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ters
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ly
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t n
etwo
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Hy
b
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CC B
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C
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p
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A
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r
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M
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Netwo
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k
Un
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C
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Un
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1.
I
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W
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Sm
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C
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tatio
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a
n
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m
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en
s
o
r
s
th
at
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m
m
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icate
v
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o
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wir
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tech
n
o
lo
g
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to
r
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a
p
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r
ticu
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s
er
v
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(
e.
g
.
,
s
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ity
s
y
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tem
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,
b
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in
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au
to
m
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ma
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ag
em
en
t,
p
eo
p
le
s
af
ety
,
an
d
em
er
g
en
cy
)
[
1
]
,
[
2
]
.
T
h
e
u
n
iv
er
s
ity
in
f
r
astru
ctu
r
e
o
r
c
ellu
lar
s
y
s
tem
s
ar
e
co
m
m
o
n
l
y
u
s
ed
to
ex
c
h
an
g
e
d
ata
b
etwe
en
s
m
ar
t
d
ev
ices
an
d
s
en
s
o
r
s
o
n
th
e
ca
m
p
u
s
b
u
t
in
s
p
ec
if
ic
ca
s
es.
Fo
r
in
s
tan
ce
,
d
ir
ec
t
wir
eless
n
etw
o
r
k
(
e.
g
.
,
MA
NE
T
)
co
n
n
ec
tio
n
s
ca
n
b
e
u
tili
ze
d
as
a
b
ac
k
u
p
in
f
r
astru
ctu
r
e
in
em
er
g
en
cies,
as
well
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in
th
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f
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tu
r
e
s
m
ar
t
d
ev
elo
p
m
en
t
o
f
s
p
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if
ic
ap
p
licatio
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s
[
3
]
,
[
4
]
.
T
h
e
im
p
lem
en
tatio
n
o
f
MA
NE
T
in
s
m
ar
t
ca
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p
u
s
es
s
tr
u
g
g
le
m
an
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s
u
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d
ch
allen
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s
u
ch
as
is
s
u
es
r
elate
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to
n
o
d
es
m
o
b
ilit
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v
ar
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in
g
s
ig
n
al
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tr
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g
th
in
d
if
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en
t
ar
ea
s
,
an
d
lim
itatio
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s
in
co
m
m
u
n
icatio
n
r
a
n
g
e,
r
esu
ltin
g
in
u
n
r
eliab
le
co
m
m
u
n
icatio
n
[
5
]
.
Fu
r
t
h
er
m
o
r
e,
s
elec
tin
g
an
o
p
tim
al
a
n
d
ef
f
icien
t
r
o
u
tin
g
p
r
o
to
c
o
l
is
cr
u
cial
wh
en
d
ea
lin
g
with
em
er
g
en
cies,
s
ig
n
al
atten
u
atio
n
,
in
ter
f
e
r
en
ce
,
lo
ca
lizati
o
n
,
an
d
p
o
wer
co
n
s
tr
ain
ts
[
6
]
.
T
h
er
ef
o
r
e
,
s
ev
er
al
r
o
u
tin
g
p
r
o
to
co
ls
ca
n
b
e
u
tili
ze
d
f
o
r
d
ata
tr
an
s
m
is
s
io
n
in
s
m
ar
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ca
m
p
u
s
es
b
ased
o
n
v
ar
i
o
u
s
r
esear
ch
s
tu
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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t J I
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&
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T
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I
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N:
2252
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8
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P
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timiz
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o
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p
r
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co
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ta
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g
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b
r
o
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d
c
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s
t m
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a
g
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s
ma
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K
a
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-
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)
1057
an
d
d
ir
ec
tio
n
s
s
u
ch
as
s
p
r
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wait,
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w
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an
d
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ab
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in
g
[
7
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[
8
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.
Data
tr
an
s
m
is
s
io
n
in
wir
eless
n
etwo
r
k
s
th
at
co
n
tain
m
o
b
ile
n
o
d
e
s
tak
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lo
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g
tim
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ea
ch
th
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esti
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im
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o
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tr
ib
u
tio
n
p
at
ter
n
s
,
m
o
b
ilit
y
p
atter
n
s
,
an
d
p
h
y
s
ical
f
ac
to
r
s
.
T
h
er
e
f
o
r
e,
t
h
is
ty
p
e
o
f
n
etwo
r
k
co
n
n
ec
tio
n
is
k
n
o
wn
as
a
d
elay
/d
is
r
u
p
tio
n
to
ler
a
n
t
n
etwo
r
k
in
g
(
DT
N)
b
ec
au
s
e
o
f
its
la
ck
o
f
“e
n
d
-
to
-
en
d
”
co
n
n
ec
tiv
ity
,
wh
ich
ca
u
s
es
s
ig
n
if
ican
t
d
elay
s
[
9
]
.
DT
Ns
h
av
e
m
em
o
r
ies
to
s
to
r
e
co
p
ies
o
f
m
ess
ag
es
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etwe
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ile
n
o
d
es
u
n
til
th
ey
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ea
ch
th
eir
d
esti
n
atio
n
,
t
h
u
s
o
v
er
co
m
in
g
th
e
ch
allen
g
es
o
f
in
ter
m
itten
t
an
d
h
ete
r
o
g
e
n
eo
u
s
co
n
n
ec
tiv
ity
in
s
m
ar
t
ca
m
p
u
s
in
f
r
astru
ctu
r
e
d
esig
n
.
Fin
ally
,
it
is
wo
r
th
m
en
tio
n
in
g
th
at
th
e
ter
m
(
DT
Ns)
also
d
escr
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es
n
etwo
r
k
s
in
wh
ich
en
d
-
to
-
e
n
d
c
o
n
n
ec
tiv
ity
is
n
o
t
av
ailab
le
an
d
o
u
ta
g
es a
r
e
p
o
s
s
ib
le
d
u
e
t
o
wir
eless
r
ad
io
r
an
g
e
lim
itatio
n
s
an
d
r
eso
u
r
ce
co
n
s
tr
ain
ts
[
1
0
]
.
Sev
er
al
r
o
u
tin
g
p
r
o
t
o
co
ls
ar
e
co
n
s
id
er
ed
r
eliab
le
a
n
d
ad
e
q
u
ate
f
o
r
s
m
ar
t
ca
m
p
u
s
es
ap
p
licatio
n
s
s
u
ch
as
s
p
r
ay
an
d
wait
an
d
p
r
o
b
a
b
ilis
tic
f
lo
o
d
in
g
p
r
o
to
co
ls
[
1
0
]
,
[
1
1
]
.
T
h
ese
p
r
o
to
co
ls
ca
n
ad
d
r
ess
th
e
u
n
iq
u
e
r
eq
u
ir
em
e
n
ts
o
f
s
m
ar
t
ca
m
p
u
s
en
v
ir
o
n
m
en
ts
[
1
2
]
.
Mo
r
e
o
v
er
,
o
p
tim
izin
g
an
d
b
alan
c
in
g
th
e
t
r
ad
e
-
o
f
f
s
b
etwe
en
th
e
p
ar
am
eter
s
o
f
th
ese
p
r
o
to
co
ls
ar
e
co
n
s
id
er
e
d
ch
allen
g
in
g
d
u
e
to
th
e
n
atu
r
e
o
f
s
m
a
r
t
ca
m
p
u
s
en
v
ir
o
n
m
en
ts
.
I
n
a
d
d
i
t
i
o
n
,
t
h
is
r
es
e
a
r
c
h
a
i
m
s
t
o
a
n
a
l
y
z
e
t
h
e
e
f
f
i
ci
e
n
c
y
o
f
t
h
e
r
o
u
t
i
n
g
p
r
o
t
o
c
o
l
s
;
s
p
r
a
y
a
n
d
w
a
i
t
a
n
d
i
ts
b
i
n
a
r
y
v
e
r
s
i
o
n
,
a
n
d
p
r
o
b
a
b
i
l
i
s
t
i
c
f
l
o
o
d
i
n
g
u
s
e
d
i
n
(
D
T
N
s
)
f
o
r
s
p
e
c
i
f
i
c
a
p
p
l
i
c
at
i
o
n
s
.
T
h
e
a
n
a
l
y
s
is
i
s
c
o
n
s
i
d
e
r
e
d
o
p
t
i
m
i
z
a
ti
o
n
-
b
a
s
e
d
a
p
p
r
o
a
c
h
t
h
a
t
t
es
t
d
i
f
f
e
r
e
n
t
p
a
r
a
m
e
t
e
r
s
u
n
d
e
r
t
h
e
s
e
p
r
o
t
o
c
o
l
s
.
B
e
n
h
a
m
i
d
a
e
t
a
l
.
[
1
3
]
p
r
o
p
o
s
ed
s
o
lu
tio
n
s
f
o
r
u
s
in
g
DT
N
in
I
o
T
ap
p
licatio
n
s
to
ad
d
r
ess
th
e
“e
n
d
-
to
-
e
n
d
”
co
n
n
e
ctiv
ity
ch
allen
g
es
in
a
s
p
ec
if
ic
en
v
ir
o
n
m
e
n
t.
T
h
e
s
tu
d
y
p
r
o
v
id
e
d
a
b
r
o
a
d
s
u
r
v
e
y
o
f
th
e
u
s
e
o
f
DT
N
s
o
lu
tio
n
s
in
th
e
I
o
T
d
o
m
ain
.
Similar
l
y
,
a
s
tu
d
y
p
er
f
o
r
m
ed
b
y
Fra
ir
e
an
d
Fin
o
ch
ietto
[
1
4
]
p
r
esen
ted
th
e
DT
N
o
f
T
h
i
n
g
s
p
ar
ad
ig
m
th
at
co
v
er
s
n
ew
ca
p
a
b
ilit
ies
o
f
I
o
T
,
its
ap
p
licatio
n
s
,
ar
ch
itectu
r
e,
an
d
s
er
v
ices.
Fu
r
th
er
m
o
r
e
,
th
e
au
th
o
r
s
[
1
5
]
s
h
o
wed
th
at
th
e
DT
N
r
o
u
tin
g
p
r
o
to
c
o
l
is
s
till
in
u
s
e,
r
eq
u
ir
in
g
th
e
d
ev
elo
p
m
en
t
o
f
a
p
r
a
ctica
l,
r
eliab
le,
an
d
r
o
b
u
s
t
p
r
o
to
c
o
l
f
o
r
s
m
ar
t
ap
p
licatio
n
s
s
u
ch
as
I
o
T
.
