People
who
are
unable
to
see
(blind)
uses
Braille
as
a
principal
mode
of
information
access
all
throughout
the
world.
Almost
every
country
has
adopted
"Braille"
system
standard
technique
obtaining
for
visually
impaired.
Tactile
signing,
Braille,
and
moon
some
unique
languages
deaf-blind
persons.
is
one
most
popular
modes
communication
among
these
options.
This
paper
provides
solution
that
includes
mechanism
bridging
gap
between
English
text
characters.
The
main
objective
work
develop
text-to-braille
conversion
using
Renesas
Microcontroller.
proposed
microcontroller
PC
convert
Text
format
an
average
person
impaired
communicate
with
each
other.
Results
show
efficient
accurate
conversion.
Applied Computational Intelligence and Soft Computing,
Journal Year:
2022,
Volume and Issue:
2022, P. 1 - 17
Published: Aug. 28, 2022
Fog
computing
domain
plays
a
prominent
role
in
supporting
time-delicate
applications,
which
are
associated
with
smart
Internet
of
Things
(IoT)
services,
like
healthcare
and
city.
However,
cloud
is
capable
standard
for
IoT
data
processing
owing
to
the
high
latency
restriction
cloud,
it
incapable
satisfying
needs
time-sensitive
applications.
The
resource
provisioning
allocation
process
fog-cloud
structure
considers
dynamic
alternations
user
necessities,
also
restricted
access
resources
fog
devices
more
challenging.
global
adoption
IoT-driven
applications
has
led
rise
structure,
permits
perfect
connection
mobile
edge
resources.
effectual
scheduling
application
tasks
environments
challenging
task
because
heterogeneity,
stochastic
behaviours,
network
hierarchy,
controlled
abilities,
mobility
elements
IoT.
deadline
most
significant
challenge
due
variations
requirement
parameters.
In
this
paper,
Mayfly
Taylor
Optimisation
Algorithm
(MTOA)
developed
model.
MTOA-based
Deep
Q-Network
(DQN)
showed
better
performance
energy
consumption,
service
level
agreement
(SLA),
computation
cost
0.0162,
0.0114,
0.0855,
respectively.
International Journal of Computer Network and Information Security,
Journal Year:
2023,
Volume and Issue:
15(4), P. 84 - 95
Published: Aug. 2, 2023
Load
balancing
plays
a
major
part
in
improving
the
performance
of
fog
computing,
which
has
become
requirement
layer
for
distributing
all
workload
equal
manner
amongst
current
Virtual
machines
(VMs)
segment.
The
distribution
load
is
complicated
process
as
it
consists
numerous
users
computing
environment.
Hence,
an
effectual
technique
called
Mutated
Leader
Algorithm
(MLA)
proposed
fogging
Firstly,
initialized
with
layer,
cloud
and
end
user
layer.
Then,
task
submitted
from
under
cluster
nodes.
Afterwards,
done
each
resources
VM
are
predicted
using
Deep
Residual
Network
(DRN).
accomplished
by
allocating
reallocating
to
VMs
based
on
resource
constraints
optimally
MLA.
Here,
needed
optimizing
objectives.
Lastly,
if
overloaded
then
jobs
pulled
associated
allocated
loaded
VM.
Thus
MLA
achieved
minimum
execution
time
1.472ns,
cost
$69.448
0.0003%
respectively.
Computers & Electrical Engineering,
Journal Year:
2024,
Volume and Issue:
119, P. 109506 - 109506
Published: July 26, 2024
Cloud
computing
has
revolutionized
the
way
businesses
and
organizations
manage
their
computational
workloads.
However,
massive
data
centers
that
support
cloud
services
consume
a
lot
of
energy,
making
energy
sustainability
critical
concern.
To
address
this
challenge,
article
introduces
an
innovative
approach
to
optimize
consumption
in
environments
through
knowledge
acquisition.
The
proposed
method
uses
Knowledge
Acquisition
version
Gray
Wolf
Optimizer
(KAGWO)
algorithm
collect
on
availability
use
renewable
within
centers,
contributing
improved
computing.
KAGWO
is
introduced
provide
systematic
for
addressing
complex
problems
by
integrating
global
optimization
principles,
enhancing
decision-making
processes
with
fewer
configuration
parameters.
This
conducts
comparative
analysis
between
Swarm
Intelligence
Approach
(KASIA)
Genetic
Algorithm
(Pittsburgh)
highlight
benefits
advantages
former.
By
comparing
performance
KAGWO,
Pittsburgh
KASIA
terms
sustainability,
study
offers
valuable
insights
into
effectiveness
knowledge-acquisition-based
algorithms
optimizing
usage
environments.
results
demonstrate
outperforms
offering
more
accurate
acquisition
capabilities,
resulting
enhanced
sustainability.
Overall,
demonstrates
substantial
improvements
ranging
from
0.53%
5.23%
over
previous
paper
baselines,
particular
significance
found
slightly
outperforming
new
small,
medium
large
scenarios.
International Journal of Emerging Technologies in Learning (iJET),
Journal Year:
2022,
Volume and Issue:
17(18), P. 261 - 274
Published: Sept. 21, 2022
The
Internet
of
Things
ecosystem
pertains
to
web-enabled
connected
devices
that
operate
built-in
processors
record,
send,
and
act
on
information
from
their
surroundings
via
embedded
communication
hardware.
