
95
As
is
c
lear
in
t
h
e
eq
u
a
tio
n
n
u
m
b
er
(
8
)
an
d
F
ig
u
r
e
3
th
at
th
e
en
er
g
y
d
is
s
ip
ated
in
t
h
e
n
et
w
o
r
k
d
o
es
n
o
t
o
n
l
y
d
ep
en
d
o
n
t
h
e
n
u
m
b
er
o
f
clu
s
ter
h
ea
d
s
b
u
t
also
o
n
th
e
n
u
m
b
er
o
f
e
x
clu
d
ed
n
o
d
e
s
,
th
at
p
r
o
d
u
ce
s
th
e
o
p
tim
a
l
v
a
lu
e
4
,
8
3
J
at
1
0
ex
clu
d
ed
n
o
d
es
a
n
d
7
clu
s
ter
s
.
Un
f
o
r
tu
n
atel
y
,
th
e
m
o
s
t
an
a
l
y
tical
m
et
h
o
d
s
ar
e
u
n
s
u
itab
le
f
o
r
W
SNs
,
b
ec
au
s
e
th
e
y
ta
k
e
u
p
a
lo
t
o
f
m
e
m
o
r
y
a
n
d
r
eq
u
ir
e
h
ea
v
y
p
r
o
ce
s
s
i
n
g
.
A
n
e
w
b
io
-
in
s
p
ir
ed
al
g
o
r
ith
m
h
a
s
ap
p
ea
r
ed
an
d
it
h
a
s
s
h
o
w
ed
a
g
r
ea
t
a
b
ilit
y
to
s
o
l
v
e
d
i
f
f
icu
l
t
p
r
o
b
lem
s
,
w
h
ich
is
Fire
f
l
y
alg
o
r
ith
m
.
5
.
4
.
F
iref
ly
Alg
o
rit
h
m
T
h
e
Fire
f
l
y
A
l
g
o
r
ith
m
,
d
e
v
el
o
p
ed
b
y
Xi
n
-
S
h
e
Ya
n
g
i
n
2
0
0
8
,
b
elo
n
g
s
w
it
h
n
at
u
r
e
-
in
s
p
i
r
ed
m
eta
-
h
eu
r
i
s
tic
alg
o
r
it
h
m
s
.
I
t
w
a
s
b
ased
o
n
b
eh
av
io
r
o
f
th
e
f
las
h
i
n
g
c
h
ar
ac
ter
is
tic
s
o
f
th
e
f
ir
ef
l
ies
in
o
r
d
er
to
j
o
in
th
eir
m
ati
n
g
co
m
p
a
n
io
n
s
(
co
m
m
u
n
icat
io
n
)
o
r
to
attr
ac
t p
r
e
y
[
6
]
.
T
o
s
i
m
p
lify
th
e
ca
lcu
latio
n
s
,
t
h
e
a
lg
o
r
it
h
m
i
s
g
en
er
ated
b
y
t
h
r
ee
f
u
n
d
a
m
e
n
t
al
r
u
les:
1.
R
eg
ar
d
l
ess
o
f
g
en
d
e
r
,
a
f
i
r
ef
ly
w
ill b
e
att
r
a
ct
ed
t
o
b
r
ig
h
t f
i
r
ef
l
ies.
2.
Fo
r
an
y
t
w
o
f
lash
in
g
f
ir
ef
lies
,
th
e
less
b
r
ig
h
t o
n
e
w
ill m
o
v
es
to
th
e
b
r
ig
h
te
r
o
n
e.
T
h
u
s
th
e
ir
att
r
ac
tiv
en
ess
i
s
p
r
o
p
o
r
ti
o
n
al
w
ith
th
eir
b
r
ig
h
tn
ess
.
I
f
th
e
r
e
is
n
o
b
r
ig
h
te
r
f
ir
ef
ly
,
it w
ill m
o
v
e
a
t
r
an
d
o
m
.
3.
T
h
e
b
r
ig
h
tn
ess
o
f
th
e
f
i
r
ef
ly
r
e
lates
t
o
o
b
ject
iv
e
p
r
o
b
lem
s
.
4.
Fro
m
th
es
e
th
r
e
e
r
u
les
,
th
e
Fig
u
r
e
4
s
h
o
w
s
th
e
f
l
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2
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8938
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NC
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S
[1
]
I.
F
.
A
k
y
il
d
iz,
W
.