Allao
u
i
et
a
l.
[
1
5
]
p
r
o
p
o
s
ed
h
ier
ar
c
h
ical
to
p
o
lo
g
y
DT
N
r
o
u
tin
g
f
o
r
I
o
T
ap
p
licatio
n
s
.
Mo
r
eo
v
er
,
Sar
r
o
s
et
a
l.
[
1
6
]
d
is
cu
s
s
ed
h
o
w
DT
N
ca
n
im
p
r
o
v
e
d
ata
co
llectio
n
f
r
o
m
in
ter
m
itten
tly
co
n
n
ec
ted
d
ev
ices,
s
u
ch
as I
o
T
a
n
d
s
en
s
o
r
n
etwo
r
k
s
in
r
em
o
te
ar
ea
s
.
Fu
r
th
er
m
o
r
e
,
Dian
a
an
d
L
o
ch
in
[
1
7
]
p
r
o
p
o
s
ed
a
s
to
ch
asti
c
p
r
o
b
a
b
ilit
y
m
o
d
el
to
ac
h
iev
e
t
h
e
en
d
-
to
-
en
d
d
ela
y
d
is
tr
ib
u
tio
n
f
o
r
t
h
e
B
S
W
r
o
u
tin
g
p
r
o
t
o
co
l
in
DT
N
n
etwo
r
k
s
.
T
h
e
m
o
d
el
was
u
s
ed
to
esti
m
ate
th
e
d
elay
d
is
tr
ib
u
tio
n
o
f
th
e
B
SW
p
r
o
to
co
l
in
h
eter
o
g
en
eo
u
s
n
etwo
r
k
s
,
th
o
u
g
h
it
lack
ed
a
m
o
b
ilit
y
m
o
d
el
an
d
f
o
cu
s
es o
n
o
n
e
s
p
ec
if
ic
p
r
o
to
c
o
l.
Li
et
a
l.
[
1
8
]
r
ev
iewe
d
th
e
ev
o
lu
tio
n
o
f
DT
N
p
r
o
to
co
l te
s
tin
g
an
d
ev
alu
atio
n
b
u
t
d
id
n
o
t
d
is
cu
s
s
B
SW
o
r
p
r
o
b
ab
ilis
tic
r
o
u
tin
g
ap
p
r
o
ac
h
e
s
.
An
o
th
er
s
tu
d
y
p
er
f
o
r
m
ed
b
y
Ab
d
elk
ad
er
et
a
l.
[
1
9
]
e
v
alu
ated
th
e
p
er
f
o
r
m
a
n
ce
o
f
DT
N
r
o
u
tin
g
p
r
o
to
c
o
ls
.
T
h
ey
also
ex
p
lain
ed
th
e
d
esig
n
o
f
r
ea
l
-
life
s
ce
n
ar
io
s
th
at
in
v
o
lv
ed
v
eh
ic
les
an
d
p
e
d
estrian
s
r
o
am
i
n
g
in
a
s
m
ar
t
city
.
T
h
e
s
tu
d
y
u
s
ed
a
lo
w
-
d
e
n
s
ity
n
etwo
r
k
with
a
m
ax
im
u
m
o
f
9
0
n
o
d
es.
Mo
r
e
o
v
er
,
Sp
ah
o
[
8
]
an
aly
ze
d
th
e
e
n
er
g
y
co
n
s
u
m
p
tio
n
o
f
d
if
f
er
en
t
r
o
u
tin
g
p
r
o
to
c
o
ls
in
a
DT
N
u
s
in
g
th
e
o
p
p
o
r
tu
n
is
tic
n
etwo
r
k
en
v
ir
o
n
m
en
t
(
ONE
)
s
im
u
lato
r
.
T
h
ey
s
h
o
wed
th
at
th
e
r
esu
lts
m
ay
v
ar
y
b
ased
o
n
s
p
e
cif
ic
ap
p
licatio
n
s
(
e
.
g
.
,
s
m
ar
t
c
am
p
u
s
es
ap
p
licatio
n
s
)
.
A
b
d
alla
an
d
Salam
ah
[
2
0
]
co
m
p
ar
e
d
th
e
p
er
f
o
r
m
an
ce
o
f
DT
N
p
r
o
to
c
o
ls
s
u
ch
as
GeO
p
p
s
,
Geo
Sp
r
ay
,
Ma
x
Pro
p
th
at
ar
e
u
s
ed
in
v
eh
icu
lar
ad
h
o
c
n
etwo
r
k
s
(
V
ANE
T
s
)
with
p
o
s
itio
n
-
b
ased
r
o
u
tin
g
(
e.
g
.
,
A
-
STAR,
C
A
R
,
Gy
T
AR
)
u
s
in
g
th
e
M
-
g
r
id
m
o
b
ilit
y
m
o
d
el.
T
h
e
s
tu
d
y
s
h
o
wed
th
at
th
e
r
esu
lts
v
ar
ied
b
ased
o
n
th
e
a
p
p
licatio
n
s
o
f
in
ter
est
i
n
VANE
T
s
.
I
n
ad
d
itio
n
to
th
e
p
r
ev
io
u
s
wo
r
k
s
in
th
e
liter
atu
r
e,
Sh
i
nko
et
a
l.
[
2
1
]
ass
ess
ed
th
e
p
er
f
o
r
m
an
ce
o
f
VDT
N
r
o
u
tin
g
p
r
o
to
c
o
ls
in
a
cr
o
s
s
r
o
ad
s
ce
n
ar
io
.
T
h
e
y
ev
al
u
ated
th
e
s
p
ec
if
ic
d
y
n
am
ics
o
f
u
s
er
m
o
b
ilit
y
an
d
th
eir
im
p
ac
t
o
n
DT
N
p
r
o
to
c
o
l
p
er
f
o
r
m
an
ce
.
Ma
d
a
m
o
r
i
et
a
l.
[
2
2
]
u
s
ed
DT
Ns
as
a
b
ac
k
b
o
n
e
f
o
r
l
o
w
-
co
s
t
s
m
ar
t
city
in
f
r
astru
ctu
r
e,
as
an
alter
n
ativ
e
to
r
ely
in
g
o
n
ex
p
en
s
iv
e
ce
llu
lar
o
r
W
i
-
Fi
co
n
n
ec
tiv
ity
f
o
r
I
o
T
d
ev
ices.
Fu
r
th
er
r
esear
ch
is
n
ee
d
ed
to
f
u
lly
u
n
d
e
r
s
tan
d
f
ac
t
o
r
s
s
u
ch
as
p
r
ed
ictab
ilit
y
,
s
p
e
ed
,
an
d
d
is
tr
ib
u
tio
n
o
f
h
u
m
a
n
m
o
v
em
en
t
with
in
I
o
T
ec
o
s
y
s
tem
s
.
T
h
e
wo
r
k
o
f
A
g
u
s
s
alim
et
a
l.
[
2
3
]
ex
am
i
n
ed
th
e
p
er
f
o
r
m
an
ce
o
f
s
ev
er
al
DT
N
r
o
u
tin
g
p
r
o
to
co
l
s
in
a
s
m
ar
t
city
s
ce
n
ar
io
f
o
r
Su
r
ab
ay
a,
I
n
d
o
n
esia.
T
h
e
s
tu
d
y
ca
lled
f
o
r
m
o
r
e
co
m
p
r
eh
e
n
s
iv
e
test
in
g
an
d
an
aly
s
is
.
Oth
er
s
tu
d
ies
s
u
ch
as
th
e
o
n
e
p
er
f
o
r
m
ed
b
y
E
r
et
a
l.
[
2
4
]
ex
p
lo
r
ed
th
e
u
s
e
o
f
VDT
Ns
f
o
r
d
ata
ag
g
r
e
g
atio
n
in
s
m
ar
t
cities,
ex
ten
d
in
g
th
e
s
co
p
e
b
ey
o
n
d
v
e
h
icle
-
b
ased
ap
p
licatio
n
s
.
Ag
u
s
s
alim
an
d
Pu
tr
a
[
2
5
]
s
u
g
g
ested
a
Su
r
ab
ay
a
Sm
ar
t
C
ity
s
ce
n
ar
io
u
tili
zin
g
VDT
N
as
a
lo
w
-
co
s
t
s
tr
ateg
y
f
o
r
d
ata
co
llectio
n
.
T
h
e
a
u
th
o
r
s
im
p
r
o
v
ed
th
e
r
o
u
ti
n
g
p
r
o
to
co
l,
s
u
ch
as
s
p
r
ay
an
d
h
o
p
d
is
tan
ce
(
SNHD)
,
wh
ich
is
s
ig
n
if
ican
tly
u
s
ed
in
s
m
ar
t
city
im
p
lem
en
tatio
n
.
T
h
e
s
tu
d
y
o
f
Go
a
et
a
l.
[
2
6
]
im
p
r
o
v
ed
t
h
e
s
p
r
ay
an
d
wait
r
o
u
tin
g
p
r
o
t
o
co
l
t
o
ad
d
r
ess
tr
af
f
ic
task
s
in
u
r
b
an
s
ce
n
ar
io
s
.
T
h
e
wo
r
k
ev
alu
ated
th
e
p
r
o
p
o
s
ed
o
p
tim
izatio
n
o
n
ly
o
n
t
h
e
ON
E
p
latf
o
r
m
,
with
o
u
t
co
n
s
id
er
i
n
g
o
t
h
er
s
im
u
latio
n
en
v
ir
o
n
m
en
ts
o
r
r
ea
l
-
wo
r
ld
d
ep
lo
y
m
e
n
ts
.
