Internati
o
nal
Journal of Ele
c
trical
and Computer
Engineering
(IJE
CE)
Vol
.
5
,
No
. 3,
J
une
2
0
1
5
,
pp
. 45
4~
46
3
I
S
SN
: 208
8-8
7
0
8
4
54
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
Energy efficient scheme to
Jointly Optimize Coverage and
Connectivity in Large Scal
e Wi
rel
ess S
e
ns
or Network
Deep
ak S. Sa
k
k
ari
*,
T
.
G.
B
a
sa
v
a
r
a
ju
*
*
*JNTUH, H
y
der
a
bad, India
** Departement
of CSE, Gov
e
rn
ment SKSJTI, Bangalor
e
, India
Article Info
A
B
STRAC
T
Article histo
r
y:
Received Feb 9, 2015
Rev
i
sed
Mar
19
, 20
15
Accepted Apr 16, 2015
Efficient cov
e
rage and connectivity
ar
e two important factors that ensur
e
better service qu
ality
especially
duri
ng tracking targets or monito
ring even
ts
in wireless sensor network. Although
massive amount of studies has been
carried ou
t in
th
e past to
enhan
c
e cov
e
rag
e
and connectivity
iss
u
es, t
ill date
ver
y
few studies
have witnessed
a signi
fi
can
t and
s
t
andard ou
tco
m
es
that c
a
n
opt further
.
Hence, this pap
e
r in
troduces a computa
tion
a
lly
efficien
t
techn
i
que for
jointly
addr
essing both c
over
a
ge and
connectivity
problems
in
large-scale wireless sensor network th
at
ensur
e
s optim
al
netw
ork lif
etim
e
too. Th
e proposed s
y
stem has
been
empirically
design
ed,
and
algorithms
form
ulated to en
s
u
re energ
y
effi
cien
t m
onitoring
of event. Th
e o
u
tcom
es
of
the s
t
ud
y
ar
e co
m
p
ared with s
t
andard en
erg
y
ef
fici
ent hier
archi
cal proto
c
ol
to ben
c
hmark th
e results.
Keyword:
Co
nn
ectiv
ity
C
ove
rage
Energy E
fficie
n
cy
Op
tim
izat
io
n
W
i
reless Sen
s
or
Netwo
r
k
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
:
Deepa
k
S. Sakkari,
Research Sc
holar,
Jawa
harl
al
Ne
hr
u Tec
h
nol
ogi
cal
Uni
v
ersi
t
y
,
Hy
de
raba
d,
I
n
di
a.
Em
a
il: d
eep
ak
sak
k
a
ri@g
m
a
il.
co
m
1.
INTRODUCTION
Th
e ar
ea
of
w
i
r
e
less sensor
netw
or
k
h
a
s
r
e
ceiv
ed
q
u
ite a l
o
t atten
tio
n
from th
e research co
mm
u
n
i
t
y
i
n
l
a
st
t
e
n
y
ear
s o
w
i
n
g t
o
t
h
e
adva
nt
age
s
as
wel
l
as s
p
ont
a
n
eo
usl
y
e
vol
vi
ng
c
h
al
l
e
nges
i
n
t
h
e t
ech
n
o
l
o
gy
.
A
w
i
r
e
less sen
s
o
r
n
e
twor
k co
m
p
r
i
ses
o
f
th
e
gr
ou
p of
sen
s
or
no
d
e
s th
at
are eith
er
po
sitio
n
e
d in
a un
iqu
e
locatio
n
(un
i
fo
rm
) o
r
d
i
stribu
ted
arbitrarily in
th
e
en
v
i
ron
m
en
t (rando
m
)
. Th
e
sen
s
o
r
no
d
e
s
are sm
all elec
tron
ic
d
e
v
i
ces th
at
hav
e
t
h
e cap
a
b
i
lity to
sen
s
e certain
p
h
y
si
cal
attrib
u
t
es lik
e m
o
istu
re,
h
e
at, m
o
tio
n
,
p
r
essu
re,
sm
oke, et
c. R
i
ght
f
r
om
habi
t
a
t
m
oni
t
o
ri
n
g
t
o
heal
t
h
ca
re a
ppl
i
cat
i
o
n,
wi
r
e
l
e
ss sens
or
ne
t
w
o
r
k
has
fo
u
nd i
t
s
ap
p
licab
ility i
n
m
u
ltip
le co
mmercial n
eed
s [1
]. A cl
o
s
er lo
ok
at th
e op
eration
of wi
reless sen
s
o
r
network
f
i
nd
s th
at t
h
er
e ar
e t
h
r
e
e typ
e
s of
sen
s
o
r
nodes e.g
.
m
e
m
b
er
sen
s
or
n
o
d
e
s,
clu
s
ter
h
e
ad
, an
d b
a
se station. Th
e
m
e
m
b
er senso
r
n
ode
gat
h
e
r
s t
h
e raw
phy
si
c
a
l
dat
a
and t
r
a
n
sm
its
to
th
e clu
s
ter h
e
ad
. It
is said
th
at clu
s
tered
usu
a
l
l
y
posses
s
hi
g
h
er
resi
d
u
a
l
energy
c
o
m
p
are
d
t
o
m
e
m
b
er
no
des
.
The
cl
ust
e
r hea
d
i
s
req
u
i
r
e
d
t
o
p
o
sses
s
suc
h
hi
gh
resi
dual
e
n
e
r
gy
as
t
h
ey
are m
a
i
n
l
y
resp
onsi
b
le
for tran
sm
it
tin
g
m
a
ssiv
e
ly ag
greg
ated
d
a
ta to
th
e
sin
k
. Th
is
p
h
e
n
o
m
en
on
is term
ed
as d
a
ta
ag
greg
atio
n [2
]. Hence, i
n
orde
r to vis
u
alize the e
ffective data
agg
r
e
g
at
i
on
ph
enom
eno
n
, i
t
is essent
i
a
l
t
h
at al
l t
h
e node
s ret
a
i
n
m
a
xim
u
m
energy
and
assi
st
s i
n
for
w
ardi
n
g
n
on-red
und
an
t
d
a
ta to
th
e b
a
se statio
n
.
Hen
c
e, th
ere are
va
rious i
n
ternal as
well as exte
rnal factors
that
play a
cru
c
ial ro
le in d
a
ta ag
g
r
eg
at
io
n
pro
c
ess. Th
e in
tern
al
pa
ram
e
t
e
rs are r
out
i
n
g p
r
ot
oc
o
l
s, bat
t
e
ry
l
i
f
et
im
e,
packet
re
d
u
n
d
a
nci
e
s, sec
u
ri
t
y
prot
ocol
s
,
et
c. whi
l
e
t
h
e e
x
ternal factors
are interfe
re
nce, noise, scattering,
ch
ann
e
l fad
i
ng, etc. In
sp
ite o
f
su
ch
po
tential cap
ab
ilitie
s, wireless senso
r
s suffer
from certain
issu
es e.g.
restricted
co
mp
u
t
ation
a
l capab
ility, less b
u
ffer, fi
n
ite
b
a
ttery life, m
i
n
i
mal reso
urce av
ailab
ility. Owin
g
t
o
suc
h
c
h
aracteri
s
tics, the
perform
a
nce
of t
h
e
net
w
or
k i
s
hi
g
h
l
y
affect
e
d
where
the
prim
e cause
s is en
er
gy [
3
].
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
IJEC
E V
o
l
.
5, No
. 3,
J
u
ne 2
0
1
5
:
45
4 – 4
6
3
45
5
A
p
ar
t fr
o
m
th
e
is
s
u
e
s
d
i
s
c
u
s
s
e
d
ab
ov
e,
th
er
e
a
r
e
certain
m
o
re p
r
o
m
in
e
n
t issu
es in
wi
reless sen
s
or
net
w
or
k t
e
rm
ed as c
ove
ra
ge
and c
o
nne
ct
i
v
i
t
y
i
ssues, w
h
i
c
h i
s
t
h
e m
a
jor
foc
u
s
of t
h
e p
r
esent
pa
pe
r. T
h
e t
e
rm
cover
age
i
s
de
fi
ne
d as t
h
e
op
t
i
m
a
l
sensi
n
g a
n
d
t
r
a
n
sm
i
ssi
o
n
di
st
ance
req
u
i
red
by
t
h
e
sen
s
or
n
o
d
e t
o
pe
r
f
o
r
m
m
o
n
ito
rin
g
th
e ev
en
t in
a p
a
rt
icu
l
ar lo
catio
n
[4
]. So
m
e
t
i
m
es
, co
v
e
rag
e
is al
so
in
terp
reted
as criteria to
en
sure
o
p
tim
al
serv
ice q
u
a
lity. Th
e sig
n
i
fican
ce of th
e co
v
e
rag
e
i
ssu
e is v
e
ry pro
m
in
en
t an
d
very clo
s
ely asso
ciated
wi
t
h
t
h
e ene
r
g
y
fact
or [
5
]
.
It
was seen i
n
m
a
ny
cases t
h
at
red
u
ct
i
o
n o
f
ba
t
t
e
ry
l
i
f
e spont
aneo
usl
y
re
duc
es t
h
e
co
v
e
rag
e
area
an
d
t
h
ereb
y adv
e
rsely affect th
e qu
ality o
f
serv
ices. Th
is
may n
o
t
b
e
a big
issu
e in
sm
a
ll-scale
n
e
two
r
k
,
bu
t po
ssess a ch
allen
g
i
n
g
issu
e in
larg
e scale n
e
twork. Th
e seco
nd
term
co
n
n
ectivity
is represente
d
as th
e cap
ab
ility o
f
th
e m
o
te to
en
su
re reach
a
b
ility to
th
e
sin
k
at th
e time o
f
d
a
ta aggreg
atio
n [6
]. Hen
ce,
cove
ra
ge a
n
d
connectivity are ve
ry closely associated
wi
th each ot
her
and ha
s
pote
n
tial affect in se
rvice
q
u
a
lity, rou
ting
,
and
d
a
ta agg
r
eg
ation
.
