Indonesi
an
Journa
l
of El
ect
ri
cal Engineer
ing
an
d
Comp
ut
er
Scie
nce
Vo
l.
12
,
No.
3
,
Decem
ber
201
8
, p
p.
1045
~
1053
IS
S
N: 25
02
-
4752, DO
I:
10
.11
591/ijeecs
.v1
2
.i
3
.pp
1
045
-
1
053
1045
Journ
al h
om
e
page
:
http:
//
ia
es
core.c
om/j
ourn
als/i
ndex.
ph
p/ij
eecs
A
N
ovel
M
ulti
pat
h Routin
g R
in
g Proto
col
Adapted
for WM
SN
B.M.
Ta
j
,
M.
Ait Kbi
r
Facul
t
y
of
Sci
en
ce
s a
nd
T
ec
hnol
og
y
,
L
abor
a
tor
y
LIST,
Univ
ersity
of
Abdelma
le
k
Essadi,
l’Aé
roport, Km
10,
Z
ia
t
en. BP
:
4
16,
T
angier, 600
00,
Moroc
co
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
J
un
6
, 2018
Re
vised Jul
2
1
,
2018
Accepte
d
S
ep
2
1
, 201
8
In
thi
s
pape
r
an
enha
nc
ed
protocol
of
m
ult
ipa
th
r
outi
ng
ring
that
is
suita
ble
for
tra
nsferri
ng
images
b
y
m
aki
ng
m
any
upgra
des.
First,
instead
of
using
propa
gation
betw
ee
n
the
lay
e
rs,
we
use
ce
rta
in
par
amete
rs
such
dista
nc
e
and
del
a
y
to
pic
k
the
next
node
o
f
the
lower
lay
er.
Th
en,
we
used
an
het
ero
g
ene
ous
n
et
work,
in
cl
udin
g
sensors
(ca
pture
and
send
i
m
age
s)
and
conne
c
tors
(serve
as
a
bridg
e
t
o
the
sink).
Fin
al
l
y
,
we
used
t
he
p
y
rami
d
dec
om
positi
on
t
ec
hniqu
e.
To
a
void
conge
st
ion
,
we
adj
ust
th
e
num
ber
of
le
ve
ls
base
d
on
the
st
ate
of
the
net
work.
To
v
eri
f
y
our
protocol,
we
use
d
Casta
lia
sim
ula
t
or
to
sim
ula
te
t
he
real
tra
nsm
ission
condi
ti
ons.
The
n,
w
e
compare
d
it
wit
h
GPSR
protoc
ol
and
the
original
Multi
pa
th
routi
ng
ring
protoc
ol
.
Our
proposed
protoc
ol
prove
s
it
s
eff
ic
ie
nc
y
b
y
tra
nsfe
rring
m
ore
images
with
bet
t
er
qual
i
t
y
(PS
NR)
and
consum
ing
le
ss
ene
rg
y
c
om
par
ed
to
othe
r
pro
toc
ols
.
Ke
yw
or
ds:
Ca
sta
li
a
GP
SR
Mult
ipath ro
uting ri
ng
M
W
SN
Pyram
idal t
echn
iq
ue
Copyright
©
201
8
Instit
ut
e
o
f Ad
vanc
ed
Engi
n
ee
r
ing
and
S
cienc
e
.
Al
l
rights re
serv
ed.
Corres
pond
in
g
Aut
h
or
:
B.M
. Ta
j
,
Faculty
of S
ci
e
nces a
nd Tec
hnol
og
y,
Lab
or
at
ory
L
I
ST, Un
i
versi
ty
o
f
Abdel
m
a
le
k
Essa
di,
l’Aéro
port,
K
m
1
0,
Ziat
en.
BP
:
416, Ta
ng
i
er, 6
0000, M
orocco
.
Em
a
il
:
ben
na
ni.taj@gm
ai
l.com
1.
INTROD
U
CTION
The
rap
i
d
devel
op
m
ent
in
the
m
ic
ro
-
el
ect
ro
m
echan
ic
al
syst
e
m
(MEM
S)
has
m
ade
possible
t
he
creati
on
of
m
iniat
ur
iz
ed
a
nd
af
ford
a
ble
sens
or
s
.
The
s
e
m
iniat
ur
iz
ed
sens
or
s
c
omm
un
ic
at
e
wirelessl
y.
A
se
ns
or
is
a
c
om
bin
at
ion
of
m
ul
ti
ple
com
p
on
e
nts
li
ke
tra
ns
m
is
sio
n
unit
,
powe
r
unit
co
ntr
ol,
pro
cessi
ng
unit
and co
ntr
ol
un
i
t [1
]
. In
addit
io
n
to
the
basic c
om
po
ne
nts,
a
s
ens
or
ca
n be e
qu
i
pp
e
d wit
h
s
pecial
sen
s
ors
wh
ic
h
can
sen
se
an
d
m
easur
e
th
e
su
r
rou
nd
i
ng
env
ir
onm
ent
su
ch
as
te
m
per
at
ur
e,
di
sta
nce,
pr
es
s
ure
et
c
.,
and
t
ran
s
f
or
m
them
into
di
gital
values.
T
he
acq
uire
d
da
ta
are
store
d
or
tra
ns
m
it
ted
base
d
on
t
he
need.
Nev
e
rtheless
,
t
he
li
m
i
ta
ti
on
of
a
sens
or
is
a
big
iss
ue
f
or
m
any
reas
on
s
.
First,
there
is
a
li
m
it
ation
i
n
the
processi
ng
power
wh
ic
h
affe
ct
s
pr
oce
ssin
g
of
d
at
a.
T
he
n,
the
li
m
it
ed
energy
aff
ect
s
the
a
m
ou
nt
of
store
d
data. Fi
nally
, th
e li
m
it
at
ion
in
term
o
f
ene
r
gy
aff
ect
s
the life
tim
e d
ur
at
io
n o
f
se
ns
ors
[
2]
.
Figure
1. Str
uc
ture of
a se
nsor
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
12
, N
o.
3
,
Dece
m
ber
2
01
8
:
1045
–
1053
1046
A
net
wor
k
of
l
ink
e
d
se
ns
ors
(hu
ndreds
or
t
hous
a
nd
no
des
in
a
la
r
ge
are
a)
f
or
m
s
a
wir
el
ess
sens
or
netw
ork
(
WSN).
