International Journal of Sensors Wireless Communications and Control,
Journal Year:
2024,
Volume and Issue:
14(2), P. 122 - 133
Published: Jan. 22, 2024
Background:
Wireless
Sensor
Networks
(WSNs)
have
emerged
as
a
crucial
technology
for
various
applications,
but
they
face
lot
of
challenges
relevant
to
limited
energy
resources,
delayed
communications,
and
complex
data
aggregation.
To
address
these
issues,
this
study
proposes
novel
approaches
called
GAN-based
Clustering
LSTM-based
Data
Aggregation
(GCLD)
that
aim
enhance
the
performance
WSNs.
Methods:
The
proposed
GCLD
method
enhances
Quality
Service
(QoS)
WSN
by
leveraging
capabilities
Generative
Adversarial
(GANs)
Long
Short-Term
Memory
(LSTM)
method.
GANs
are
employed
clustering,
where
generator
assigns
cluster
assignments
or
centroids,
discriminator
distinguishes
between
real
generated
assignments.
This
adversarial
learning
process
refines
clustering
results.
Subsequently,
LSTM
networks
used
aggregation,
capturing
temporal
dependencies
enabling
accurate
predictions.
Results:
evaluation
results
demonstrate
superior
in
terms
delay,
PDR,
consumption,
accuracy
than
existing
methods.
Conclusion:
Overall,
significance
advancing
WSNs
highlights
its
potential
impact
on
applications.
Journal of Engineering and Applied Science,
Journal Year:
2024,
Volume and Issue:
71(1)
Published: Jan. 3, 2024
Abstract
Rapid
technological
advances
have
made
daily
life
easier
and
more
convenient
in
recent
years.
As
an
emerging
technology,
the
Internet
of
Things
(IoT)
facilitates
interactions
between
physical
devices.
With
advent
sensors
features
on
everyday
items,
they
become
intelligent
entities
able
to
perform
multiple
functions
as
services.
IoT
enables
routine
activities
intelligent,
deeper
communication,
processes
efficient.
In
dynamic
landscape
IoT,
effective
service
discovery
is
key
optimizing
user
experiences.
A
Quality
Service
(QoS)-aware
technique
proposed
this
paper
address
challenge.
Through
whale
optimization
genetic
algorithms,
our
method
aims
streamline
decision-making
selection.
The
bio-inspired
techniques
employed
approach
facilitate
services
efficiently
than
traditional
methods.
Our
results
demonstrate
superior
performance
regarding
reduced
data
access
time,
optimized
energy
utilization,
cost-effectiveness
through
comprehensive
simulations.
Journal of Engineering and Applied Science,
Journal Year:
2024,
Volume and Issue:
71(1)
Published: June 15, 2024
Abstract
The
effectiveness
and
longevity
of
IoT
infrastructures
heavily
depend
on
the
limitations
posed
by
communication,
multi-hop
data
transfers,
inherent
difficulties
wireless
links.
In
dealing
with
these
challenges,
routing,
transmission
procedures
are
critical.
Among
fundamental
concerns
attainment
energy
efficiency
an
ideal
distribution
loads
among
sensing
devices,
given
restricted
resources
at
disposal
devices.
To
meet
present
research
suggests
a
novel
hybrid
energy-aware
routing
approach
that
mixes
Particle
Swarm
Optimization
(PSO)
algorithm
fuzzy
clustering.
begins
clustering
to
initially
group
sensor
nodes
their
geographical
location
assign
them
clusters
determined
certain
probability.
proposed
method
includes
fitness
function
considering
consumption
distance
factors.
This
feature
guides
optimization
process
aims
balance
distance.
hierarchical
topology
uses
advanced
PSO
identify
cluster
head
nodes.
MATLAB
simulator
shows
our
outperforms
previous
approaches.
Various
metrics
have
demonstrated
significant
improvements
over
DEEC
LEACH.
reduces
52%
16%,
improves
throughput
112%
10%,
increases
packet
delivery
rates
83%
15%,
extends
network
lifespan
48%
27%,
respectively,
compared
LEACH
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: July 18, 2024
Abstract
The
Internet
of
Things
(IoT)
is
an
extensive
system
interrelated
devices
equipped
with
sensors
to
monitor
and
track
real
world
objects,
spanning
several
verticals,
covering
many
different
industries.
IoT's
promise
capturing
interest
as
its
value
in
healthcare
continues
grow,
it
can
overlay
on
top
challenges
dealing
the
rising
burden
chronic
disease
management
aging
population.
To
address
difficulties
associated
IoT-enabled
healthcare,
we
propose
a
secure
routing
protocol
that
combines
fuzzy
logic
Whale
Optimization
Algorithm
(WOA)
hierarchically.
suggested
method
consists
two
primary
approaches:
trust
strategy
WOA-inspired
clustering
methodology.
first
methodology
plays
critical
role
determining
trustworthiness
connected
IoT
equipment.
Furthermore,
WOA-based
framework
implemented.
A
fitness
function
assesses
likelihood
acting
cluster
heads.
This
formula
considers
factors
such
centrality,
range
communication,
hop
count,
remaining
energy,
trustworthiness.
Compared
other
algorithms,
proposed
outperformed
them
terms
network
lifespan,
energy
usage,
packet
delivery
ratio
by
47%,
58%,
17.7%,
respectively.
