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o dat
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h
e s
am
e t
o t
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ei
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s
t
an
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e,
r
e
s
i
d
ual
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gy
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and n
ode
dens
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t
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.
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d
i
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D
S
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A
has
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e
n
s
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node
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©
20
16 U
n
i
ver
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t
a
s
A
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mad
D
ah
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.
A
l
l
r
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g
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t
s r
eser
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.
1.
I
n
tr
o
d
u
c
ti
o
n
A
W
SN
of
r
andom
l
y
dep
l
o
y
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el
f
-
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s
ens
or
no
des
t
o m
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or
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c
a
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t
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ons
of
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bor
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t
oget
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t
o t
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ens
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d t
o t
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t
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on.
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g
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at
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nded t
o t
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ght
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app
l
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c
a
t
i
ons
s
uc
h as
c
ons
um
er
W
S
N
appl
i
c
at
i
on
s
[
1
-
6
].
W
SN
dev
i
c
es
ar
e ba
t
t
er
y
o
per
at
e
d;
s
av
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ng
po
w
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s
t
h
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t
h
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s
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n
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or
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p
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a pac
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1]
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x
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at
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]
i
s
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o r
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n
d bal
anc
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h
e en
er
g
y
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o
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m
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on i
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pos
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ar
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g
y
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o
ns
um
pt
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or
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andi
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obs
i
n t
he n
et
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or
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.
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he bat
t
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t
ed
nod
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t
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o
w
n
l
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m
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t
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h
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t
t
o t
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s
t
a
nc
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t
c
an c
om
m
uni
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at
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e
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t
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l
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om
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uni
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at
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t
a
t
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o
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t
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nk
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dea of
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c
hi
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al
ar
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h
i
t
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t
ur
e
i
s
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p t
hes
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y
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ul
t
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op c
om
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uni
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at
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s
t
r
at
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y
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n t
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l
at
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t
t
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e c
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l
g
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t
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s
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f
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t
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t
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m
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om
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c
net
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or
k
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d,
dat
a c
ol
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t
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on a
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or
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d
i
n
g
w
i
t
h
l
i
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on
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ent
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T
hes
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m
ot
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t
o pr
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e
w
c
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go
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t
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t
ud
y
t
he D
i
s
t
r
i
bu
t
ed a
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S
el
f
-
or
gan
i
z
i
n
g Loa
d B
a
l
anc
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ng
C
l
us
t
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i
n
g f
or
W
S
N
.
T
he
m
os
t
i
m
por
t
ant
i
s
s
ue c
ons
i
der
ed
w
h
en
pl
a
nni
ng
W
S
N
C
l
us
t
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i
s
t
he
ener
g
y
c
ons
um
pt
i
on
p
er
no
de
an
d h
o
w
t
he
nex
t
pr
ot
oc
ol
c
an
i
m
pr
ov
e
t
hi
s
.
B
y
s
w
i
t
c
hi
n
g
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e
ac
t
i
v
i
t
i
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t
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po
w
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c
ons
um
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i
s
opt
i
m
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z
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l
eads
t
o
t
he
i
nc
r
eas
ed
net
w
or
k
l
i
f
e t
i
m
e [
1]
.
I
n s
ec
t
i
on 2
w
e di
s
c
us
s
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s
o
m
e of
t
he r
el
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l
us
t
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bas
ed pr
ot
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s
,
t
h
e pr
opos
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D
is
t
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ib
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lf
-
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Load
B
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l
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A
l
gor
i
t
hm
i
n s
ec
t
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on
3,
a
n
d i
n s
ec
t
i
on
4
w
e ana
l
y
s
ed t
he
ne
w
pr
o
pos
ed a
l
gor
i
t
hm
w
i
t
h t
he
s
t
andar
d c
l
us
t
er
i
n
g al
gor
i
t
hm
s
and f
i
nal
l
y
c
onc
l
ud
ed
i
n t
he s
ec
t
i
on
5.
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
D
i
s
t
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bu
t
ed
C
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us
t
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n
g B
as
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d on
N
od
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t
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an
d D
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anc
e i
n
W
ir
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s
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(
S
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k
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)
917
2.
R
el
at
ed
W
o
r
k
Man
y
c
l
us
t
er
i
n
g
a
l
gor
i
t
hm
s
hav
e
b
een
pr
op
os
ed
c
ons
i
der
i
ng
t
he
di
s
t
r
i
but
e
d
pr
oc
es
s
i
ng
and
di
r
ec
t
t
r
ans
m
i
s
s
i
on
f
r
om
C
l
us
t
er
H
ead
(
C
H
)
t
o
ba
s
e
s
t
at
i
on
l
i
k
e
L
EAC
H
,
H
E
ED
.
T
hus
i
f
t
h
e
di
s
t
anc
e
be
t
w
ee
n
t
he
bas
e
s
t
at
i
o
n
a
nd
t
he
c
l
us
t
er
hea
d
i
s
l
ar
ge
t
h
en
l
ar
g
e
am
ount
of
en
er
g
y
i
s
c
ons
um
ed
t
o
s
end
t
he
dat
a
t
o
t
he
bas
e
s
t
a
t
i
o
n
[
3]
.
T
he
a
bo
v
e
m
ent
i
o
ned
al
gor
i
t
hm
us
es
m
ul
t
i
-
hop
pr
o
pag
at
i
on,
i
nc
r
eas
es
ener
g
y
c
o
ns
er
v
a
t
i
o
n.
W
i
t
h
m
ul
t
i
-
hop
c
l
us
t
er
i
n
g,
a
l
i
nk
i
s
es
t
abl
i
s
h
ed
bet
w
e
en t
he m
ul
t
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p
l
e c
l
us
t
e
r
head
nod
es
l
i
k
e c
hai
n an
d t
hes
e C
H
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s
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k
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bor
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t
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f
or
w
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d
t
h
e
s
ens
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d
at
a
b
y
t
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ghb
or
nod
es
i
n
t
he
gr
ou
p
t
o
t
h
e
bas
e
s
t
at
i
o
n.
T
hi
s
m
ul
t
i
-
c
l
us
t
er
i
n
g
m
ec
hani
s
m
i
s
a
bl
e
t
o
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al
anc
e
t
h
e
ener
g
y
c
ons
um
pt
i
on
am
ong
al
l
s
e
ns
or
nodes
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d
ac
hi
e
v
es
a
n ob
v
i
ous
i
m
pr
ov
em
ent
on t
he n
et
w
or
k
l
i
f
et
i
m
e [
3]
.
E
ne
r
gy
-
A
wa
r
e
M
u
lt
i
le
v
e
l
C
l
us
t
er
i
ng
(
E
AM
C
)
[
3]
has
t
he f
ol
l
o
w
i
ng s
al
i
en
t
f
eat
ur
es
.
I
t
ai
m
s
i
n r
educ
i
ng t
he num
ber
o
f
c
l
us
t
er
hea
ds
as
c
l
us
t
er
he
ads
c
ons
um
e
m
or
e
ener
g
y
t
hus
l
es
s
t
he
num
ber
of
CH
s
m
or
e
i
s
t
he
l
i
f
et
i
m
e of
t
he
W
S
N
.
E
A
M
C
f
or
m
s
c
l
us
t
er
i
ng t
r
ee t
o
r
educ
e t
h
e am
ount
of
r
el
a
y
no
des
f
ur
t
her
end
i
ng up i
n r
educ
e
d am
ount
of
dat
a t
r
ans
m
i
s
s
i
on,
s
how
s
ada
pt
i
v
e n
at
ur
e i
n
addi
t
i
on a
nd
r
em
ov
al
of
nod
es
i
nt
o t
h
e c
l
us
t
er
s
r
es
ul
t
i
ng
i
n r
o
bus
t
n
e
s
s
of
t
he al
g
or
i
t
hm
.