In
case o
f
n
o
n
-
av
ailab
ility
o
f
routes (p
oor con
n
ectiv
ity), ag
greg
ated
dat
a
d
o
es
n’t
re
ach
si
nk
an
d gi
ve ri
se
t
o
ei
t
h
e
r
packet
dr
o
p
o
r
hi
g
h
er del
a
y
i
n
t
h
e
net
w
o
r
k.
Thi
s
pa
pe
r, t
h
eref
ore
,
st
u
d
i
e
s vari
ou
s p
r
i
o
r
t
echni
ques
an
d di
sc
usses
t
h
e pr
o
b
l
e
m
s
t
h
at
have
bee
n
id
en
tified
fro
m
th
e rev
i
ew of th
e literatu
re.
Th
e p
a
p
e
r pr
esen
ts a si
m
p
le an
d
yet h
i
gh
ly effectiv
e so
lu
ti
o
n
t
o
add
r
ess t
h
e si
gni
fi
cant
i
ssue
s
of
co
vera
ge
and c
o
nn
ect
i
v
i
t
y
i
n
wi
rel
e
ss
sens
or
net
w
or
k an
d e
n
s
u
re
opt
i
m
al
ener
gy
prese
r
v
a
t
i
on al
on
g
wi
t
h
i
t
.
Sect
i
o
n
2
di
scus
ses t
h
e p
r
i
o
r re
searc
h
t
e
c
hni
ques
f
o
l
l
o
we
d
by
pr
obl
em
id
en
tif
icatio
n
i
n
Section
3.
Sectio
n
4
d
i
scu
sses th
e pr
opo
sed
m
o
d
e
l,
an
d
Sectio
n
5
d
i
scu
s
ses
about
th
e
im
pl
em
ent
a
t
i
o
n a
n
d
res
u
l
t
di
s
c
ussi
o
n
.
Fi
nal
l
y
,
co
ncl
u
di
n
g
r
e
m
a
rks a
r
e
bei
n
g
m
a
de i
n
Sec
t
i
on
6.
2.
RELATED WORK
In t
h
e past
de
cade,
th
ere
h
a
s b
e
en
enou
gh work
carried
o
u
t
toward
s m
itig
atin
g
conn
ectiv
ity an
d
cove
ra
ge i
ssu
e
s
i
n
wi
rel
e
ss se
nso
r
net
w
or
k.
Ou
r
pri
o
r
w
o
r
k
[7]
has al
rea
d
y
di
scusse
d c
o
upl
e
of
p
r
i
o
r re
search
atte
m
p
ts and excavate
d
the re
search
gap. This section di
scusses som
e
m
o
re significa
nt
st
udi
es t
h
at
hav
e
bee
n
in
v
e
stig
ated
an
d
stud
ied
to
ex
p
l
o
r
e t
h
e
b
e
tter p
o
s
sib
ilities o
f
cov
e
rag
e
an
d
con
n
ectiv
ity in
wireless
sen
s
o
r
net
w
or
k. Z
a
i
d
i
et
al
. [8]
ha
v
e
prese
n
t
e
d a
fram
e
wor
k
wh
ere t
h
e a
u
t
h
or
has a
d
o
p
t
e
d c
o
st
-
b
ase
d
m
e
t
r
i
c
s t
o
ens
u
re e
fficie
n
t co
vera
ge i
n
wi
reless se
nso
r
ne
t
w
or
k.
The a
u
t
h
ors
have
ad
o
p
t
e
d t
w
o-
di
m
e
nsi
onal
det
e
rm
i
n
i
s
t
i
c
b
a
sed t
ech
ni
q
u
e
for t
h
e de
pl
oy
m
e
nt
as wel
l
as i
n
ran
d
o
m
based de
pl
oy
m
e
nt
t
oo. The
o
u
t
c
om
e
o
f
th
e system
was ev
al
u
a
ted
with
resp
ect to p
e
rform
a
n
ce p
a
ram
e
ters e.g
.
p
r
ob
ab
ility o
f
co
v
e
rag
e
in
both
on
e
and
t
w
o-
di
m
e
nsi
o
nal
area
.
Ho
we
ver
,
t
h
e
out
c
o
m
e
was not
fo
u
n
d
t
o
b
e
be
nchm
arke
d.
A
g
ar
wal
et
al
. al
so
co
n
tinu
e
d
d
i
scu
ssion
of effici
en
cy in
co
v
e
rag
e
and
co
n
n
ect
iv
ity. [9
] co
n
s
i
d
eri
n
g
th
e
p
r
ob
lem
s
o
f
su
rv
eillan
ce
sy
st
em
. The
aut
h
or
has
ad
opt
e
d
si
gni
fi
c
a
nt
ra
n
dom
i
z
ed t
ech
ni
q
u
e
u
s
i
ng
g
r
eedy
t
echni
que
w
h
e
r
e t
h
e
sim
u
l
a
t
i
on w
o
r
k
i
s
ca
rri
ed
o
u
t
usi
n
g M
o
nt
e C
a
rl
o a
p
p
r
oac
h
f
o
r a
d
d
r
essi
n
g
t
h
e
u
n
i
f
orm
cove
ra
ge i
s
s
u
e
s
u
nde
r
fi
ni
t
e
sensi
ng
r
a
di
us
fram
e
wo
rk
. The e
v
al
u
a
t
i
on o
f
t
h
e
o
u
t
c
om
e was val
i
d
at
ed
usi
n
g
ga
t
h
ere
d
co
ver
e
d
area
wi
t
h
o
u
t
a
n
y
c
o
m
p
arat
i
v
e pe
rf
orm
a
nce eva
l
uat
i
on.
T
h
e c
ove
ra
ge f
act
or
was
ve
ri
fi
ed
fo
r M
ont
e C
a
r
l
o a
n
d
Gree
dy
t
echni
que
s onl
y
.
Si
m
i
l
a
r l
i
n
e of research w
o
rk w
a
s carri
ed o
u
t
b
y
B
u
l
u
t
et
al
. [10]
i
nve
st
i
g
at
i
ng t
h
e
red
u
nda
ncy
i
s
s
u
es i
n
c
ove
ra
g
e
fact
o
r
of
wi
r
e
l
e
ss sens
o
r
n
e
t
w
o
r
k
.
T
h
e a
u
t
h
ors
ha
ve
ad
opt
e
d
gra
p
h t
h
eory
w
h
er
e th
e conn
ectiv
ity o
f
t
h
e n
e
ighb
or
g
r
ap
h w
a
s th
e
p
r
i
m
e f
o
cu
s of
t
h
e stud
y. By
ad
op
ting
sch
e
d
u
ling
t
echni
q
u
e, t
h
e out
c
o
m
e
of t
h
e st
udy
was e
v
a
l
uat
e
d usi
ng
nu
m
b
er of t
h
e act
i
v
e sens
or
no
d
e
s wi
t
h
speci
fi
c Qo
S
v
a
lu
e with
ou
t an
y
p
e
rfo
rm
ance com
p
arative analysis. Beauda
ux et al
. [1
1]
have i
nvest
i
g
at
ed
on
k-C
o
vera
ge
p
r
ob
lem
s
in
w
i
r
e
less sen
s
or
netw
or
k.
W
i
t
h
an
aid of
layer
-
b
a
sed
lo
calized
algo
r
i
t
h
m
,
th
e f
r
a
m
e
w
o
r
k
pr
ov
id
es
en
h
a
n
c
ed
cap
a
b
ility with
rest
ricted
rou
t
es with
redun
dan
c
i
e
s. Th
e
o
u
t
come o
f
th
e system
was ev
alu
a
ted
u
s
ing
num
ber
of
act
i
v
e
no
des
o
n
WS
Net
si
m
u
l
a
t
o
r a
n
d
was
fo
un
d
n
o
t
t
o
be
benc
hm
arked
.
Wan
g
et
al
. [
1
2]
ha
v
e
st
udi
e
d
t
h
e c
o
vera
ge i
s
s
u
es
con
s
i
d
eri
n
g
a
uni
que a
p
pl
i
cat
i
on o
f
sa
n
d
st
o
r
m
m
oni
t
o
ri
ng
. The
o
u
t
c
om
e of t
h
e
st
udy
was e
v
al
uat
e
d u
s
i
n
g n
o
d
e de
nsi
t
y
on
t
h
e t
r
ansm
i
ssi
on ra
nge
on
var
i
ous c
h
an
nel
t
y
pes. H
o
w
e
ve
r
,
t
h
e
out
c
o
m
e
of t
h
e st
u
d
y
wa
s
n
o
t
f
o
un
d
be
nc
hm
arked.
K
r
a
n
aki
s
et
al
.
[
1
3]
ha
ve i
n
t
r
od
uc
ed a
m
odel
t
o
pr
o
v
i
d
e
bet
t
e
r ra
nge
o
f
t
h
e di
rect
i
o
na
l
ant
e
nna
o
n
m
u
lt
i
p
l
e
hop
s.
W
i
t
h
an ai
d
of
per
f
o
r
m
a
nce param
e
t
e
rs e.g.
h
op
stretch
factor,
th
e ou
tco
m
e of th
e
stud
y w
a
s ev
al
u
a
ted
w
i
th
ou
t an
y
p
e
r
f
orm
a
nce com
p
arative a
n
alysis wit
h
ot
he
r si
g
n
i
f
i
c
a
n
t
p
r
ot
ocol
s
.
