Internati
o
nal
Journal of Ele
c
trical
and Computer
Engineering
(IJE
CE)
Vol.
5, No. 6, Decem
ber
2015, pp. 1486~
1
491
I
S
SN
: 208
8-8
7
0
8
1
486
Jo
urn
a
l
h
o
me
pa
ge
: h
ttp
://iaesjo
u
r
na
l.com/
o
n
lin
e/ind
e
x.ph
p
/
IJECE
Tree Bas
e
d Energy Bal
a
n
c
ing Rou
t
ing P
r
ot
ocol b
y
S
e
lf
Organizing in Wireless Sensor Networks
Syed
Um
ar
, P
.
V.
R.
D Pr
as
a
d
a
R
a
o
,
Sride
v
i Gu
tt
a
Dept
o
f
C
S
E
,
K L
U
n
i
v
e
r
si
t
y
, G
u
nt
u
r
,
AP,
I
ndi
a
Article Info
A
B
STRAC
T
Article histo
r
y:
Received Apr 27, 2015
Rev
i
sed
Au
g
30
, 20
15
Accepted
Sep 17, 2015
Today
the wireless sensor networks (W
SN) pla
y
a cruc
ia
l role
in wireless
techno
log
y
in various dom
ains like m
ilit
ar
y, m
e
dicin
e
, com
m
unicat
ions etc
.
The energ
y
con
s
ervation is
the
cruci
a
l fa
ctor in
the W
S
N. The W
S
N is
a
s
y
stem which h
a
s more number of
nodes in
which various
sensors are
fabricated on
th
e nodes to monitor vari
ous facto
r
s of the given task. Thes
e
nodes will form
a network b
y
connect
ing the o
n
e to oth
e
r for t
h
e effecti
v
e
communication
between th
e nod
es, and se
nds the whole inform
a
tion to the
base station (BS
)
. As the nodes which we use for the WSN are
of low cost
and are
bat
t
er
y o
p
erat
ed.
The m
a
i
n
drawb
ack
is
re
plac
em
ent of th
e
batt
er
y in
the W
S
N. The m
a
in goal is to c
onserve
the en
er
g
y
consumption
in WSN and
als
o
to balan
ce t
h
e load on W
S
N. F
o
r this man
y
proto
c
ols are
designed lik
e
L
E
A
CH,
PE
GASIS,
PE
DA
P,
e
t
c
.
in t
hose balancing th
e load
and time
delay
e
d. some drawbacks are there.
So we proposed a protocol so called
“Tree Based
Energ
y
Balancin
g routi
ng Protocol b
y
Self
Organizing
”
(TEBRSO), in
which instead of
routing ta
b
l
es a routing tree will be used for
routing from no
des to base station (B
S), which
chooses one root/control nod
e
for the bro
a
dcas
ting messages to
the sele
cted sen
s
or nodes. B
y
th
is protocol
we can
save
the
energ
y
consumption in
WSN and can
extend th
e life time of
it. Th
e performance of this protocol is
better w
h
en we com
p
are with other
energ
y
sav
i
ng pr
otocols.
Keyword:
Netwo
r
k
lifeti
m
e
R
out
i
n
g pr
ot
oc
ol
s
W
i
rel
e
ss se
ns
o
r
net
w
or
ks
W
i
reless tech
no
log
y
Copyright ©
201
5 Institut
e
o
f
Ad
vanced
Engin
eer
ing and S
c
i
e
nce.
All rights re
se
rve
d
.
Co
rresp
ond
i
ng
Autho
r
:
G. Si
va Na
ges
w
ara
R
a
o,
Depa
rt
m
e
nt
of
C
o
m
put
er Sci
e
nce a
n
d
E
ngi
neeri
n
g
,
K L Un
iv
ersity,
Gree
nfi
e
l
d
s,
V
a
dde
swa
r
am
, Gu
nt
u
r
Di
st
ri
ct
, A
n
dh
ra P
r
a
d
e
s
h
52
2
5
0
2
.
Em
a
il: siv
a
n
a
gs@k
l
u
n
i
v
e
rsity.in
1.
INTRODUCTION
N
o
w
a
d
a
y th
e
w
i
r
e
less Sen
s
or
N
e
t
w
ork
s
took
a
g
r
eat
revo
l
u
tio
n in
the co
m
m
uni
cat
i
ons t
echn
o
l
o
gy
.