A
r
obus
t
c
l
us
t
er
he
ad s
e
l
ec
t
i
on
i
s
i
m
por
t
ant
,
s
o t
hat
c
l
us
t
er
hea
ds
s
pend
l
es
s
en
er
g
y
o
n
aggr
e
gat
i
ng
an
d
f
or
w
ar
di
n
g
m
es
s
ages
,
doi
n
g
g
ener
al
r
o
ut
e
m
ai
nt
e
nanc
e
an
d
s
om
e
ot
her
s
i
m
i
l
ar
ac
t
i
ons
.
W
e ar
e def
i
ni
n
g t
h
e a
l
g
or
i
t
hm
as
s
uc
h
us
ed
i
n [
4]
,
t
he
c
ons
t
r
a
i
ne
d
s
pan c
(
x
)
of
a
node
‘
x
’
i
n t
h
e
E
C
D
S
a
l
gor
i
t
hm
i
s
def
i
ned
as
t
h
e s
m
al
l
er
of
:
t
he
num
ber
of
unc
o
v
er
ed n
ei
ghb
or
s
of
‘
x
’
and t
he c
o
ns
t
r
ai
n
t
of
‘
x
’
.
T
he
nei
g
hbor
s
of
‘
x
’
a
r
e
def
i
ned as
‘
x
’
and
al
l
ot
her
nod
es
w
i
t
h
w
hi
c
h
‘
x
’
s
har
es
a
c
om
m
u
ni
c
at
i
on
l
i
nk
of
good
qu
al
i
t
y
[
4]
.
W
e
us
e
t
he
r
ec
ei
v
ed
s
i
gna
l
s
t
r
en
gt
h
i
nd
i
c
at
or
(
R
S
S
I
)
t
o det
er
m
i
ne l
i
nk
qual
i
t
y
.
R
S
S
I
i
s
di
r
ec
t
l
y
pr
o
por
t
i
ona
l
t
o t
he r
e
c
ei
v
ed s
i
gn
al
s
t
r
engt
h.
U
s
i
ng
t
hi
s
w
e
c
a
n
c
o
m
m
uni
c
at
e
t
o
t
he
nod
es
t
hat
ar
e
i
n
t
he
r
ad
i
o
r
an
ge
near
b
y
w
i
t
h
s
t
r
ong
l
i
nk
c
onnec
t
i
o
n
an
d
l
es
s
er
r
et
r
ans
m
i
s
s
i
on
t
o
de
l
i
v
er
t
h
e
dat
a
s
uc
c
es
s
f
ul
l
y
.
T
he
qual
i
t
y
of
t
he
l
i
nk
i
s
dec
i
ded
b
y
R
S
S
I
and
no
de
d
i
s
t
anc
e
[
4
]
.
A
dj
us
t
i
ng
a
n
odes
‟
ne
i
g
hbor
hood
b
as
ed
o
n
t
he
l
i
nk
qual
i
t
y
a
l
l
o
w
s
us
t
o
us
e
t
he
l
o
w
es
t
pos
s
i
bl
e
p
o
w
er
s
et
t
i
n
g
f
or
t
r
ans
m
i
s
s
i
ons
i
n
or
der
t
o
c
o
m
m
uni
c
at
e
w
i
t
h o
t
her
no
des
i
n
t
he
c
l
us
t
er
.
T
hi
s
l
ead
s
t
o s
om
e addi
t
i
on
al
ener
g
y
s
av
i
ngs
.
I
n H
i
er
ar
c
hi
c
al
S
p
at
i
al
C
l
u
s
t
er
i
ng
(H
S
C
) [
5
]
i
n M
ul
t
i
-
hop
W
SN
s
,
has
c
ons
i
der
e
d t
he
pr
obl
em
of
s
pat
i
al
c
l
us
t
er
i
ng f
or
appr
ox
i
m
at
e dat
a
c
ol
l
ec
t
i
on
wh
i
c
h
i
s
f
eas
i
bl
e an
d en
er
g
y
-
ef
f
i
c
i
ent
.
S
pa
t
i
a
l
c
l
us
t
er
i
ng
ai
m
s
t
o gr
oup t
he
hi
g
hl
y
c
or
r
el
at
ed s
ens
or
n
odes
i
nt
o t
he s
am
e
c
l
us
t
er
f
or
r
ot
at
i
v
e
l
y
r
ep
or
t
i
ng
r
epr
es
ent
at
i
v
e
d
at
a
l
at
e
r
.
I
n
or
der
t
o
dec
i
de
t
he
s
i
m
i
l
ar
nodes
t
he
aut
h
or
s
c
ons
i
der
ed
m
agni
t
ude
an
d
t
r
end
of
t
hei
r
s
en
s
ui
ng
r
ea
di
ngs
.
W
i
t
h
s
uc
h
m
et
r
i
c
s
HS
C
i
s
pr
op
os
e
d
t
o gr
oup t
h
e m
os
t
s
i
m
i
l
ar
s
ens
or
nodes
i
n a di
s
t
r
i
bu
t
ed
w
a
y
[
5]
.
H
S
C
r
uns
on a
pr
ebu
i
l
t
dat
a c
ol
l
ec
t
i
on
t
r
e
e,
an
d t
h
us
get
s
r
i
d of
s
om
e ex
t
r
a r
equi
r
em
ent
s
s
uc
h as
g
l
ob
al
net
w
or
k
t
opo
l
og
y
i
nf
or
m
at
i
on an
d r
i
g
or
ous
t
i
m
e s
y
nc
hr
oni
z
at
i
o
n.
I
n c
l
us
t
er
-
he
ads
s
el
ec
t
i
o
n
m
et
hod c
ons
i
der
i
ng
ener
g
y
b
al
anc
i
ng f
or
w
i
r
el
es
s
s
ens
or
net
w
or
k
[
6]
m
ai
nl
y
c
onc
er
ns
abo
ut
r
em
ov
i
n
g du
pl
i
c
at
e d
at
a f
r
om
s
ens
or
nodes
.
I
n or
d
er
t
o
r
educ
e
W
S
N
s
ener
g
y
c
on
s
u
m
pt
i
on,
C
H
s
ar
e
s
el
ec
t
ed d
y
n
am
i
c
al
l
y
bas
e
d
on
c
l
us
t
er
r
ot
a
t
i
o
n
m
e
c
hani
s
m
.
H
ow
e
v
er
,
t
he
C
H
w
hi
c
h i
s
al
r
e
ad
y
s
el
ec
t
ed c
anno
t
not
be s
e
l
ec
t
ed
agai
n unl
es
s
t
he r
o
und
pr
oc
es
s
i
s
o
v
er
,
ev
e
n t
hou
gh
t
he
no
de
i
s
s
a
i
d t
o
ha
v
e m
or
e en
er
g
y
t
h
a
n ot
her
n
od
es
.
F
ol
l
o
w
i
ng t
h
i
s
,
i
n
W
S
N
s
t
her
e ex
i
s
t
s
a k
i
nd of
i
r
r
e
gul
ar
ener
g
y
c
ons
um
pt
i
on
s
t
at
us
am
on
g
s
ens
or
no
des
b
ec
aus
e
of
C
H
s
ov
er
he
ad
ener
g
y
us
a
ges
,
t
h
e
c
l
us
t
er
h
eads
ar
e
s
el
ec
t
ed
bas
e
d
on t
he r
es
i
d
ual
e
ner
g
y
of
t
he node,
i
r
r
es
p
ec
t
i
v
e of
t
he f
ac
t
w
h
et
her
a no
de has
be
c
o
m
e a c
l
us
t
er
head
i
n
t
h
e
pr
e
v
i
ous
r
o
und
or
no
t
,
b
ut
s
i
nc
e
t
he
c
a
l
c
ul
at
i
n
g
r
es
i
dua
l
ener
g
y
f
or
e
ac
h
no
de
i
t
s
e
l
f
c
ons
um
es
m
or
e
ener
g
y
,
eac
h
no
de
c
hec
k
s
i
t
s
c
u
r
r
ent
ener
g
y
i
t
s
el
f
and
c
hoos
es
a
C
H
t
hem
s
el
v
es
bas
e
d
o
n
t
he
c
al
c
ul
at
i
on
ana
l
y
s
i
s
r
es
ul
t
[
6
]
.