S
t
ergi
o
p
oul
os et
al
. [
14]
i
n
ves
t
i
g
at
ed o
n
t
h
e
co
or
di
nat
i
o
n
i
ssues
owi
n
g
t
o
t
h
e
m
obi
l
i
t
y
of senso
r
n
o
d
es u
n
d
er c
o
n
s
t
r
ai
nt
s
of R
F
com
m
uni
cat
i
o
n i
n
w
i
rel
e
ss sens
or
net
w
or
k. T
h
e
aut
h
or
s
have
pr
op
ose
d
a c
ont
rol
t
e
c
h
ni
q
u
e t
o
e
n
s
u
r
e
o
p
t
i
m
al
con
n
ect
i
v
i
t
y
of t
h
e
net
w
or
k,
w
h
e
r
e t
h
e
o
u
t
c
om
es we
re
ev
alu
a
ted
u
s
ing
cov
e
rag
e
p
e
rform
a
n
ce facto
r
o
n
m
u
ltip
le
s
a
m
p
les. Th
e ou
tco
m
e o
f
th
e stu
d
y
still
miss
es th
e
b
e
n
c
h
m
ar
k
i
ng
. Sim
i
lar
d
i
r
ect
io
n
of
th
e study co
nsid
er
ing
m
o
b
ili
ty w
a
s also
seen
t
h
e
wo
rk
o
f
Er
d
e
l
j
et al.
[1
5]
. H
o
we
ver
,
t
h
i
s
st
udy
wa
s eval
uat
e
d
usi
ng
perce
n
t
a
ge
cove
ri
n
g
t
i
m
e
as t
h
e per
f
o
r
m
a
nce fact
o
r
i
n
bo
t
h
ci
rcul
ar a
n
d
ra
nd
om
rout
e a
p
pr
oac
h
. R
e
n e
t
al
. [1
6]
have
fo
rm
ul
at
ed a
m
a
xim
i
zati
on
i
ssue f
o
r c
ove
rage
en
h
a
n
cem
en
t co
nsid
eri
n
g quality an
d
connectiv
ity as tw
o
essen
tial p
a
ra
m
e
ters. Un
iqu
e
ly, th
e
study also
discusses with
forecasting of
energy
fluct
u
ation a
nd
outcomes were eval
ua
ted
using c
o
vera
ge
quality in both
cent
r
al
i
zed an
d dece
nt
ral
i
zed al
go
ri
t
h
m
s
.
Em
phasi
s on e
n
er
gy
effi
ci
ent
al
ong
wi
t
h
ad
dressi
n
g
co
ver
a
ge a
n
d
connectivity issues
was also
seen i
n
t
h
e w
o
rk
d
one
by
N
o
ori
a
nd R
a
feh
[1
7]
. T
h
e o
u
t
c
om
e of t
h
e st
u
d
y
wa
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
En
erg
y
efficient sch
e
me to Jo
i
n
tly Op
timize
Co
verag
e
an
d
Co
nn
ectivity in
…
(
D
eep
ak S. Sakk
a
ri
)
45
6
evaluate
d
with num
b
er of ac
tive nodes a
n
d c
o
vera
ge
rate on
NS2
simu
lato
r and com
p
ared
with
OGDC
(O
pt
i
m
al
Geogra
p
hi
cal
Den
s
i
t
y
C
ont
rol
)
p
r
ot
ocol
[
18]
. T
a
ym
ouri
an
d Kan
g
a
v
an [
1
9]
have f
o
cu
sed
on t
h
e
co
m
p
u
t
atio
n
a
l co
m
p
lex
ity o
f
th
e in
v
e
stig
at
in
g
th
e co
nn
ectiv
ity to
leran
ce in
wireless sen
s
or
n
e
twork. The
aut
h
ors
ha
ve a
d
o
p
t
e
d
b
o
t
h
g
r
ap
h t
h
e
o
ry
as
wel
l
as m
i
ni
ng t
ech
ni
q
u
es a
nd t
e
st
e
d
o
n
m
u
lt
i
p
l
e
di
st
ri
but
i
o
n
testb
e
d
.
Th
e outco
m
e
o
f
th
e st
u
d
y
was ev
aluated
u
s
i
n
g conn
ectiv
ity to
leran
ce.
Hen
ce, it
can
b
e
seen
th
at th
ere
are som
e
pot
ent
i
a
l
st
udi
es be
i
ng d
o
n
e co
nsi
d
eri
ng t
h
e i
s
s
u
es of co
ve
rage
and co
n
n
ect
i
v
i
t
y
, but
a cl
oser l
o
o
k
at th
e p
r
ior wo
rk
shows th
at
m
u
ch
work
i
s
e
m
p
h
a
si
zed
on c
ove
ra
ge issues as com
p
ared to c
o
nnect
ivity
issues, and
foc
u
s
was m
u
ch less towards
ac
hieving ene
r
gy
efficie
n
cies.
Very fe
w st
udies
in t
h
e
past a
r
e
found
to be be
nchm
arke
d,
whic
h is anot
her re
searc
h
ga
p fo
r whic
h reason, it becom
e
s di
fficult to access the quality
of t
h
e t
ech
ni
q
u
e
s bei
ng
di
scus
sed. Al
s
o
, i
t
was fo
un
d t
h
at
al
go
ri
t
h
m
co
m
p
l
e
xi
t
y
i
s
l
e
ss conce
n
t
r
at
e
d
w
h
en t
h
e
tech
n
i
qu
es ar
e
d
i
scu
s
sed
w
ith r
e
spect to
th
e
p
e
rf
or
m
a
n
ce par
a
m
e
ter
s
. H
e
nce, all th
e above issu
es ar
e
p
o
in
t of
foc
u
s i
n
t
h
e
i
m
pl
em
ent
a
t
i
on o
f
t
h
e
p
r
o
p
o
se
d
m
odel
i
n
ne
xt
s
ect
i
on.
3.
PROBLEM IDENTIFICATION
Th
e
p
r
ob
lem
s
th
at are
b
e
ing
i
d
en
tified
after
rev
i
ewing
th
e
so
lu
tion
s
offered
in ex
isting
syste
m
are d
i
scu
ssed
as fo
llo
ws:
Few Benchmarked S
t
udies
:
Th
ere are
v
e
ry
few
b
e
n
c
h
m
ark
e
d
stud
ies in
th
is p
r
ob
lem
.
It is essen
tial to
un
de
rst
a
n
d
t
h
a
t
any
sol
u
t
i
o
n
t
o
wa
rds c
o
ve
rage a
n
d co
n
n
ect
i
v
i
t
y
shoul
d al
so e
n
s
u
re
opt
i
m
al
energy
prese
r
vation. One m
eans to accom
p
lis
h this to perform
com
p
arative an
alysis of prior solution to a
n
y
ener
gy
effi
ci
e
n
t
pr
ot
oc
ol
s i
n
wi
rel
e
ss sens
or
net
w
or
k. It
has bee
n
see
n
t
h
at
LEAC
H
an
d i
t
s
vari
ant
s
offers
optim
a
l
energy efficiency
i
n
wi
rel
e
ss net
w
o
r
k
[
20]
.
Su
rp
ri
si
n
g
l
y
, ve
ry
fe
w
st
udi
es t
o
wa
rd
co
v
e
r
a
g
e
an
d co
nn
ectiv
ity ar
e fo
und
to be
com
p
ared with L
E
ACH.
Broader Sche
mes of Ene
r
gy Efficienc
y
: It was foun
d
t
h
at th
ere are m
u
ltip
le tech
n
i
ques for con
s
erv
i
n
g
ener
gy
e.
g. i
m
pl
em
ent
i
ng
sl
eep sche
d
u
l
i
ng al
go
ri
t
h
m
[2
1]
, sel
ect
i
o
n
of cl
ust
e
r
he
ads [
2
2]
, ene
r
gy
ef
f
i
cien
t ro
u
t
i
n
g
sch
e
m
e
s [
2
3
]
, min
i
m
i
z
i
n
g
d
a
ta r
e
d
undan
c
ies [
2
4
]
, etc. H
o
w
e
v
e
r, ver
y
f
e
w
of
such
techniques
we
re found to be closely associated w
ith
add
r
essi
ng
cov
e
rag
e
and
conn
ectiv
ity issu
es i
n
wi
rel
e
ss se
ns
or
net
w
o
r
k
.
Imprac
tical Assump
tion
: M
a
j
o
rity of th
e prio
r stud
ies i
n
ad
dre
ssi
ng
co
v
e
rage
i
ssues
ha
ve ass
u
m
e
d t
h
e
sen
s
ing
cap
a
b
ility to
lie wit
h
in
t
h
e sen
s
ing
area as
d
e
term
in
ist
i
c [25
]
, wh
ich
is
qu
ite an
im
p
r
actical
assum
p
t
i
on as i
t
i
s
not
possi
b
l
e for a sen
s
o
r
t
o
expl
ore al
l
t
h
e sens
or ra
n
g
e o
f
ot
he
r se
nso
r
s i
n
case
o
f
large scale
network.
Also, t
h
ere are m
a
ny studies like
[2
6]
[2
7]
t
h
at
ha
ve
em
phasi
zed
o
n
cl
ust
e
r hea
d
t
o
ens
u
re
ene
r
gy
efficiency. Howe
ve
r, suc
h
schem
e
s
ha
ve
an adde
d
flaw as
if the cl
uster hea
d
stops
work
i
n
g
for any p
a
rticu
l
ar reason
(security, circu
itry failu
re) th
e conn
ectiv
ity to
th
e o
t
h
e
r sen
s
o
r
n
o
d
e
s
are
d
r
astically lo
st lead
ing
t
o
p
a
rtitio
n
i
n
g
pro
b
l
em
s in
large-scale sp
arse
n
e
two
r
k
.