In
t
h
e
WS
N t
h
e m
i
cro se
ns
or
s an
d m
i
cro sy
st
em
s are em
bedde
d
w
h
i
c
h
c
ons
um
e l
e
ss p
o
we
r a
n
d e
n
er
gy
. T
o
em
bed t
h
e m
i
cro se
ns
ors
we
use t
h
e a
d
vanc
es t
echn
o
l
o
gy
of
M
E
M
S
(M
i
c
ro
El
ect
rical Mechanical
Sy
ste
m
)
[1
]. By
u
s
i
n
g
th
ese typ
e
s we h
a
v
e
m
a
n
y
ad
v
a
n
t
ag
es like fau
lt to
lerant, bu
ild
ing
a l
a
rg
e n
e
t
w
ork
with
in
seco
nds
wi
t
h
e
ffect
i
v
e c
o
m
m
uni
cat
i
o
ns
[2]
fr
om
t
h
e vari
o
u
s se
ns
or
n
o
d
e
s. T
h
e
WS
N u
s
ed i
n
m
a
ny
dom
ai
ns
lik
e en
v
i
ron
m
e
n
t
m
o
n
ito
ri
n
g
, p
o
llu
tion
m
o
n
ito
ring
etc., th
e wo
rk
ing
pro
c
ed
ure of th
e
WSN is th
e n
o
d
e
s will
col
l
ect
t
h
e al
l
the i
n
f
o
rm
ati
o
n
i
n
a hu
ge am
ount
i
t
sen
d
s t
h
at
t
o
t
h
e dat
a
b
a
se whi
c
h i
s
cal
l
e
d t
h
e base
st
at
i
o
n
an
d th
en
th
e
ap
p
lication
w
ill b
e
ex
ecu
t
ed. A
s
w
e
know
th
at t
h
e
WSN
no
d
e
s are spread rand
omly an
d
depl
oyed
in va
rious places of the
ta
rget re
gion.
If
we
use t
h
e m
acro co
m
pone
nts
de
ploy
m
e
nt of nodes
will be
d
i
fficu
lt. To
wo
rk
p
r
op
erly
we
h
a
v
e
t
o
main
tain
th
e
sufficien
t
b
a
ttery
wh
en
t
h
e nod
es are
d
e
p
l
o
y
ed in
th
e
t
a
rget
re
gi
o
n
.
As t
h
e
no
des
are de
pl
oy
e
d
i
n
de
nsel
y
t
h
e
no
des
pr
o
duce
t
h
e rel
u
ct
a
n
t
dat
a
an
d t
h
ese
dat
a
sho
u
l
d
be com
b
i
n
e
d
an
d sh
o
u
l
d
re
d
u
ce t
h
e
t
r
ansm
i
ssi
on b
a
nd
wi
dt
h. T
o
avoi
d t
h
e d
u
p
l
i
cat
i
on o
f
t
h
e d
a
t
a
we
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
Tree B
a
se
d E
n
ergy B
a
l
a
nci
n
g
Ro
ut
i
n
g Pr
ot
o
c
ol
by
Sel
f
Or
g
ani
zi
ng
i
n
Wi
r
e
l
e
ss Se
ns
or…
(
Syed Umar
)
1
487
have
m
a
ny
pr
o
t
ocol
s a
n
d t
o
m
a
i
n
t
a
i
n
t
h
e e
n
er
gy
c
ons
um
pt
i
o
n
w
e
have
m
a
ny
pr
ot
oc
ol
s l
i
k
e P
E
G
A
S
I
S, TB
C
,
LEAC
H
, HE
E
D
etc. Here i
n
this we consider that we
m
a
i
n
t
a
i
n
som
e
cont
rol
o
r
pa
re
nt
no
des
whi
c
h ha
ve
ch
ild
n
o
d
e
s, the in
fo
rm
atio
n
fro
m
th
e ch
ild no
d
e
s will
b
e
sen
t
to
t
h
e
p
a
ren
t
/ co
n
t
ro
l
no
d
e
s fro
m
th
at n
odes the
in
fo
rm
atio
n
wi
ll p
a
ss to th
e
base statio
n
.
Th
e
po
wer consu
m
p
tio
n
in the nod
es
u
s
ed
fo
r th
e m
a
n
y
o
p
e
ration
s
wh
ich
will b
e
h
e
l
p
fu
l an
d so
m
e
are not
hel
p
fu
l
.
To
a
v
oi
d
t
h
ose un
hel
p
f
u
l
ope
rat
i
o
ns we
pr
o
p
o
s
e
a pr
ot
oc
ol
cal
l
e
d “Tree
B
a
se
d Ener
gy
Balan
c
in
g
rou
tin
g
Pro
t
o
c
o
l
by
Self Org
a
n
i
zin
g
”
(TEBRS
O).
Here th
e i
n
fo
rm
atio
n
will b
e
co
llected
b
y
the
n
o
d
e
s and
it
will b
e
sen
t
t
o
t
h
e Base Station
(BS). Th
e
n
e
twork life tim
e
can b
e
d
e
fin
e
d
in m
a
n
y
ways lik
e
1
)
.Th
e
tim
e ta
k
e
n
t
o
start th
e n
e
two
r
k
op
eratio
n
till to
d
eath
of th
e
first no
d
e
. 2).Th
e
time tak
e
n
to
start th
e
n
e
two
r
k
o
p
e
rat
i
o
n
till to
d
eat
h
o
f
last
n
o
d
e
s. H
e
re for th
e
u
s
ag
e w
e
adopt th
e first
op
tion
.
For th
e
d
a
ta fusion
we c
o
nsider two cases
in t
h
e
network.
C
a
se I:
Ho
w m
u
ch t
h
e vol
u
m
e of dat
a
can be se
nt
or re
cei
ved f
r
om
i
t
s chi
l
d
n
odes t
o
any
o
f
t
h
e
sen
s
o
r
no
des do
es no
t
m
a
t
t
er
.