T
hus
s
el
ec
t
i
ng
c
l
us
t
er
h
e
ads
bas
e
d
o
n
t
hei
r
r
es
i
d
ual
e
ner
g
y
,
has
l
ed t
o t
he f
or
m
at
i
on
o
f
a s
e
ns
or
net
w
or
k
w
h
i
c
h c
o
ns
u
m
e
s
l
es
s
en
er
g
y
as
c
om
par
ed t
o L
E
A
C
H
[
11
-
2
1
].
G
r
i
d
B
as
ed
C
H
S
el
ec
t
i
o
n
m
e
c
hani
s
m
(
G
B
C
H
S
)
[
11
]
pr
opos
e
d t
o
par
t
i
t
i
on
t
he
n
et
w
or
k
ar
ea t
o
un
i
f
or
m
s
i
z
e
.
G
B
C
H
S
f
oc
us
s
es
on m
i
ni
m
i
s
i
ng t
he en
er
g
y
di
s
s
i
pat
i
on
and
m
a
x
i
m
i
z
i
n
g t
h
e
net
w
o
r
k
l
i
f
e t
i
m
e.
T
hi
s
pr
opos
ed
m
et
hod e
l
i
m
i
nat
ed t
he
d
y
n
am
i
c
/
s
c
hedul
e
d r
e
-
c
l
us
t
er
i
ng
pr
oc
es
s
as
t
he
C
H
i
s
r
ot
at
ed
w
i
t
h
i
n
t
he
G
r
i
d
p
ar
t
i
t
i
o
n
a
nd
ado
pt
e
d
m
ul
t
i
hop
c
om
m
uni
c
at
i
o
n
and
m
i
ni
m
u
m
di
s
t
anc
e t
o r
o
ut
e
t
he p
ac
k
et
s
t
o t
he d
es
t
i
n
at
i
on.
A
n
a
l
y
t
ic
a
l k
-
c
onnec
t
i
v
i
t
y
pr
oba
bi
l
i
t
y
es
t
i
m
at
i
on [
2
2]
ana
l
y
s
e
d t
he k
-
c
onnec
t
i
v
i
t
y
pr
oba
bi
l
i
t
y
an
d l
i
nk
s
t
abi
l
i
t
y
c
ons
i
der
i
ng t
he f
adi
n
g t
ec
h
ni
q
ues
.
T
he pac
k
et
s
w
er
e r
out
e
d t
hr
ou
gh
mi
n
i
mu
m k
-
node d
i
s
j
oi
nt
c
o
m
m
uni
c
at
i
on
pat
hs
f
or
s
m
a
l
l
s
c
al
e l
ogn
or
m
al
f
adi
ng,
R
a
y
l
ei
gh f
adi
ng
and
N
ak
agam
i
–
m
w
i
t
h
s
up
er
i
m
pos
ed l
og
nor
m
al
s
had
o
w
i
n
g f
adi
ng t
ec
hni
ques
.
B
y
an
al
y
s
i
ng t
h
e
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.
1
4
,
N
o
.
3
,
S
ept
em
ber
201
6
:
9
16
–
92
2
918
par
am
et
er
s
of
node
d
ens
i
t
y
(
λ
)
an
d
l
ogar
i
t
hm
i
c
s
t
andar
d
de
v
i
at
i
on
(
∑)
,
t
he
m
i
ni
m
u
m
node
dens
i
t
y
r
e
qu
i
r
ed
i
s
i
d
ent
i
f
i
e
d.
Mos
t
of
t
he c
l
us
t
er
i
ng a
l
gor
i
t
hm
s
f
ol
l
o
w
r
eg
ul
ar
d
epl
o
y
m
en
t
of
s
ens
or
no
d
es
i
n
di
s
t
r
i
b
ut
e
d
f
as
hi
o
n
w
i
t
ho
ut
c
ons
i
der
i
ng
t
he
no
de
di
s
t
a
nc
e
t
o
t
he
s
i
nk
.
T
hi
s
appr
o
ac
h
i
s
d
i
f
f
er
ent
i
n
pr
ac
t
i
c
a
l
i
m
pl
em
ent
at
i
on
w
her
e
t
he
no
des
ar
e r
an
do
m
l
y
d
ep
l
o
y
ed.
D
S
L
B
C
A
f
or
m
c
l
us
t
er
w
i
t
h
hi
g
hl
y
ba
l
anc
e
d i
n e
ner
g
y
w
h
i
c
h i
n
t
e
r
n r
ed
uc
es
t
he
num
ber
of
c
l
us
t
er
s
gener
at
ed.
D
S
L
B
C
A
c
hec
k
s
t
he
c
onnec
t
e
d
no
d
es
(
node
d
ens
i
t
y
)
an
d
di
s
t
a
nc
e
of
t
he
nod
es
t
o
de
t
er
m
i
ne
t
he
c
l
us
t
er
r
adi
us
.
3.
D
S
L
B
C
A
(D
i
s
tr
i
b
u
te
d
S
e
l
f
-
o
r
g
a
n
i
z
i
n
g
L
o
a
d
B
a
l
a
n
c
i
n
g
C
l
u
s
te
r
i
n
g
A
l
g
o
r
i
th
m
)
T
he al
gor
i
t
hm
s
f
or
c
l
us
t
er
i
ng a
pp
l
i
c
at
i
ons
w
er
e
un
i
f
or
m
l
y
d
i
s
t
r
i
but
ed
W
S
N
’
s
f
ai
l
i
ng
t
o
c
ons
i
der
t
he
d
i
s
t
anc
e
of
t
he
i
n
di
v
i
dua
l
n
odes
t
o
t
he
b
as
e
s
t
at
i
on,
a
nd
t
he
d
ep
l
et
i
on
of
ener
g
y
i
s
t
oo
hi
g
h d
ue
t
o
unb
al
a
nc
ed t
opo
l
og
i
c
al
s
t
r
uc
t
ur
e.
T
he D
S
L
B
C
A
i
s
us
ed f
or
av
o
i
d
i
ng
ex
t
r
a
cl
us
t
er
s
f
or
c
ov
er
i
ng a
l
l
t
h
e nod
es
and c
r
eat
es
a m
or
e bal
anc
e
d c
l
us
t
er
i
n t
er
m
s
o
f
ener
g
y
.
D
S
L
B
C
A
i
s
di
v
i
de
d t
o
t
hr
ee p
has
es
:
C
H
s
e
l
ec
t
i
on
phas
e,
C
l
us
t
er
f
or
m
at
i
on
phas
e
an
d R
e
-
C
l
us
t
er
i
ng phas
e
.
P
h
as
e
I
:
C
l
us
t
er
he
ad
s
e
l
e
c
t
i
on
pr
oc
es
s
i
s
i
n
i
t
i
at
e
d
di
r
ec
t
l
y
onc
e
t
h
e
s
ens
or
n
od
es
ar
e
dep
l
o
y
ed
i
n
t
he
en
v
i
r
onm
ent
.
Let
N
t
r
ef
er
s
t
o
t
he
s
et
of
t
r
i
gger
node,
c
hos
e
n
b
y
t
he
di
s
t
r
i
but
ed
al
g
or
i
t
hm
D
S
L
B
C
A
.