I
n
fact,
it
cov
er
s
a
la
rg
e
area
and
use
d
in
m
ulti
ple
areas:
m
i
li
ta
r
y,
m
edical
,
in
du
st
rial
m
on
it
or
ing
or
env
i
ronm
ental
ph
e
no
m
ena,
e
tc
.
The
acq
uir
ed
data
are
tra
ns
m
itted
fr
om
on
e
se
nsor
node
t
o
ano
t
her
unti
l
t
hey
reac
h
the
sink
(
base
sta
ti
on)
[1
]
.
T
his
s
ink
is
an
e
xit
to
a
rem
ote
ext
ern
al
de
vice
(e
.g
.
th
e
internet)
. T
his
dev
ic
e c
an
b
e
us
e
d
f
or sto
rin
g,
a
naly
zi
ng a
nd
pr
ocessi
ng
da
ta
as sho
wn in
the
F
i
gure
2
[
2]
/
Figure
2.
WSN arc
hitec
ture
On
the
co
ntra
r
y
of
WSN
w
hi
ch
ca
n
tr
ansm
i
t
on
ly
scal
a
r
da
ta
,
W
MS
N
ca
n
tra
ns
m
it
m
or
e
siz
ed
an
d
com
plex
data
l
ike
m
ultim
edia
co
ntent.
In
MWS
W,
se
nsor
nodes
a
re
e
quipp
e
d
with
se
nsors
that
ca
n
ca
pture
m
ul
tim
edia
con
te
nt.
This
ki
nd
of
net
wor
k
ha
s
seve
ral
st
ruct
ur
es
[
3
]
incl
ud
i
n
g
the
sin
gl
e
-
ti
er
flat
,
the
sing
le
-
ti
er
cl
us
te
red
and
m
ulti
-
ti
er.
In
ou
r
pa
per,
we
ap
plied
th
e
second
str
uc
ture
by
usi
ng
sens
or
s
(cap
t
ure
an
d
transm
it
in
age
s)
a
nd
co
nnect
or
(sim
ple
n
od
es
ser
ving
as
a
bri
dge).
T
he
F
igure
3
dep
ic
ts
the
a
rch
it
ect
ur
e
that
we
us
e
d.
I
n
f
act
,
W
M
SN
r
equ
i
res
so
m
e
QOS
dem
and
s
.
These
dem
and
s
c
ould
be
t
he
highest
ba
ndwi
dth
dem
and
,
the
us
e
of
cr
os
s
-
la
ye
r,
the
li
m
it
of
r
eso
ur
ces
(e
nergy,
m
e
m
or
y,
et
c...
)
an
d
th
e
c
od
i
ng
of
m
ultim
edia
con
te
nt [3].
Figure
3. Use
d wirele
ss
m
ultim
edia se
nsor
net
work arc
hitec
ture
Wh
e
n
it
c
om
es
to
process
im
ages,
m
any
m
e
thods
e
xist.
T
he
pyram
id
m
e
t
hod
[
4
]
is
one
of
t
he
m
os
t
eff
ic
ie
nt
te
ch
ni
qu
e
s.
It
us
es
th
e
Gau
s
sia
n.
T
he
Gau
s
sia
n
pyr
a
m
id
is
cal
culat
ed
as
f
ollow
s
.
The
ori
gi
nal
im
age
is
processe
d
w
it
h
a
Gau
ssian
kernel.
As
a
resu
lt
,
we
get
an
im
age
with
a
low
pass
fil
te
red
ver
si
on
of
t
he
o
ri
gin
al
im
age.
The
F
ig
ur
e
4 s
hows
t
his
proc
ess.
Figure
4. Ga
ussi
an
a
nd Lap
la
ci
an
py
ram
ids
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
A Novel M
ulti
path
Ro
utin
g
Ri
ng Pr
oto
c
ol A
dapte
d
fo
r WM
SN
(
B.M.
T
aj
)
1047
In
W
MSN
,
m
a
ny
la
ye
rs
interf
ere
in
the
tra
nsfer p
r
ocess
li
ke
rad
io
la
ye
r
,
Ma
c
la
ye
r,
app
li
c
at
ion
la
ye
r
and
es
pecial
ly
the
r
outi
ng
la
ye
r.
R
ou
ti
ng
pr
oto
c
ols
play
s
a
m
ajo
r
ro
le
i
n
m
anag
in
g
t
he
l
i
m
i
te
d
res
ourc
es
an
d
deliveri
ng
im
a
ges
in
go
od
qual
it
y
at
the
sa
m
e
tim
e
.
Ma
ny
r
ou
ti
ng
pro
tocols
e
xist
li
ke
cl
us
te
red
r
ou
ti
ng
protoc
ol
and
m
ul
ti
path
routing
protoc
ol.
I
n
cl
us
te
red
prot
oco
ls
,
nodes
ar
e
gr
ou
ped
int
o
a
set
cal
le
d
clu
ste
rs
.
Each
cl
us
te
r
ha
s
a
cl
us
te
r
-
he
ad
with
wh
ic
h
al
l
oth
er
m
e
m
b
ers
c
omm
un
ic
at
e.
It
is
the
onl
y
node
i
n
the
c
luster
that
is
al
lowe
d
to
se
nd
data
out
of
t
he
cl
us
te
r.
Ma
ny
pr
oto
c
ols
in
th
e
sam
e
cat
eg
or
y
e
xis
t,
su
c
h
a
s
Tee
n
[
5],
M
-
Leach
[
6],
LEAC
H
[
7]
et
c.
Mult
ipath
prot
oco
ls
c
onsis
t
of
us
in
g
different
nodes
be
tween
t
he
s
our
ce
an
d
the
sin
k.
The
r
oad
to
ta
ke
ca
n
be
sta
ti
c
or
dynam
ic
dep
e
nd
i
ng
on
t
he
r
ou
ti
ng
proto
co
l.
The
re
a
re
m
ulti
ple
protoc
ols
li
ke
DD
[8
]
,
SPIN
[9
]
,
S
AR
[
10
]
,
GP
SR
[11
]
,
m
ulti
path
rou
ti
ng
ri
ng
[
12
]
,
et
c
.
In
t
his
work,
We
are
interes
te
d
in
m
ulti
path
r
ou
ti
ng
row
ing
.