Case II: T
h
e data sent or rece
ived
from
the child
n
o
d
es ca
n`t
be f
u
se
d an
d t
h
e m
e
ssage
l
e
ngt
h i
s
t
h
e
sum
of the
own c
o
llected info
rm
ation and t
h
e
receive
d
data.
2.
R
E
SEARC
H M
ETHOD
As we k
n
o
w t
h
e w
o
r
k
i
n
g pr
oced
u
r
e of
W
S
N i
s
col
l
ect
ing
vari
o
u
s i
n
f
o
rm
at
i
on of t
h
e gi
ven t
a
s
k
related
and
send
ing
to
th
e Base Statio
n
[1
]. Th
e no
d
e
s
are sprea
d
in the target ar
ea depl
oy
ed ran
d
o
m
l
y so, t
h
e
b
a
se station
will b
e
far away fro
m
th
e nod
es
after
fin
i
sh
i
n
g
th
e task th
e
nod
es
will d
i
e due to
th
e m
o
re en
erg
y
consum
ption.
To sol
v
e suc
h
energy
i
n
ef
fi
ci
ency
m
a
ny
pro
t
ocol
s was
pr
opos
ed, som
e
of them
are LE
ACH,
PEG
A
S
I
S,
HE
ED et
c.
I
n
t
h
e
LEAC
H
pr
ot
o
c
ol
s
o
m
e
node
s are c
h
ose
n
a
s
t
h
e cl
ust
e
r
h
ead
or
co
nt
r
o
l
no
de
s
wh
ere so
m
e
ch
ild
n
o
d
e
s will b
e
con
n
ected
to
th
o
s
e an
d
these co
n
t
ro
l nod
es will act as
th
e p
a
ren
t
nod
es, all
th
e in
fo
rm
atio
n
of th
e ch
ild
n
o
d
e
s
will b
e
co
llected
b
y
the clu
s
ter h
e
ad
s an
d
throug
h
t
h
e clu
s
ter
h
e
ad
s th
e
in
fo
rm
atio
n
sen
t
th
e
b
a
se statio
n
.
Here th
e en
erg
y
co
n
s
um
p
t
io
n
will b
e
m
o
re so
m
i
sb
alan
cin
g
th
e en
erg
y
con
s
um
pt
i
on i
s
d
o
n
e
due
t
o
m
o
re l
o
ad
on
t
h
e
n
odes
.
In
t
h
e
HEE
D
Pr
ot
oc
ol
i
.
e.
,
Hy
bri
d
e
n
er
gy
ef
fi
ci
en
t
d
i
stribu
ted
clusterin
g
algo
rithm
.
Th
e HEED
is th
e im
p
r
ov
ised
v
e
rsi
o
n of t
h
e LEAC
H in
selectin
g
th
e C
l
u
s
ter
head C
H
. At each tim
e
HEED protoc
ols se
lects the CH based on the re
sidual ene
r
gy
usa
g
e at the node
s.
Wh
en
we co
mp
are
with
HEED and
LEAC
H, HEED
will effectiv
ely p
r
o
l
on
gs th
e n
e
t
w
ork
life tim
e
an
d
t
h
e
dra
w
back
i
s
co
nsum
pt
i
o
n
o
f
e
n
er
gy
i
s
m
o
re.
To o
v
e
r
com
e
t
h
e dra
w
back
of t
h
e
HEE
D
,
PEG
A
SI
S [
2
]
Prot
oc
ol
s w
a
s pr
o
pose
d
.
To u
s
e t
h
e
opt
i
m
i
zed pow
er an
d t
h
i
s
can
be do
ne,
here
t
h
e Gree
dy
Al
go
ri
t
h
m
can be used t
o
f
o
rm
a chai
n m
odel
of t
h
e
sens
or
n
odes
.
Thi
s
PE
G
A
SI
S
pr
ot
oc
ol
i
s
m
o
re p
o
w
er e
ffi
ci
ent
p
r
ot
ocol
t
h
an t
h
e
ot
he
r
pr
ot
oc
ol
s l
i
k
e LE
AC
H.
Wh
en
we co
mp
are it with
the PEGASI
S we can see the PEGASIS is 300% m
o
re effici
ent than the L
E
ACH.
We ha
ve som
e
ot
her
pr
ot
oc
ol
s l
i
k
e TB
C
(Tree B
a
sed C
l
ust
e
ri
n
g
) an
d PE
DA
P are ot
he
r
pr
ot
oc
ol
s w
h
i
c
h use
s
th
e tree b
a
sed ro
u
ting pro
c
ess. Th
e
TBC
is simila
r to
LEAC
H
[3
] an
d is so
m
e
what i
m
p
r
ov
ised. Th
e
im
provising
of the TBC that
with th
e LEACH is in which each node rec
o
rd
s the information of its neighbors
and
build topogra
phy through
com
puting. The drawbac
k
is that so
m
e
nodes cons
um
es
m
o
re energy which are
away
f
r
om
t
h
e
base st
at
i
o
n.
T
h
e PE
D
A
P i
s
s
i
m
i
l
a
r t
o
t
h
e
P
E
GA
SI
S
pr
ot
o
c
ol
an
d i
s
o
f
i
m
provi
sed
ve
r
s
i
o
n
.