Fin
ally
,
b
ased
o
n
o
u
r
e
x
ten
s
iv
e
in
v
esti
g
atio
n
o
f
t
h
e
liter
atu
r
e,
we
f
o
u
n
d
th
at
th
e
r
e
is
a
lack
o
f
s
tu
d
ies
th
at
p
r
o
v
id
e
s
u
f
f
icien
t
k
n
o
wle
d
g
e
o
r
g
u
id
e
in
f
o
r
m
atio
n
o
n
t
h
e
s
elec
tio
n
o
f
th
e
m
o
s
t
s
u
itab
le
r
o
u
tin
g
p
r
o
to
c
o
l
alo
n
g
s
id
e
th
eir
p
ar
am
eter
s
tu
n
in
g
f
o
r
s
m
ar
t
ca
m
p
u
s
ap
p
licatio
n
s
as
well
as
o
n
th
e
d
esig
n
o
f
th
e
ap
p
r
o
p
r
i
ate
in
f
r
astru
ctu
r
e
to
im
p
lem
en
t
th
ese
ap
p
licatio
n
s
.
T
h
e
liter
atu
r
e
h
as
f
o
cu
s
ed
o
n
th
e
g
en
er
al
im
p
lem
en
tatio
n
s
an
d
co
m
p
ar
is
o
n
s
o
f
r
o
u
tin
g
p
r
o
to
c
o
ls
.
T
h
e
co
n
tr
i
b
u
tio
n
s
o
f
th
is
r
esear
ch
ar
e:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
7
6
I
n
t J I
n
f
&
C
o
m
m
u
n
T
ec
h
n
o
l
,
Vo
l.
14
,
No
.
3
,
Dec
em
b
er
20
25
:
1
0
5
6
-
1
0
7
1
1058
−
Dev
elo
p
r
ea
l
-
wo
r
l
d
s
im
u
latio
n
s
wh
er
e
th
e
d
esig
n
o
f
s
m
ar
t
ca
m
p
u
s
is
a
d
o
p
tab
le
to
s
tu
d
y
t
h
e
s
elec
tio
n
o
f
th
e
m
o
s
t a
p
p
r
o
p
r
iate
p
r
o
to
c
o
ls
f
o
r
s
m
ar
t c
am
p
u
s
.
−
Pro
v
id
e
k
n
o
wled
g
e
g
u
i
d
e
f
o
r
d
esig
n
in
g
s
m
ar
t
ca
m
p
u
s
in
f
r
astru
ctu
r
e
b
y
s
im
u
latin
g
r
ea
l
s
ce
n
ar
io
s
an
d
tu
n
in
g
all
p
ar
am
eter
s
r
elate
d
to
th
r
ee
r
o
u
tin
g
p
r
o
to
co
ls
;
s
p
r
ay
an
d
wait,
B
S
W
,
an
d
p
r
o
b
a
b
ilis
tic
f
lo
o
d
in
g
.
T
h
is
d
o
cu
m
e
n
t
is
o
r
g
a
n
ized
as
:
Sectio
n
2
d
escr
ib
es
th
e
r
esear
ch
m
eth
o
d
o
lo
g
y
a
n
d
its
d
etail
s
.
Sectio
n
3
p
r
esen
ts
th
e
ex
p
er
im
en
tal
r
e
s
u
lts
an
d
d
is
cu
s
s
in
g
th
em
.
T
h
e
wh
o
le
wo
r
k
is
co
n
clu
d
e
d
in
s
ec
tio
n
4.
2.
RE
S
E
ARCH
M
E
T
H
O
D
2
.
1
.
Sim
ula
t
i
o
n
env
iro
m
ent
T
h
e
ca
m
p
u
s
o
f
th
e
Un
iv
er
s
ity
o
f
Mo
s
u
l
(
USC
-
Mo
s
u
l)
is
ad
o
p
ted
to
i
m
p
lem
en
t
th
e
s
ce
n
ar
io
s
o
f
th
is
s
tu
d
y
.
T
h
is
p
ar
t
o
f
ca
m
p
u
s
i
n
clu
d
es
3
0
d
if
f
e
r
en
t
b
u
ild
in
g
s
d
is
tr
ib
u
ted
o
v
e
r
an
a
r
ea
esti
m
ated
at
1
s
q
u
a
r
e
k
ilo
m
eter
as
s
h
o
wn
in
Fig
u
r
e
1
.
T
h
e
Fig
u
r
e
s
1
(
a
)
-
1
(
c)
co
n
ta
in
s
in
f
o
r
m
atio
n
ab
o
u
t
th
e
b
u
il
d
in
g
s
,
th
eir
f
lo
o
r
s
,
th
e
n
u
m
b
er
o
f
s
tatic/m
o
b
ile
s
en
s
o
r
s
(
e.
g
.
,
s
tu
d
en
ts
,
f
ac
u
lties
,
an
d
s
taf
f
wh
o
u
s
e
th
e
b
u
il
d
in
g
)
.
I
t
s
h
o
u
ld
b
e
m
en
tio
n
ed
th
at
ea
c
h
p
er
s
o
n
i
n
th
e
ca
m
p
u
s
ca
r
r
ies
a
s
m
ar
tp
h
o
n
e
th
at
co
n
tain
s
s
en
s
o
r
s
th
a
t
en
ab
le
th
em
to
u
s
e
th
e
s
m
ar
t
ca
m
p
u
s
s
er
v
ices
an
d
ap
p
licatio
n
s
.
Mo
r
eo
v
er
,
Fig
u
r
e
2
d
ep
icts
th
e
lo
ca
tio
n
s
o
f
th
e
b
u
ild
in
g
s
o
n
th
e
ca
m
p
u
s
m
a
p
.
T
h
e
p
o
licy
o
f
t
h
e
Un
iv
e
r
s
ity
o
f
Mo
s
u
l
r
eq
u
ir
es
th
at
ea
ch
b
u
ild
i
n
g
b
e
ac
c
o
m
p
an
ied
b
y
a
f
ix
ed
n
u
m
b
er
o
f
s
tatic
s
en
s
o
r
s
s
u
ch
as
f
ir
e
d
etec
to
r
s
,
air
q
u
ali
ty
s
en
s
o
r
s
,
ac
ce
s
s
co
n
tr
o
l
s
en
s
o
r
s
,
tem
p
er
atu
r
e
s
en
s
o
r
s
,
h
u
m
id
ity
s
en
s
o
r
s
,
an
d
en
er
g
y
m
o
n
ito
r
i
n
g
s
en
s
o
r
s
,
wh
ich
ar
e
d
ep
lo
y
ed
b
ased
o
n
th
e
s
ize
an
d
n
u
m
b
er
o
f
f
lo
o
r
s
o
f
ea
c
h
b
u
ild
in
g
.
All
th
e
in
f
o
r
m
atio
n
i
n
Fig
u
r
e
1
w
as
o
b
tain
ed
f
r
o
m
th
e
I
T
team
r
esp
o
n
s
ib
le
f
o
r
th
e
ca
m
p
u
s
n
etwo
r
k
in
f
r
astru
ct
u
r
e
.
(
a)
(
b
)
(
c)
Fig
u
r
e
1
.
USC
-
m
o
s
u
l
b
u
ild
i
n
g
s
an
d
s
tatis
tics
ab
o
u
t th
e
f
lo
o
r
s
,
an
d
th
e
n
u
m
b
e
r
o
f
d
y
n
a
m
ic/s
tatic
s
en
s
o
r
s
:
(
a)
f
lo
o
r
s
,
(
b
)
s
tatic
s
en
s
o
r
,
an
d
(
c)
m
o
b
ile
s
en
s
o
r
Fig
u
r
e
2
.
USC
-
Mo
s
u
l
ca
m
p
u
s
ar
ea
o
f
s
tu
d
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J I
n
f
&
C
o
m
m
u
n
T
ec
h
n
o
l
I
SS
N:
2252
-
8
7
7
6
P
a
r
a
mete
r
-
o
p
timiz
ed
r
o
u
tin
g
p
r
o
to
co
ls
fo
r
ta
r
g
eted
b
r
o
a
d
c
a
s
t m
ess
a
g
es in
s
ma
r
t
… (
K
a
r
a
m
M
h
eid
e
Al
-
S
o
fy
)
1059
2
.
2
.
Descript
io
n
o
f
s
m
a
rt
c
a
m
pu
s
s
ce
na
rio
s
I
n
th
is
s
ec
tio
n
,
th
e
m
o
s
t c
o
m
m
o
n
s
ce
n
ar
io
s
th
at
th
e
USC
-
Mo
s
u
l
is
tr
y
in
g
to
ad
o
p
t w
er
e
h
ig
h
lig
h
ted
:
Scen
ar
io
1
(
E
m
e
r
g
en
c
y
Sit
u
atio
n
)
:
I
n
th
e
ev
e
n
t
o
f
a
n
y
em
er
g
en
cy
o
n
ca
m
p
u
s
d
u
e
to
n
atu
r
al
d
is
aster
s
in
clu
d
in
g
f
ir
e,
f
lo
o
d
,
ea
r
th
q
u
a
k
e,
elec
tr
ical
h
az
a
r
d
o
u
s
,
o
r
ev
en
r
u
s
h
h
o
u
r
s
in
ar
r
iv
al/d
e
p
ar
tu
r
e
at
th
e
ca
m
p
u
s
g
ates
th
at
m
ay
o
b
s
tr
u
ct
th
e
m
o
v
em
en
t
o
f
p
eo
p
le.
Su
ch
s
itu
atio
n
s
m
ay
ca
u
s
e
co
n
f
u
s
io
n
a
n
d
co
m
m
u
n
icatio
n
f
ailu
r
e
as
it
f
r
eq
u
en
tly
r
ep
o
r
ted
.
I
n
th
is
ca
s
e,
th
e
u
n
iv
er
s
ity
o
f
f
icials
n
ee
d
to
e
x
p
lo
ite
t
h
e
MA
NE
T
n
etwo
r
k
t
o
s
en
d
n
o
tific
atio
n
s
to
u
s
er
s
to
r
em
ain
in
th
eir
c
o
lleg
es o
r
leav
e
in
ad
d
itio
n
to
o
r
g
an
izin
g
tr
af
f
ic.
Scen
ar
io
2
(
C
o
n
ten
t
D
is
s
em
i
n
atio
n
)
:
Du
e
to
th
e
lar
g
e
n
u
m
b
er
o
f
s
taf
f
an
d
s
tu
d
en
ts
,
ad
m
in
is
tr
ato
r
s
an
d
lectu
r
er
s
'
r
eso
r
t
to
d
is
s
em
in
atio
n
o
f
lar
g
e
f
iles
(
e.
g
.