4.
PROP
OSE
D
SYSTE
M
The
pri
m
e aim
of t
h
e
pr
op
ose
d
sy
stem
is to prese
n
t a cost effi
cient schem
e
to ensure
optim
a
l
cove
ra
ge a
nd c
o
n
n
ect
i
v
i
t
y
al
o
n
g
wi
t
h
e
n
e
r
gy
co
nser
vat
i
o
n i
n
wi
rel
e
ss se
ns
or
net
w
o
r
k
.
T
h
e case st
u
d
y
o
f
t
h
e
pr
o
pose
d
sy
st
em
i
s
experi
m
e
nt
ed wi
t
h
t
h
e
exam
pl
e of
m
a
ssi
ve dat
a
ag
gre
g
at
i
o
n p
h
e
nom
eno
n
w
h
e
r
e t
h
e
fo
rm
ul
at
i
on i
s
do
ne t
o
en
su
re
t
h
at
t
i
m
e
requ
i
r
ed
fo
r
per
f
o
r
m
i
ng dat
a
a
g
gr
egat
i
o
n
i
s
n
o
t
m
u
ch ext
e
nsi
v
e al
on
g
with
reten
tion
o
f
op
ti
m
a
l serv
ice qu
ality. Tab
l
e 1
h
i
gh
lights th
e no
tatio
n
u
s
ed
in
em
p
i
rical d
i
scu
ssi
o
n
o
f
t
h
e
pr
o
pose
d
sy
st
e
m
.
Tabl
e 1.
Li
st
o
f
N
o
t
a
t
i
o
n Use
d
No
ta
tio
n
Meaning
No
ta
tio
n
Meaning
η
No.
of Nodes
S
R
Sensing
Radius
T
R
Trans
m
itting Radi
us
(c,d)
c & d are
1
s
t
and 2
nd
position of the n
ode
T
S
Trans
m
itt
ance
stat
e
O
S
Of
f
State
S
SRS
Sense/receive
stat
e
S
P
Probability of Stat
es
σ
Anticipated ener
gy used by
sensing node
SI
M
area
Si
m
u
lation
Are
a
S
OFF
Sensing states in off
m
ode
S
i
Sensing state in i
th
m
ode
C
mi
n
M
i
nim
a
l Cover
a
ge
θ
Probability of
successf
ul trans
m
ission
δ
Probability to be retained in T
S
N
ID
Node
I
D
N
res
_
en
g
Node with r
e
sidual ener
gy
inform
ation
d
mi
n
M
i
n
i
mu
m
d
i
s
t
a
n
c
e
N
me
m
b
e
r
M
e
m
b
er
nodes
Th
e propo
sed
syste
m
m
o
d
e
ls
th
e wireless sen
s
o
r
n
e
t
w
ork in
to
m
u
lt
ip
le
sin
g
l
e layered
clu
s
ters of
sam
e
sen
s
o
r
no
d
e
s of m
u
ltip
le sizes. It
was
d
o
n
e
t
o
facilita
te clu
s
ter-b
a
sed
co
mm
u
n
i
cati
o
n with th
e si
nk
in a
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
IJEC
E V
o
l
.
5, No
. 3,
J
u
ne 2
0
1
5
:
45
4 – 4
6
3
45
7
faster m
a
n
n
e
r.
Co
n
s
i
d
eri
n
g this tree-b
a
sed st
ru
ct
u
r
e,
a co
mm
u
n
i
catio
n
m
o
d
e
l is bu
ilt wit
h
sp
ecific
n
u
m
b
e
r
of
cl
ust
e
rs i
f
t
h
e
net
w
or
k i
s
f
o
u
nd t
o
ha
ve
η
se
nsor nodes,
where
η
is always greater tha
n
the
m
a
xim
u
m
num
ber
of nodes in a particular cluste
r.
The system
also conside
r
s that
η
sensor node
s are struct
urally approxi
m
ated
b
y
lo
cu
s th
at
are ind
e
p
e
nd
en
tly an
d
un
iform
l
y d
i
strib
u
t
ed
in
a sing
le
sh
ap
e, S
SRS
=[0,1]
x
[0
,1
],
wh
ere th
e
op
p
o
si
t
e
ed
ge
s are basi
cal
l
y
i
d
ent
i
f
i
e
d.
The p
r
op
ose
d
sy
st
em
adopt
s t
h
e sha
p
e o
f
t
h
e t
o
rus t
o
pre
v
ent
red
u
nda
nci
e
s
o
w
i
n
g t
o
ed
ge e
ffect
s.
4.
1. Ad
dressi
n
g
Co
ver
age
Is
sues:
The c
o
vera
ge
i
ssues
of
t
h
e
wi
rel
e
ss se
ns
o
r
net
w
or
k a
r
e
m
i
ti
gat
e
d
by
c
onsi
d
eri
n
g
t
h
e
st
at
es o
f
t
h
e
WSN system
.
We co
n
s
i
d
er t
h
e syste
m
h
a
s eq
u
ilibrated
t
o
its stead
y state, an
d ev
ery senso
r
no
d
e
is treated
as
in
d
e
p
e
nd
en
t o
f
th
e first o
r
d
e
r with
state p
r
o
b
ab
ilities rep
r
esen
ted
b
y
S
P
. C
onsi
d
er S
R
i
s
t
h
e sensi
ng
radi
us a
n
d
T
R
be t
h
e t
r
a
n
s
m
i
t
t
i
ng ra
di
u
s
.
The
co
vera
ge
m
odel
consi
d
e
r
s t
h
at
a
p
o
i
n
t
c
ϵ
T
S
is sai
d
to
b
e
co
v
e
red
if t
h
ere is
at
l
east
one se
n
s
or
n
o
d
e i
n
t
h
e
regi
on
wi
t
h
se
nsi
n
g st
at
e wi
t
h
i
n
S
R
wh
ich
will id
en
tify the ev
en
t is o
c
curring
at
poi
nt
c
. Hen
c
e, u
s
ing
g
e
o
m
etrical ap
p
r
o
a
ch
in
th
e state-b
a
sed
top
o
l
og
y, th
e sen
s
i
n
g
p
r
ob
ab
ility o
f
th
e
part
i
c
ul
a
r
se
ns
or
n
o
d
e ca
n
be
re
prese
n
t
e
d
as
π
S
R
2
S
P.
Th
erefo
r
e, th
e prob
abilit
y th
at no
sen
s
or
no
d
e
can
sen
s
e
an eve
n
t at position
c
can
be represe
n
ted as (1-
π
S
R
2
S
P
)
η
.
T
h
ere
f
ore, (1-
π
S
R
2
S
P
)
η
c
a
n be sai
d
t
o
be t
h
e
p
r
ob
ab
ility th
at reg
i
on
c
is not h
a
v
e
co
v
e
rage. Hen
ce,
u
s
ing
pro
b
a
b
ility t
h
eory, th
e coverag
e
fun
c
tion
can
b
e
represe
n
ted as:
red
c is cove
covered
c is not
c
f
0
1
)
(
(1
)
Hen
c
e, m
a
th
ematical rep
r
esen
tatio
n of
p
r
ob
ab
ility th
at
the po
sitio
n
x
is no
t co
v
e
red
can
b
e
rep
r
esented
as
P[
f(
c)
=1
]=(1
-
π
S
R
2
S
P
)
η
. Th
e eq
.(1
)
h
i
gh
lig
h
t
s th
e pro
b
ab
ility fu
n
c
tion
f(c
)
th
at is
rep
r
esen
ted
b
y
th
e
con
d
i
t
i
onal
cri
t
eri
a
f
o
r
re
pres
ent
i
n
g
c
ove
red
o
r
unc
o
v
ere
d
regi
on
o
f
wi
rel
e
ss se
nso
r
net
w
o
r
k
.
T
h
e
r
ef
or
e, t
h
e
math
e
m
atica
l
rep
r
esen
tation
of th
e area
(SIM
area
) i
s
n
o
t
c
ove
red
u
p
ca
n
be
d
e
pi
ct
ed as
,
)
(
.
c
f
dc
SIM
area
and s
o
E[
A]
=
∫
dc. P[
f(c
)=
1]
=(
1-
π
S
R
2
S
P
)
η
, where E[SIM
area
] is expected area that is
not
cove
re
d up
. Si
m
i
l
a
rl
y
,
math
e
m
atica
l
represen
tatio
n o
f
th
e ex
p
ect
ed
area t
h
at
i
s
not
c
ove
red
up i
s
1
-
E
[
SI
M
area
]
=
1-(1
-
π
S
R
2
S
P
)
η
.