S
u
,
Y.
S
a
n
k
a
ra
su
b
ra
m
a
n
ia
m
,
E.
Ca
y
irci,
“
Wi
re
les
s
se
n
so
r
n
e
tw
o
rk
s:
a
su
rv
e
y
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Co
mp
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ter
Ne
two
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3
8
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4
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).
[2
]
Je
n
n
if
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r
Yic
k
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th
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u
k
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rjee
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a
k
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h
o
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l,
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W
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n
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r
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5
2
(
2
0
0
8
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2
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–
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3
3
0
.
[3
]
G
.
A
n
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st
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si,
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.
Co
n
ti
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M
.
Di
F
r
a
n
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A
.
P
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ss
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re
ll
a
,
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En
e
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n
so
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,
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Ho
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tw
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rk
s
,
v
.
7
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.
3
,
p
.
5
3
7
-
5
6
8
,
M
a
y
,
2
0
0
9
.
[4
]
G
.
G
u
p
ta,
M
.
Y
o
u
n
is
,
“
L
o
a
d
-
b
a
la
n
c
e
d
c
lu
ste
r
in
g
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n
w
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n
so
r
n
e
tw
o
rk
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,
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in
:
Pro
c
e
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d
in
g
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th
e
In
ter
n
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l
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n
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e
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e
o
n
Co
mm
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n
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ICC 2
0
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3
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A
n
c
h
o
ra
g
e
,
A
las
k
a
,
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a
y
2
0
0
3
.
[5
]
S
.
G
h
ias
i,
A
.
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riv
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sta
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a
,
X
.
Ya
n
g
,
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.
S
a
rra
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,
“
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n
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a
g
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zin
e
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DPI
1
(
1
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(2
0
0
4
)
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5
8
–
2
6
9
.
[6
]
W
e
n
d
i
R.
He
in
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lma
n
,
A
n
a
n
th
a
Ch
a
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ra
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sa
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Ha
ri
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a
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t
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m
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f
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r
w
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ss
m
icro
se
n
so
r
n
e
tw
o
rk
s
,
”
IEE
E
In
ter
n
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ti
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l
C
o
n
fer
e
n
c
e
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n
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ste
m S
c
ien
c
e
s
,
p
p
1
-
1
0
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2
0
0
0
.
[7
]
G
.
S
m
a
ra
g
d
a
k
is,
I.
M
a
tt
a
,
A
.
Be
sta
v
ro
s
,
S
EP
:
A
S
tab
le
El
e
c
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P
ro
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u
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r
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in
:
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c
o
n
d
In
te
rn
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ti
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l
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p
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0
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2
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.
[8
]
L
i
Qin
g
,
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g
x
in
Zh
u
,
M
in
g
w
e
n
W
a
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,
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DEEC:
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sig
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o
f
a
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m
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n
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s w
irele
ss
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n
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r
n
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rk
s
,
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mp
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ter
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n
s
2
9
(2
0
0
6
)
2
2
3
0
–
2
2
3
7
.
[9
]
P
a
r
u
l
S
a
in
i
,
A
ja
y
.
K.S
h
a
r
m
a
,
“
En
e
rg
y
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ff
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t
S
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m
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f
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ste
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tero
g
e
n
e
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u
s
W
irele
ss
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n
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r
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tw
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rk
s
,
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ter
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ti
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l
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o
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ter
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9
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5
8
8
8
7
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l.
6
,
n
o
.
2
,
S
e
p
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e
r
2
0
1
0
.
[1
0
]
B.
M
o
sta
f
a
,
C.
S
a
a
d
,
H.
A
b
d
e
rra
h
m
a
n
e
,
“
I
m
p
ro
v
in
g
T
h
re
sh
o
ld
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strib
u
te
d
En
e
rg
y
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ici
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t
Clu
ste
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g
A
lg
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rit
h
m
f
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g
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n
e
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u
s
W
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ss
S
e
n
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r
Ne
tw
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rk
s
,
”
Pro
c
e
e
d
in
g
s
o
f
th
e
T
h
ir
d
IE
EE
I
n
ter
n
a
ti
o
n
a
l
Co
ll
o
q
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iu
m
i
n
In
fo
rm
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t
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n
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c
ien
c
e
a
n
d
T
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c
h
n
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lo
g
y
(
CIS
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4
)
,
2
0
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2
2
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t.