,
s
o
f
t
war
e
u
p
d
ates,
s
ec
u
r
ity
ca
m
e
r
a
r
ec
o
r
d
in
g
s
,
an
d
ed
u
ca
tio
n
al
v
i
d
eo
s
)
ef
f
icien
tly
in
o
r
d
e
r
to
a
v
o
id
n
etwo
r
k
c
o
n
g
esti
o
n
an
d
r
ely
o
n
a
ce
n
tr
al
s
er
v
er
.
Scen
ar
io
3
(
Saf
ety
an
d
Secu
r
i
ty
)
:
T
o
en
h
a
n
ce
th
e
s
ec
u
r
ity
p
o
licy
in
ca
m
p
u
s
an
d
cr
ea
te
a
s
af
e
en
v
ir
o
n
m
e
n
t,
th
e
u
n
iv
e
r
s
ity
h
as
co
n
n
ec
ted
m
o
r
e
th
a
n
(
1
0
0
)
ca
m
e
r
as
d
is
tr
ib
u
ted
i
n
s
id
e
th
e
ca
m
p
u
s
a
n
d
at
th
e
m
ain
g
ates.
T
h
is
ac
ce
ler
a
tes
th
e
r
esp
o
n
s
e
to
em
er
g
en
cies
s
itu
atio
n
s
an
d
s
en
d
a
d
is
tr
ess
ca
l
l
to
s
ec
u
r
it
y
p
er
s
o
n
n
el
in
s
id
e
th
e
ca
m
p
u
s
as we
ll a
s
m
o
n
ito
r
in
g
g
u
ests
an
d
tr
ac
k
in
g
a
n
y
a
b
n
o
r
m
al
b
e
h
av
io
u
r
th
at
c
o
u
ld
t
h
r
ea
ten
th
e
s
af
ety
.
Scen
ar
io
4
(
An
n
o
u
n
ce
m
e
n
ts
)
:
T
h
e
ad
m
in
is
tr
atio
n
r
eso
r
ts
to
u
s
in
g
ad
v
e
r
tis
em
en
ts
to
s
en
d
s
p
ec
if
ic
in
f
o
r
m
atio
n
to
p
eo
p
le
in
s
id
e
a
b
u
ild
in
g
af
f
iliated
with
a
co
lleg
e
t
h
r
o
u
g
h
s
o
cial
an
n
o
u
n
ce
m
en
ts
d
ir
ec
ted
to
s
o
m
e
g
r
o
u
p
s
in
s
id
e
th
e
ca
m
p
u
s
,
wh
ich
ca
n
co
n
tr
ib
u
te
to
ef
f
ec
tiv
e
co
m
m
u
n
icatio
n
an
d
tar
g
etin
g
s
p
e
cif
ic
b
u
ild
in
g
s
with
r
elate
d
g
r
o
u
p
s
.
T
h
is
s
ce
n
ar
io
a
ls
o
in
clu
d
es sen
d
in
g
n
o
tific
atio
n
s
d
u
r
in
g
u
n
iv
er
s
ity
ev
en
ts
.
2
.
3
.
Set
t
ing
up
ex
perim
ent
s
T
h
e
s
ettin
g
s
o
f
th
e
p
r
o
p
o
s
ed
e
x
p
er
im
en
ts
ar
e
illu
s
tr
ated
as f
o
llo
ws:
−
R
o
u
tin
g
Pro
to
co
ls
:
T
h
r
ee
m
ai
n
r
o
u
tin
g
p
r
o
to
co
ls
ar
e
u
s
ed
:
a)
Pro
b
ab
ilis
tic
f
lo
o
d
in
g
:
T
h
is
p
r
o
to
co
l
s
tan
d
s
o
u
t
as
a
s
o
lu
tio
n
f
o
r
n
etwo
r
k
s
with
in
ter
m
itten
t
co
n
n
ec
tiv
ity
wh
er
e
th
er
e
is
n
o
g
u
ar
a
n
tee
o
f
th
e
p
o
s
s
ib
ilit
y
o
f
co
m
m
u
n
ic
atio
n
at
an
y
tim
e
b
etwe
en
n
o
d
es
b
ec
au
s
e
it
co
n
s
u
m
es
n
etwo
r
k
r
eso
u
r
ce
s
.
I
t
r
elies
o
n
th
e
p
r
in
cip
le
o
f
p
r
ed
ictab
ilit
y
o
f
d
eli
v
er
y
b
ased
o
n
p
r
e
-
d
eter
m
in
ed
p
r
o
b
ab
ilit
ies,
wh
ich
ca
n
en
h
an
ce
th
e
d
eliv
er
y
r
ate
o
f
m
ess
ag
e
an
d
m
in
im
ize
th
e
co
s
t
o
f
lo
w
-
lev
el
co
m
m
u
n
icatio
n
[
1
2
]
.
b)
Sp
r
ay
an
d
wait:
I
t
wo
r
k
s
lik
e
its
p
r
ed
ec
ess
o
r
in
n
etwo
r
k
s
w
ith
in
ter
m
itten
t
co
n
n
ec
tiv
ity
,
b
u
t
it
d
ep
e
n
d
s
o
n
a
s
tr
ateg
y
i
n
v
o
lv
i
n
g
two
p
h
ases
f
o
r
r
o
u
tin
g
m
ess
ag
es.
T
h
e
f
ir
s
t
is
ca
lled
Sp
r
ay
in
g
,
wh
er
e
th
e
s
o
u
r
ce
n
o
d
e
s
en
d
s
co
p
ies
o
f
th
e
m
ess
ag
e
with
a
p
r
e
-
d
ef
in
e
d
v
alu
e
(
L
)
to
r
an
d
o
m
ly
s
el
ec
ted
n
o
d
es
.
T
h
e
s
ec
o
n
d
is
ca
lled
W
ait,
wh
er
e
if
th
e
d
esti
n
atio
n
n
o
d
e
is
n
o
t
r
ea
c
h
ed
in
th
e
s
p
r
ay
i
n
g
p
h
ase,
t
h
e
n
o
d
e
th
at
h
as
a
co
p
y
o
f
th
e
m
ess
ag
e
f
o
r
war
d
s
it o
n
ly
to
its
d
esti
n
atio
n
d
ir
ec
tly
[
7
]
.
c)
B
in
ar
y
s
p
r
ay
a
n
d
wait:
s
im
ilar
to
its
p
r
ed
ec
ess
o
r
(
s
p
r
ay
a
n
d
wait)
in
ter
m
s
o
f
its
wo
r
k
in
g
s
tr
ateg
y
,
b
u
t
i
t
r
elies
o
n
b
in
ar
y
d
is
tr
ib
u
tio
n
.
T
h
at
is
,
wh
en
a
n
o
d
e
ca
r
r
y
i
n
g
c
o
p
ies
o
f
m
ess
ag
es
(
r
ec
eiv
ed
f
r
o
m
th
e
s
o
u
r
ce
n
o
d
e)
e
n
co
u
n
ter
s
an
o
th
er
n
o
d
e
th
at
d
o
es
n
o
t
ca
r
r
y
an
y
co
p
ies
it
s
en
d
s
h
alf
o
f
its
co
p
ies
to
th
e
n
ew
n
o
d
e
an
d
s
o
o
n
.
T
h
is
p
r
o
ce
s
s
co
n
tin
u
es
ev
er
y
tim
e
it
en
co
u
n
ter
s
a
n
ew
n
o
d
e
u
n
til
it
h
as
o
n
e
co
p
y
lef
t,
d
ir
ec
t tr
an
s
m
is
s
io
n
o
cc
u
r
s
to
th
e
d
esti
n
atio
n
at
t
h
is
m
o
m
en
t [
2
7
]
.
−
M
o
v
em
en
t
Patter
n
s
:
L
ev
y
Fli
g
h
t
is
th
e
m
o
b
ilit
y
p
atter
n
u
s
ed
in
th
is
wo
r
k
[
2
8
]
.
T
y
p
icall
y
,
th
is
m
o
d
el
m
ak
in
g
n
o
d
es
c
r
o
s
s
th
e
wo
r
k
in
g
en
v
ir
o
m
e
n
t
b
o
r
d
er
s
f
o
r
t
h
is
r
eseo
n
th
e
m
o
d
el
is
alter
ed
b
y
L
ev
y
Fli
g
h
t
with
E
x
p
o
n
en
tial
C
u
t
-
o
f
f
th
at
m
ak
e
th
e
n
o
d
es
to
m
o
v
e
i
n
s
id
e
th
e
e
n
v
ir
o
m
en
t.
C
o
n
s
eq
u
en
t
ly
,
th
is
m
o
d
e
l
is
b
est p
atter
n
f
o
r
th
is
r
esear
ch
th
at
r
ef
lect
th
e
m
o
b
ilit
y
o
f
s
taf
f
an
d
s
tu
d
en
ts
in
s
id
e
th
e
th
e
c
am
p
u
s
.
−
E
v
alu
atio
n
Me
tr
ics:
T
o
ev
alu
ate
th
e
ex
p
er
im
en
ts
p
er
f
o
r
m
a
n
ce
ca
r
r
ied
o
u
t
in
th
is
wo
r
k
,
th
r
ee
m
etr
ices
wer
e
u
s
ed
:
1
)
Fra
cti
on
-
co
v
er
ed
ar
ea
s
with
in
th
e
u
n
iv
e
r
s
ity
ar
e
co
v
e
r
ed
b
y
th
e
d
y
n
a
m
ic
n
o
d
es.
2
)
Nu
m
b
er
o
f
m
ess
ag
es
p
r
o
d
u
c
ed
b
y
n
o
d
es
in
a
s
im
u
latio
n
en
v
ir
o
n
m
en
t.
3
)
Fra
ctio
n
o
f
ac
k
n
o
wled
g
e
d
n
o
d
es,
wh
ich
is
th
e
n
u
m
b
er
o
f
n
o
d
es
r
ec
eiv
ed
m
ess
ag
es.
T
h
ese
m
etr
ics
o
f
f
e
r
an
u
n
d
er
s
ta
n
d
in
g
o
f
th
e
n
etwo
r
k
'
s
p
er
f
o
r
m
a
n
ce
,
m
ess
ag
e
d
eliv
er
y
ef
f
ec
tiv
e
n
ess
,
an
d
r
eso
u
r
ce
im
p
ac
t
o
n
n
o
d
es [
2
8
]
,
[
2
9
]
.
