Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Oct. 25, 2024
Edge
computing
has
emerged
as
a
prominent
trend
in
the
field
of
information
technology,
offering
flexible
and
robust
resources
for
industrial
Internet.
How
to
migrate
container
accurately
is
crucial
edge
Internet,
it
plays
vital
role
enhancing
service
response
speed
safeguarding
uninterrupted
continuity
production
operations.
In
this
paper,
we
explore
problem
migration
within
aiming
reduce
latency
enhance
reliability.
We
establish
two-objective
optimization
model
comprehensively
capture
formulate
constrained
model.
The
formulated
provides
systematic
framework
that
effectively
balances
trade-off
between
reducing
To
tackle
strategy
derived
from
model,
propose
algorithm
based
on
improved
binary
whale
algorithm.
Our
incorporates
adaptive
probability
position
weight
hunting
searching
operations,
search
efficiency
during
solving
process.
experimental
results
demonstrate
effectiveness
established
objective
value,
while
proposed
surpasses
existing
algorithms
by
achieving
an
average
reduction
at
least
15.59%
value.
Computer Networks,
Journal Year:
2024,
Volume and Issue:
245, P. 110371 - 110371
Published: March 27, 2024
Recently,
container-based
solutions
have
become
de
facto
compute
units
of
modern
cloud-native
applications.
However,
the
exponential
growth
in
data
traffic
and
power
consumption
these
technologies
to
handle
high
alarm
strong
need
for
energy
evaluation
approaches
containerized
clouds.
Furthermore,
proliferation
highly
distributed
edge
clouds
raises
additional
concerns
regarding
future
cloud
architectures.
This
article
presents
a
detailed
overview
methods
techniques
monitoring
within
popular
platforms.
The
study
offers
an
in-depth
approaches,
demonstrating
variations
measured
based
on
chosen
technique.
A
well-known
container
orchestration
platform
named
Kubernetes
(K8s)
has
been
applied
our
extensive
measurements.
work
argues
that
energy-efficient
will
play
vital
role
building
more
sustainable
eco-friendly
digital
infrastructure
by
optimizing
reducing
carbon
footprint,
paving
way
greener
future.
paper
also
discusses
open
challenges
research
directions
sustainability,
leading
conclusion,
offering
lessons
learned
prospects
potential
foster
practices
ecosystem.
Sensors,
Journal Year:
2024,
Volume and Issue:
24(17), P. 5551 - 5551
Published: Aug. 28, 2024
In
the
dynamic
world
of
cloud
computing,
auto-scaling
stands
as
a
beacon
efficiency,
dynamically
aligning
resources
with
fluctuating
demands.
This
paper
presents
comprehensive
review
techniques,
highlighting
significant
advancements
and
persisting
challenges
in
field.
First,
we
overview
fundamental
principles
mechanisms
auto-scaling,
including
its
role
improving
cost
performance,
energy
consumption
services.
We
then
discuss
various
strategies
employed
ranging
from
threshold-based
rules
queuing
theory
to
sophisticated
machine
learning
time
series
analysis
approaches.
After
that,
explore
critical
issues
practices
several
studies
that
demonstrate
how
these
can
be
addressed.
conclude
by
offering
insights
into
promising
research
directions,
emphasizing
development
predictive
scaling
integration
advanced
techniques
achieve
more
effective
efficient
solutions.
IEEE Sensors Journal,
Journal Year:
2024,
Volume and Issue:
24(10), P. 15748 - 15772
Published: April 5, 2024
This
article
provides
an
overview
of
recent
research
on
edge-cloud
architectures
in
hybrid
energy
management
systems
(HEMS).
It
delves
into
the
typical
structure
IoT
system,
consisting
three
key
layers:
perception
layer,
network
and
application
layer.
The
architecture
adds
two
more
middleware
layer
business
also
addresses
challenges
proposed
architecture,
including
standardization,
scalability,
security,
privacy,
regulatory
compliance,
infrastructure
maintenance.
Privacy
concerns
can
hinder
adoption
HEMS.
Therefore,
we
provide
these
solutions
for
HEMS
that
address
them.
concludes
by
discussing
future
trends
These
include
increased
use
artificial
intelligence
edge
level
to
improve
performance
reliability
blockchain
security
privacy
computing
systems.