This
s
pec
ia
l
pr
ot
oco
l,
buil
d
la
ye
rs
sta
rting
from
the
sink,
and
eac
h
node
belo
ngs
to
a
la
ye
r.
The
inter
m
ediat
e
no
des
are
ch
os
en
between
the
lo
we
r
la
ye
rs
un
ti
l
arr
ivi
ng
to the si
nk.
Durin
g
T
his
pa
per,
we
are
go
i
ng
to
ha
ve
dif
f
eren
t
sect
io
ns
.
First,
we
ar
e
goin
g
to
prese
nt
the
relat
ed
works.
T
hen,
we
will
detai
l
our
pr
oto
c
ol.
Af
te
r
t
hat,
w
e
are
goin
g
to
exp
la
in
a
nd
a
naly
ze
the
res
ults
of
si
m
ulati
on
s tha
t we m
ade.
Fin
al
ly
, w
e w
il
l fi
nish o
ur p
a
pe
r wit
h
a
final c
oncl
us
i
on.
2.
RESEA
R
CH MET
HO
D
The
m
os
t im
po
rtant thin
g
in
WSN is
trans
fe
rr
in
g data t
o
th
e sink
. Act
uall
y, on
e
of
t
he
bi
g
chall
en
ges
that
w
e
face
is
the
dista
nce
betwee
n
nodes
beca
use
of
t
he
li
m
i
te
d
tra
ns
m
issio
n
ra
nge
of
nodes
.
Mult
ipath
r
ou
t
ing
pr
oto
c
ols
can
so
l
ve
this
issue.
M
ulti
ple
protoc
ols
al
rea
dy
exist
li
ke
G
PSR
an
d
Mult
ipath
routin
g
ri
ng.
2.1.
G
PS
R
R
ou
tin
g Pro
t
oc
ol
The
G
reed
y
P
erim
e
te
r
Stat
eless
Rou
ti
ng
al
gorithm
Con
sist
s
of
f
orwardi
ng
pack
et
s
us
ing
m
ulti
ple
m
et
ho
ds.
At
fir
st,
we
use
the
gr
ee
dy
f
orwardin
g
to
deliver
pack
et
s
to
t
he
cl
os
est
node
.
T
o
tran
sm
i
t
the
pack
et
to the ne
xt
node
, w
e
use t
he
posit
ion (
or
i
gin
and the
destina
ti
on
of the
pac
ket)
a
nd the
lo
cal
o
ptim
al
g
reed
y.
In
the
first
ph
ase
Of
GP
SR
,
we
us
e
t
he
or
igin
an
d
the
de
sti
nation
of
t
he
pac
ket
f
or
forw
a
r
ding
it
t
o
the
ne
xt
ho
p
us
i
ng
t
he
loc
al
op
ti
m
al
gr
e
edy.
A
ny
sen
s
or
node
knows
the
ra
dio
po
si
ti
on
of
his
nei
ghbors
.
The
ne
xt
ho
pe
is
picked
base
d
on
desti
natio
n'
s
po
sit
io
n.
T
his
proces
s
is
rep
eat
e
d
unti
l
the
pac
ket
gets
to
its
destinat
io
n.
Figure
5. Exa
m
ple o
f
gree
dy
forwar
ding.y i
s the cl
os
est
point o
f x
neig
hbers fo
rw
a
r
d
The
F
ig
ur
e
5
s
hows
an
e
xam
ple
of
the
gr
ee
dy
nex
t
ho
pe
cho
ic
e.
In
the
fig
ur
e,
the
se
nsor
node
X
sen
ds
a
pack
et
to
D,
an
d
the
range
of
X
app
ea
rs
in
a
ci
r
cl
e.
The
arc
w
it
h
rad
ius
is
e
qu
al
to
the
distance
be
twee
n
Y
a
nd
D.
T
he
sen
sor
node
X
trans
m
it
s
the
pack
e
t
to
Y
if
the
distance
bet
ween
Y
an
d
D
i
s
le
s
s
than
the d
ist
a
nce
be
tween
D
a
nd a
ny o
t
her sen
sor
nod
e
. T
his
pro
cess is re
peate
d un
ti
l t
he pac
ket r
eac
he
d D.
The
previ
ous
al
gorithm
is
us
ed
by
sens
or
nodes
to
get
inf
orm
ation
of
al
l
it
s
neighbors.
This
updat
e
process
is
re
pe
at
ed
per
i
od
ic
al
ly
.
Du
ri
ng
this
process,
al
l
node
s
transm
it
t
heir
inf
orm
ation
(ID,
po
sit
io
n,
et
c.
)
to the net
w
ork
.
If
a
node
is
not
receivin
g
a
be
acon
as
a
res
pons
e
from
a
neig
hbor
f
or
l
onge
r
tha
n
tim
eou
t
inte
rv
a
l
,
a
GP
SR
r
ou
te
r
will
con
sider
the
neig
hbor
as
dead
or
go
ne
ou
t
of
r
an
ge,
and
rem
ov
es
the
neig
hbor
f
r
om
it
s
ta
ble. T
he 802.
11 m
ac la
ye
r
i
nd
ic
at
es t
he
li
nk level
of r
et
ra
ns
m
issi
on
f
ai
lu
res
to
n
ei
ghbor
s.
The
ad
va
ntage
of
grade
f
or
wardin
g
is
the
dep
e
nd
e
nce
only
on
the
kn
ow
le
dg
e
of
th
e
fo
r
wa
rd
i
ng
node'
s
i
m
m
ediat
e
neighb
or
s
.
I
n
this
ste
p,
th
e
den
sit
y
of
node
s
is
m
or
e
im
po
rtant
than
oth
e
r
thin
gs
li
ke
the
nu
m
ber
of
no
de
s.
In
this
proc
ess,
we
use
m
u
lt
i
-
hop.
Als
o,
t
he
total
nu
m
ber
of
nodes
m
us
t
be
higher
tha
n
the
nu
m
ber
of the
neig
hbor'
s n
od
e. Once t
his
process
fail
s, we
us
e t
he pe
rim
eter
fo
rw
a
rd
i
ng
m
et
ho
d.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
12
, N
o.
3
,
Dece
m
ber
2
01
8
:
1045
–
1053
1048
2.2.