−
C
o
m
m
u
n
icatio
n
:
T
h
e
n
o
d
es
with
in
th
e
USC
-
Mo
s
u
l
u
s
e
W
i
-
Fi
tech
n
o
lo
g
y
f
o
r
c
o
m
m
u
n
i
ca
tio
n
wh
eth
er
s
tatic
o
r
d
y
n
am
ic.
Als
o
,
5
0
m
eter
s
is
p
r
o
p
o
s
ed
as
th
e
r
el
iab
le
co
m
m
u
n
icatio
n
r
an
g
e
b
etwe
en
n
o
d
es
wh
er
e
th
e
ch
a
n
n
els with
f
r
ee
n
o
is
e
an
d
co
m
m
u
n
icatio
n
i
n
a
f
r
ee
s
p
ac
e.
−
No
d
es
Dis
tr
ib
u
tio
n
:
T
h
e
Gau
s
s
ian
ap
p
r
o
ac
h
u
tili
ze
d
to
r
e
p
r
esen
t
f
ix
e
d
n
o
d
es
with
in
th
e
USC
-
Mo
s
u
l
ac
cu
r
ately
r
ev
ea
ls
th
e
ac
tu
al
d
is
tr
ib
u
tio
n
o
f
b
u
ild
in
g
s
o
n
th
e
ca
m
p
u
s
,
as
illu
s
tr
ated
in
Fig
u
r
e
1
.
Similar
ly
,
th
is
ap
p
r
o
ac
h
is
ap
p
lied
to
th
e
d
is
tr
ib
u
tio
n
o
f
p
eo
p
le
o
n
th
e
ca
m
p
u
s
.
R
ath
er
th
an
b
ein
g
co
n
ce
n
tr
ated
i
n
o
n
e
lo
ca
tio
n
,
th
e
n
o
d
es
in
USC
-
Mo
s
u
l
ar
e
s
p
r
ea
d
ac
r
o
s
s
v
ar
io
u
s
in
d
iv
id
u
al
p
lace
s
th
at
a
p
p
r
o
x
im
ately
ad
h
e
r
e
to
a
Ga
u
s
s
ian
d
is
tr
ib
u
tio
n
[
3
0
]
,
[
3
1
]
.
2
.
4
.
E
x
perim
ent
f
e
a
t
ures
T
h
e
s
im
u
lato
r
th
at
is
u
s
ed
f
o
r
s
im
u
latin
g
th
e
USC
-
Mo
s
u
l
is
NetL
o
g
o
.
Mo
r
e
o
v
er
,
th
e
Un
i
v
er
s
ity
o
f
Mo
s
u
l
en
v
ir
o
n
m
en
t
is
s
im
u
lated
in
ter
m
s
o
f
d
im
en
s
io
n
s
,
n
o
d
e
m
o
b
ilit
y
,
an
d
r
o
u
tin
g
s
tr
at
eg
y
,
in
ad
d
itio
n
to
ad
ju
s
tin
g
th
e
p
a
r
am
eter
s
an
d
o
th
er
d
etails
o
f
t
h
e
s
im
u
lato
r
as
s
h
o
wn
in
T
ab
les
1
a
n
d
2
.
I
t
is
wo
r
th
n
o
tin
g
th
at
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
7
6
I
n
t J I
n
f
&
C
o
m
m
u
n
T
ec
h
n
o
l
,
Vo
l.
14
,
No
.
3
,
Dec
em
b
er
20
25
:
1
0
5
6
-
1
0
7
1
1060
in
th
is
s
tu
d
y
,
th
r
ee
s
ce
n
ar
i
o
s
wer
e
s
im
u
lated
wh
er
e
ea
ch
s
ce
n
ar
io
u
s
ed
o
n
e
o
f
th
e
p
r
e
v
io
u
s
ly
m
e
n
tio
n
ed
r
o
u
tin
g
p
r
o
t
o
co
ls
(
p
r
o
b
a
b
ilis
t
ic
f
lo
o
d
in
g
,
s
p
r
a
y
an
d
wait,
an
d
b
in
ar
y
s
p
r
ay
a
n
d
wait
)
r
esp
ec
tiv
ely
with
ch
an
g
in
g
th
e
v
alu
e
o
f
th
e
p
ar
a
m
eter
(
δ
=
0
.
1
,
0
.
5
,
0
.
9
)
r
esp
e
ctiv
ely
in
t
h
e
f
i
r
s
t
s
ce
n
ar
io
.
As
f
o
r
t
h
e
s
ec
o
n
d
a
n
d
th
ir
d
s
ce
n
ar
io
s
,
t
h
e
p
ar
am
eter
(
L
=
3
,
5
,
7
,
1
0
,
2
0
)
was
ch
an
g
ed
r
esp
ec
tiv
ely
as
well.
No
te
th
at
ea
ch
s
ce
n
a
r
io
was
r
u
n
f
o
r
3
0
tim
es
wh
e
n
m
ak
in
g
ea
ch
c
h
an
g
e
.
Fo
r
r
ap
id
im
p
lem
e
n
tatio
n
o
f
th
es
e
ex
p
er
im
e
n
ts
,
th
e
d
is
tr
ib
u
ted
p
r
o
ce
s
s
in
g
p
r
in
cip
l
e
was
ac
tiv
ated
,
wh
ich
en
a
b
le
s
th
e
s
im
u
lato
r
to
d
is
tr
ib
u
te
t
h
e
lo
ad
s
o
n
t
h
e
C
PU
co
r
es
o
f
th
e
wo
r
k
s
tatio
n
s
.
Fin
ally
,
th
e
r
esu
lts
ar
e
s
to
r
ed
in
t
h
e
f
o
r
m
o
f
.
C
SV
f
iles
an
d
(
R
lan
g
u
ag
e)
ar
e
u
s
ed
to
p
lo
t th
e
r
esu
lts
.
T
ab
le
1
.
Sp
ec
if
icatio
n
s
o
f
th
e
ex
p
er
im
en
tal
s
etu
p
f
o
r
s
im
u
lat
in
g
th
e
USC
-
m
o
s
u
l
I
t
e
m
V
a
l
u
e
S
t
a
t
i
c
n
o
d
e
s (S
N
)
4
0
5
M
o
b
i
l
e
n
o
d
e
s
(
M
N
)
4
2
1
9
S
N
R
a
n
g
e
o
f
c
o
mm
u
n
i
c
a
t
i
o
n
Wi
-
F
i
(
5
0
m)
M
N
R
a
n
g
e
o
f
c
o
mm
u
n
i
c
a
t
i
o
n
Wi
-
F
i
(
5
0
m)
S
N
d
i
s
t
r
i
b
u
t
i
o
n
La
t
t
i
c
e
d
e
p
l
o
y
me
n
t
M
N
d
i
s
t
r
i
b
u
t
i
o
n
N
o
r
mal
(
G
a
u
ss
i
a
n
)
d
e
p
l
o
y
me
n
t
R
o
u
t
i
n
g
p
r
o
t
o
c
o
l
s
P
r
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b
a
b
i
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P
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t
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o
f
m
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v
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m
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n
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s f
o
r
M
N
Le
v
y
f
l
i
g
h
t
w
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h
e
x
p
o
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n
t
i
a
l
c
u
t
o
f
f
F
r
e
q
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e
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c
y
o
f
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x
e
c
u
t
i
o
n
30
T
ab
le
2
.
Par
am
eter
t
u
n
in
g
o
f
t
h
e
ex
p
er
im
e
n
ts
P
a
r
a
me
t
e
r
V
a
l
u
e
D
e
scri
p
t
i
o
n
D
e
l
t
a
0
.
1
,
0
.
5
,
0
.
9
P
r
o
b
a
b
i
l
i
st
i
c
f
l
o
o
d
i
n
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a
d
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u
st
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a
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s t
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3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Resul
t
s
T
h
r
ee
m
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ex
p
e
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im
en
ts
wer
e
d
esig
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ed
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o
n
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f
o
r
ea
ch
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to
co
l,
b
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o
n
th
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co
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s
id
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d
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n
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s
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e
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u
tp
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lts
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ex
p
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en
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3
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u
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s
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c
ed
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s
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ate
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f
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d
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an
d
p
r
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v
id
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a
lu
ab
le
in
s
ig
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ts
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to
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tr
al
te
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en
cy
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s
p
r
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d
,
an
d
s
k
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ata
as
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en
r
ich
with
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etter
u
n
d
er
s
t
an
d
in
g
o
f
th
e
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v
er
all
p
e
r
f
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m
an
ce
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v
ar
iab
ilit
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o
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ex
p
er
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m
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tal
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n
d
itio
n
s
.
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h
e
an
aly
s
is
ap
p
r
o
ac
h
o
f
th
is
wo
r
k
en
ab
les
to
d
r
aw
m
ea
n
in
g
f
u
l
co
n
cl
u
s
io
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s
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d
id
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tify
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ar
ea
s
th
at
war
r
a
n
t f
u
r
th
er
in
v
esti
g
atio
n
th
e
ex
p
e
r
im
en
ts
(
as
o
b
s
er
v
ed
later
in
t
h
is
s
ec
tio
n
)
.
T
h
e
r
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lts
o
f
th
e
ex
p
er
im
en
ts
f
o
r
th
e
im
p
lem
en
ted
p
r
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to
co
ls
B
SW
,
s
p
r
ay
an
d
wait,
an
d
p
r
o
b
a
b
ilis
tic
ar
e
s
u
m
m
ar
iz
ed
i
n
T
ab
le
3
aim
i
n
g
at
g
iv
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n
g
an
o
v
er
all
v
iew
o
f
th
e
b
e
h
av
io
r
a
n
d
th
en
ta
k
e
m
o
r
e
in
s
ig
h
t
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n
th
e
e
x
p
er
im
e
n
ts
,
th
e
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ar
am
eter
L
d
ea
lt
with
(
s
p
r
a
y
an
d
wait
an
d
B
SW
p
r
o
to
co
l
s
)
,
wh
ile
d
elta
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a
p
ar
am
eter
th
at
d
ea
lt
with
p
r
o
b
ab
ilis
tic
p
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co
l
.