T
hes
e
t
r
i
gger
nod
es
c
al
c
u
l
at
e d
i
s
t
a
nc
e
f
r
om
t
he
bas
e
s
t
at
i
o
n
a
nd c
l
us
t
er
dens
i
t
y
as
r
,
t
he
r
ad
i
us
of
t
he
c
l
us
t
er
,
a
nd
dec
l
ar
es
b
y
s
el
f
as
t
em
por
ar
y
c
l
us
t
er
he
ads
(
T
CH
i
)
,
w
h
er
e
i
i
s
t
he
num
ber
of
par
al
l
el
t
em
por
ar
y
c
l
us
t
er
hea
ds
dec
i
ded
b
y
:
=
[
(
)
/
(
)
]
(
1
)
W
h
er
e
β
i
s
t
h
e
s
ens
or
par
am
et
er
s
di
f
f
er
s
w
i
t
h
t
h
e
a
p
pl
i
c
a
t
i
o
n,
C
r
(
n)
i
s
t
h
e
c
on
n
ec
t
i
v
i
t
y
d
ens
i
t
y
and
D
(
n)
i
s
t
he
d
i
s
t
anc
e
f
r
om
t
he bas
e
s
t
at
i
on
an
d
n
c
al
c
ul
at
e
d us
i
ng
E
quat
i
o
n
(
2)
,
an
d f
l
o
or
f
unc
t
i
on t
o r
ou
ndof
f
c
al
c
ul
at
i
on.
(
)
=
10
|
−
|
1
0
.
(
2
)
Let
A
b
e
t
he
s
i
g
na
l
s
t
r
engt
h
w
i
t
h
d
i
s
t
anc
e
a
d
i
s
t
anc
e
of
1
m
et
er
f
r
o
m
t
he
bas
e
s
t
at
i
on,
[
10]
and
(
)
is
t
h
e
k
-
hop ne
i
gh
bor
of
nod
e
n
,
an
d
(
)
is
k
-
hop nei
ghb
or
s
of
node
n
,
(
)
=
{
∈
|
≠
˄
(
,
)
≤
}
(
3
)
W
h
er
e
d(
n,
v
)
i
s
t
he h
ops
b
et
w
ee
n n
ode
v
and no
de
n
.
T
he c
onnec
t
ed
no
de d
ens
i
t
y
f
or
t
he t
r
i
gg
er
no
de
i
s
c
al
c
ul
at
e
d b
y
:
(
)
=
|
(
,
)
/
,
∈
(
)
∪
{
}
|
|
(
)
|
(
4
)
I
f
t
w
o c
l
us
t
er
he
ads
w
h
i
c
h
ar
e ha
v
i
ng t
he s
am
e c
onne
c
t
i
v
i
t
y
dens
i
t
y
,
t
he
CH
n
od
e
w
h
ic
h
is
hav
i
n
g s
hor
t
er
d
i
s
t
anc
e
t
o
t
he
bas
e
s
t
at
i
on
w
i
l
l
b
e
w
i
l
l
b
e c
h
os
en
b
y
t
h
e c
on
nec
t
i
n
g n
od
es
.
C
al
c
u
l
at
e
no
de
w
e
i
ght
w
(
n)
[
10]
b
y
c
ons
i
der
i
ng
t
h
e t
i
m
es
of
nod
e b
ei
ng
el
ec
t
ed
a
s
c
l
us
t
er
h
ead
i
n pr
e
v
i
ous
r
oun
ds
,
c
l
us
t
er
dens
i
t
y
,
an
d di
s
t
anc
e f
r
om
t
he
bas
e s
t
at
i
on,
g
i
v
en
b
y
as
s
t
at
e
d i
n
equa
t
i
o
n (
5)
.
(
)
=
∅
×
[
(
)
]
+
×
(
)
(
)
−
×
[
(
)
]
,
(
6)
gi
v
en,
0
≤
∅
,
,
≤
1
,
˂
+
˂
1
W
h
er
e
ᶲ
,
ᶿ
and
γ
as
t
he
ef
f
ec
t
f
ac
t
or
s
v
ar
i
es
w
i
t
h
t
y
p
e
of
appl
i
c
at
i
ons
,
R
e(
n)
bei
ng
r
es
i
dua
l
ener
g
y
of
nod
e
n
, [1
0
],
E(
n
)
is
i
ni
t
i
a
l
en
er
g
y
of
nod
e
n
,
an
d
H
(
n)
,
no
de
n
bei
ng el
ec
t
ed
as
c
l
us
t
er
he
ad
pr
ev
i
o
us
l
y
.
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
D
i
s
t
r
i
bu
t
ed
C
l
us
t
er
i
n
g B
as
e
d on
N
od
e D
e
ns
i
t
y
an
d D
i
s
t
anc
e i
n
W
ir
e
le
s
s
…
(
S
as
i
k
u
mar
P
)
919
T
he node
N
t
t
r
i
g
ger
s
c
l
us
t
er
i
ng
pr
oc
es
s
b
y
s
en
di
n
g ne
i
gh
bor
di
s
c
o
v
er
y
(
H
el
l
o)
Mes
s
ages
t
o
i
t
s
k
-
hop n
od
es
near
b
y
.
T
he ne
i
gh
bor
s
w
ho
r
ec
e
i
v
e
t
hi
s
m
es
s
age us
i
ng
(
6)
w
i
l
l
c
al
c
ul
a
t
e t
h
e r
es
pec
t
i
v
e
w
e
i
ght
s
a
nd t
h
em
s
el
v
es
dec
l
a
r
e as
C
H
,
i
f
t
he
y
ar
e s
at
i
s
f
y
i
ng t
he
w
e
i
g
ht
t
hr
es
hol
d.
T
he
par
am
et
er
s
of
T
(w
)
and
T
(k
)
s
hou
l
d
be
i
nv
ok
ed o
n r
eg
ul
ar
bas
i
s
b
y
t
he a
l
g
or
i
t
hm
,
s
uc
h w
a
y
t
ha
al
l
t
he n
od
es
f
i
nds
i
t
s
el
f
a c
l
us
t
er
t
o j
o
i
n.
C
H
_D
ec
l
ar
at
i
on
i
n
T
(w
),
(T
(w
)
<
T
(k
)
),
i
t
dec
l
ar
es
i
t
s
el
f
t
he
c
l
us
t
er
head,
w
her
e
T
(
w)
i
s
w
ai
t
i
ng
t
i
m
e,
and
T
(k
)
i
s
t
he
r
ef
r
es
h
t
i
m
e
r
el
at
e
d
t
o
di
s
t
r
i
but
i
o
n
of
nod
es
and
s
p
ec
i
fi
c
app
l
i
c
at
i
ons
[
10
]
.
T
he s
et
t
i
n
gs
of
T
(
w
)
and
T
(k
)
s
houl
d ens
ur
e t
hat
e
ac
h nod
e i
n t
h
e net
w
or
k
c
an
fi
nd
i
t
s
o
w
n
c
l
us
t
er
he
ad,
a
nd
t
h
e
a
l
gor
i
t
hm
r
es
t
ar
t
s
t
he
c
l
us
t
er
i
ng
pr
oc
es
s
af
t
er
T
(k
)
c
ir
c
u
la
r
l
y
.
P
h
as
e I
I
:
D
S
L
B
C
A
dec
i
des
t
he c
l
us
t
er
s
i
z
e a
nd t
hi
s
s
i
z
e
i
s
k
ept
as
t
hr
es
ho
l
d,
t
he
num
ber
of
nodes
par
t
i
c
i
p
at
i
ng i
n t
he c
l
us
t
er
nodes
s
hou
l
d ha
v
e t
o
f
or
m
c
l
us
t
er
s
w
i
t
h i
n t
h
e t
hr
es
hol
d l
i
m
i
t
.
I
f
t
hi
s
c
l
us
t
er
s
i
z
e
i
nc
r
eas
es
b
e
y
o
nd t
hr
es
ho
l
d a
dd
i
t
i
on
al
o
v
er
h
ead
i
s
c
r
eat
ed
an
d r
educ
es
t
h
e
net
w
or
k
l
i
f
e t
i
m
e.
I
f
C
H
r
e
c
ei
v
es
J
oi
n_C
H
s
e
nt
b
y
a
node,
C
H
w
i
l
l
c
hec
k
t
he
node d
ens
i
t
y
t
hr
es
hol
d
an
d
t
he
n
i
t
w
i
l
l
a
c
c
ept
ne
w
m
e
m
ber
and
up
dat
e
c
l
us
t
er
s
i
z
e
i
f
t
he
s
i
z
e
i
s
s
m
al
l
er
t
ha
n
t
hr
es
ho
l
d,
v
i
c
e
v
er
s
a.