Multi
-
Pa
th
Routin
g Ri
ng
Mult
ipath
r
ou
t
ing
ri
ng
is
a
routin
g
prot
oc
ol
that
is
us
in
g
the
noti
on
of
la
ye
rs
ar
ou
nd
th
e
sink,
and
each
la
ye
r
co
ntainer
node
).
T
he
distanc
e
from
the
sink
det
erm
ines
the
le
vel
of
t
he
la
ye
r
sta
rting
from
0
(sink)
. T
his
protoc
ol foll
ows
two
ste
ps
: c
ons
tructi
on
ph
as
e
and the
sen
ding
ph
a
se.
I
n
the
first
st
ep
Th
e
sin
k
node
cr
eat
es
the
la
ye
rs
by
broa
dcasti
ng
t
he
to
po
l
og
y
s
et
up
pack
et
.
The
nodes
wh
i
ch
recei
ve
it
be
long
to
la
ye
r
1.
T
he
n,
the
node
s
that
bel
ong
t
o
le
vel
1
Broa
dcasts
the
sam
e
pack
et
.
Nodes
receivin
g
t
he
pa
cket
f
orm
la
yer
s.
This
proce
ss
is
re
peate
d
un
ti
l
al
l
no
des
ha
ve
a
la
ye
r
l
evel.
Af
te
r
this ste
p ends, t
h
e tra
nsm
issi
on
step
begins
.
T
he
F
i
gure
6 de
picts t
he
for
m
at
ion
of
la
ye
rs.
Figure
6.
N
ode
s org
a
nized
in
l
ay
ers
Ma
ny
ways
of
transm
it
ti
ng
pa
ckets
f
r
om
hig
he
r
la
ye
rs
exi
st.In
[
13]
they
pro
pose
a
n
al
gorithm
in
wh
ic
h
a
routin
g
ta
ble
is
no
t
need
e
d.
When
a
no
de
wan
ts
to
transm
it
a
pack
et
,
it
broa
dcasts
it
to
the
lowe
r
le
vel.
The
n,
th
e
interm
ed
ia
te
node
does
the
sam
e
thing
.
T
hi
s
pr
oce
ss
is
rep
eat
ed
unti
l
the
pack
et
gets
to
th
e
base s
ta
ti
on.
3.
PROP
OSE
D PROTO
COL
In
t
his
pap
e
r,
we
ar
e
goi
ng
t
o
propose
an
im
pr
ov
e
d
m
ultip
at
h
r
ou
ti
ng
ring
r
ou
ti
ng
prot
oco
l,
w
hich
i
s
adopted
t
o
im
a
ge
tra
ns
fe
r.
O
ur
pro
pose
d
pro
tocol
Co
nsum
e
s
le
ss
ene
rg
y
a
nd
ca
n
tra
nsfer
m
or
e
im
ages
with
a
bette
r
qual
it
y.
Actuall
y,
ori
gi
nal
m
ult
ipath
r
ou
ti
ng
rin
g
pr
oto
c
ol
us
es
br
oad
ca
st
betwe
en
la
ye
rs
to
tr
ansm
i
t
pack
et
s
an
d
does
n'
t
us
e
any
routin
g
ta
ble,
wh
ic
h
has
m
ul
ti
ple
dr
aw
bac
ks.
First,
the
en
erg
y
co
nsum
pt
ion
is
high
beca
us
e
of
the
re
peati
ng
broa
dcasti
ng
process
.
Sec
ond,
the
pro
pa
gation
of
pac
kets
pro
vokes
a
c
olli
sio
n
of
pa
ckets.
Fi
na
ll
y,
this
pr
otoc
ol
su
f
fer
s
fro
m
a
sever
e
loss
of
pac
kets
w
hich
af
fects
th
e
nu
m
ber
of
re
cei
ved
i
m
ag
es.
I
n
or
de
r
to
s
olv
e
the
se
pro
blem
s,
we
propose
d
a
heter
og
e
ne
ou
s
arc
hitec
ture
base
d
on
se
nsors
an
d
connecto
rs.
Al
so
, the
transm
i
ssion
process i
s b
ase
d
on ro
uting
table
wh
ic
h
m
ini
m
iz
es the traf
fic in eac
h
la
ye
r.
Finall
y, the im
age c
om
pr
ession rati
o i
s ada
p
ta
ble in fu
nctio
n of t
he
sta
te
of the
n
et
work.
3.1.
Constr
u
ction
Ph
as
e
A
t
first,
the
la
ye
r
ID
of
al
l
nodes
is
-
1.
A
lso,
A
node
c
on
ta
in
s
two
routing
ta
bles
(one
f
or
lo
we
r
connecto
rs
a
nd
on
e
f
or
lowe
r
sens
or
s
)
w
hich
are
init
ia
ll
y
e
m
pt
y.
The
for
m
at
ion
of
la
ye
rs
sta
rts
from
t
he
sin
k
by
broa
dcasti
ng
a
c
on
st
ru
ct
io
n
pa
cket.
This
pack
et
c
onta
in
s
the
posit
io
n
of
t
he
sin
k.
Th
e
bo
t
h
kinds
of
node
s
that
receive
th
e
pack
et
form
t
he
la
ye
r
1.
Als
o
,
they
st
or
e
th
e
po
sit
io
n
of
th
e
sink
a
nd
the
delay
from
the
sin
k
.
The
n,
the
node
s
of
la
ye
r
1
broad
ca
s
t
the
con
str
uction
pac
ket
again
.
T
he
nodes
that
receive
this
pack
e
t
fo
rm
the
la
ye
r
2.
Th
e
la
ye
rs
that
are
upper
tha
n
1
store
data
ab
out
al
l
po
ssible
paths
f
r
om
the
sink
inclu
ding
t
he
total
distance
f
ro
m
the
sink
,
t
he
total
dela
y
fr
om
the
sink
,
the
RSSI
of
the
lower
node
,
t
he
distance
fro
m
the
lowe
r
node
an
d
the
rem
ai
nin
g
energy
of
al
l
the
nodes
of
th
e
path.
I
f
a
node
receives
a
pa
cket
from
a
se
ns
or
,it
stores
the
i
nform
at
ion
about
the
pat
h
in
the
sens
or
r
outi
ng
ta
ble
oth
e
rw
ise
it
store
them
i
n
co
nnect
or
routi
ng
ta
ble.