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h
e
two
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ar
am
et
er
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wer
e
in
v
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lv
ed
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ex
p
lain
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eir
im
p
ac
t
o
n
th
e
b
eh
a
v
io
r
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f
th
e
p
r
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to
c
o
ls
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n
a
d
d
itio
n
,
th
r
ee
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etr
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r
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tak
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in
to
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u
n
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p
ar
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n
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o
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d
er
t
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m
ea
s
u
r
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th
e
p
er
f
o
r
m
an
ce
o
f
th
e
n
etwo
r
k
;
1
)
th
e
n
u
m
b
e
r
o
f
m
ess
ag
es
co
n
s
u
m
ed
th
a
t
wer
e
co
p
ied
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d
d
is
tr
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ted
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r
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s
s
th
e
n
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k
.
2
)
th
e
p
lace
s
co
v
er
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d
with
co
m
m
u
n
icatio
n
s
.
3
)
Ack
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o
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es
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ich
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p
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ab
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o
f
r
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eiv
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k
n
o
wled
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m
en
t
(
A
C
K)
,
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ich
ca
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b
e
ex
p
r
ess
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as
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p
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ce
n
tag
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o
f
n
o
d
es
p
ar
ticip
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g
in
th
e
tr
a
n
s
m
is
s
io
n
.
Fin
ally
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th
e
tim
e
o
f
f
u
ll
co
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v
e
r
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ce
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in
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r
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r
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in
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r
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ir
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th
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ex
p
er
im
en
ts
.
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s
h
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in
T
ab
le
3
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f
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r
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SW
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u
m
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ile
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r
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r
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3
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n
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m
b
er
o
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r
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ag
e
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eliv
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a
0
.
9
.
A
s
t
h
e
p
r
o
b
a
b
i
l
i
s
ti
c
p
r
o
t
o
c
o
l
r
e
q
u
i
r
es
le
s
s
a
m
o
u
n
t
o
f
t
i
m
e
c
o
m
p
a
r
e
d
to
o
t
h
e
r
p
r
o
t
o
c
o
l
s
,
i
t
i
m
p
o
s
e
d
a
h
i
g
h
e
r
o
v
e
r
h
e
a
d
o
n
t
h
e
n
e
t
w
o
r
k
t
h
a
n
B
SW
a
n
d
s
p
r
a
y
a
n
d
w
a
i
t
.
T
ab
le
3
.
T
h
e
p
ea
k
o
b
s
er
v
atio
n
o
f
th
e
r
esu
lts
P
a
r
a
me
t
e
r
s
M
e
ss
a
g
e
s
F
r
a
c
t
i
o
n
o
f
p
l
a
c
e
s
c
o
v
e
r
e
d
F
r
a
c
t
i
o
n
o
f
n
o
d
e
s
a
c
k
n
o
w
l
e
d
g
e
d
T
i
m
e
f
u
l
l
c
o
n
v
e
r
g
e
n
c
e
A
v
e
r
a
g
e
T
i
me
(
h
o
u
r
)
B
i
n
a
r
y
s
p
r
a
y
a
n
d
w
a
i
t
L3
4
4
8
0
.
9
9
9
8
0
.
1
4
5
5
2
9
5
.
2
2
9
5
.
3
L5
6
3
6
1
0
.
1
7
2
9
2
3
8
.
5
2
8
0
.
0
2
L7
8
7
6
1
0
.
2
2
0
9
2
6
6
3
0
0
L1
0
9
3
6
1
0
.
2
2
4
8
2
0
2
.
0
2
2
4
1
L2
0
1
2
7
1
0
.
9
9
9
8
0
.
2
8
9
5
2
3
4
.
3
2
3
4
.
6
S
p
r
a
y
a
n
d
w
a
i
t
L3
5
0
2
1
0
.
1
6
2
8
2
8
9
.
2
3
9
6
.
8
L5
7
2
0
1
0
.
1
9
4
5
2
6
1
.
1
6
3
4
9
.
3
L7
8
5
6
0
.
9
9
9
9
0
.
2
1
6
2
2
7
5
.
6
2
7
6
.
4
2
L1
0
9
9
0
0
.
9
9
9
4
0
.
2
3
7
8
2
3
3
2
6
0
L2
0
1
2
6
7
0
.
9
9
9
4
0
.
2
9
0
8
1
6
3
.
2
1
6
3
.
5
P
r
o
b
a
b
i
l
i
st
i
c
D
e
l
t
a
0
.
1
3
8
7
6
0
.
9
2
8
1
0
.
8
4
7
.
7
8
7
.
7
8
D
e
l
t
a
0
.
5
3
7
6
7
0
.
9
0
2
8
0
.
8
1
5
4
.
4
6
4
.
4
6
D
e
l
t
a
0
.
9
3
5
6
5
0
.
8
9
1
9
0
.
7
7
2
3
.
8
6
3
.
8
6
Fig
u
r
e
3
d
ep
icts
th
e
b
en
c
h
m
a
r
k
in
g
o
f
th
e
B
SW
p
r
o
to
co
l
.
I
t
also
h
ig
h
lig
h
ts
th
e
av
er
ag
e
m
ax
im
u
m
m
ess
ag
e
co
n
s
u
m
p
tio
n
,
th
e
av
er
ag
e
m
ax
im
u
m
co
v
er
ed
a
r
ea
,
an
d
th
e
a
v
er
ag
e
m
ax
im
u
m
p
er
ce
n
tag
e
o
f
n
o
d
es
th
at
r
ec
eiv
ed
m
ess
ag
es,
r
esp
ec
tiv
ely
.
Fig
u
r
e
3
(
a)
r
e
f
lects
a
clea
r
in
v
er
s
e
r
elatio
n
s
h
ip
b
etwe
en
m
ess
ag
e
co
n
s
u
m
p
tio
n
an
d
t
h
e
tim
e
r
e
q
u
ir
ed
f
o
r
m
ess
ag
e
d
eliv
er
y
.
As
th
e
L
f
ac
to
r
in
c
r
ea
s
es,
m
ess
ag
e
co
n
s
u
m
p
tio
n
g
r
o
ws,
wh
ile
th
e
tim
e
o
f
m
ess
ag
e
d
eliv
er
y
d
ec
r
ea
s
es.
Ho
wev
er
,
an
ex
clu
s
io
n
was
o
b
s
er
v
e
d
at
L
=7
,
wh
er
e
th
e
p
r
o
to
co
l
s
h
o
wed
a
d
e
v
iatio
n
f
r
o
m
its
ty
p
ical
b
eh
av
io
r
.
T
h
is
an
o
m
aly
s
u
g
g
ests
th
at
asp
ec
t
s
s
u
ch
as
n
etwo
r
k
d
y
n
am
ics
o
r
n
o
d
e
d
is
tr
ib
u
tio
n
m
ig
h
t
h
av
e
im
p
ac
te
d
th
e
m
ess
ag
e
d
eliv
er
y
p
r
o
ce
s
s
.
Desp
ite
th
e
in
cr
ea
s
e
in
th
e
n
u
m
b
er
o
f
m
ess
ag
es,
th
e
tim
e
tak
en
also
in
cr
ea
s
ed
f
o
r
two
r
ea
s
o
n
s
:
T
h
e
f
ir
s
t
r
ea
s
o
n
is
th
e
m
o
v
em
en
t p
atter
n
s
ch
ar
ac
ter
is
tic
at
th
e
USC
,
an
d
th
e
s
ec
o
n
d
is
th
e
ch
allen
g
e
o
f
lo
ca
tin
g
an
a
d
jace
n
t
n
o
d
e
th
at
ass
is
t
s
in
r
elay
in
g
th
e
m
ess
ag
e.
Ad
d
itio
n
ally
,
th
er
e
is
a
d
ec
lin
e
in
th
e
r
ate
o
f
m
ess
ag
e
in
cr
ea
s
e
lik
en
ed
to
th
e
in
itial
s
tar
tin
g
p
o
in
t.
Fo
r
ex
am
p
le,
wh
en
ch
a
n
g
in
g
t
h
e
L
f
ac
t
o
r
f
r
o
m
(
3
to
7
)
th
e
n
u
m
b
e
r
o
f
m
ess
ag
es
in
cr
ea
s
es
b
y
d
o
u
b
le,
wh
ile
ch
an
g
in
g
th
e
f
ac
to
r
f
r
o
m
(
1
0
to
2
0
)
th
e
m
ess
ag
es
r
is
e
s
lig
h
tly
.
On
th
e
o
th
er
h
an
d
,
Fig
u
r
e
3
(
b
)
s
h
o
ws
th
at
th
e
ar
ea
s
c
o
v
er
e
d
b
y
co
m
m
u
n
icatio
n
s
ar
e
alm
o
s
t
f
u
lly
ac
h
iev
e
d
ac
r
o
s
s
all
ca
s
es
as
th
e
s
p
r
a
y
f
ac
to
r
(
L
)
in
cr
ea
s
es
f
r
o
m
3
to
2
0
.
T
h
is
co
m
es
at
th
e
ex
p
en
s
e
o
f
tim
e
,
as
a
h
ig
h
er
L
r
ed
u
ce
s
th
e
tim
e
n
ee
d
ed
f
o
r
f
u
ll
co
n
v
er
g
en
ce
,
as
in
d
icate
d
in
T
ab
le
4
.
Me
an
wh
ile,
Fig
u
r
e
3
(
c
)
s
h
o
ws
th
at
in
cr
ea
s
in
g
th
e
s
p
r
ay
f
ac
to
r
(
L
)
lead
s
to
a
g
r
ea
ter
n
u
m
b
er
o
f
r
ea
c
h
ab
le
AC
K
n
o
d
es
in
th
e
s
am
e
g
iv
en
tim
e
f
r
am
e.
I
t
ca
n
also
b
e
u
s
ef
u
l
in
u
n
d
er
s
tan
d
i
n
g
th
e
tr
ad
e
-
o
f
f
s
b
etwe
en
th
e
s
p
r
ay
f
ac
to
r
a
n
d
th
e
AC
K
n
o
d
e
d
is
s
em
in
atio
n
p
er
f
o
r
m
an
ce
in
a
b
in
ar
y
s
p
r
a
y
-
an
d
-
wait
p
r
o
t
o
co
l,
wh
ich
is
a
co
m
m
o
n
tech
n
iq
u
e
u
s
ed
in
d
ela
y
-
to
ler
an
t
n
et
wo
r
k
en
v
i
r
o
n
m
e
n
ts
.