Hence
,
the propos
ed system
can easily
evaluate the cove
red area as wel
l
as uncovere
d
area in trans
m
ission
zone i
n
wi
rel
e
ss sens
or net
w
or
k an
d can t
a
ke necessa
ry
act
i
on. It
can al
so be sai
d
t
h
at
1-E
[
SIM
area
]
=
1-
(1
-
π
S
R
2
S
P
)
η
is goi
ng t
o
be the
problem
space in our study, whic
h is the area
that is not covered
up a
n
d ca
lls for
i
m
p
l
e
m
en
tin
g
certain
tech
n
i
qu
es to
en
su
re op
ti
m
a
l
coverage. Consi
d
ering the fact in this
case as
l
og(
1-
c)
≤
-c
fo
r c
<1
,
will prov
id
e th
e sch
e
me as,
π
S
R
2
S
P
=
σ
(
η
)/
η
. Th
en
the con
d
ition
for
an
ticip
ated
coverag
e
is g
i
v
e
n
b
y
,
1-
(1
-
σ
(
η
)/
η
)
η
⩾
1-
e
-
ωσ
(
η
)
, whe
r
e
σ
(
η
)/
η≤
1
After assign
ing
th
e fun
c
tion
o
f
co
verag
e
and
its p
r
ob
ab
ility, th
e area is co
m
p
u
t
ed
th
at do
esn
’
t co
m
e
unde
r the cove
rage are
a
. For the easiness in
com
putation,
t
h
e expected area to be covere
d up is com
puted that
w
ill fu
rn
ish
th
e b
e
tter
p
r
ob
ab
ility o
f
the co
v
e
rag
e
area co
nsid
ered for th
e study. Thu
s
, as l
o
ng
as
σ
(
η
)
α
(infinit
y), the e
x
pected cove
rage
approac
h
es
1.
σ
(
η
) can
be m
a
ppe
d as the
anticipated power
use
d
by
th
e sen
s
ing
nod
es. Fo
r t
h
e
purpo
se
of
o
p
timizatio
n
,
t
h
e
p
r
op
o
s
ed system
will ado
p
t
a tech
n
i
q
u
e
th
at
will u
s
e
p
r
ob
ab
ility th
eo
ry
for exh
i
b
i
t
i
n
g
th
e
fact that an
arb
itrary
v
a
riab
le
will h
a
v
e
p
o
s
itiv
e
p
r
ob
ab
ility o
f
b
e
ing
positive (Second
Order Mom
e
nt). It will also com
pute va
ri
ance of a
r
ea A for which the
system
should
m
e
et
the condition
of expect
ed area
as E[SIM
area
]
2
. The system
also c
onsi
d
ers
a
v
er
a
g
e
field approxim
a
tion that the
sens
or
n
o
d
e
s a
r
e
beha
vi
n
g
i
n
depe
n
d
ent
l
y
i
n
t
h
e si
m
u
l
a
t
i
on area i
n
t
h
e
p
r
e
s
ence
of
nei
g
h
b
o
r
n
odes
.
4.2. Ad
dressin
g
Connecti
v
ity
Iss
ues:
The propose
d system
considers possibility of two
ideas
for ens
u
ri
ng
optim
a
l connect
ivity in the
sen
s
o
r
n
e
two
r
k, as Figu
re
1
.
Th
e fi
rst id
ea fo
cuses on
th
e to
po
log
y
of th
e g
r
aph
conn
ectiv
ity to
b
e
ex
tracted
fro
m
th
e av
ailab
ility o
f
th
e sen
s
o
r
nod
es in th
e n
e
two
r
k
.
Th
e second
facto
r
propo
ses
m
o
re h
a
rd
co
nd
itio
n
con
s
i
d
eri
n
g
co
nt
ent
i
o
n i
s
s
u
es
i
n
net
w
or
k.
T
h
e
pr
o
pos
ed
syste
m
ad
op
ts heu
r
istic fo
r m
i
t
i
g
atin
g th
e proble
m
s
o
f
con
t
en
tion
i
ssu
es i
n
wireless sen
s
or n
e
t
w
o
r
k
for ensuring
b
e
tter con
n
ectiv
ity so
lu
tio
ns. Th
e targ
et
of th
e
co
nn
ectiv
ity
can
b
e
d
i
scu
ssed
as fo
llo
ws: Co
n
s
i
d
er
an
ev
en
t h
a
s o
c
cu
rred
i
n
p
o
sitio
n
c
, whe
r
e
c
ϵ
T
S
. T
h
e
co
mm
u
n
i
catio
n
m
o
d
e
l will a
tte
m
p
t
to
b
r
o
a
d
cast th
is ev
ent to
n
e
x
t
p
o
s
iti
o
n
d
, where
d
ϵ
T
S
. There
f
ore, the
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
En
erg
y
efficient sch
e
me to Jo
i
n
tly Op
timize
Co
verag
e
an
d
Co
nn
ectivity in
…
(
D
eep
ak S. Sakk
a
ri
)
45
8
ev
en
t m
e
ssag
e
is tran
smitted
fro
m
o
n
e
to
an
o
t
h
e
r
n
o
d
e
in
m
u
lt
ip
le p
o
s
itio
n
s
. Th
e
d
e
sig
n
p
r
in
ci
p
l
e o
f
the
propose
d
study is form
ulated in s
u
ch a
wa
y that it
shoul
d support the
m
u
lti-hop com
m
unication syste
m
in
w
i
r
e
less sen
s
or
n
e
t
w
or
k. H
e
n
ce, along
w
i
t
h
addr
essing
t
h
e cov
e
r
a
g
e
an
d
con
n
ecti
v
ity issu
es, th
e
pr
opo
sed
syste
m
also ensure
selection
of cluster hea
d
in the
sam
e
process. One
of t
h
e a
dva
ntages
o
f
th
is p
r
o
cess is
th
at
t
h
e o
p
t
i
m
al
select
i
on
of cl
ust
e
r hea
d
e
n
s
u
re
s ene
r
gy
e
ffi
ci
ent
r
out
i
n
g i
n
dat
a
ag
gre
g
at
i
on
p
r
oce
ss as
wel
l
as i
t
also
en
sures
opti
m
a
l
co
nn
ectiv
ity a
m
o
n
g
th
e clu
s
ter.
Fi
gu
re
1.
Sce
n
ari
o
of
co
ve
rag
e
an
d c
o
n
n
ect
i
v
i
t
y
Th
e so
lu
tion
t
o
ad
dress t
h
e con
n
ectiv
ity
p
r
ob
lem
s
in
p
r
opo
sed system
co
n
s
ists o
f
form
u
l
atin
g
certain
o
p
tim
al
con
d
ition
s
t
o
en
su
re m
o
re
ro
bu
st con
n
ecti
v
ity a
m
o
n
g
the clu
s
ters. Th
e form
u
l
atio
n
in
itiates
with
th
e fact th
at
so
ur
ce no
de (
i
n
c
-po
s
ition
)
will b
e
transmitt
in
g
to
th
e d
e
stin
atio
n
nod
e (in
d
-po
s
itio
n) if
th
ere is a presen
ce
o
f
m
u
ltip
le
ho
p
e
s in th
e
receiv
i
n
g
state at th
e lo
cati
o
n s
o
, s
1
,
. .
.
,s
K
suc
h
that:
P
1
: It is th
e first co
nd
itio
n
o
f
t
h
e
p
a
th
settin
g
wh
ere |c-s
0FF
|
≤
S
R
(
c
ca
n
be se
nse
d
;
)
P
2
: it is a seco
n
d
con
d
ition
of th
e p
a
t
h
settin
g
wh
ere |s
i
-s
i-
1
|
≤
T
R
for i=1. . . . K,
henc
e, the eve
n
t ca
n
b
e
tran
sm
itted
fro
m
s
i-1
to
s
i
, an
d it will b
e
receiv
e
d
sin
ce s
i
is in the
recei
ving state.
P
3
: It is th
e seco
nd
con
d
ition
o
f
th
e
p
a
th settin
g
wh
ere |s
K
-d
|
≤
T
R
(s
K
can
tran
sm
it to
d
)
Hence
,
the propose
d
system
supports c
o
nnec
tivity for
m
u
ltiple hop (k)
network. The system
co
nsid
ers conditio
n
fo
r m
i
n
i
mal co
nn
ectiv
ity if, fo
r an
y
n
ode
x to
node y, t
h
ere is al
ways existence
of at
least
o
n
e
edg
e
b
e
tween
th
em
. Th
i
s
so
lu
tion
altho
ugh
m
i
t
i
g
a
tes
m
i
n
i
m
a
l co
n
n
ectiv
ity issu
es b
u
t
d
o
e
sn’t m
i
tig
ate
i
ssues rel
a
t
e
d t
o
co
nt
ent
i
o
n.
Hence
,
i
t
i
s
necessary
t
o
f
o
r
m
ul
at
e a condi
t
i
on f
o
r c
o
nt
en
t
i
onl
ess co
n
n
ec
t
i
v
i
t
y
fo
r
whi
c
h p
u
r
p
ose
t
h
e pr
op
ose
d
sy
st
em
has t
o
ens
u
re t
h
at
w
h
en t
h
e n
ode c
o
m
m
uni
cat
es wi
t
h
ot
her
no
de,
t
h
ere
sho
u
l
d
be as
su
rance t
h
at
t
h
e
dest
i
n
at
i
o
n n
o
d
e l
i
e
s wi
t
h
i
n
t
h
e se
nsi
n
g st
at
e, an
d n
o
ot
he
r
sens
or
n
odes
wi
t
h
i
n
th
e n
e
i
g
hbo
rhoo
d of
d
e
stin
atio
n nod
e sh
ou
l
d
tr
y to p
e
r
f
orm
tran
sm
issio
n
.
If th
is con
d
iti
o
n
of co
n
t
en
tio
n less
co
nn
ectiv
ity is
m
e
t, red
u
n
d
a
ncies can
b
e
con
t
ro
lled
wh
ich will in
d
i
rectly
in
flu
e
n
ce th
e en
erg
y
con
s
erv
a
tion
p
o
s
itiv
ely (less
red
und
an
cies
less retra
n
sm
ission
en
erg
y
con
s
erv
a
tio
n). Al
o
n
g
with
conn
ectiv
ity, the
p
r
op
o
s
ed
system
en
su
res t
h
at
sen
s
i
n
g
n
o
d
e
s will requ
ire
bein
g with
i
n
cov
e
rag
e
area
wi
th
resp
ect t
o
S
R
.