T
hen
,
th
e
node
s
of
la
ye
r
2
broad
ca
st
the
c
onstructi
on
pack
et
t
o
for
m
up
per
la
ye
rs
.
T
he
sam
e
pro
eess
is
rep
eat
e
d
a
gain
and
a
gain
unti
l
al
l
nodes
belo
ng
to
their
co
rresp
onding
la
ye
r.
T
he
F
ig
ur
e
7
sho
ws
t
he
network
after
form
at
ion
. T
hen tw
o ph
a
ses b
e
gin
:
upda
te
p
ha
se a
nd tran
sm
issi
on
phase.
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
A Novel M
ulti
path
Ro
utin
g
Ri
ng Pr
oto
c
ol A
dapte
d
fo
r WM
SN
(
B.M.
T
aj
)
1049
Figure
7. Co
nnect
or
s a
nd se
nsors
for
m
ed
in l
ay
ers
3.2.
Tr
an
smi
ssion
P
hase
Durin
g
t
his
ph
ase,
se
ns
or
no
des
tra
ns
m
it
their
data
t
ow
a
r
d
the
sin
k.
I
n
our
protoc
ol,
s
ens
or
nodes
captu
re
i
m
ages
and
se
nd
them
to
connecto
r
node
s.
I
n
oth
e
r
hand,
c
onnect
ors
ser
ve
as
a
bri
dg
e
th
rou
ghou
t
the
diff
e
re
nt
la
ye
rs
unti
l
the
sin
k.
All
no
des
of
la
ye
r
1
se
nd
their
pack
et
s
di
rectl
y
to
the
s
ink
by
a
dju
sti
ng
the
transm
issi
on
powe
r
in
f
onct
ion
of
t
he
sin
k
'
s
RSSI.
T
he
s
ens
or
nodes
of
a
la
ye
r
n
tran
sm
it
their
data
to
the
connecto
rs
of
t
he
lo
we
r
(n
-
1).
Be
fore
sen
ding
a
ny
pack
et
,
the
sel
ect
io
n
of
the
ne
xt
node
f
ollows
the
F
ig
ur
e
8.
Th
us
,
t
he
ne
xt
r
od
e
can
c
ha
ng
e
de
pe
ndin
g
on
t
he
tra
ff
ic
an
d
pac
kets
c
an
fo
ll
ow
dif
f
eren
t
path
s
as
sh
ow
n
in
F
ig
ure
9.
(a)
(b)
Figure
8. The
process
u
se
d
t
o sel
ect
the
nex
t
nod
e
3.
3
.
Up
d
at
e
and
Im
age
Compressi
on
This
ste
p
sta
rts
after
the
form
at
ion
phase,
a
nd
it
is
an
essenti
al
par
t
of
our
protoc
ol.
It
he
lps
to
fin
d
const
antly
the
path
wh
ic
h
ha
s
the
le
ast
traf
fic.
The
up
date
process
us
es
per
i
od
ic
a
nd
per
m
anen
t
wa
y.
Eac
h
per
i
od
of
ti
m
e,
the
si
nk
sta
rts
this
process,
a
nd
it
goes
fro
m
la
ye
r
to
la
ye
r.
Seco
nd,
w
he
n
a
co
nnect
or
node
transm
it
s
a
pack
et
,
it
up
date
s
it
s
relat
i
ve
i
nfor
m
at
ion
in
the
nodes
of
the
uppe
r
la
ye
r.
Actuall
y,
we
update
essenti
al
ly
the
delay
an
d
t
he
rem
ai
nin
g
e
ne
rg
y.
A
nother
featur
e
of
our
protoc
ol
is
the
va
riant
c
om
pr
essio
n
rati
on
base
d
on
the
delay
.
Ea
ch
pe
rio
d
of
ti
m
e,
the
routin
g
pr
oto
c
ol
cal
culat
es
t
he
num
ber
of
le
vels
ba
sed
on
the
thr
ou
ghput
of
the
li
nk
bet
ween
the
se
nso
r
an
d
t
he
sin
k.
As
s
how
n
in
T
able
1,
m
or
e
th
e
delay
is
sho
rt
le
ss
the
com
pr
essi
on
is.
T
hen,
th
e
cal
culat
ed
va
lue
is
tra
ns
m
i
tt
ed
to
a
pp
li
ca
ti
on
la
ye
r
us
in
g
T
he
cr
os
s
la
ye
ring
te
chn
iq
ue
.
As
a d
irect
e
ff
ect
,
we
c
on
t
ro
l t
he si
ze of the
pac
ket foll
owin
g
t
he
sta
te
of
t
he netw
ork
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
12
, N
o.
3
,
Dece
m
ber
2
01
8
:
1045
–
1053
105
0
Table
1.
N
um
ber
of
Level
i
n
Pyram
idal Tec
hn
i
qu
e
in
Fonc
ti
on
of
De
bit
Deb
it
o
f
the lin
k
in Kb
p
s
Nu
m
b
e
r
o
f
lev
els
>=1
0
0
1
1
0
0
>…>=7
5
2
7
5
>…>=5
0
3
5
0
>…>=2
5
4
4.
RESU
LT
S
AND DI
SCUS
S
ION
4
.
1
.
Pr
opose
d
A
ppli
ca
tions
In
orde
r
t
o
e
valuate
our
pr
oto
c
ol,
we
c
r
eat
ed
a
m
ulti
m
edia
ap
plica
ti
on
i
n
Ca
sta
li
s
sim
ulator.
This
a
pp
li
cat
io
n
us
es
O
pen
c
v
to
c
om
pr
ess
a
nd
dec
om
pr
ess
i
m
ages
by
a
pply
ing
m
ulti
ple
le
vels
in
py
r
a
m
idal
com
pr
essio
n
te
chn
i
qu
e
.
Als
o,
va
ry
in
g
the
tim
e
of
sen
di
ng
im
ages
by
us
in
g
a
tim
er.
In
our
ap
pli
cat
ion
,
we
f
ollow
m
ulti
ple
ste
ps
.
Fir
st,
the
sens
or
node
s
captu
re
the
gray
i
m
age
i
m
age.
Then,
the
capt
ur
e
d
im
age
is
treat
ed
by
us
i
ng
the
Ga
us
sia
n
and
La
placi
an
t
ran
sf
orm
s.