I
n
c
as
e of
f
ai
l
ur
e,
i
t
has
t
o
f
i
n
d a
ne
w
C
H
t
o
j
oi
n
a
nd
p
ar
t
i
c
i
p
at
e
i
n
t
he
net
w
or
k
.
E
ac
h
of
t
he n
o
des
par
t
i
c
i
p
at
i
ng
i
n t
h
e n
et
w
or
k
has
a l
o
ok
up t
ab
l
e t
o s
a
v
e t
he
i
nf
or
m
at
i
on C
H
,
s
i
z
e
of
t
he
node
(
nod
e d
ens
i
t
y
)
P
h
a
s
e
III:
D
SL
BC
A a
l
g
o
r
i
t
h
m
a
v
oi
ds
fi
x
ed
c
l
us
t
er
heads
i
n
t
h
e
net
w
or
k
b
y
d
y
n
am
i
c
c
l
us
t
er
i
ng
s
c
he
m
e.
P
er
i
od
i
c
r
epl
ac
em
ent
t
o
C
H
i
s
i
m
pl
em
ent
ed
t
o
bal
a
nc
e
t
he
no
de
en
er
g
y
c
ons
u
m
pt
i
on.
T
he
c
l
us
t
er
i
s
s
t
at
i
c
unt
i
l
t
h
e
r
e
-
e
l
ec
t
i
on
i
s
t
r
i
gg
er
ed
at
T
(e
)
,
w
h
er
e
T
(e
)
i
s
t
he
t
hr
es
hol
d
t
i
m
e
t
o
re
-
c
l
us
t
er
bas
ed on
r
es
i
d
u
al
ener
g
y
.
C
H
g
at
her
s
t
he
i
nd
i
v
i
d
ual
w
ei
g
ht
s
of
al
l
i
t
s
m
e
m
ber
s
and
s
el
ec
t
s
t
he
ne
w
C
H
bas
ed
hi
g
hes
t
w
e
i
gh
t
,
r
ed
uc
i
ng
w
i
t
h
ex
c
han
ge
of
c
ont
r
o
l
o
v
e
r
head.
H
enc
e
t
he
nec
es
s
i
t
y
f
or
r
e
-
c
l
us
t
er
i
ng
t
he
ent
i
r
e
n
et
w
or
k
i
s
no
t
nee
ded
as
t
he
n
e
w
C
H
i
s
c
hos
en
w
i
t
h
i
n
t
he ex
i
s
t
i
n
g c
l
us
t
er
.
T
he
abov
e
pr
op
os
ed
D
S
L
B
C
A
al
gor
i
t
hm
i
s
ex
t
ended
f
or
m
obi
l
e
W
S
N
env
i
r
o
nm
ent
t
o
o
a
s
D
SL
BC
A
-
Mob
i
l
e (
D
S
L
B
C
A
-
M)
and f
ou
nd c
ha
l
l
e
ngi
ng i
m
pr
ov
em
ent
s
ov
er
t
he c
om
par
ed
al
g
or
i
t
hm
s
b
y
m
odi
f
y
i
ng
w
e
i
ght
c
al
c
u
l
at
i
on
w
i
t
h a
n ad
di
t
i
on
al
par
am
et
er
as
:
(
)
=
∅
×
[
(
)
]
+
×
(
)
(
)
−
×
[
(
)
]
+
×
[
(
)
]
(
6)
W
h
er
e
m
obi
l
i
t
y
f
ac
t
or
(
v
e
l
o
c
i
t
y
)
and
C
(
n)
r
epr
es
en
t
s
t
h
e c
on
nec
t
i
v
i
t
y
l
eng
t
h
of
i
n
t
e
r
v
al
a
no
de
n
i
s
as
s
oc
i
a
t
ed
t
o a
C
H
,
w
i
t
h t
he
as
s
um
pt
i
on C
H
s
h
ou
l
d be s
t
at
i
onar
y
.
4.
S
i
m
u
l
a
ti
o
n
R
e
s
u
l
ts
W
e
c
o
m
par
ed c
l
as
s
i
c
al
c
l
us
t
er
i
ng a
l
g
or
i
t
hm
s
w
i
t
h t
h
e pr
opos
ed a
l
gor
i
t
hm
i
n t
er
m
s
of
pac
k
et
s
s
ent
,
c
l
us
t
er
c
ou
nt
,
en
er
g
y
an
d no
des
a
l
i
v
e.
S
i
m
ul
at
i
o
n par
am
et
er
s
ar
e s
ho
w
n
i
n
T
abl
e 1.
E
ac
h
no
de as
s
i
gn
s
i
t
s
el
f
a r
an
dom
v
al
ue b
et
w
een
0 a
nd
1.
I
f
t
hi
s
v
a
l
u
e
i
s
l
es
s
t
h
an t
he
t
hr
es
hol
d,
t
hat
no
de
bec
om
es
a
c
l
us
t
er
he
ad.
E
ac
h
no
de c
al
c
ul
a
t
es
i
t
s
w
ei
ght
us
i
ng e
qua
t
i
o
n (
5)
and
(
6)
,
i
f
t
h
e
w
ei
g
ht
of
an
y
n
ode
i
s
gr
eat
er
t
h
an
t
he
av
er
a
ge
w
e
i
ght
of
a
l
l
t
he
a
l
i
v
e
n
odes
t
he
n
t
hat
no
de
bec
om
es
t
he c
l
us
t
er
he
ad.
D
S
L
BC
A a
n
d
D
S
L
BC
A
–
M
ar
e c
om
par
ed
w
i
t
h
t
h
e
c
la
s
s
ic
a
l a
lg
or
i
t
hm
s
s
uc
h as
L
EAC
H
an
d
H
E
ED
.
T
o c
om
par
e t
he al
g
or
i
t
hm
s
w
e u
s
ed num
ber
of
r
ounds
r
ef
er
r
i
ng t
he i
nt
er
v
al
bet
w
ee
n i
n
i
t
i
al
c
l
us
t
er
i
n
g t
o r
e
-
c
l
us
t
er
i
n
g as
w
e
l
l
f
r
o
m
one r
e
-
c
l
us
t
er
i
n
g pr
oc
es
s
t
o a
not
her
r
e
-
c
l
us
t
er
i
ng pr
oc
es
s
.
E
ac
h r
ou
nd s
t
ar
t
s
w
i
t
h a
s
et
-
up
-
p
has
e
f
ol
l
o
w
e
d b
y
s
t
ead
y
-
s
ta
te
-
p
h
as
e f
or
f
or
w
ar
d
t
he
dat
a t
o
S
i
nk
.
A
l
gor
i
t
hm
w
i
t
h
l
es
s
er
dead
no
des
i
s
c
hos
en as
t
he b
et
t
er
one
.
F
r
o
m
t
he
F
i
gur
e
1,
i
t
c
a
n
b
e
deduc
e
d
t
ha
t
t
he
num
ber
of
t
hr
oughput
is
h
ig
h
in
it
i
a
ll
y
f
o
r
LE
A
C
H
,
H
E
E
D
an
d D
S
LB
C
A
-
M b
ut
w
i
t
h r
ou
nds
t
h
e
nodes
d
i
e f
as
t
er
i
n L
E
A
C
H
,
H
E
E
D
a
nd
D
SL
BC
A
-
M a
nd
henc
e
ef
f
i
c
i
enc
y
i
s
r
ed
uc
ed c
o
ns
i
der
a
bl
y
w
i
t
h
t
i
m
e.
B
ut
i
n t
he c
as
e
of
D
S
L
B
C
A
,
t
he
pac
k
et
s
ar
e t
r
ans
f
er
r
ed f
or
a
m
uc
h l
onger
t
i
m
e as
t
he nodes
ar
e
a
bl
e t
o s
t
a
y
al
i
v
e
f
or
a
l
on
ger
t
i
m
e.