IoT
applications
span
education,
healthcare
self-driving
cars.
high
delay
supplied
through
the
connecting
network
data
centers
huge
traffic
can
cause
system
become
congested,
so
cloud
is
not
suggested
for
delay-sensitive
it
extremely
difficult
provide
educational
applications,
particularly
in
a
mix
fog
conditions.
Fog
computing
was
created
address
this
problem
improve
time-sensitive
by
considering
quality
service
(QoS).
Allocation
resources
scheduling
tasks
are
challenging
issues
environment.
Resources
required
each
application
includes
several
modules
run.
In
paper,
we
used
Weighted
Greedy
Knapsack
(WGK)
based
algorithm
resource
allocation
modules/components
system.
We
have
considered
smart
parade
certain
services/resources
proposed
method
experimented
iFogSim.
Proposed
shows
better
energy
consumption
execution
cost
than
concurrent,
First-Come-First-Served
(FCFS)
Delay-Priority
algorithms.
Journal of Electrical and Computer Engineering,
Journal Year:
2022,
Volume and Issue:
2022, P. 1 - 12
Published: Sept. 24, 2022
Cloud
computing
has
become
the
most
challenging
research
field
in
current
information
technology
scenario.
In
this,
a
set
of
user
tasks
are
scheduled
and
allocated
to
numerous
kinds
heterogeneous
virtual
machines
(VMs)
cloud
data
centers
(CDCs),
these
VMs
hosted
by
diverse
types
physical
(PMs).
It
extends
several
features,
encompassing
elasticity,
safety,
sustainability,
even
adequate
maintenance
compared
traditional
centers.
There
techniques
available
for
VM
scheduling
allocation.
However,
it
still
requires
existence
new
mechanisms
that
can
reduce
execution
time
(ET)
tasks,
improve
optimization
energy
usage
resource
utilization
(RU),
consumption.
Along
with
optimization,
(VMS)
allocation
(VMA)
two-level
issues
need
be
considered
essential
policies
govern
mechanisms.
Hence,
executing
optimal
VMS
VMA
center,
methodologies,
such
as
enhanced
shark
smell
algorithm
(ESSOA)
at
first
level
Brownian
movement-centered
gravitation
search
(BMGSA)
second
level,
proposed
this
work
define
policies.
Firstly,
requests
reserved
on
appropriate
PM
ESSOA,
which
lowest
cost
within
deadline
limits,
BMGSA
decides
chosen
limitations
level.
To
demonstrate
algorithm’s
efficiency,
simulations
carried
out
using
Java
language-based
CloudSim
simulator,
mechanism
outcomes
acquired
existing
approaches.
The
simulation
results
show
suggested
is
efficient
terms
cost,
degree
imbalance
(DOI),
make
span
(MS),
(RU).
2022 IEEE International Conference on Data Science and Information System (ICDSIS),
Journal Year:
2022,
Volume and Issue:
unknown, P. 1 - 6
Published: July 29, 2022
The
Users
can
access
Cloud
services
anytime
and
from
any
location,
depending
on
their
needs.
In
a
cloud
platform,
data
of
vast
amount
is
transferred
the
user
to
server
vice-versa.
Whenever
VM
Scheduling
takes
longer
than
expected,
or
selected
does
not
exist
in
datacenter
may
utilize
more
Energy
consumption
SLA
(Service
Level
Agreement)
violations
with
Migrations.
Because
primary
element
Environment,
VM's
assignment
must
be
done
correctly;
resources
utilized
effectively,
no
occur
less
Two
approaches
are
implemented
for
comparison
i.e.,
Modified
Particle
Swarm
optimization
(MPSO),
Genetic
Algorithm
(GA).
MPSO
resulted
better
GA
by
6.0S%,
LR-MMT
32.2%,
at
27.81%
compared
Local
Regression-Minimum
Migration
Time
(LR-MMT)
energy
consumption.
48.39%,
91.6%,
S3.73%
migrations.
5%,
RegressionRandom
Selection
(LR-RS)
71.21%,
67.21%
Regression-Maximum
Correlation
(LR-MC)
Violation.
Therefore,
acquired
results
indicated
that
suggested
approach
converges
optimal
solutions
higher
quality
existing
algorithms
QoS
parameters.
International Journal of Membrane Science and Technology,
Journal Year:
2023,
Volume and Issue:
10(5), P. 478 - 490
Published: Oct. 9, 2023
The
concept
of
Software-Defined
Networking
(SDN)
has
been
a
fascinating
and
growing
interest
in
the
field
research.
programmable
network
component
is
allowed
by
SDN’s
promising
characteristics
partitions
control
plane
together
with
forwarding
plane.
Energy
Efficiency
(EE)
turned
out
to
be
vital
design
requisite
for
modern
networking
mechanisms
since
energy
costs
supply
hugely
entire
networks.
Nevertheless,
as
it
necessary
handle
trade-off
betwixt
EE
Network
Performance
(NP),
designing
energy-effective
solutions
non-trivial.
Thus,
utilizing
Energy-Aware
Routing
(EAR)
approaches,
this
paper
reviews
methodologies
Consumption
(EC)
on
SDN.
latest
research
related
traffic-aware
solution,
compacting
TCAM
end-host
aware
solutions,
rule
placement
heuristic
approach-centric
EAR
routing
protocol
was
highlighted
review
article
terms
optimal
EC
Finally,
centered
metrics,
current
methodologies’
performance
assessed
evaluation.
By
routing,
type
helpful
future
efficient