[
9
]
The dra
w
back of
this protoc
ol
build
the
topology which will
cause the la
rge
am
ount
of
waste
of e
n
e
r
gy. The
B
S
i
n
t
h
e
net
w
or
k
need
s t
o
b
u
i
l
d
t
h
e
t
o
po
gr
aphy
t
o
col
l
ect
t
h
e i
n
fo
rm
at
i
o
n
of t
h
e se
nso
r
n
odes
o
f
pare
nt
an
d
ch
ild
nod
es, so
d
e
lay will be th
ere. To
o
v
erco
m
e
a
ll th
e
d
r
awback
s
we p
r
op
o
s
ed
a
p
r
o
t
o
c
o
l
called “Tree
B
a
sed
E
n
er
gy
B
a
l
a
nci
n
g
r
o
ut
i
ng Pr
ot
oc
ol
b
y
Sel
f
Or
gani
zi
ng”
(T
EB
R
S
O
)
.
3.
SYSTE
M
MO
DEL
To pe
rf
o
r
m
t
h
e wo
rki
ng
of t
h
i
s
pr
ot
ocol
w
e
assum
e
t
h
e fol
l
o
wi
ng
pr
o
p
e
rt
i
e
s t
o
desi
g
n
t
h
e sy
st
em
m
odel
t
o
t
h
e
pr
ot
oc
ol
1)
Th
e
Sen
s
or
Nod
e
s are
d
e
p
l
o
y
ed
in th
e targ
eted
reg
i
on
of
sq
u
a
re field
where
th
ere will
b
e
o
n
l
y
b
a
se station
wh
ich
is far away
fro
m
th
e area and
each
n
o
d
e
s will h
a
v
e
a un
iqu
e
id (i
d
e
n
t
i
f
ier).
2)
After th
e
d
e
p
l
o
y
m
e
n
t
o
f
senso
r
nod
es th
ey
w
ill k
e
ep
o
p
e
rate till th
e energ
y
will b
e
ex
h
a
u
s
ted
and
the node
s are
stationary.
3)
Each
of th
e
no
d
e
will h
a
v
e
th
eir own
capab
ilities an
d
can
ch
ang
e
th
e p
o
wer lev
e
ls an
d
can
directly communicate
with t
h
e BS
4)
The B
S
i
s
not
ener
gy
c
onst
r
ai
ned
an
d i
t
i
s
st
at
i
onary
.
5)
Th
e Sensor nod
e can
g
e
t th
e lo
catio
n
info
rmatio
n
th
ro
ugh
th
e GPS
o
r
b
y
th
e po
sitio
n
algo
rith
m
s
and they a
r
e location a
w
are
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
IJECE
Vol. 5, No. 6, D
ecem
ber
2015 :
1486 –
1491
1
488
4.
TREE BASE
D ENE
R
GY
BALANCING ROUTIN
G
P
R
OTO
C
OL B
Y
SELF
O
R
G
ANIZ
I
NG
The m
a
i
n
of “Tree B
a
sed E
n
ergy
B
a
l
a
nci
n
g
ro
ut
i
ng P
r
ot
oc
ol
by
Sel
f
O
r
g
a
ni
zi
ng”
(TEB
R
S
O)
[2]
-
[
4]
is achieve net
w
ork life tim
e
longer
while using for vari
ous applications.
In this
case at each round the
Base
St
at
i
on assi
gns
one
r
oot
hea
d
no
de a
n
d b
r
o
a
dcast
i
t
s
n
ode
uni
que
i
d
t
o
al
l
t
h
e co
o
r
di
nat
e
s of
t
h
e se
ns
or
no
des
to trace the
pat
h
from
the bas
e
stati
on to the
root nodes and from
root nod
es to c
h
ild
nodes
whic
h can
be built
for each
nodes
. In this TEB
RSO the
root
can be
cha
n
ge
d and
reconstruct routing
path with less
del
a
y and
u
s
ing
th
e less en
erg
y
. So, b
y
u
s
ing
th
is
p
r
o
t
o
c
o
l
th
ere will b
e
a b
e
tter lo
ad
balance is ach
iev
e
d wh
en
com
p
ared wi
t
h
t
h
e ot
he
r pr
ot
o
c
ol
s.
The working proce
d
ure
ca
n be
cla
ssified
i
n
to
th
e fo
llowing stag
es:
1
)
In
itializatio
n
Stag
e.
2)
C
o
nst
r
uct
i
o
n of
t
r
ee pat
h
s
t
at
e
3)
Tra
n
sm
i
ssi
on
of
t
h
e c
o
l
l
ect
ed
dat
a
f
r
om
sel
f-o
r
g
ani
z
e
d
no
des
Exc
h
an
ge
of
d
a
t
a
fr
om
B
S
t
o
No
des
1
)
In
itializatio
n
State
In
th
is stag
e t
h
e Base Station
send
s t
h
e all p
ack
ets t
o
all n
o
d
e
s in
t
h
e
n
e
two
r
k
lik
e t
o
in
form
th
e
no
des t
o
begi
n
t
h
e t
a
sk
.