In
o
r
d
e
r to
en
su
re th
e o
p
tim
al
co
n
n
ectiv
ity, sensin
g
n
o
d
e
s sh
ou
ld
b
e
cov
e
red u
p
in
th
e area with
resp
ect to T
R
as
well. Th
erefo
r
e, cond
itio
n of
min
i
m
u
m
co
v
e
rag
e
can b
e
represen
ted
as C
mi
n
=m
i
n
{
S
R
, T
R
}.
5.
IMPLEME
N
TATION &
RESULT
The p
r
op
ose
d
sy
st
em
i
s
im
plem
ent
e
d o
n
3
2
-
bi
t
W
i
nd
o
w
s
OS wi
t
h
1.
8
4
GHz
(m
i
n
) pr
o
cesso
r spee
d,
and
p
r
og
ram
m
i
ng
pl
at
f
o
rm
i
s
co
nsi
d
e
r
ed
i
n
M
a
t
l
a
b. Th
e
pr
im
e pur
p
o
se
of
t
h
e
pr
o
pose
d
s
y
st
em
i
s
t
o
en
h
a
nce
t
h
e co
vera
ge a
nd c
o
nnect
i
v
i
t
y
i
ssues wi
t
h
o
p
t
i
m
a
l
energy
usa
g
e i
n
t
h
e a
r
ea of
wi
rel
e
ss
sens
or
net
w
or
k. T
h
e
sim
u
l
a
t
i
on i
s
carri
ed
out
co
n
s
i
d
eri
n
g 5
0
0
-
1
00
0 sen
s
o
r
nod
es. In
ord
e
r to
p
e
rfo
rm
th
is
g
o
a
l, fo
llo
wi
n
g
th
e
work
has been carried
out:
Desi
g
n
of
C
o
v
e
ra
ge E
n
h
a
n
ce
ment
:
T
h
e i
m
pl
em
ent
a
t
i
on f
o
r e
nha
nci
n
g c
o
vera
ge i
s
s
u
e i
s
carri
e
d
out
i
n
dual
st
eps
whe
r
e t
h
e fi
rst
st
ep
pr
ovi
des al
t
e
rat
i
on an
d
the s
econd step
provides c
ove
rage
. The first stage
ev
alu
a
tes t
h
e en
tire tran
sm
iss
i
o
n
as well as
sen
s
ing
area
o
f
a sp
eci
fic senso
r
nod
e
u
n
til
it co
nv
erg
e
s t
o
a
targ
et po
in
t. Th
is stag
e in
itiates b
y
co
nv
erti
n
g
a
b
i
gg
er sen
s
ing
zon
e
in
WSN to
m
o
d
u
lar sen
s
ing
zon
e
fo
r easi
n
ess i
n
com
put
at
i
on a
nd e
x
t
r
act
s
var
i
ous i
n
f
o
rm
at
ion
(resi
dual
e
n
ergy
) at
t
h
e c
r
oss-
sect
i
on
of
i
t
s
n
e
igh
bor transmissio
n
area wh
ich
its in
tersects, so
th
at
it can
b
e
treated
as targ
et in
th
e
n
e
x
t
co
nsecu
ti
v
e
st
ep o
f
c
o
vera
ge e
nha
ncem
ent
.
I
n
o
r
de
r t
o
i
m
pl
e
m
ent this, t
h
e proposed
system
conside
r
s
random
depl
oy
m
e
nt
of
sens
o
r
s i
n
t
h
e
si
m
u
l
a
ti
on a
r
ea o
f
hom
oge
no
us
WSN
SI
M
area
, w
h
i
c
h i
s
w
hol
l
y
c
ove
r
e
d.
The p
r
o
p
o
se
d al
go
ri
t
h
m
i
s
execut
e
d by
al
l
t
h
e
m
odul
ar s
u
b
-re
gi
o
n
s
of
SIM
area.
Let
x
is a tran
sm
issio
n
area of ra
di
us
Rad
an
d let an
o
t
h
e
r wireless sen
s
or
n
o
d
e
y
b
e
p
o
s
ition
e
d
with
in
t
h
e ran
g
e
of
x
and is
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
IJEC
E V
o
l
.
5, No
. 3,
J
u
ne 2
0
1
5
:
45
4 – 4
6
3
45
9
d
e
no
ted b
y
y
ϵ
n
ode
(x
).
If
the
dist
ance
between the
target
Tar
i
n
t
h
e
re
gi
on
an
d
x
is less th
an
Rad
, th
at
is
the distance (
Ta
r
,
x
)<
Rad
,
Tar
i
s
covere
d by
x
. Let
,
anot
he
r no
de z be p
o
s
i
t
i
oned i
n
t
h
e
com
m
uni
cat
i
on
ran
g
e
Comm
R
of
x an
d i
s
rep
r
esent
e
d as
z
ϵ
no
de(
x
)
. Th
e co
nd
itio
n
p
r
op
osed
h
e
re is th
at o
f
th
e Eu
clid
ian
di
st
ance bet
w
e
e
n
x
and
z
is less th
an
CommR,
the
n
they
can comm
unicate w
ith each
othe
r. T
h
e syste
m
also
assu
m
e
s t
h
at in
o
r
d
e
r to en
sure co
nn
ectiv
ity o
f
th
e n
e
twork, th
e
Co
mm
R
of each s
e
ns
or node
m
u
st
not
be sm
all
e
r
t
h
an d
o
u
b
l
e
of
i
t
s
sensi
n
g radi
us
Rad
.
Design
o
f
C
o
nn
ectivity En
han
cemen
t:
T
h
e
enha
ncem
ent of the connectivity
i
n
t
h
e pr
op
ose
d
sy
st
em
i
s
per
f
o
r
m
e
d by
con
s
i
d
eri
n
g
n
u
m
ber of set
of
sens
or
n
odes
e
n
cap
sul
a
t
i
n
g t
h
e t
a
r
g
et
s. T
h
e
im
pl
em
ent
a
t
i
o
n
of c
ove
rage
pa
rt
al
l
o
cat
es a cost
fo
r eve
r
y
sens
or n
o
d
e th
at il
lu
strates th
e th
ere
are number
of targets in
t
h
e si
m
u
l
a
t
i
on area t
h
at
nee
d
s t
o
be c
o
n
n
ec
t
e
d t
o
eac
h
ot
her
.
T
h
e f
o
rm
ul
at
i
on
o
f
t
h
e
wei
g
ht
co
nsi
d
e
r
s
p
a
r
a
m
e
ter
s
lik
e r
e
sidu
al en
erg
y
and
nu
m
b
er
o
f
no
n-
en
capsu
lated
tar
g
ets.
W
h
en ch
oo
si
n
g
a sen
s
o
r
node
fo
r a c
ove
r set
,
p
r
evi
ous
st
ag
e si
gni
fi
es
o
n
i
t
s
cove
rage c
ont
ri
b
u
t
i
o
n
,
t
h
at
i
s
t
o
say
,
se
l
ect
i
ng t
h
e
on
e
cove
ri
n
g
as m
a
ny
t
a
rget
s u
n
c
ove
re
d as p
o
s
s
i
b
l
e
i
n
t
h
i
s
ph
ase, w
h
i
l
e
t
h
i
s
pha
se of
desi
g
n
o
f
co
nnect
i
v
i
t
y
con
s
i
d
er
s t
h
e
t
r
adeo
ff
bet
w
een
p
o
we
r a
n
d c
o
v
e
rage
co
nt
ri
but
i
on.
Po
wer Op
timiza
tio
n:
Th
e
prop
o
s
ed
syste
m
i
n
itially i
m
p
l
e
m
en
ts a fix
e
d
p
o
i
n
t
iteratio
n
alg
o
rith
m
to
find
th
e stab
le state p
r
o
b
a
b
ilities. In
ad
d
ition
,
t
h
e stab
le state p
r
ob
ab
ilities wil
l
d
e
p
e
n
d
on
–
i
) th
e nu
m
b
er of
n
o
d
e
s in
t
h
e n
e
twork, ii) th
e tran
sm
issio
n
and
sen
s
i
n
g
rad
i
us an
d
iii) th
e prob
ab
ility o
f
sen
s
ing
an
ev
en
t,
wh
ich
is an
ex
tern
al p
a
ram
e
ter th
at d
e
p
e
n
d
s
on
th
e even
t d
e
n
s
ity. We ob
tain
th
e stead
y state b
y
sim
u
l
a
t
i
ng t
h
e pr
o
pose
d
m
odel
t
o
a defi
ned
range
of si
m
u
l
a
t
i
on ro
un
ds a
nd w
h
e
n
t
h
e n
ode
depl
et
es t
h
e
po
we
r.
The p
r
o
p
o
se
d sy
st
em
i
s
desi
gne
d u
s
i
n
g t
w
o al
go
ri
t
h
m
s
i
.
e. i
)
al
go
ri
t
h
m
for e
n
er
gy
ef
fi
ci
ent
cove
ra
g
e
and
co
nn
ectiv
ity an
d
ii) al
g
o
rithm to
redu
ce the o
v
e
rh
ead. Th
e di
sc
ussi
ons
of t
h
e
f
o
rm
ul
ated algorithms are as
fo
llows:
A
l
gori
t
h
m
f
o
r
E
n
ergy E
ffi
ci
e
n
t
C
o
ver
age
a
n
d C
o
nne
ct
i
v
i
t
y
Inpu
t
: Nod
e
s
(
η
), T
r
ansm
ission ra
nge (T
X
),
Ener
gy
(E)
Outp
ut
:
m
i
ni
m
u
m
coverage
wi
t
h
e
n
e
r
gy
pr
eservat
i
o
n
Start
1.