2
0
1
4
,
T
e
to
u
a
n
,
M
o
r
o
c
c
o
,
IEE
E
Ex
p
lo
re
,
2
0
1
4
:
4
3
0
–
4
3
4
.
[1
1
]
R.
Ku
lk
a
rn
i
a
n
d
G
.
V
e
n
a
y
a
g
a
m
o
o
rth
y
,
“
P
a
rt
icle
sw
a
r
m
o
p
ti
m
iz
a
ti
o
n
in
w
irele
ss
-
se
n
so
r
n
e
tw
o
rk
s:
A
b
rie
f
su
rv
e
y
,
”
IEE
E
T
ra
n
s.
S
y
st
.
,
M
a
n
,
Cy
b
e
rn
.
C,
A
p
p
l.
Re
v
.
to
b
e
p
u
b
li
sh
e
d
.
D
OI:
1
0
.
1
1
0
9
/T
S
M
CC.
2
0
1
0
.
2
0
5
4
0
8
0
.
[1
2
]
X
in
-
Sh
e
Ya
n
g
a
n
d
X
i
n
g
sh
i
He
,
(2
0
1
3
).
“
F
iref
ly
A
l
g
o
rit
h
m
:
R
e
c
e
n
t
A
d
v
a
n
c
e
s
a
n
d
A
p
p
li
c
a
ti
o
n
s
,
”
In
t.
J
.
S
w
a
rm
In
telli
g
e
n
c
e
,
Vo
l.
1
,
N
o
.
1
,
p
p
.
3
6
–
5
0
.
DO
I:
1
0
.
1
5
0
4
/
IJSI.
2
0
1
3
.
0
5
5
8
0
1
[1
3
]
X.
-
S
.
Ya
n
g
,
“
Cu
c
k
o
o
S
e
a
rc
h
a
n
d
F
iref
ly
A
lg
o
rit
h
m
:
O
v
e
rv
i
e
w
a
n
d
A
n
a
l
y
sis,”
S
tu
d
ies
i
n
Co
mp
u
ta
t
io
n
a
l
In
telli
g
e
n
c
e
,
v
o
l.
5
1
6
,
n
o
.
2
0
1
4
,
p
p
.
1
-
2
6
,
2
0
1
4
.
B
I
O
G
RAP
H
I
E
S
O
F
AUT
H
O
RS
Ba
g
h
o
u
ri
M
o
sta
f
a
w
a
s
b
o
rn
i
n
T
a
n
g
ier
M
o
ro
c
c
o
.
He
’s
a
m
e
m
b
e
r
in
th
e
P
h
y
sic
s
d
e
p
a
rtme
n
t,
T
e
a
m
Co
m
m
u
n
ica
ti
o
n
S
y
ste
m
s,
F
a
c
u
lt
y
o
f
sc
ien
c
e
s,
Un
iv
e
rsit
y
o
f
A
b
d
e
lma
lek
Ess
a
â
d
i,
T
e
to
u
a
n
M
o
r
o
c
c
o
,
h
is
re
se
a
rc
h
a
re
a
is:
ro
u
ti
n
g
a
n
d
re
a
l
ti
m
e
p
ro
to
c
o
ls
f
o
r
e
n
e
r
g
y
o
p
ti
m
iza
ti
o
n
in
w
irel
e
s
s
se
n
s
o
rs
n
e
tw
o
rk
s.
He
o
b
tain
e
d
a
M
a
ste
r'
s
d
e
g
re
e
in
El
e
c
tri
c
a
l
a
n
d
Co
m
p
u
t
e
r
En
g
in
e
e
rin
g
f
ro
m
th
e
F
a
c
u
lt
y
o
f
S
c
ien
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
o
f
T
a
n
g
ier
in
M
o
ro
c
c
o
in
2
0
0
2
.
He
g
ra
d
u
a
ted
e
n
a
b
li
n
g
tea
c
h
in
g
c
o
m
p
u
ter
sc
ien
c
e
f
o
r
se
c
o
n
d
a
ry
q
u
a
li
fy
in
g
sc
h
o
o
l
in
2
0
0
4
.
In
2
0
0
6
,
h
e
g
ra
d
u
a
ted
f
ro
m
DES
A i
n
A
u
to
m
a
ti
c
s
a
n
d
in
f
o
rm
a
ti
o
n
p
ro
c
e
ss
in
g
a
t
th
e
sa
m
e
f
a
c
u
lt
y
.