Here
we c
o
nsi
d
e
r
t
h
e
no
des a
s
N
t
o
cal
cul
a
t
e
t
h
e ener
gy
l
e
vel
of t
h
e
no
de t
h
ey
use
the form
ula.
(
1
)
EL is th
e en
ergy facto
r
fo
r th
e lo
ad b
a
lan
ce an
d
α
is a con
s
tan
t
wh
ich reflects th
e m
i
n
i
m
u
m
en
erg
y
un
it.
Each
nod
e send
s its p
ack
et to th
e n
o
d
e
s and d
r
aw a circle with
Rc in
th
e o
n
e
tim
e
slo
t
.
Th
en
all th
e
n
o
d
e
s m
o
n
ito
r
th
e ch
an
n
e
l during
th
is ti
m
e
sl
o
t
, and
reco
rd
s all th
e in
fo
rmatio
n
and
stores in
its
m
e
m
o
r
y
. Th
e
m
e
m
o
ry
cont
ai
ns t
h
e i
n
fo
rm
ati
on
o
f
t
h
e
nei
g
hb
o
r
no
des.
After t
h
e in
itial p
h
a
se th
e “Tree Based
En
erg
y
Ba
lan
c
in
g
rou
ting
Poto
co
l b
y
Self
Org
a
n
i
zin
g
”
(TEBRSO)
operates in rounds. The
DA
TA_PAK will be send t
o
the base
station from
nodes so each
round
cont
ai
n
s
t
h
ree
pha
ses l
i
k
e Tr
ee C
onst
r
uct
i
o
n p
h
ase, sel
f
o
r
ga
ni
zat
i
on a
n
d dat
a
col
l
ect
ed fr
om
all
t
h
e no
des
an
d
tran
sm
it
te
d
p
h
a
ses
2)
C
o
nst
r
uct
i
o
n of
t
r
ee pat
h
s
t
age
In t
h
e c
o
nst
r
uc
t
i
on p
h
ase
we
bui
l
d
a
ro
ut
i
n
g
t
r
ee fo
r b
r
oa
d
cast
t
h
e
m
e
ssage,
we assi
g
n
a
no
de t
o
base
st
at
i
on as r
o
ot
and
b
r
oa
dcast
r
oot
ID a
n
d r
o
o
t
and t
h
e net
w
or
k l
i
f
e t
i
m
e of vari
ous
p
r
ot
oc
ol
s are s
h
ow
n
bel
o
w
Tabl
e
1. E
ach
no
de t
r
i
e
s t
o
se
l
ect
s a co
nt
r
o
l
no
de/
m
a
i
n
n
o
d
e
whi
c
h
have
no
des
nei
g
h
b
o
r
s
usi
n
g
t
h
e
EL
[5]
.
Tabl
e
1. Li
fet
i
m
e of
Net
w
or
k
o
f
Di
ffe
rent
S
c
hem
e
s
Ev
er
y nod
e ch
oo
ses
o
n
e
main
/co
n
t
r
o
l nod
e f
r
o
m
its
n
e
ig
hb
or
nod
es an
d
ev
er
y node r
eco
rd
s its
nei
g
hb
o
r’s i
n
f
o
rm
at
i
on i
n
t
h
e fo
rm
of t
a
bl
e. B
y
t
h
at
we can k
n
o
w cl
earl
y
whi
c
h n
ode ac
t
s
as pare
nt
no
de an
d
whic
h
node act
s as child node
and we
can c
o
m
pute the EL.
If t
h
e p
a
ren
t
no
d
e
h
a
s no
ch
ild
th
en
itself acts as
leaf nod
e to it.
Each
n
o
d
e
sent a ev
ery p
a
cket to
its p
a
ren
t
n
o
d
e
s will
b
e
fu
sed
with
th
e co
nsu
m
p
tio
n
of
m
i
n
i
m
u
m
ener
gy
ca
n
be
ch
ose
by
no
de
nearest
t
o
i
t
.
“Tree
B
a
sed E
n
e
r
gy
B
a
l
a
nci
n
g
r
o
ut
i
n
g
P
r
ot
ocol
b
y
Sel
f
Org
a
n
i
zin
g
”
(TEBRSO)
b
y
th
is appro
a
ch
a ro
u
ting tr
ee
is con
s
tru
c
ted
an
d th
e nod
es
will b
e
still h
a
v
e
t
h
e
p
o
s
sib
ility o
f
co
nn
ecting
to their n
e
arest n
e
i
g
hbo
rs. To
co
nstru
c
t th
e ro
u
t
i
n
g tree
we
u
s
e th
e BS t
o
co
m
p
u
t
es
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
Tree B
a
se
d E
n
ergy B
a
l
a
nci
n
g
Ro
ut
i
n
g Pr
ot
o
c
ol
by
Sel
f
Or
g
ani
zi
ng
i
n
Wi
r
e
l
e
ss Se
ns
or…
(
Syed Umar
)
1
489
the topogra
phy Eve
n
tho
ugh
we can fulfill this
work
without the c
ontrol
of BS
, a large
am
ount
of e
n
e
r
gy is
wasted in t
h
e
next phase
3)
Tra
n
sm
i
ssi
on
of
t
h
e c
o
l
l
ect
ed
dat
a
f
r
om
sel
f-o
r
g
ani
z
e
d
no
des
[2]
,
[
3
]
After th
e co
m
p
letio
n
of th
e Initializa
tio
n
stag
e, Tr
ee con
s
tru
c
tio
n fo
r t
h
e
ro
u
ting
pu
rp
ose and
we go
fo
r t
h
e t
r
a
n
sm
i
ssi
on
of
dat
a
from
B
S
t
o
no
des a
nd a
f
t
e
r t
h
e gi
ven t
a
sk com
p
l
e
t
e
d
t
h
e no
des se
nds t
h
e
in
fo
rm
atio
n
to
Base Statio
n fo
r th
e
req
u
i
red an
alysis.