Af
te
r
that,
we
di
vid
e
the
ob
ta
i
ne
d
im
age
on
bl
ocks
of 8
×
8. Finall
y, we
apply
RL
E/Hu
ff
m
an
p
rocess as s
how
n
i
s
F
ig
ur
e
10.
Figure
10. C
om
pr
ession/d
ec
om
pr
essio
n process
of JP
EG im
age u
sin
g
t
he
p
yram
idal co
m
pr
ession
te
c
hniq
ue
4
.
2
.
Sim
ulat
i
on
P
ar
ame
ter
s
In
ou
r
pa
per
,
we
us
ed
a
distribu
ti
on
of
20
0
node
s
ov
er
200x200
m
2
as
sh
own
in
the
F
igure
11.
Th
e
Table
2
s
ho
ws
the
par
am
et
er
s
us
e
d
in
our
sim
ulati
on
s.
The
F
ig
ure
12
sho
ws
the
ori
gin
al
i
m
age
.
Figure
11. Dist
rib
ution o
f nod
es in t
he
s
pace
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
A Novel M
ulti
path
Ro
utin
g
Ri
ng Pr
oto
c
ol A
dapte
d
fo
r WM
SN
(
B.M.
T
aj
)
1051
Table
2.
Sim
ul
at
ion
’s
p
a
ram
e
te
rs
Para
m
eter
Valu
e
Tpo
lo
g
y
size
2
0
0
x
2
0
0
m
2
Si
m
u
latio
n
ti
m
e
2
6
0
0
s
Nu
m
b
e
r
o
f
no
d
es
200
Period
between
se
n
d
in
g
pack
ets
0
.1 s
I
m
ag
e
co
m
p
ressio
n
90%
Nu
m
b
e
r
o
f
tr
ials
20
Initial p
o
wer
400j
BS p
o
sitio
n
(0,0
)
Percentag
e of
sen
so
rs
50%
Percentag
e of
con
n
ecto
rs
50%
MAC pro
to
co
l
Tun
ab
le M
AC
Figure
12. Ori
gin
al
im
age to
be
se
nt
4
.
3
.
Discussi
on
Res
ults
To
e
valuate
ou
r
pro
posed
r
outi
ng
pr
oto
c
ol,
we
com
par
e
d
it
with
GPSR
and
m
ulti
path
r
ou
ti
ng
rin
g
routin
g
prot
oc
o
l.
Als
o,
we
us
e
d
three
a
ppr
oac
hes.
Fir
st,
we
assess
t
he
e
nergy
eff
ic
ie
ncy
by
cal
culat
ing
.
The
en
er
gy
con
s
um
ption
of
the
hall
net
work
pe
r
tim
e
.
Seco
nd,
we
evaluate
the
m
ul
tim
edia
ef
fici
ency
by
getti
ng
the
com
plete
d
i
m
a
ges
by
the
sin
k
in
f
un
ct
io
n
of
ti
m
e.
F
inally,
we
us
e
d
the
PSN
R
of
rece
iving
i
m
ages
to
m
easur
e
their
qual
it
y.
Actuall
y,
we
m
easur
e
the
num
ber
of
im
ages
in
functi
on
of
their
corres
pondin
g PSNR.
Figure
13. E
ne
rg
y c
onsu
m
ption pe
r
ti
m
e
The
F
ig
ure
13
represents
th
e
energy
co
ns
um
pt
ion
pe
r
ti
m
e
fo
r
al
l
node
s.
It
sho
ws
a
com
par
ison
betwee
n
PS
N
R,
m
ult
ipath
r
ou
ti
ng
rin
g
an
d
ou
r
prot
oc
ol.
The
grap
h
s
hows
that
both
GP
SR
a
nd
Mu
lt
ipath
routin
g
rin
g
co
ns
um
es
near
ly
the
sam
e
hig
h
l
evel
of
e
nergy.
Also
,
it
shows
that
ou
r
proto
col
consum
es
by
far
le
ss
ener
gy
th
an
the
oth
e
r
prot
oco
ls.
The
s
e
resu
lt
s
c
ould
be
e
xp
la
ine
d
by
m
any
reasons.
First,
the
GP
SR
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
12
, N
o.
3
,
Dece
m
ber
2
01
8
:
1045
–
1053
1052
routin
g
prot
oc
ol
us
es
gr
e
edy
per
im
et
er
and
the
pe
rim
e
te
r
fo
r
wardin
g
m
eth
ods.
The
se
m
et
hods
m
ake
a
lot
of
transm
issi
on
s,
wh
ic
h
m
eans
high
ene
rg
y
c
on
s
um
ption
.
A
lso
,
the
c
on
sta
nt
update
f
or
neig
hbors
m
ake
the
nodes
co
nsum
es
m
or
e
ene
r
gy
.
Seco
nd,
the
m
ulti
path
rou
ti
ng
rin
g
us
es
the
broad
ca
st
to
tra
ns
m
it
data
from
la
ye
r
to
la
ye
r
un
ti
l
the
sin
k.
Th
us
,
al
l
node
s
of
t
he
net
work
c
onsu
m
e
a
l
ot
of
e
ne
rg
y.
Wh
e
n
it
com
e
s
to
ou
r
protoc
ol,
it
co
ns
um
es
le
ss
en
erg
y
f
or
m
any
reasons
.
First
of
al
l,
e
ver
y
tr
ansm
issi
on
ene
rg
y
is
a
dju
ste
d
to
the
distance
of
the
ta
rg
et
ed
no
de.
The
n,
we
don'
t
us
e
t
he
broa
dc
ast
as
a
m
et
ho
d,
but
a
pack
et
m
us
t
be
receiv
ed
by
a sp
eci
fic c
onne
ct
or
.
A
ls
o,
t
he
u
s
e
of h
et
e
rog
eneous
node
s
by
u
sin
g
a
perce
ntage o
f
no
des t
o
tra
ns
m
i
t t
he
data
cal
le
d
connect
or
s
.
The
rest
of
nods
Ar
e
cal
le
d
sens
or
s
,
an
d
they
tur
n
to
sle
ep
sta
te
when
they
delive
r
the
i
m
age.