He
w
o
rk
tea
c
h
e
r
o
f
c
o
m
p
u
ter sc
ien
c
e
in
th
e
h
ig
h
sc
h
o
o
l
Ch
a
k
k
o
r
S
a
a
d
w
a
s
b
o
rn
in
T
a
n
g
ier
M
o
ro
c
c
o
.
He
’s
a
m
e
m
b
e
r
in
th
e
P
h
y
sic
s
d
e
p
a
rtme
n
t,
T
e
a
m
Co
m
m
u
n
ica
ti
o
n
a
n
d
d
e
tec
ti
o
n
S
y
st
e
m
s,
F
a
c
u
lt
y
o
f
sc
ien
c
e
s,
Un
iv
e
rsit
y
o
f
A
b
d
e
l
m
a
le
k
Ess
a
â
d
i,
T
e
to
u
a
n
M
o
ro
c
c
o
,
a
n
d
h
is
re
se
a
rc
h
a
re
a
is:
w
ir
e
les
s
in
telli
g
e
n
t
se
n
so
rs
a
n
d
th
e
irs
a
p
p
l
ica
ti
o
n
s,
f
re
q
u
e
n
c
y
e
sti
m
a
ti
o
n
a
lg
o
rit
h
m
s
f
o
r
f
a
u
lt
s
d
e
tec
ti
o
n
a
n
d
d
ia
g
n
o
sis
sy
ste
m
in
e
lec
t
ro
m
e
c
a
n
ica
l
m
a
c
h
in
e
s.
He
o
b
tain
e
d
t
h
e
M
a
ste
r'
s
d
e
g
re
e
in
El
e
c
tri
c
a
l
a
n
d
Co
m
p
u
ter
En
g
i
n
e
e
rin
g
f
ro
m
th
e
F
a
c
u
lt
y
o
f
S
c
ien
c
e
s
a
n
d
T
e
c
h
n
iq
u
e
s
o
f
Tan
g
ier,
M
o
ro
c
c
o
in
2
0
0
2
.
He
g
ra
d
u
a
ted
e
n
a
b
li
n
g
tea
c
h
in
g
c
o
m
p
u
ter
sc
ien
c
e
f
o
r
se
c
o
n
d
a
ry
q
u
a
li
fy
in
g
sc
h
o
o
l
in
2
0
0
3
.
I
n
2
0
0
6
,
h
e
g
ra
d
u
a
ted
f
ro
m
DES
A i
n
A
u
to
m
a
ti
c
s
a
n
d
in
f
o
rm
a
ti
o
n
p
ro
c
e
ss
in
g
a
t
th
e
sa
m
e
f
a
c
u
lt
y
.
H
e
w
o
rk
s
a
s
t
e
a
c
h
e
r
o
f
c
o
m
p
u
ter
sc
ien
c
e
in
th
e
h
ig
h
sc
h
o
o
l.
A
b
d
e
rra
h
m
a
n
e
Ha
jrao
u
i
is
a
p
ro
fe
ss
o
r
o
f
th
e
Hig
h
e
r
Ed
u
c
a
ti
o
n
a
t
Un
iv
e
rsit
y
o
f
A
b
d
e
lm
a
l
e
k
Ess
a
â
d
i.
He
’s
a
d
irec
to
r
th
e
sis
in
th
e
P
h
y
sic
s
d
e
p
a
rt
m
e
n
t,
Co
m
m
u
n
ica
ti
o
n
a
n
d
d
e
tec
ti
o
n
S
y
ste
m
s
lab
o
ra
to
r
y
,
F
a
c
u
lt
y
o
f
sc
i
e
n
c
e
s,
Un
iv
e
rsit
y
o
f
A
b
d
e
l
m
a
le
k
Essa
â
d
i,
T
e
to
u
a
n
M
o
r
o
c
c
o
.
His
re
se
a
rc
h
a
re
a
s
a
re
:
S
ig
n
a
l
p
ro
c
e
ss
in
g
a
n
d
im
a
g
e
,
a
u
to
m
a
ti
o
n
,
a
u
to
m
a
ti
o
n
sy
ste
m
s,
s
im
u
latio
n
sy
st
e
m
s,
A
n
ten
n
a
s
a
n
d
ra
d
iatio
n
,
m
icro
w
a
v
e
d
e
v
ic
e
s
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