De
fi
ne si
m
u
l
a
t
i
on pa
ram
e
ters
η
, T
X
, E
.
2
.
Form
u
l
ate p
r
ob
ab
ility fu
n
c
tio
n
for co
v
e
rag
e
red
c is cove
covered
c is not
c
f
0
1
)
(
3. C
o
m
put
ed c
ove
re
d area
π
S
R
2
S
P
4. C
o
m
put
e U
n
cove
re
d are
a
(1
-
π
S
R
2
S
P
)
η
5.
A
ppl
y
C
o
n
d
i
t
i
on f
o
r
ant
i
c
i
p
at
ed c
o
vera
ge
1-
(1
-
σ
(
η
)/
η
)
η
⩾
1-
e
-
ωσ
(
η
)
, whe
r
e
σ
(
η
)/
η≤
1
6.
A
ppl
y
C
o
n
d
i
t
i
on o
f
c
o
nnec
t
i
v
i
t
y
|c-s
0FF
|
≤
S
R
|s
i
-s
i-1
|
≤
T
R
|s
K
-d|
≤
T
R
7.
De
fi
ne t
h
ree
st
at
e m
e
t
r
i
c
of
ene
r
gy
E
o
, E
S
, E
T
.
8. C
o
m
put
e ant
i
ci
pat
e
d e
n
er
gy
de
pl
et
i
on i
n
st
eady
st
at
e:
E= (E
o
σ
o
+E
S
σ
S
+E
T
.
σ
T
.)//
σ
o,
σ
S,
σ
T
are anticipated ene
r
gy in
T
o
, O
S
, and
S
SRS
.
9
.
Defin
e
tran
smissio
n
pro
b
a
bilit
y:
θ
=
θ
1
/(1
-
δ
+
δ
θ
1
)
10
.
A
ppl
y
m
i
nim
i
zati
on f
u
nct
i
o
n
argm
in(E
o
p
o
+E
S
p
S
+E
T
.p
T
)
11
. E
v
al
uat
e
t
h
e m
i
nim
u
m
covera
ge
r=m
i
n{r
s
, r
T
}
End
In t
h
e above algorithm
,
θ
is t
h
e proba
bility
of successful
data packet tra
n
smission, a
nd
θ
1
can be re
pre
s
ent
e
d
as proba
b
ility of the i
n
itial successf
ul data
transm
ission atte
m
p
t.
δ
is t
h
e assu
m
p
tio
n of
p
r
ob
ab
ility to
b
e
retain
ed
in
th
e tran
sm
issio
n
state. As d
i
scussed
in
th
e prev
iou
s
sectio
n th
at th
e p
r
opo
sed
syste
m
p
e
rfo
r
m
sel
ect
i
on of cl
ust
e
r hea
d
f
o
r
opt
i
m
i
z
i
ng t
h
e ener
gy
by
reduci
ng t
h
e
o
v
er
hea
d
o
w
i
n
g
t
o
cont
ent
i
on
. The
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
En
erg
y
efficient sch
e
me to Jo
i
n
tly Op
timize
Co
verag
e
an
d
Co
nn
ectivity in
…
(
D
eep
ak S. Sakk
a
ri
)
46
0
opt
i
m
i
zati
on i
s
do
ne by
est
i
m
at
i
ng t
h
e ov
erhea
d
o
f
ene
r
gy
con
s
um
ed by
t
h
e com
m
u
n
i
cat
i
on m
odu
l
e
wi
t
h
f
o
llow
i
ng
step
s e.g.
A
l
gori
t
h
m f
o
r reduci
n
g
over
hea
d
Inpu
t
: N
ID
, T
R
, S
I
M
area
, N
res_eng
.
Out
put
:
Uni
q
u
e
f
u
si
n
g
of
dat
a
pac
k
et
s wi
t
h
l
e
ss
ene
r
gy
Steps
:
Start
1
In
itialize si
mu
latio
n
area;
2
In
itialize Tree [F
T
:{N
ID
, T
x_
Range
, Sink
x,
y
}]
;
3 Est
i
m
at
e Si
nk-l
o
cat
i
on:
Si
nk
x
=Are
a+B
dist
Si
nk
y
=Ar
e
a+B
dist
4
In
itialize
Neig
hbo
rho
o
d
d
e
nsity
(ND
max
=
N-1
).
5 Pe
rf
o
r
m
Energy
base
d s
o
rt
i
n
g
o
f
n
odes
N
res_eng1
, N
res_eng2
, …….N
res_engn
6 Select the fi
rst
k
elem
ents in the
set as t
h
e
CHS
of net
w
orks.
K={C
H
1
, C
H
2
, C
H
3
, CH
4
, CH
5
}
7
S
e
l
e
c
t
me
mb
e
r
n
o
d
e
w
i
t
h
mi
n
i
mu
m d
i
s
t
a
n
c
e
N
me
mb
e
r
d
mi
n
8. C
o
m
put
e l
o
c
a
t
i
on
of
C
H
9. Calc
ulate the distance
from
a
ll other
nodes
10
. Deci
de
t
h
e num
ber of
m
e
m
b
er
fo
r
e
v
ery
cl
ust
e
r hea
d
, a
n
d
Card
in
al (N
m
e
mber node
)
CH
11
. Pe
rf
o
r
m
com
m
uni
cat
i
on t
o
respect
i
v
e
cl
ust
e
r
hea
d
.
End
Th
e propo
sed
syste
m
is i
m
p
l
e
m
en
ted
in
Matlab
co
n
s
i
d
eri
n
g
th
e case st
u
d
y
of m
u
ltip
l
e
cycles o
f
cove
ra
ge a
n
d
co
nn
ectivity
p
r
obl
em
s. Each
of
t
h
e e
v
e
n
t
n
ode
s ca
n
g
e
n
e
rate an ev
en
t
with
a certain firing
p
r
ob
ab
ility. The firing
prob
abilit
y is related
t
o
th
e user i
n
put sen
s
ing
t
h
e
p
r
o
b
a
b
ility.
It
can
be see
n
f
r
om
t
h
e resul
t
s
t
h
at
i
t
s
t
r
ansce
i
ver m
odul
e c
o
nsum
es
m
o
st
o
f
t
h
e e
n
er
gy
i
n
a wi
rel
e
ss
sen
s
o
r
nod
e.
Th
e
o
b
j
ectiv
e of a
n
e
two
r
k
is t
o
ex
tend
t
h
e cov
e
rag
e
and
co
nn
ectiv
ity m
ech
an
ism
fro
m
all o
f
its
sen
s
o
r
nod
es.
Each
sen
s
or no
d
e
was in
itial
i
zed
b
y
a ran
d
o
m
resid
u
a
l en
erg
y
lev
e
l. A
n
e
two
r
k
was assessed
base
d
on
i
t
s
pa
cket
del
i
v
ery
r
a
t
i
o
(Fi
g
u
r
e
1
)
an
d t
o
t
a
l
p
o
w
e
r c
ons
um
pt
i
on
(Fi
g
ure
2)
a
n
d
t
h
e
d
u
rat
i
o
n
of
an
atte
m
p
t to
in
crease conn
ectiv
ity.
Fi
gu
re
2.
Pac
k
et
Del
i
v
ery
R
a
t
i
o
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
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:
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IJEC
E V
o
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5, No
. 3,
J
u
ne 2
0
1
5
:
45
4 – 4
6
3
46
1
To i
nve
stigate
the effect
of in-n
et
wo
rk
c
ove
r
a
ge a
n
d c
o
n
n
e
c
t
i
v
i
t
y
t
o
t
h
e
p
e
rf
orm
a
nce o
f
a net
w
o
r
k
,
di
ffe
re
nt
val
u
e
s
of ra
di
us w
e
re con
s
i
d
e
r
ed
i
n
t
h
e sim
u
l
a
t
i
ons. F
o
r c
o
m
p
ari
s
on p
u
r
p
oses, f
r
e
que
nt
l
y
used
LEAC
H
al
go
ri
t
h
m
[28]
i
s
co
nsi
d
e
r
ed
. As e
xpect
e
d
, b
o
t
h
p
ack
et d
e
li
v
e
ry ratio
an
d
to
t
a
l en
erg
y
op
timizatio
n
i
n
crease wi
t
h
t
h
e n
u
m
b
er of
no
des
,
rega
r
d
l
e
ss of ra
di
us a
nd
net
w
or
k st
r
u
ct
u
r
es.
Whe
n
com
p
ari
ng t
h
e t
o
t
a
l
energy cons
umed in a
n
atte
mpt to exte
nd t
h
e cove
ra
ge
and connectivity proces
s in
WSN
,
t
h
e pe
rf
orm
a
nce o
f
n
e
two
r
k
s
with th
e p
r
o
p
o
s
ed n
e
twork
structu
r
e is b
e
tter th
an
th
ose with
LEACH. Desp
ite th
e ob
v
i
o
u
s
ad
v
a
n
t
ag
es o
f
u
s
ing
LEACH p
r
o
t
o
c
o
l
for clu
s
ter org
a
n
i
zatio
n
,
few feat
ures are still n
o
t su
pp
orted
.
LEACH
assum
e
s a hom
ogeneo
u
s di
s
t
ri
but
i
o
n o
f
se
nso
r
n
o
d
es i
n
t
h
e gi
ve
n area.