T
a
k
i
ng
i
n
t
he
per
c
ent
ag
es
of
10,
20,
30,
40
t
o
100
%
,
t
h
e
bei
ng
t
he
no
de
l
i
f
e
t
i
m
e of
D
S
LB
C
A
i
s
m
or
e t
he pac
k
et
s
end r
at
i
o s
t
ea
di
l
y
s
how
h
i
g
her
per
f
or
m
anc
e.
A
t
30%
,
5
0%
and 7
0%
of
r
ounds
t
he
D
S
LB
C
A
s
ho
w
s
s
t
ea
d
y
t
hr
ou
ghpu
t
abo
ut
4
4.
44%
r
a
i
s
e
t
han t
he
ot
her
al
g
or
i
t
hm
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
1
6
9
3
-
6
930
T
E
L
KO
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K
A
V
o
l.
1
4
,
N
o
.
3
,
S
ept
em
ber
201
6
:
9
16
–
92
2
920
T
abl
e 1.
S
i
m
ul
at
i
on
P
ar
am
et
er
s
P
ar
a
m
et
er
s
V
al
ues
I
ni
t
i
al
E
ner
gy
1 J
T
r
ans
m
i
s
s
i
on ener
gy
50 nJ
R
ec
ept
i
on ener
gy
50 nJ
F
r
ee s
pa
c
e
ener
gy
(
E
f
s
)
10 pJ
M
ul
t
i
pat
h
f
adi
ng
ener
gy
(
E
m
p)
0.
0013 pJ
D
at
a
A
ggr
egat
i
on
E
ner
gy
(
E
D
A
)
5 nJ
A
r
ea
10000*
10000 m
2
P
a
c
k
e
t
s
i
ze
:
J
oi
n m
es
s
age
(
P
jm
)
A
c
k
now
l
edgem
ent
(
P
ac
k
)
C
l
us
t
er
head
m
es
s
age (
P
c
hm
)
P
a
c
k
e
t
s
i
ze
(
P
si
z
e
)
2000 B
i
t
s
2000 B
i
t
s
2000 B
i
t
s
2000 B
i
t
s
C
oor
di
nat
es
of
t
he
S
i
n
k
(
50,
175)
N
um
ber
o
f
node
s
1000
N
um
ber
o
f
r
ounds
100
S
peed of
t
he M
obi
l
e node
(
M
obi
l
e
E
nv
i
r
onm
en
t
)
0.
02 m
/
s
e
c
F
i
gur
e
1.
T
hr
ough
put
of
t
he
net
w
or
k
f
or
v
ar
i
o
us
al
gor
i
t
hm
s
T
he
nu
m
ber
of
c
l
us
t
er
s
f
or
m
ed
per
r
ound
i
n
bot
h
t
h
e
al
g
or
i
t
hm
s
is
in
it
ia
ll
y
t
h
e
s
a
m
e
a
s
s
ho
w
n
i
n
F
i
gur
e
2
. B
u
t
w
i
t
h
r
ounds
i
t
c
a
n
be
s
ee
n t
h
at
t
her
e
ar
e m
or
e
c
l
us
t
er
s
i
n
t
h
e
c
as
e
of
D
S
L
B
C
A
as
c
om
par
ed t
o LE
A
C
H
,
H
E
E
D
and D
S
L
B
C
A
-
M
.
T
he num
ber
of
c
l
us
t
er
s
t
o be
f
or
m
ed as
s
i
gned
as
1
0 a
n
d o
v
er
t
he
i
t
er
at
i
o
ns
i
t
i
s
i
dent
i
f
i
ed
t
hat
af
t
er
25
%
of
i
t
er
a
t
i
o
ns
(
25
r
ounds
)
o
n
l
y
l
es
s
num
ber
of
nodes
i
n
t
he
LE
A
C
H
ar
e al
i
v
e
and
t
he
y
f
or
m
as
a s
i
ng
l
e
c
l
us
t
er
.
T
he per
f
or
m
anc
e o
f
H
E
E
D
i
s
good u
pt
o 3
5%
of
i
t
er
at
i
o
ns
and du
e t
o s
t
ab
l
e c
l
us
t
e
r
s
i
n D
S
LB
C
A
s
ho
w
s
l
es
s
num
ber
of
c
l
u
s
t
er
s
and i
s
m
ai
nt
ai
n
ed c
ons
t
ant
ov
er
i
t
er
at
i
o
ns
c
om
par
ed
t
o t
he
m
obi
l
e D
S
LB
C
A
(
D
S
LB
C
A
-
M)
,
i
n t
he
l
at
er
s
t
a
ges
s
ho
w
s
due t
o m
obi
l
i
t
y
f
ac
t
or
D
S
L
B
C
A
-
M
f
r
equent
l
y
c
h
ang
es
t
op
ol
o
g
y
a
nd a
pr
e
y
t
o f
r
equ
ent
r
e
-
c
l
us
t
er
i
n
g.
T
o anal
y
s
e
t
he
en
er
g
y
ef
f
i
c
i
enc
y
nod
e n
um
ber
70
i
s
c
hos
en
t
o c
om
par
e
i
t
s
ener
g
y
c
ons
um
pt
i
on s
ubj
ec
t
t
o v
a
r
i
ous
al
gor
i
t
hm
s
.
F
i
gur
e 3 s
how
s
t
h
e r
es
i
du
al
e
ner
g
y
le
v
e
l
i
n t
he
a
lg
o
r
it
h
m
s
is
in
it
ia
ll
y
s
a
m
e
.
A
t
30
%
an
d 50%
of
r
ounds
i
t
c
an b
e s
ee
n t
ha
t
t
he
r
es
i
dua
l
en
er
g
y
in
node
70
i
s
m
or
e i
n t
he c
as
e of
D
S
LB
C
A
ab
out
11%
a
nd 1
3%
,
f
i
nal
l
y
r
eac
h
es
1
9
%
at
t
he
en
d
of
100 r
o
unds
as
c
om
par
ed t
o
LE
A
C
H
,
H
E
E
D
a
nd D
S
L
B
C
A
-
M.
F
r
o
m
t
he
F
i
gur
e
4
,
i
t
c
an
b
e
c
onc
l
u
ded
t
hat
t
he
n
odes
di
e
f
as
t
er
i
n
LE
A
C
H
,
H
E
E
D
and
D
SL
BC
A
-
M as
c
om
par
ed t
o D
S
L
B
C
A
.
B
ut
i
n t
he c
as
e of
D
S
LB
C
A
,
t
h
e pac
k
et
s
ar
e t
r
ans
f
er
r
ed
f
or
a
m
uc
h l
ong
er
t
i
m
e as
t
he n
odes
ar
e ab
l
e
t
o s
t
a
y
a
l
i
v
e f
or
a
l
on
ger
t
i
m
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
D
i
s
t
r
i
bu
t
ed
C
l
us
t
er
i
n
g B
as
e
d on
N
od
e D
e
ns
i
t
y
an
d D
i
s
t
anc
e i
n
W
ir
e
le
s
s
…
(
S
as
i
k
u
mar
P
)
921
F
i
gur
e
2.
N
um
ber
of
c
l
us
t
er
s
of
t
he net
w
or
k
f
or
v
ar
i
ous
al
g
or
i
t
hm
s
F
i
gur
e
3.
R
es
i
du
al
en
er
g
y
of
t
he no
des
f
or
v
ar
i
ous
a
l
gor
i
t
hm
s
F
i
gur
e 4.
A
l
i
v
e
n
odes
i
n
t
he
net
w
or
k
f
or
v
ar
i
ous
a
l
gor
i
t
hm
s
T
he pr
opos
ed
a
l
gor
i
t
hm
s
s
ho
w
n
i
m
pr
ov
ed r
es
u
l
t
s
b
y
e
ner
g
y
s
a
v
i
ng
and
de
ad
nod
es
c
ount
o
v
er
m
ul
t
i
p
l
e r
ou
nds
.