T
h
e
n
u
m
b
er
o
f
AC
K
n
o
d
es
r
ea
ch
ed
is
a
n
im
p
o
r
tan
t
m
etr
ic,
as
it
in
d
icate
s
th
e
lev
el
o
f
m
ess
ag
e
d
eliv
e
r
y
co
n
f
ir
m
atio
n
in
th
e
n
etwo
r
k
.
Fig
u
r
e
4
d
ep
icts
th
e
b
e
n
ch
m
a
r
k
in
g
o
f
th
e
s
p
r
ay
a
n
d
wait
p
r
o
to
co
l
u
n
d
er
th
e
im
p
ac
t
o
f
ch
an
g
in
g
th
e
s
p
r
ay
f
ac
to
r
(
L
=
3
,
5
,
7
,
1
0
,
2
0
)
f
o
r
th
e
s
am
e
m
etr
ics
in
t
h
e
p
r
ev
io
u
s
p
r
o
to
c
o
l.
As
th
e
s
p
r
ay
f
ac
to
r
i
n
cr
ea
s
es
th
e
n
u
m
b
e
r
o
f
m
ess
ag
es
co
n
s
u
m
ed
in
cr
ea
s
es
as
s
h
o
wn
in
Fig
u
r
e
4
(
a
)
,
b
u
t
th
e
tim
e
r
eq
u
ir
ed
f
o
r
th
e
m
ess
ag
e
to
r
ea
ch
its
d
esti
n
atio
n
d
ec
r
e
ases
T
ab
le
4
.
Als
o
,
th
e
co
v
er
ag
e
p
lace
s
wer
e
alm
o
s
t
o
b
tai
n
ed
c
o
m
p
letely
as
s
h
o
wn
in
Fig
u
r
e
4
(
b
)
at
a
tim
e
r
ate
th
at
d
ec
r
ea
s
es
as
th
e
s
p
r
ay
f
ac
to
r
(
L
)
in
cr
ea
s
es.
Fig
u
r
e
4
(
c)
,
d
em
o
n
s
tr
ates
th
at
th
e
n
u
m
b
e
r
o
f
n
o
d
es
th
at
r
ec
eiv
e
d
ata
m
ess
ag
es
(
AC
K)
in
cr
ea
s
es
wh
en
s
p
r
ay
f
ac
to
r
(
L
)
in
cr
e
ases
.
T
h
is
b
eh
av
io
r
is
ex
p
ec
ted
b
ec
au
s
e,
with
m
o
r
e
n
o
d
es,
th
er
e
will
b
e
m
o
r
e
p
o
s
s
ib
le
p
ath
s
f
o
r
th
e
m
ess
ag
e
to
tr
av
el,
an
d
ev
e
n
tu
ally
will lea
d
to
m
o
r
e
m
ess
ag
e
d
u
p
licatio
n
a
n
d
p
o
ten
tial m
ess
ag
e
lo
s
s
.
Mo
r
eo
v
er
,
it
is
o
b
s
er
v
ed
th
at
th
e
B
SW
p
r
o
to
co
l
o
u
tp
e
r
f
o
r
m
s
th
e
s
p
r
ay
an
d
wait
p
r
o
to
co
l
in
two
way
s
;
First,
it
tak
es
le
s
s
t
im
e
to
r
o
u
te
th
e
m
ess
ag
e
to
its
d
es
tin
atio
n
,
d
u
e
to
th
e
b
i
n
ar
y
d
is
t
r
ib
u
tio
n
s
tr
ateg
y
it
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
7
6
I
n
t J I
n
f
&
C
o
m
m
u
n
T
ec
h
n
o
l
,
Vo
l.
14
,
No
.
3
,
Dec
em
b
er
20
25
:
1
0
5
6
-
1
0
7
1
1062
ad
o
p
ts
.
S
ec
o
n
d
,
t
h
e
n
u
m
b
e
r
o
f
n
o
d
es
r
ec
eiv
in
g
th
e
m
ess
ag
e
s
(
AC
K)
is
less
,
wh
ich
r
ed
u
ce
s
th
e
o
v
e
r
h
ea
d
an
d
co
n
s
u
m
p
tio
n
o
f
n
etwo
r
k
r
eso
u
r
ce
s
.
(
a)
(
b
)
(
c)
Fig
u
r
e
3
.
B
en
ch
m
ar
k
in
g
th
e
b
i
n
ar
y
s
p
r
a
y
an
d
wait
in
ter
m
s
o
f
:
(
a)
m
ess
ag
es,
(
b
)
USC
-
m
o
s
u
l
p
lace
s
co
v
er
e
d
,
an
d
(
c)
ac
k
n
o
wled
g
ed
n
o
d
es,
f
o
r
d
if
f
e
r
en
t v
al
u
es o
f
L
-
f
ac
to
r
(
a)
(
b
)
(
c)
Fig
u
r
e
4
.
B
en
ch
m
ar
k
in
g
th
e
s
p
r
ay
an
d
wait
p
r
o
to
co
ls
in
ter
m
s
o
f
in
ter
m
s
o
f
:
(
a)
m
ess
ag
e
s
,
(
b
)
USC
-
m
o
s
u
l
p
lace
s
co
v
er
ed
,
an
d
(
c)
ac
k
n
o
wled
g
ed
n
o
d
es,
f
o
r
d
if
f
e
r
en
t v
alu
es o
f
L
-
f
ac
to
r
Fig
u
r
e
5
d
ep
icts
th
e
p
r
o
b
a
b
i
lis
tic
f
lo
o
d
in
g
p
r
o
to
c
o
l
b
en
c
h
m
ar
k
in
g
.
T
h
er
e
f
o
r
e,
in
Fig
u
r
e
5
(
a)
an
in
v
er
s
e
r
elatio
n
s
h
ip
was
o
b
s
er
v
ed
b
etwe
en
in
cr
ea
s
in
g
th
e
f
ac
to
r
(
d
elta
=
0
.
1
,
0
.
5
,
0
.
9
)
an
d
th
e
n
u
m
b
e
r
o
f
m
ess
ag
es
co
n
s
u
m
ed
,
wh
ich
i
s
ex
p
ec
ted
b
ec
au
s
e
a
h
i
g
h
er
d
elta
v
alu
e
in
d
icate
s
a
h
ig
h
e
r
p
r
o
b
a
b
ilit
y
o
f
th
e
n
o
d
e
f
o
r
war
d
i
n
g
th
e
m
ess
ag
e.
T
h
e
in
c
r
ea
s
e
in
d
elta
v
al
u
e
was
ac
co
m
p
an
ied
b
y
a
d
ec
r
e
ase
in
th
e
co
v
e
r
ed
p
lace
s
o
b
tain
ed
an
d
th
e
n
u
m
b
er
o
f
n
o
d
es
th
at
r
ec
eiv
ed
d
ata
m
ess
ag
es
(
A
C
K)
as
s
h
o
wn
in
Fig
u
r
e
s
5
(
b
)
an
d
5(
c)
r
esp
ec
tiv
ely
,
wh
ich
r
ed
u
ce
s
th
e
o
v
er
h
ea
d
an
d
co
n
s
u
m
p
tio
n
o
f
n
etwo
r
k
r
eso
u
r
ce
s
.
Fin
ally
,
a
s
lig
h
t
in
cr
ea
s
e
in
d
elta
af
f
ec
ted
th
e
ti
m
e
m
etr
ic,
wh
ich
was r
ed
u
ce
d
b
y
h
alf
f
o
r
th
e
m
ess
ag
e
to
r
ea
ch
its
d
esti
n
atio
n
.
(
a)
(
b
)
(
c)
Fig
u
r
e
5
.
B
en
ch
m
ar
k
in
g
th
e
p
r
o
b
ab
ilis
tic
f
lo
o
d
in
g
in
ter
m
s
o
f
in
ter
m
s
o
f
:
(
a)
m
ess
ag
es,
(
b
)
USC
-
m
o
s
u
l
p
lace
s
co
v
er
ed
,
an
d
(
c)
ac
k
n
o
wled
g
ed
n
o
d
es
,
f
o
r
d
if
f
e
r
en
t v
alu
es o
f
d
elta
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J I
n
f
&
C
o
m
m
u
n
T
ec
h
n
o
l
I
SS
N:
2252
-
8
7
7
6
P
a
r
a
mete
r
-
o
p
timiz
ed
r
o
u
tin
g
p
r
o
to
co
ls
fo
r
ta
r
g
eted
b
r
o
a
d
c
a
s
t m
ess
a
g
es in
s
ma
r
t
… (
K
a
r
a
m
M
h
eid
e
Al
-
S
o
fy
)
1063
Fu
r
th
er
m
o
r
e
,
th
e
th
r
ee
r
o
u
tin
g
p
r
o
to
co
ls
ac
r
o
s
s
th
e
th
r
ee
m
etr
ics
wer
e
ev
alu
ated
.
Fig
u
r
es
6
to
1
4
p
r
esen
t
th
e
b
o
x
p
l
o
t
an
aly
s
is
f
o
r
all
ex
p
er
im
en
ts
co
n
d
u
cted
.
T
h
e
f
ig
u
r
es
s
h
o
w
m
u
ltip
le
-
c
o
lo
u
r
ed
b
ar
s
,
ea
c
h
r
ep
r
esen
tin
g
a
d
if
f
e
r
en
t
r
ep
lic
ate
(
R
1
,
R
2
3
,
R
1
0
,
etc.
)
,
wh
er
e
R
d
en
o
tes
a
r
u
n
,
f
o
r
ea
ch
ex
p
er
im
en
t.
T
h
e
y
-
ax
is
d
is
p
lay
s
th
e
v
alu
e
m
ea
s
u
r
ed
s
u
ch
as
th
e
n
u
m
b
er
o
f
m
ess
ag
es,
th
e
f
r
ac
tio
n
o
f
c
o
v
er
ed
p
lace
s
,
an
d
th
e
f
r
ac
tio
n
o
f
ac
k
n
o
wled
g
e
d
n
o
d
es,
wh
e
r
ea
s
th
e
x
-
ax
i
s
lis
t
s
th
e
d
if
f
er
en
t
ex
p
e
r
im
en
ts
.