A
fter a
wh
il
e, t
hey be
c
om
e act
ive to del
iver
a
no
t
her im
age,
an
d
t
he c
yc
le
is rep
eat
ed
a
gain
a
nd a
gain.
Figure
14. N
um
ber
o
f recei
ve
d
im
age as
f
unct
ion o
f
tim
e
Figure
15. perc
entage
of r
e
cei
ved com
plete
d im
age
as fun
ct
io
n o
f protoc
ol
The
F
i
gure
14
is
a
gr
a
ph
th
at
rep
re
sents
t
he
num
ber
of
com
plete
d
i
m
a
ges
by
the
sin
k
pe
r
ti
m
e.
It
ref
le
ct
s
t
he
m
ul
tim
edia
eff
ic
ie
ncy
of
t
he
t
hr
ee p
ro
t
oco
ls.
In
this
fi
gure,
w
e
ca
n
see
cl
e
arly
That o
ur pro
t
oco
l
is
m
or
e
eff
ic
ie
nt
tha
n
oth
e
r
prot
oco
ls.
T
hese
res
ul
ts
are
c
onfirm
ed
by
the
gr
a
ph
of
F
ig
ure
15
w
hich
sho
ws
t
he
per
ce
ntage
of
com
plete
d
i
m
a
ges.
It
s
how
s
t
hat
our
protoc
ol
is
th
e
m
os
t
eff
ic
ie
nt
a
nd
m
ulti
path
routin
g
rin
g
i
s
the
le
ast
ef
fici
ent.
In
fact,
w
e
can
ex
plain
these
r
esults
w
it
h
m
any
reasons.
First,
G
PS
R
us
es
interm
ediat
e
nodes
by
a
pply
ing
a
G
reed
y
Perim
et
er
m
eth
od
c
onsta
ntly
.
Since
the
de
nsi
ty
of
nodes
a
ff
ect
s
GP
SR
r
ou
ti
ng
protoc
ol,
t
he
nu
m
ber
of
int
erm
ediat
e
no
de
s
inc
reases.
The
delive
red
pack
et
s
to
t
he
sin
k
decr
eas
e
,
w
hich
aff
ect
s
The
im
age
co
ns
tr
uc
te
d
by
the
sink.
On
the
ot
her
s
ide,
Mult
ipath
routin
g
rin
g
suffe
rs
from
a
severe
pro
blem
wh
ic
h
is
the
broa
dca
st.
Act
ually
,
w
hen
a
se
nsor
node
se
nd
s
a
pa
cket,
it
ca
n
be
receive
d
in
f
ull
ra
ng
e
of
t
ran
sm
issi
on
ca
us
in
g
the
colli
sion
of
pack
et
s
.
T
his
pro
blem
re
du
c
es
co
ns
ide
ra
bly
the
am
ou
nt
of
the
receive
d
pack
e
ts
by
the
si
nk
and
the
num
ber
of
c
om
plete
d
i
m
ages
is
le
ss.
Finall
y,
our
prot
oco
l
has
m
ulti
ple
featur
e
s
that
m
ake
it
m
or
e
eff
ic
ie
nt.
First,
it
us
es
la
ye
rs
,
w
hich
li
m
it
the
num
ber
of
interm
ediat
e
nodes
.
Th
u
s,
t
he
pac
kets
ar
rive
qui
ckly
to
T
he
sink.
Sec
ond,
t
he
ch
oice
of
th
e
ne
xt
node
is
base
d
on
dela
y
and
distance.
S
o,
i
t
can
avo
id
c
onge
sti
on.
Thir
d,
us
i
ng
the
de
la
y
as
a
crit
e
ria
to
choose
the
com
pr
essio
n
rati
o
m
akes
us
c
on
tr
ol
the
siz
e
of
the
pac
kets.
Ac
tua
ll
y,
the
avera
ge
of
the
c
ompressi
on
rati
o
i
s
10%,
wh
ic
h
pro
ves
the
eff
ic
ie
ncy
of
our
pr
oto
c
ol
.
Finall
y,
Usin
g
c
onnect
or
node
s
to
co
nduc
t
the
pack
et
to
the
sin
k,
dim
inishes
the co
ll
isi
on z
ones a
nd c
onges
ti
on
. T
hese
f
ea
tures
m
ake ou
r
pro
t
oco
l m
or
e
su
it
able f
or
W
MSN tra
nsfer
.
Figure
16. N
um
ber
o
f recei
ve
d
im
ages p
er
PSN
R
us
in
g GPSR
Figure
17. N
um
ber
o
f recei
ve
d
im
ages p
er
PSN
R
us
in
g
M
ulti
path routi
ng r
i
ng
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
A Novel M
ulti
path
Ro
utin
g
Ri
ng Pr
oto
c
ol A
dapte
d
fo
r WM
SN
(
B.M.
T
aj
)
1053
Figure
18. N
um
ber
o
f recei
ve
d
im
ages p
er
PSN
R
us
i
ng our p
ro
t
oco
l
The
F
ig
ur
es
16,
17
a
nd
18
s
how
t
he
total
nu
m
ber
of
im
a
ger
pe
r
P
SN
R
qual
it
y.
Accord
i
ng
to
t
he
F
igure
17,
Mu
lt
ipath
r
ou
ti
ng
rin
g
has
the
m
ini
m
u
m
received
im
ages
even
if
they
a
re
com
plete
d.
T
hu
s
,
the
nu
m
ber
of
lost
i
m
ages
is
hig
h
,
w
hich
is
91
00
im
ages.
In
th
e
F
igur
e
16,
G
PSR
delive
rs
a
la
rg
e
va
riet
y
im
ages
from
lower
qu
al
it
y
to
co
m
plete
i
m
ages.
Al
though,
the
num
ber
of
lost
i
m
ages
is
69
76
im
ages,
wh
ic
h
is
i
m
po
rtant.
Fin
al
ly
,
the
F
ig
ure
18
s
hows
t
ha
t
our
protoc
ol
i
s
nea
r
to
100
%
of
ef
fici
enc
y
by
99%
of
c
om
plete
i
m
age
s
an
d
0
l
os
t
im
ages.
Th
ese
res
ults
c
onfirm
the
pr
e
vious
res
ults
m
aki
ng
ou
r
protoc
ol
the
best
am
on
g
th
e
three
protoc
ols
.
5.