He
re
the eac
h node
collects the i
n
form
ation to ge
nerat
e
th
e DATA_PAK wh
ich
is t
r
an
sm
itted
to
Base Statio
n
[7
]. Th
e Tran
smissio
n
pro
c
ess can
b
e
exp
l
ain
e
d
i
n
th
ree seg
m
en
ts b
e
low as:
a)
Segm
ent 1
b)
Segm
ent 2
c)
Segm
ent 3
Fi
gu
re
1.
Pr
oce
ss o
f
t
h
e
perm
it
t
e
d l
eaf
no
des
sen
d
t
h
ei
r
dat
a
t
o
t
h
ei
r
pa
re
nt
no
des
Segm
ent
1:
In t
h
e first se
gment we use t
o
chec
k
whether th
ere is commu
n
i
catio
n
in
terface b
e
t
w
een
th
e ch
ild
no
des t
o
pa
ren
t
no
de. T
h
e ch
i
l
d
no
de se
nd
s
i
t
s
ID t
o
i
t
s
p
a
rent
no
de
du
r
i
ng t
h
at
t
i
m
e.[6]
At
t
h
i
s
t
i
m
e
t
h
ree
situ
atio
n
s
o
c
cur so
th
ey d
i
v
i
de th
e p
a
ren
t
nod
es in
to
th
re
e k
i
nd
s. In
th
e First situ
atio
n
if th
ere is n
o
leaf n
o
d
e
t
o
pare
nt
n
o
d
e
t
h
en t
h
er
e i
s
not
hi
n
g
t
o
sen
d
l
eaf n
ode
. I
n
t
h
e Seco
nd si
t
u
at
i
on i
f
t
h
e p
a
rent
n
o
d
e has
m
o
re
than the
one leaf node
th
en
after th
e transm
i
ssio
n
o
f
d
a
ta t
h
e p
a
ren
t
no
d
e
g
e
ts th
e in
co
rrect ID .fro
m
th
e leaf
n
o
d
e
s m
ean
s d
u
p
lication
o
c
cu
rs.[1
0
]
In
th
e th
ird
situ
atio
n
i
f
t
h
e parent
no
de has
onl
y
one l
eaf
no
de t
h
en i
t
receives t
h
e c
o
rrect
ID from
the leaf node.
T
h
ese situati
o
n
depe
nds
on the
segm
ent 2.
Segm
ent
2:
The t
h
ree si
t
u
a
t
i
on ca
n de
pe
n
d
o
n
t
h
e Se
gm
ent
2
.
S
o
in
t
h
e first situ
ation
if th
e p
a
ren
t
n
o
d
e
s t
u
rn
s
in
to
sleep
m
o
d
e
u
n
til n
e
x
t
time slo
t
b
e
g
i
n
s
. Fo
r th
e Secon
d
situ
ation
to th
e ch
ild
n
o
d
e
s a co
n
t
ro
l p
ack
et can
b
e
sen
t
fro
m
th
e p
a
ren
t
nod
es
an
d
t
h
is con
t
rol p
ack
et ch
oo
ses on
e of its child
n
o
d
e
t
o
tran
sm
it
th
e d
a
ta
in
th
e
next se
gm
ent. For the t
h
ird situation,
a c
ontrol pac
k
et recei
ved from
the pa
rent
node a
nd tells to leaf node t
o
tran
sm
it
th
e d
a
ta in
th
e n
e
x
t
seg
m
en
ts. In
th
i
s
seg
m
en
t th
e leaf no
des wh
ich
can
con
f
irm
e
d
th
e
d
a
ta b
e
fore it
tran
sm
its [8
].
Segm
ent
3:
Th
e
p
e
rm
itted
leaf no
d
e
s send
th
eir
d
a
ta to
th
eir p
a
ren
t
nod
es,
wh
ile o
t
h
e
r leaf
n
o
d
e
s in
sleep
m
o
d
e
.
The
pr
ocess
ca
n
be s
h
ow
n i
n
t
h
e Fi
gu
re
1
[1
0
]
, [1
1]
.
Here
t
h
e eac
h
no
de
nee
d
s t
o
gene
rat
e
a
n
d
t
r
ansm
i
t
a DAT
A_
PA
K i
n
eac
h r
o
u
n
d
t
h
e
n
t
h
e
no
de m
a
y
ex
h
a
u
s
t its en
erg
y
and
d
i
e. If an
y n
o
d
e
d
i
e th
en
th
ere
will b
e
ch
an
ge in
th
e to
pog
raph
y is
m
o
re [4
]. So
to
ove
rc
om
e i
t
t
h
e n
odes
w
h
i
c
h
di
e be
f
o
re i
t
i
n
f
o
rm
s t
o
nei
g
hb
o
r
n
o
d
es t
h
a
t
part
i
c
ul
ar
n
o
d
es i
s
dy
i
n
g
.