E
v
en af
t
er
s
ev
er
al
i
t
er
at
i
o
n
s
w
e ar
e ab
l
e t
o
w
i
t
nes
s
t
h
e per
f
or
m
anc
e
of
s
t
at
i
on
ar
y
nod
es
an
d f
i
x
ed C
H
’
s
s
h
o
w
i
ng
bet
t
er
r
es
ul
t
s
t
h
an
t
he m
obi
l
e
no
des
du
e t
o
l
i
n
k
s
t
abi
l
i
t
y
a
nd t
opo
l
o
g
y
c
han
ges
.
5.
C
o
n
c
l
u
s
i
o
n
I
n
t
h
i
s
ar
t
i
c
l
e,
w
e
pr
o
pos
e
d
a
d
i
s
t
r
i
bu
t
ed
l
o
ad
bal
anc
i
n
g
c
l
us
t
er
i
ng
al
gor
i
t
hm
f
or
W
S
N
s
,
c
ons
i
der
i
ng
op
t
i
m
al
t
hr
es
h
ol
d
f
or
c
l
us
t
er
s
c
onf
i
g
ur
at
i
on.
C
om
par
ed
w
i
t
h
LE
A
C
H
,
H
E
E
D
an
d
D
SL
BC
A
-
M
al
gor
i
t
hm
,
t
he
pr
opos
e
d
a
l
gor
i
t
hm
s
uppor
t
s
t
o
f
or
m
a
s
t
at
i
c
c
l
us
t
er
and
i
m
pr
ov
e
d
net
w
or
k
l
i
f
e t
i
m
e.
T
he s
i
mul
at
i
o
n r
es
ul
t
s
ho
w
s
t
hat
t
he al
g
or
i
t
hm
i
s
m
or
e
s
t
abl
e and i
m
pr
ov
ed
per
f
or
m
anc
e
abou
t
1
5%
o
v
er
al
l
c
ons
i
der
i
ng
r
es
i
dua
l
e
ner
g
y
an
d
n
et
w
or
k
l
i
f
e
t
i
m
e.
C
ons
i
der
i
ng
t
he pr
ac
t
i
c
a
l
i
m
pl
i
c
at
i
ons
w
e hav
e us
ed 1
000
0
x
1000
0 ar
ea
w
i
t
h 10
00 no
des
t
o f
or
our
ana
l
y
s
i
s
and f
ound t
ha
t
t
he pr
op
os
ed s
c
hem
e i
s
s
how
i
ng i
m
pr
ov
e
d r
es
ul
t
s
f
or
bot
h s
t
at
i
c
and m
obi
l
e
env
i
r
onm
ent
pr
o
v
i
ng
t
he
s
c
hem
e
s
uppor
t
i
ng
s
c
al
ab
i
l
i
t
y
and
s
upp
or
t
s
net
w
or
k
of
d
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e
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Z
i
gbee)
f
or
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o
m
m
uni
c
at
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on
.
R
ef
er
en
ces
[1
]
R
een
-
C
hen
g W
a
ng,
R
uay
-
S
hi
ung
C
ha
ng,
J
e
i
-
H
s
i
ang
Y
en,
P
u
-
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Le
e
.
A
D
y
nam
i
c
T
opol
ogy
R
ef
or
m
a
t
i
on A
l
gor
i
t
hm
f
or
P
ow
er
S
a
v
i
ng i
n Z
i
gB
ee S
e
n
s
or
N
et
w
or
k
s
.
I
n
t
er
na
t
i
o
nal
J
our
n
al
o
f
D
i
s
t
r
i
b
ut
ed
S
en
s
or
N
et
w
or
k
s
.
2013;
201
3:
10
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN
:
1
6
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3
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6
930
T
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201
6
:
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16
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2
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[2
]
S
ant
ar
P
al
S
i
ngh,
S
C
S
har
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.
A
S
ur
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ey
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d R
out
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e on A
dv
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ppl
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C
AC
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A)
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I
ndi
a,
M
um
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.
201
5;
45:
687
-
695
.
[3
]
X
i
nf
ang Y
an,
J
i
a
ngt
a
o X
i
,
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o
e F
C
hi
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o,
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ang
uang Y
u
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En
e
rg
y
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A
w
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ul
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s
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et
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nf
or
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at
i
on P
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o
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e
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s
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ng
.
S
y
dn
ey
,
A
us
t
r
al
i
a.
200
8
:
38
7
-
3
92
.
[4
]
J
ul
i
a A
l
b
at
h,
M
ay
ur
T
hak
ur
,
S
anj
ay
M
adr
i
a
.
E
ner
gy
C
ons
t
r
ai
nt
C
l
us
t
er
i
ng A
l
gor
i
t
h
m
s
f
o
r
W
ir
e
les
s
S
ens
or
N
et
w
or
k
s
.
A
d H
oc
N
et
wo
r
k
s
.
201
3;
11
(
8)
:
2
512
-
2525
.
[5
]
Z
hi
da
n
L
i
u,
W
e
i
X
i
ng,
Y
ongc
hao
W
a
ng,
D
ong
m
i
ng
Lu
.
H
i
er
ar
c
h
i
c
al
S
p
at
i
al
C
l
us
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er
i
n
g
i
n
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u
l
t
i
h
op
W
i
r
el
e
s
s
S
en
s
or
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et
w
or
k
s
.
I
nt
er
nat
i
ona
l
J
our
na
l
of
D
i
s
t
r
i
but
e
d S
ens
or
N
et
w
or
k
s
.
20
13;
1
1
.
[6
]
C
hoon
-
S
un
g
N
am
,
Y
oung
-
S
hi
n H
a
n
,
D
o
ng
-
R
y
eol
S
hi
n
.
T
he C
l
us
t
er
-
H
e
a
ds
S
el
ec
t
io
n
M
e
t
h
od
c
on
s
i
der
i
ng
E
ner
gy
B
a
l
an
c
i
n
g f
or
W
i
r
el
e
s
s
S
en
s
or
N
et
w
or
k
s
.
I
nt
er
nat
i
ona
l
J
our
n
al
of
D
i
s
t
r
i
but
e
d
S
ens
or
N
et
w
or
k
s
.
2013
;
6
.
[7
]
W
end
i
B
H
ei
nz
el
m
an
,
A
nant
h
a P
C
handr
ak
a
s
an
,
H
ar
i
B
al
a
k
r
i
s
hnan
.
A
n A
ppl
i
c
at
i
on
-
S
pe
c
i
f
i
c
P
r
o
t
o
c
ol
A
r
c
hi
t
ec
t
ur
e f
or
W
i
r
e
l
es
s
M
i
c
r
os
en
s
or
N
et
w
or
k
s
.
I
E
E
E
T
r
a
ns
a
c
t
i
o
ns
on
W
i
r
el
e
s
s
C
om
m
uni
c
at
i
o
ns
.
2002;
1(
4)
:
660
-
670
.
[8
]
A
M
ut
hul
ak
s
hm
i
,
S
H
ar
i
r
am
an
.
Load
B
al
anc
ed
W
i
t
h D
i
s
t
r
i
bu
t
ed S
e
l
f
O
r
gan
i
z
at
i
o
n i
n
F
i
l
e S
har
i
ng
an
d
F
ile
A
c
c
e
s
s
in
g
.
I
nt
e
r
nat
i
ona
l
J
our
n
al
o
n R
ec
ent
a
nd I
nnov
at
i
o
n T
r
e
nds
i
n C
om
p
ut
i
ng
an
d
C
om
m
uni
c
at
i
on
.
2014
;
2(
5)
;
9
90
-
996
.
[9
]
V
W
i
ndha M
ahy
as
t
ut
y
,
A Ad
y
a
Pra
m
u
d
i
t
a
.