Thi
s
scenari
o
i
s
not
very
re
al
i
s
t
i
c
.
A
n
o
t
h
e
r
b
i
gg
est p
r
o
b
l
em
w
ith
th
e
LEA
C
H
alg
o
r
ith
m
is
clu
s
ter
h
ead
selectio
n
is done qu
ite r
a
ndomly f
o
r
w
h
ich
r
easo
n
, th
e co
r
e
nodes ar
e v
e
r
y
f
a
st d
e
p
l
eted
of en
erg
y
. Th
e
p
r
op
o
s
ed
algor
ith
m
d
o
e
s th
e en
erg
y
m
a
nagem
e
nt
usi
ng e
n
hanc
em
ent
desi
gn
f
o
r
cove
ra
ge a
nd c
o
n
n
ect
i
v
i
t
y
. T
h
e pr
o
p
o
s
ed
sy
st
em
al
so ens
u
r
e
s t
h
at
while cove
rage and c
o
nnect
ivity are enha
nced, it shou
l
d
n
’
t
ha
ve any
negat
i
v
e i
n
fl
uence
o
n
i
t
s
ener
gy
/
lifetim
e of the
nodes
.
It is quite evident from
Figure 2 a
n
d Figure
3 that
t
h
e propos
ed syste
m
ha
s s
u
ccess
f
ull
y
derive
d a
n
algorithm
that can
perfor
m
energy efficient covera
ge a
nd
conn
ectiv
ity. Th
e
p
r
op
o
s
ed
sy
stem
perfo
rm
s
cum
u
l
a
t
i
v
e en
ergy
o
p
t
i
m
i
zati
on al
on
g
wi
t
h
e
nha
ncem
ent
of
co
vera
ge
an
d c
o
n
n
ect
i
v
i
t
y
l
e
vel
.
Fi
gu
re
4
illu
strate th
e an
alysis o
f
con
n
ectiv
ity lev
e
l o
f
th
e
p
r
op
o
s
ed
syste
m
, wh
ere
it can
b
e
seen
t
h
at propo
sed
syste
m
can
m
a
in
tain
sm
o
o
t
h
ascen
t
in
th
e curv
e rep
r
esen
ting
sp
ont
a
n
eo
us
dat
a
t
r
ansm
i
ssi
on
p
r
oces
s.
He
n
ce, t
h
e
co
nn
ectiv
ity lev
e
l is foun
d
with
m
a
x
i
m
u
m ascen
t alo
n
g
with e
n
ergy
efficiency for propose
d
sys
t
e
m
as
com
p
ared t
o
the LEAC
H
al
gorithm
Fi
gu
re
3.
Tot
a
l
Ene
r
gy
O
p
t
i
m
i
zat
i
on
Fi
gu
re
4.
A
n
al
y
s
i
s
of C
o
nnec
t
i
v
i
t
y
Level
Fi
gu
re
5
re
pre
s
ent
s
t
h
e a
n
al
y
s
i
s
o
f
t
h
e
c
ove
rage
l
e
vel, where it ca
n
be s
een t
h
at proposed system
is
foun
d with m
a
x
i
m
u
m
co
v
e
rag
e
lev
e
l
as com
p
ared
to
LEACH al
go
rithm
.
Fi
gu
re
5.
A
n
al
y
s
i
s
of C
o
vera
ge Le
vel
Fi
gu
re 6.
A
n
al
y
s
i
s
of Ene
r
gy
Depl
et
i
o
n per
packet
(m
J)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
En
erg
y
efficient sch
e
me to Jo
i
n
tly Op
timize
Co
verag
e
an
d
Co
nn
ectivity in
…
(
D
eep
ak S. Sakk
a
ri
)
46
2
Fi
gu
re
6
rep
r
e
s
ent
s
t
h
e
anal
y
s
i
s
of t
h
e e
n
ergy
c
o
nsum
pt
i
on
per
pac
k
e
t
(m
J). Int
e
res
t
i
ngl
y
,
t
h
e
pr
o
pose
d
sy
st
em
ext
e
nds t
h
e
cove
ra
ge a
n
d
c
o
n
n
ect
i
v
i
t
y
level alo
n
g
with
en
erg
y
o
p
tim
iza
tio
n
an
d is
foun
d to
be o
f
su
peri
or
desi
g
n
(
w
i
t
h
respect
t
o
e
n
e
r
gy
) c
o
m
p
ared
t
o
LEAC
H
p
r
ot
ocol
. Fi
gu
re
6 i
s
a
m
i
cro l
e
vel
analysis for Figure
3, where the
fram
e
wor
k
c
u
m
u
latively
ensu
res
be
tter strategies
fo
r e
n
hanci
n
g
issue
s
pert
ai
ni
ng t
o
c
ove
ra
ge an
d con
n
ect
i
v
i
t
y
. H
e
nce, t
h
e p
r
op
ose
d
sy
st
em
offers a si
m
p
l
e
and ef
fi
ci
ent
co
vera
ge
an
d conn
ectiv
ity so
lu
tion
s
fo
r
larg
e-scale wi
reless sen
s
or
n
e
twork.
6.
CO
NCL
USI
O
N
The
pr
o
p
o
s
ed
sy
st
em
hi
ghl
i
g
ht
s o
p
t
i
m
i
z
at
ion
p
r
o
cess t
h
a
t
i
s
desi
g
n
e
d
t
o
c
onst
r
uct
t
h
e pr
o
p
o
sed
n
e
two
r
k
st
ru
ct
u
r
e,
wh
ich
h
e
lp
s m
a
in
tain
in
g th
e t
o
tal en
erg
y
con
s
u
m
p
tio
n
at a low level. Sim
u
latio
n
resu
lt
s
sho
w
by
usi
n
g
t
h
e p
r
o
p
o
sed
m
odel
,
t
h
e pac
k
et
del
i
v
e
r
y
ra
t
i
o
, an
d cum
u
l
a
t
i
v
e ener
gy
o
p
t
i
m
i
zat
i
on ha
s bee
n
in
creased
. Th
e en
tire po
licy o
f
d
e
sign
ing
en
h
a
n
cem
en
t o
f
co
v
e
rag
e
and
co
nn
ectiv
ity issu
es in
WSN is b
a
sed
o
n
a prob
ab
ilistic ap
pro
a
ch
.Th
e
p
r
o
p
o
s
ed
syste
m
h
a
s u
s
ed
an enh
a
n
c
emen
t p
o
licy that targ
ets to
preserv
e
cu
m
u
lativ
e en
erg
y
co
nsu
m
p
tio
n
an
d
add
r
esses ex
ten
d
i
ng
co
nn
ectiv
ity to
o
b
y
a
p
r
ob
ab
ilistic m
e
t
h
od
of
t
u
r
n
i
n
g
of
f al
l
t
h
e
red
u
nda
nt
s
e
ns
or
n
ode
s
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NC
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
IJEC
E V
o
l
.
5, No
. 3,
J
u
ne 2
0
1
5
:
45
4 – 4
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BIOGRAP
HI
ES OF
AUTH
ORS
Deepak S
S
a
kk
ari r
ece
ived B
.
E degr
ee in
In
s
t
rum
e
ntation
& El
ectro
nics
Engine
ering fro
m
Bangalor
e
Univ
ersity
, Karn
atak
a, India. M.
Tech Degree in
Information Technolog
y
from
AAIDU, Allahabad. He is now
pursuing his Ph.D
. degree from Jawaharlal
Nehr
u Techno
logical
University
, H
y
d
e
rabad
,
Andhra
Pradesh. His res
ear
ch
interest
in
cludes Wi
reless Sensor Networks
es
peci
all
y
th
e Coverage and L
i
f
e
tim
e Optim
iza
t
ion
in W
i
reless Sensor Networks. He is currently
working a
s
As
si
sta
n
t Profe
ssor in the
De
pa
rtme
nt
of Computer Scien
ce & Engin
e
ering of Achar
y
a
Institute
of
Te
ch
nolog
y, B
a
ngalo
re, K
a
rnat
aka
.
Dr. T G Bas
a
varaju is
curren
t
l
y
working as
P
r
ofes
s
o
r and
Head of Com
p
uter S
c
ien
ce an
d
Engineering Departm
e
nt
at Gov
t
SKSJ Technolo
g
ic
al Institu
te, B
a
ngalor
e
. Prof
.B
asavaraju holds
a
Ph.D. (Engg.) fr
om Jadavpur University
, Kolk
ata in
the
area of Mobile Ad hoc Networks. He
obtain
e
d his Master’s Degree in
Computer Scien
ce
and Eng
i
neeri
ng from University
Visvesvar
a
y
a
College of
Engineering (UVCE)
, Bangalore Universi
ty
, B
a
ngalo
re and secur
e
d first rank. He hold
s
Bachelor’s degr
ee
in Computer Scien
ce
and
Engineering fro
m University
BDT Colleg
e
o
f
Engineering (U
BDTCE), Kuvempu University
, Da
vang
ere. H
e
has more th
an 16
y
e
ars of
experience in Teaching
and Indu
str
y
. He has au
thor
ed and co-
a
u
t
hored fiv
e
tex
t
b
ooks in the ar
e
a
of Computer Networking. One of
his co-author
ed
textbook on
” Mobile Wireless Ad hoc Networks:
Principles
, Protocols, and App
lications” was
published b
y
Auerbach Publishers (Tay
lor
and
Francis group), USA. His
major
areas of research ar
e Wir
e
less Ad hoc
Networks, Senso
r
Networks, and Mesh Networks. He has to his
credit m
o
re th
an 45 res
earch
publicat
ions
in
National/International Jour
nals and
Conferen
ces.
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