I
n
eac
h
ti
m
e
s
l
o
t
, th
e no
d
e
s wh
o
s
e energ
y
is go
ing
to
b
e
ex
h
a
u
s
ted will co
m
p
u
t
e a rand
o
m
d
e
lay wh
ich
m
a
k
e
s o
n
l
y
one
n
ode
b
r
oa
dc
ast
i
n
t
h
i
s
t
i
m
e
sl
ot
.
Whe
n
t
h
e
del
a
y
i
s
ende
d, t
h
e
s
e n
o
d
es
are t
r
y
i
ng t
o
b
r
oa
dcast
a pa
c
k
et
t
o
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
IJECE
Vol. 5, No. 6, D
ecem
ber
2015 :
1486 –
1491
1
490
the whole
network.
While a
ll other
nodes are m
onitoring the c
h
annel,
they will receive this pac
k
et and
per
f
o
r
m
an ID check [
11]
, [
1
2]
. The
n
t
h
ey
m
odi
fy
t
h
eir ta
bles. If c
o
nsider another cas
e the BS collects the
In
itial EL and th
e co-ord
i
n
ates in
form
atio
n
of all th
e
sen
s
ors.
On
ce the rou
ting
tree
is b
u
ilt, th
e en
erg
y
con
s
um
pt
i
on
o
f
eac
h se
ns
or
no
de i
n
t
h
i
s
r
o
u
n
d
ca
n
be c
a
l
c
ul
at
ed
by
B
S
, t
h
us
t
h
e i
n
f
o
rm
at
i
on nee
d
ed
fo
r
cal
cul
a
t
i
ng t
h
e
t
o
p
o
l
o
gy
fo
r
t
h
e ne
xt
ro
u
n
d
can be
kn
o
w
n i
n
ad
va
nce
and ca
n b
e
sh
ow
n
bel
o
w Fi
gu
re 2
.
Ho
we
ver
,
beca
use
W
S
N m
a
y be depl
oy
ed i
n
an u
n
fri
en
dl
y
envi
r
onm
ent
,
t
h
e act
ual
EL of eac
h sens
or
no
de
may be differe
n
t from
the E
L
calculated by BS. T
o
c
o
pe
with t
h
is
proble
m
, each se
ns
or node calcul
a
tes its
EL and
detects
its actual resi
dual e
n
e
r
gy i
n
each
round,
So
we
define
the calculated E
L
& E
L
1. T
h
e
sens
or
no
des
ge
nerat
e
s t
h
e e
r
r
o
r
fl
a
g
s an
d
pac
k
s
of
dat
a
o
f
resi
d
u
a
l
ener
gy
i
n
t
o
t
h
e
DA
TA
_P
A
K
,
w
h
i
c
h
nee
d
s t
o
be
send to Base st
ation
[2],
[8].
Fi
gu
re 2.
R
o
ut
i
n
g
t
r
ee ge
nerat
e
d by
TEB
R
S
O
f
o
r 10
0 n
ode
s
5.
CO
NCL
USI
O
N
In
t
h
i
s
pa
per
we i
n
t
r
o
d
u
ced
a
pr
ot
oc
ol
fo
r
bet
t
e
r
r
out
i
n
g
an
d t
h
e l
e
ss
usa
g
e
of
net
w
or
k l
i
f
e
t
i
m
e
.
Here
we c
o
m
p
ared T
E
B
R
S
O
pr
ot
oc
ol
wi
t
h
o
t
her
pr
ot
oc
ol
l
i
k
e LE
AC
H
,
P
E
GA
SI
S,
HEE
D
et
c. T
h
e TE
B
R
S
O
is the self-orga
n
ized protoc
ol,
it us
es only sm
all am
ount of energy in each
round to change the topography
fo
r
bal
a
nci
n
g t
h
e c
o
n
s
um
pt
i
on
of
ene
r
gy
.
H
e
re al
l
t
h
e l
e
a
f
no
des
uses
t
h
e
sam
e
t
i
m
e
sl
ot
fo
r t
r
a
n
sm
i
t
ting
t
h
e
d
a
ta so
t
h
at the tran
sm
issio
n
d
e
lay will b
e
less wh
en
we co
m
p
are with
oth
e
r
p
r
o
t
o
c
o
l
s.
If an
y no
d
e
b
e
fore it
d
i
e th
at p
a
rticu
l
ar nod
e send
s th
e informatio
n
to
th
e
neig
hb
or
nod
es to
b
u
ild
t
h
e
n
e
w
t
o
pog
r
a
ph
y. Th
e
TEBRSO is 200% m
u
ch m
o
re efficient tha
n
the LEAC
H
a
nd
3
00% m
o
re
effi
ci
ent
t
o
t
h
e PEG
A
S
I
S
pr
ot
oc
ol
,
i
t
i
s
10
0% m
o
re ef
fi
ci
ent
t
h
a
n
t
h
e
HEE
D
.