L
ow
E
ner
gy
A
dapt
i
v
e C
l
u
s
t
er
i
ng H
i
er
ar
c
hy
R
out
i
n
g
Pro
t
o
c
ol
f
or
W
i
r
e
l
e
s
s
S
ens
or
N
et
w
or
k
.
T
EL
KO
M
N
I
KA
.
2014
;
12(
4)
:
963
-
968
.
[
10]
Y
Li
ao,
H
Q
i
,
W
Li
.
L
oad
-
bal
a
n
c
ed c
l
u
s
t
er
i
ng
al
gor
i
t
hm
w
i
t
h di
s
t
r
i
but
ed
s
e
l
f
-
or
g
ani
z
at
i
on
f
or
w
i
r
el
es
s
s
en
s
or
n
et
w
or
k
s
.
I
EEE Se
n
s
o
rs
J
o
u
rn
a
l
.
2
013;
13(
5)
:
14
98
-
1506
.
[
11]
K
hal
i
d
H
as
eeb,
K
am
a
l
r
ul
ni
z
a
m
A
bu B
ak
ar
,
A
bd
ul
H
an
an A
bdul
l
a,
A
d
nan
A
hm
e
d.
G
r
i
d B
as
ed C
l
us
t
e
r
H
ead S
el
ec
t
i
on M
ec
ha
n
i
s
m
f
or
W
i
r
el
es
s
S
en
s
or
N
e
t
w
or
k
.
T
E
L
KO
M
N
I
KA
.
2015
;
1
3(
1)
:
269
-
276
.
[
12]
M
C
hat
t
er
j
e
e,
S
K
D
as
,
D
T
ur
g
ut
.
W
C
A
:
A
w
ei
ght
ed
c
l
u
s
t
er
i
n
g
al
g
or
i
t
h
m
s
f
or
m
ob
i
l
e
ad
h
o
c
net
w
or
k
s
.
C
l
us
t
er
C
om
put
i
ng
.
2
002;
5(
2)
:
193
-
20
4
.
[
13]
Y
F
er
nandes
s
,
D
M
al
k
hi
.
K
-
c
l
us
t
er
i
ng
i
n
w
i
r
e
l
e
s
s
ad
-
hoc
n
e
t
w
or
k
s
.
P
r
o
c
ee
di
n
gs
of
t
h
e
s
e
c
ond
A
C
M
i
nt
er
n
at
i
o
nal
w
or
k
s
ho
p
on
P
r
i
n
c
i
pl
es
of
m
obi
l
e c
o
m
put
i
ng
.
20
02
:
31
-
37
.
[
14]
M
Lehs
ai
ni
,
H
G
uy
enn
et
,
M
F
eha
m
.
A
no
v
el
c
l
u
s
t
er
-
ba
s
e
d
s
el
f
or
ga
ni
z
at
i
on
al
gor
i
t
hm
f
or
w
ir
e
le
s
s
s
en
s
or
net
w
or
k
s
.
I
nt
er
nat
i
ona
l
S
y
m
pos
i
u
m
on
C
ol
l
ab
or
at
i
v
e
T
ec
hno
l
ogi
es
and
S
y
s
t
e
m
s
,
2008.
C
T
S
2008
.
I
rv
i
n
e
,
U
SA.
200
8
:
19
-
26
.
[
15]
N
M
i
tto
n
, B
S
er
i
c
ol
a,
S
T
ix
e
u
il,
E
F
l
eu
r
y
,
I
G
Las
s
o
us
.
Se
l
f
-
s
t
a
b
il
iz
a
t
io
n
in
S
e
lf
-
or
ga
ni
z
ed W
i
r
el
e
s
s
M
ul
t
i
hop N
et
w
or
k
s
?
.
A
d H
o
c
&
S
ens
o
r
W
i
r
el
e
s
s
N
e
t
w
or
k
s
.
2
011;
1
1(
1
-
2
):
1
-
34
.
[
16]
Z
henq
uan Q
i
n,
C
a
n M
a,
Lei
W
a
ng,
J
i
aq
i
X
u,
B
i
ngx
i
an
.
A
n O
v
er
l
appi
n
g C
l
us
t
er
i
n
g A
ppr
oa
c
h f
o
r
R
out
i
ng
i
n
W
i
r
e
l
es
s
S
e
ns
or
N
e
t
w
or
k
s
.
I
nt
er
nat
i
ona
l
J
our
n
al
o
f
D
i
s
t
r
i
but
e
d S
en
s
or
N
e
t
w
or
k
s
.
2013;
11
.
[
17]
H
oom
an
H
em
a
t
k
h
ah
,
Y
ous
ef
S
K
av
i
an
.
D
C
P
V
P
:
D
i
s
t
r
i
but
ed c
l
u
s
t
er
i
ng pr
o
t
oc
ol
us
i
ng
v
ot
i
ng an
d
p
ri
o
ri
t
y
f
or
w
i
r
el
es
s
s
en
s
or
n
et
w
or
k
s
.
S
ens
or
s
(
S
w
i
t
z
er
l
and)
.
2015;
15(
3)
:
57
63
-
57
82
.
[
18]
J
i
e W
u
,
Li
y
i
Z
ha
ng
,
Y
u B
ai
,
Y
uns
h
an S
un
.
C
l
us
t
er
-
ba
s
ed c
o
ns
en
s
u
s
t
i
m
e s
y
nc
hr
oni
z
at
i
on
f
or
w
i
r
el
es
s
s
en
s
or
n
et
w
or
k
s
.
I
E
E
E
S
ens
or
s
J
o
ur
na
l
.
2
015;
15(
3)
:
14
04
-
1
413
.
[
19]
B
B
ar
an
i
dhar
an,
S
S
r
i
v
i
dhy
a,
B
S
an
t
hi
.
E
ner
gy
ef
f
i
c
i
ent
hi
er
ar
c
h
i
c
al
uneq
ual
c
l
us
t
er
i
ng
i
n w
i
r
el
e
s
s
s
en
s
or
n
et
w
or
k
s
.
In
di
an
J
our
n
al
of
S
c
i
e
nc
e an
d T
e
c
hn
ol
og
y
.
2014;
7(
3)
:
301
-
305
.
[
20]
Y
i
ng Li
ao
,
J
i
anj
i
ng S
he
n
,
Y
i
L
in
,
C
han
gl
i
n Z
hou
.
Q
ua
nt
i
t
at
i
v
e anal
y
s
i
s
of
net
w
or
k
c
o
nf
i
gur
at
i
on i
n
r
ando
m
i
z
ed di
s
t
r
i
bu
t
i
o
n
w
i
r
el
e
s
s
s
en
s
or
n
et
w
or
k
s
.
I
EEE
Se
n
s
o
rs
J
o
u
rn
a
l
.
20
14;
14(
6)
:
197
4
-
1979
.
[
21]
U
pas
an
a D
oh
ar
e,
D
K
Lob
i
y
al
,
S
us
hi
l
K
um
ar
.
E
n
er
gy
ba
l
a
nc
ed
m
o
del
f
or
l
i
f
et
i
m
e
m
ax
i
m
i
z
at
i
o
n i
n
r
ando
m
l
y
di
s
t
r
i
but
e
d w
i
r
el
e
s
s
s
en
s
or
n
et
w
or
k
s
.
W
i
r
e
l
es
s
P
er
s
ona
l
C
om
m
uni
c
at
i
ons
.
20
14;
78(
1)
:
407
-
428
.
[
22]
N
ages
h
K
N
,
S
at
y
anar
ay
an
a
D
,
M
N
G
i
ri
Pra
s
a
d
.
A
n
A
nal
y
t
i
c
al
E
x
pr
es
s
i
on
f
or
k
-
co
n
n
e
ct
i
vi
t
y
o
f
W
i
r
el
e
s
s
A
d H
o
c
N
et
w
or
k
s
.
T
EL
KO
M
N
I
KA
.
2014
;
12
(
1
):
1
79
-
188
.
Evaluation Warning : The document was created with Spire.PDF for Python.