T
h
is
ty
p
e
o
f
v
is
u
aliza
tio
n
allo
ws
f
o
r
a
co
m
p
ar
is
o
n
o
f
th
e
v
alu
es
ac
r
o
s
s
th
e
v
ar
io
u
s
r
ep
licates
an
d
ex
p
e
r
im
en
ts
.
As
ca
n
b
e
s
ee
n
in
th
e
f
o
llo
win
g
f
ig
u
r
e
s
,
all
r
u
n
s
co
n
tain
o
u
tlier
s
a
s
a
r
esu
lt
o
f
th
e
m
o
b
ili
ty
p
atter
n
u
s
e
d
in
th
e
ex
p
er
im
en
ts
.
Fig
u
r
es
6
(a
)
-
6(
e
)
,
Fig
u
r
es
7
(
a
)
-
7
(
e)
,
an
d
Fig
u
r
es
8
(a
)
-
8(
c)
s
h
o
w
th
e
b
o
x
p
l
o
t
o
f
th
e
n
u
m
b
er
o
f
d
ata
m
ess
ag
es
wh
en
v
ar
y
in
g
th
e
p
ar
am
eter
s
L
(
f
o
r
s
p
r
ay
a
n
d
wait)
an
d
d
elta
(
f
o
r
p
r
o
b
ab
i
lis
tic
f
lo
o
d
in
g
)
.
At
th
e
f
ir
s
t q
u
ar
tile
o
f
ea
ch
r
u
n
,
it is
an
ev
id
en
t th
at
th
e
p
er
f
o
r
m
an
ce
is
n
ea
r
ly
s
tab
le
wi
th
d
elay
in
s
p
r
ay
an
d
wait
an
d
b
in
ar
y
s
p
r
ay
a
n
d
wait.
T
h
is
is
r
ea
s
o
n
ab
le
b
ec
au
s
e
th
e
n
o
d
e
lo
ca
tio
n
o
n
th
e
m
ap
co
u
ld
b
e
f
ar
en
o
u
g
h
to
g
et
f
ast
m
ess
ag
es,
th
er
ef
o
r
e
t
h
e
s
im
u
latio
n
s
co
n
s
u
m
e
lo
n
g
er
tim
e
to
in
itiate
s
p
r
ea
d
in
g
m
ess
ag
es,
esp
ec
ially
with
n
o
in
te
r
m
ed
iate
n
o
d
es
t
o
tr
an
s
f
er
m
ess
ag
es.
Mo
r
e
o
v
er
,
th
e
f
ig
u
r
es
also
s
h
o
w
a
r
elativ
ely
d
if
f
er
en
t
n
u
m
b
er
o
f
m
ess
ag
es
f
o
r
t
h
e
s
am
e
p
r
o
to
co
l
p
ar
am
eter
s
.
T
h
is
is
a
n
o
r
m
al
s
itu
atio
n
co
n
s
id
er
in
g
th
e
r
o
u
tin
g
p
r
o
to
co
l
al
g
o
r
ith
m
.
So
m
e
ex
p
er
im
en
ts
f
o
r
ca
lcu
latin
g
m
e
s
s
ag
es
s
h
o
w
ch
ief
v
alu
es
f
o
r
at
least
o
n
e
o
f
th
e
r
ep
licates,
in
d
icatin
g
th
ey
m
ay
b
e
o
u
tlier
s
.
E
v
er
y
e
x
p
er
im
e
n
t
r
e
f
lects
d
if
f
er
en
t
lev
els
o
f
co
n
s
is
ten
cy
am
o
n
g
its
r
e
p
licates.
W
h
ile
s
o
m
e
r
ep
licat
es
s
h
o
w
tig
h
tly
clu
s
ter
ed
v
alu
es,
o
th
er
s
s
h
o
w
m
u
ch
g
r
ea
ter
v
ar
iatio
n
.
As
th
e
r
esu
lts
o
f
ce
r
tain
ex
p
er
im
en
ts
d
if
f
er
ed
ac
r
o
s
s
r
ep
licates,
it
m
ay
b
e
a
n
in
d
icatio
n
o
f
h
o
w
th
e
m
o
b
ilit
y
p
atter
n
a
f
f
ec
t
ed
th
e
ex
p
er
im
en
tal
c
o
n
d
itio
n
s
.
Similar
ly
,
Fig
u
r
es
9
(a
)
-
9
(
e)
,
Fig
u
r
es
1
0
(a
)
-
1
0
(
e
)
,
an
d
Fig
u
r
es
1
1
(a
)
-
11(
c)
s
h
o
w
th
e
f
r
ac
tio
n
s
o
f
co
v
er
ed
p
lace
s
in
t
h
e
USC
-
Mo
s
u
l
u
s
in
g
th
e
th
r
ee
r
o
u
tin
g
p
r
o
to
co
ls
wh
en
v
ar
y
i
n
g
t
h
e
p
a
r
a
m
eter
s
L
an
d
Delta.
Ho
wev
er
,
it
ca
n
b
e
o
b
s
er
v
ed
t
h
at
m
an
y
o
u
tlier
s
ar
e
s
h
o
wn
in
th
e
f
ig
u
r
es.
T
h
e
r
ea
s
o
n
b
e
h
in
d
th
is
b
eh
av
io
r
is
th
at
wh
en
th
e
s
im
u
latio
n
s
s
tar
t,
m
o
s
t
o
f
th
e
ar
ea
ar
e
n
o
t
r
ea
c
h
ed
b
y
th
e
n
o
d
es,
wh
ich
ca
u
s
es
m
o
s
t
o
f
th
e
ar
ea
s
n
o
t
co
v
er
e
d
.
A
d
if
f
er
en
t
p
atte
r
n
is
n
o
ticed
wh
en
test
in
g
th
e
v
ar
iatio
n
s
in
th
e
f
r
ac
tio
n
o
f
ac
k
n
o
wled
g
e
d
n
o
d
es
in
USC
-
Mo
s
u
l
,
as
illu
s
tr
ated
in
Fig
u
r
es
1
2
(a
)
-
1
2
(
e)
,
Fig
u
r
e
s
1
3
(a
)
-
1
3
(
e)
,
an
d
Fig
u
r
es
1
4
(a
)
-
1
4
(
c)
.
Fro
m
an
ap
p
licatio
n
p
er
s
p
ec
tiv
e,
th
e
f
r
ac
tio
n
o
f
ac
k
n
o
wled
g
ed
n
o
d
e
s
an
d
th
eir
r
esp
o
n
s
e
to
an
ev
e
n
t
in
d
icate
th
at
th
e
m
ess
ag
e
r
ea
ch
es
a
lar
g
er
p
o
r
tio
n
o
f
th
e
p
o
p
u
latio
n
.
Ho
w
ev
er
,
th
is
in
cr
ea
s
ed
s
h
a
r
in
g
m
ay
s
tr
ain
s
y
s
tem
ca
p
ac
ity
b
y
co
n
s
u
m
in
g
cr
itical
n
o
d
e
r
eso
u
r
ce
s
,
wh
ich
p
o
ten
tially
af
f
ec
ts
th
e
o
v
er
all
r
elia
b
ilit
y
an
d
r
esp
o
n
s
e
tim
e
o
f
th
e
s
y
s
tem
.
T
h
e
b
o
x
p
lo
t
r
ev
ea
ls
m
o
s
tly
s
tab
le
b
eh
a
v
io
u
r
wh
en
o
b
s
er
v
in
g
th
e
f
r
ac
tio
n
o
f
ac
k
n
o
wled
g
e
d
n
o
d
es
in
USC
-
Mo
s
u
l
.
W
h
ile
in
s
tab
ilit
y
ca
n
p
o
s
e
a
wea
k
n
ess
in
s
y
s
tem
d
es
ig
n
,
it
is
ess
en
tial
to
p
r
ed
ict
p
er
f
o
r
m
an
ce
an
d
p
r
e
p
ar
e
p
lan
s
ac
co
r
d
i
n
g
ly
.
On
th
e
o
th
er
h
an
d
,
th
is
v
ar
iab
ilit
y
als
o
p
r
o
v
id
es
v
alu
ab
le
in
s
ig
h
t in
to
th
e
p
r
ed
ictab
ilit
y
o
f
n
o
d
e
p
ar
ticip
atio
n
in
r
esp
o
n
s
es.
(
a)
(
b
)
(
c)
(
d
)
(
e)
Fig
u
r
e
6
.
Var
iatio
n
s
in
th
e
n
u
m
b
er
o
f
m
ess
ag
es sp
r
ea
d
in
U
SC
-
m
o
s
u
l
u
s
in
g
th
e
b
in
ar
y
s
p
r
ay
an
d
wait
f
o
r
3
0
r
u
n
s
,
wh
er
e
t
h
e
s
u
b
f
ig
u
r
es
:
(
a)
to
(
e)
c
o
r
r
esp
o
n
d
s
to
L
=3
,
5
,
7
,
1
0
,
an
d
2
0
r
esp
ec
tiv
ely
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
7
6
I
n
t J I
n
f
&
C
o
m
m
u
n
T
ec
h
n
o
l
,
Vo
l.
14
,
No
.
3
,
Dec
em
b
er
20
25
:
1
0
5
6
-
1
0
7
1
1064
T
h
is
en
ab
les
ea
r
ly
ass
es
s
m
en
t
o
f
th
e
n
etwo
r
k
'
s
m
ess
ag
e
tr
a
n
s
m
is
s
io
n
lo
ad
an
d
ch
an
n
el
u
tili
za
tio
n
,
o
f
f
er
in
g
a
clea
r
er
u
n
d
e
r
s
tan
d
i
n
g
o
f
th
e
p
o
ten
tial im
p
ac
t o
n
th
e
DT
N.
T
h
is
in
f
o
r
m
atio
n
s
u
p
p
o
r
ts
ev
alu
atin
g
th
e
s
ca
lab
ilit
y
an
d
ca
p
ac
ity
p
lan
n
in
g
r
eq
u
ir
ed
to
ac
c
o
m
m
o
d
at
e
th
e
an
ticip
ated
lo
ad
.
I
n
s
tab
ilit
y
ca
n
ch
allen
g
e
p
er
f
o
r
m
an
ce
p
r
ed
ictab
ilit
y
,
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u
t
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ep
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