CONCL
US
I
O
N
In
t
his
pa
per,
we
m
ade
an
ap
plica
ti
on
that
c
om
pr
ess/
dec
om
pr
ess
i
m
ages
us
in
g
the
Ga
ussi
an
an
d
t
he
Laplaci
an
t
ransform
s,
And
t
he
num
ber
of
le
vels
dep
e
nds
on
the
sta
te
of
t
he
netw
ork.
T
hen,
the
c
om
pr
essed
i
m
ages
are d
el
ivere
d
to
the n
e
twork
a
nd d
ec
om
po
sed
at
t
he
sink. A
ct
ually
,
we
us
e
d
this
a
pp
li
cat
io
n
to
te
st
the
eff
ic
ie
ncy
of
our
protoc
ol
in
te
rm
of
m
ultim
edia
con
te
nt
transm
is
sion
.
We
can
de
duc
e
that
our
prot
oco
l
is
m
or
e
eff
ic
ie
nt
by
delive
rin
g
i
m
ages
in
good
qual
it
y
and
bi
g
qu
a
ntit
y.
Als
o,
we
pro
ved
that
it
co
ns
um
es
le
ss
energy.
W
e c
oncl
ude that o
ur p
r
opos
e
d
prot
oco
l i
s m
or
e su
it
able fo
r
the
M
W
SN
c
om
par
ed
to
oth
er
protoc
ols.
A
lt
hough, it
could
be o
ptim
ized
to
tra
ns
fe
r m
or
e com
plex
m
ul
tim
edia con
te
nt li
ke
v
i
de
os
.
REFERE
NCE
S
[1]
Estri
n
D,
Cul
le
r
D,
Pis
te
r
K,
a
nd
Sukhatme
G.
Connecting
th
e
ph
y
si
cal
worl
d
with
per
vasiv
e
net
works
.
I
EEE
Pe
rvasiv
e
Comp
uti
ng
.
no.
1.
Jan
uar
y
2002;
Vol.
(1)
59
-
69.
[2]
Rahman
K
C.
A
surve
y
on
sensor
net
work
.
Journ
al
of
Computer
and
Information
Technol
og
y
.
no.
1,
2010
;
Vol
.
(1
)
76
-
87.
[3]
Abaz
ee
d
M,
Fai
sal
N,
Zuba
ir
S,
and
Ali
A.
Routi
ng
Protocol
s
for
W
ire
le
ss
Multi
m
edi
a
Sensor
N
et
work:
A
Survey
.
Journal
of
Senso
rs
.
2013;
1
-
11
.
[4]
Derpa
nis K
G,
T
he
Gauss
ia
n
P
y
r
amid.
2005
.
[5]
Manje
shw
ar
A
a
nd
Agrawal
D
P
.
TEEN:
ARouti
ng
Protocol
fo
r
Enha
nc
ed
Ef
fici
ency
in
W
ire
l
ess
Sensor
Network
s.
Proc.
of
the 15t
h
Inte
rn
at
ion
al Pa
ral
l
el
&
Distr
ibu
te
d
Proc
essing
Sy
m
posium
.
W
ashingt
on
DC.
US
A.
2001;
189.
[6]
Kodali
R
K,
S.
Bhanda
ri
V
S
K
A,
and
Boppana
L.
En
ergy
effi
ci
en
t
m
-
le
vel
LEACH
protocol
.
Proc.
Inte
rna
ti
o
na
l
Confer
ence
on
Advanc
es
in
Co
m
puti
ng.
Com
m
unic
a
ti
ons a
nd
I
nform
at
ic
s (ICA
CCI).
2015;
973
-
979.
[7]
Heinz
e
lman
W
R,
Chandr
aka
sa
n
A,
and
Ba
l
akr
ishnan
H.
Ene
rg
y
-
Efficient
Comm
unic
ati
on
Prot
ocol
for
W
ireless
Mic
ros
ensor
Net
works.
Proc.
of
the
33rd
Hawai
i
Internat
iona
l
C
onfe
ren
c
e
on
S
ystem
Scie
nc
es.
W
ashingt
on
DC.
US
A.
2000;
8:80
20
.
[8]
Inta
nagonwiwa
t
C,
Govindan
R,
Estri
n
D,
H
ei
demann
J,
an
d
Silva
F.
Dire
c
te
d
di
ff
usion
fo
r
wirel
ess
senso
r
net
working
.
I
EEE/ACM T
ran
sa
c
ti
ons on
Ne
tworking.
Febru
ar
y
2
003;11:
2
-
16
.
[9]
Heinz
e
lman
W
R,
Kulik
J,
and
Bal
akr
ishnan
H.
Adapt
i
ve
Prot
ocol
s
for
Infor
mation
Diss
eminat
ion
in
Wireless
Sensor
Net
work
s
.
Proc.
of
the
5th
An
nual
A
CM/IEE
E
In
te
r
nat
ion
al
Confer
enc
e
on
Mobil
e
Com
puti
ng
a
nd
Networki
ng.
Ne
w York.
US
A.
1
999;
174
-
185.
[10]
Sohrabi
K,
Gao
J,
Aila
wadhi
V,
and
Potti
e
G
J.
Protocol
s
for
sel
f
-
orga
nizati
on
o
f
a
wire
le
ss
sensor
net
work.
IE
E
E
Pe
rs
onal
Comm
unic
ati
ons
.
no
5.
Octobe
r
2000;
Vol.
(7)
16
-
27.
[11]
Karp
B
and
Ku
ng
H
T.
GPSR:
Gr
ee
dy
P
erime
t
er
Stat
e
le
ss
Rou
ti
ng
for
Wire
le
s
s
Net
works
.
Proc
.
of
th
e
6th
Ann
ual
Inte
rna
ti
ona
l
Co
nfe
ren
c
e
on
Mobile Com
puti
ng
and
Networki
ng
.
New York. NY
.
US
A.
2000;
243
-
254.
[12]
Huang
G
M,
T
ao
W
J,
Li
u
P
S,
and
L
iu
S
Y,
.
Mult
ipath
rin
g
routi
ng
in
wir
el
ess
sensor
netw
orks.
in
Appli
ed
Me
chanics and Mate
rials
.
2013;
Vol.
(347)
701
-
705.
Evaluation Warning : The document was created with Spire.PDF for Python.