B
y
usi
n
g t
h
i
s
pr
ot
oc
ol
we
c
a
n
bal
a
nce t
h
e
net
w
or
k l
o
ad
.
Eve
n
though
GST
E
B needs BS to
com
pute th
e topography,
whi
c
h leads
to a
n
in
crease i
n
e
n
e
r
gy
waste and
longer
delay, this kind
of ene
r
gy waste and longe
r
de
lay are acceptable
whe
n
com
p
ared with the
energy
co
nsu
m
p
tio
n
an
d
th
e tim
e d
e
lay fo
r d
a
ta tran
sm
it
tin
g
.
The work
s ex
tend
s to
targ
eted
reg
i
o
n
an
d
also
th
e
depl
oy
m
e
nt
and t
o
sc
hed
u
l
i
n
g
t
h
e
no
des
i
n
v
a
ri
o
u
s
regi
on
l
i
k
e i
,
k,
j
re
gi
o
n
s
et
c.
REFERE
NC
ES
[1]
I. F
.
Ak
y
ild
iz
, W
.
S
u
, Y. S
a
nkaras
ubram
ani
a
m
,
and
E.
Cay
i
rc
i, “Wire
le
ss se
ns
or networks: A
survey
,”
Computer
Netw.s
, vol. 38
,
No. 4, pp. 393–4
22, 2002
.
[2]
S.
Lindsey
and C.
Ragh
avendra,
“
P
egasis: Power-effic
i
ent
gath
er
ing in sensor in
f
o
rm
ation s
y
st
em
s,”
In Pro
c
. I
E
EE
Ae
rospac
e
Conf.
, Vol. 3
,
pp
. 112
5–1130, 2002
.
[3]
H. O. Tan and I
.
Korpeoglu, “Power
efficien
t data gath
ering
and
aggreg
ation
in wireless sensor networks,”
SIGMOD
Rec
.
, Vol. 32, No. 4
,
pp
.
66-71,
2003.
[4]
S.
S.
Sa
ta
pa
thy
a
nd N.
Sa
rma
,
“T
RE
E
PSI: T
r
ee
ba
se
d
energ
y
ef
ficient proto
c
ol
for sensor information,”
in
Proc.
IFIP In
t. Conf.
,
pp. 11–13
, 2006
.
[5]
O. Younis and
S. Fahm
y
,
“HEE
D: A h
y
br
id,
energ
y
-eff
icient, distributed
clustering
approach
for ad hoc s
e
nsor
networks,”
IEEE Trans. Mobile
Computing
, Vol. 3, No. 4
,
pp
. 66
0–669, 2004
.
[6]
R.
Sz
e
w
czy
k, J. Pola
stre,
A. Ma
inwaring
, and D.
Culler,
“Lessons
from sensor network
expedition,”
in
Proc
. 1
s
t
European Works
hop on Wireless
Sensor Networks
EWSN ‘04
, G
e
r
m
an
y
,
2004.
[7]
W. Liang and
Y. Liu, “Online da
ta gath
ering
for maximizing networ
k lifetime in sensor networks,”
IEEE Tra
n
s
Mobile Computing
, Vol. 6
,
No. 1
,
pp
. 2–11
, 2007
.
[8]
J.
H.
Cha
ng
a
n
d L.
Ta
ssiula
s
,
“Energ
y
conservin
g
routing in wireless ad hoc n
e
tw
orks,”
in
Proc. I
EEE IN
FOCOM
,
2000, vol. 1
,
pp
.
22–31.
[9]
G. Mankar and
S. T. Bodkh
e, “
T
raffic awar
e en
erg
y
efficient ro
uting proto
c
ol,”
in
Proc. 3rd ICECT
, 2011, Vol. 6,
pp. 316–320
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
Tree B
a
se
d E
n
ergy B
a
l
a
nci
n
g
Ro
ut
i
n
g Pr
ot
o
c
ol
by
Sel
f
Or
g
ani
zi
ng
i
n
Wi
r
e
l
e
ss Se
ns
or…
(
Syed Umar
)
1
491
[10]
N.
Tabassum,
Q.
E.
K.
Mamun,
and Y.
Urano,
“COSEN
:
A chain oriented sensor network for efficient
data
coll
ect
ion,
”
in
Proc. IEEE ITCC
, pp
. 262–267
, 2
006.
[11]
W
.
R. Heinzelm
a
n, A. Chandrak
as
an,
and H. Balakrishnan, “Ener
g
y
eff
i
cien
t com
m
unication protocols for wireles
s
micro sensor networks,”
in
Proc. 33rd Hawaii In
t. Conf. S
y
stem S
c
i.
, pp
. 3005-301
4, 2000
.
[12]
W
.
B. Hein
zel
m
a
n, A. Chandr
akas
an,
and
H. Balakr
ishanan
,
“An
applicatio
n
-
s
p
ecifi
c proto
c
ol arch
ite
ctur
e f
o
r
wireless micro
sensor networks,”
IEEE Trans.Wir
eless Commun
,
Vol. 1
,
No. 4, pp
. 660–670
, 2002
.
Evaluation Warning : The document was created with Spire.PDF for Python.