Enhancing
cloud
service
is
the
primary
goal
of
stakeholders.
It
a
comprehensive
that
can
be
achieved
through
optimizing
performance
metrics,
effective
resource
utilization,
and
prioritizing
user
satisfaction.
These
also
called
Quality
Service
(QoS)
are
mentioned
in
Level
Agreement
(SLA),
contractual
document.
Optimizing
experience
requires
continuous
monitoring
systems
technologies
such
as
virtualization,
scheduling,
migration,
consolidation,
load
balancing,
etc.
Scheduling
cloudlets,
virtual
machines,
balancing
crucial
for
achieving
SLA
enumerated
QoS
other
key
demands.
In
order
to
monitor
evaluate
effectiveness
any
knowledge
on
scheduling
become
imperative.
This
paper
orchestrated
identify
essential
metrics
explore
how
algorithms
enhance
performance.
Additionally,
it
seeks
conduct
comparative
evaluation
FCFS,
SJF,
Min-Min,
Max-Min,
RASA,
Suffrage,
TASA
cloudlet
using
CloudSim.
focuses
including
average
waiting
time,
makespan,
machine
utilization
ratio,
balancing.
IEEE Access,
Journal Year:
2024,
Volume and Issue:
12, P. 105234 - 105245
Published: Jan. 1, 2024
The
dynamic
landscape
of
cloud
computing
design
presents
significant
challenges
regarding
power
consumption
and
quality
service
(QoS).
Virtual
machine
(VM)
consolidation
is
essential
for
reducing
usage
enhancing
QoS
by
relocating
VMs
between
hosts.
OpenStack
Neat,
a
leading
framework
VM
consolidation,
employs
the
Modified
Best-Fit
Decreasing
(MBFD)
placement
technique,
which
faces
issues
related
to
energy
QoS.
To
address
these
issues,
we
propose
an
Energy
Efficient
Consolidation
(EEVMC)
approach.
Our
method
introduces
novel
host
selection
criterion
based
on
incurred
loss
during
identify
most
efficient
host.
For
validation,
conducted
simulations
using
real-time
workload
traces
from
Planet-Lab
Materna
over
ten
days,
leveraging
latest
CloudSim
toolkit
compare
our
approach
with
state-of-the-art
techniques.
Planet-Lab's
workload,
EEVMC
shows
reduction
in
80.35%,
59.76%,
21.59%,
7.40%,
fewer
system-level
agreement
(SLA)
violations
94.51%,
94.85%,
47.17%,
17.78%
when
compared
(MBFD),
Power-Aware
Best
Fit
(PABFD),
Medium
Power
(MFPED),
Power-Efficient
(PEBFD),
respectively.
Similarly,
Materna,
achieves
16.10%,
61.0%,
4.94%,
4.82%,
SLA
76.99%,
88.88%,
12.50%,
48.65%
against
same
benchmarks.
Additionally,
Loss-Aware
Performance
(LAPED)
significantly
reduces
total
number
migrations
time
per
active
host,
indicating
substantial
improvement
efficiency.
IEEE Access,
Journal Year:
2020,
Volume and Issue:
9, P. 3526 - 3544
Published: Dec. 28, 2020
The
high
energy
consumption
of
cloud
data
centers
is
one
the
key
issues
restricting
future
development
computing
industry.
For
two-tier
virtualized
in
which
containers
are
deployed
on
VMs,
this
paper
conducts
an
in-depth
study
problem
from
aspect
resource
management.
First,
working
model
center
defined.
By
mapping
tasks
to
and
using
VMs
isolate
different
jobs,
improves
utilization
hosts
while
ensuring
isolation
security
jobs.
Then,
energy-aware
host
management
framework
constructed,
includes
two
algorithms.
initial
static
placement
a
scheduling
algorithm,
including
load
balancing
alternate
two-sided
matching
methods
complete
respectively.
runtime
dynamic
consolidation
algorithm
takes
scheme
as
input,
utilizes
method
use
least
active
meet
real-time
requirements
containers.
Finally,
simulation
experiments
compared
with
related
algorithms
conducted
real
workload
traces.
results
show
that
proposed
have
better
performance
utilization,
number
hosts,
container
migrations
SLA
metric.
And
entire
achieves
energy-saving
effect
13.8%
at
least.
IEEE Transactions on Cloud Computing,
Journal Year:
2024,
Volume and Issue:
12(2), P. 563 - 579
Published: March 20, 2024
Pre-copy-based
Virtual
Machine
(VM)
live
migration
seamlessly
migrates
the
running
VM
to
target
physical
server
by
pre-copying
memory
pages
and
realizing
updates
through
loop
iterations.
This
method,
which
has
high
reliability
robustness,
can
effectively
achieve
load
balancing
reduce
energy
consumption.
It
is
widely
used
in
industry
manage
cluster
resources.
However,
it
also
involves
many
problems,
such
as
dirty
resulting
from
repeated
transmission
convergence
failure
of
iterative
transmission.
Hence,
pre-copy
cannot
efficiently
allocate
To
resolve
these
a
technology
based
on
similarity
proposed
this
paper.
The
access
priority
historical
was
determined
calculating
weight
Hamming
distance.
A
priority-based
delay
scheme
for
low
decrease
frequent
pages,
increase
speed
live-migration
copy
process,
overall
time
VMs.
comparative
analysis
experimental
results
six
dimensions
showed
that
method
achieved
better
efficiency
than
conventional
strategy.
Cloud
systems
are
managed
on
the
basis
of
au-tonomous
systems.
We
present
criteria
that
suitable
for
optimization
or
improvement
modern
cloud
In
every
operating
system,
task
scheduling
is
very
important.
clouds
systems,
where
large
amount
tasks
runs
numerous
machines,
optimized
leads
to
significant
reduction
computing
time.
providers
have
comply
with
service
level
agreement
from
technical
and
quality
point
view.
For
this
reason,
we
specify
limits
violation.
Clouds
virtualized
by
virtual
machines
containers.
show
approaches
power
consumption
minimization.
Fog
helps
improve
middleware
technology
between
IoT
devices.
correct
decomposition
parallel
distributed
application.
conclude
understanding
effective
work
can
design
implementation
