International Journal of Computer Networks And Applications,
Journal Year:
2024,
Volume and Issue:
11(1), P. 1 - 1
Published: Feb. 26, 2024
In
a
cloud
computing
environment,
good
resource
management
remains
major
challenge
for
its
operation.Implementing
virtual
machine
placement
(VMP)
on
physical
machines
helps
to
achieve
various
objectives,
such
as
allocation,
load
balancing,
energy
consumption,
and
quality
of
service.VMP
(virtual
placement)
in
the
is
critical,
so
it's
important
audit
implementation.It
must
take
into
account
resources
server,
including
CPU,
RAM,
storage.In
this
paper,
metaheuristic
algorithm
based
Grey
Wolf
Optimization
(GWO)
method
used
optimize
effectively
minimizing
number
active
host
servers.Experimental
results
demonstrate
effectiveness
proposed
method,
called
Virtual
Machine
Placement
(GWOVMP).The
reduces
power
consumption
by
20.99
wastage
1.80
compared
with
existing
algorithms.
IEEE Access,
Journal Year:
2020,
Volume and Issue:
8, P. 81747 - 81764
Published: Jan. 1, 2020
With
the
widespread
usage
of
cloud
computing
to
benefit
from
its
services,
service
providers
have
invested
in
constructing
large
scale
data
centers.
Consequently,
a
tremendous
increase
energy
consumption
has
arisen
conjunction
with
results,
including
remarkable
rise
costs
operating
and
cooling
servers.
Besides,
increasing
significant
impact
on
environment
due
emissions
carbon
dioxide.
Dynamic
consolidation
Virtual
Machines
(VMs)
into
minimal
number
Physical
(PMs)
is
considered
as
one
magic
solutions
manage
power
consumption.
The
virtual
machine
placement
problem
critical
issue
for
good
VM
consolidation.
This
paper
proposes
Power-Aware
technique
depending
Particle
Swarm
Optimization
(PAPSO)
determine
near-optimal
migrated
VMs.
A
discrete
version
(PSO)
adopted
based
decimal
encoding
map
VMs
best
appropriate
PMs.
Furthermore,
an
effective
minimization
fitness
function
employed
reduce
without
violating
Service
Level
Agreement
(SLA).
Specifically,
PAPSO
consolidates
minimum
PMs
major
constraint
decrease
overloaded
hosts
much
possible.
Therefore,
migrations
can
be
reduced
drastically
by
taking
consideration
main
sources
migrations;
underloaded
ones.
implemented
CloudSim
experimental
results
random
workloads
different
sizes
show
that
does
not
violate
SLA
outperforms
Best
Fit
Decreasing
algorithm
(PABFD).
It
about
8.01%,
39.65%,
66.33%,
11.87%
average
terms
consumed
energy,
migrations,
host
shutdowns
combined
metric
Energy
Violation
(ESV),
respectively.
Virtual Reality & Intelligent Hardware,
Journal Year:
2022,
Volume and Issue:
4(4), P. 279 - 291
Published: Aug. 1, 2022
This
work
initially
surveys
and
illustrates
the
multiple
open
challenges
in
field
of
industrial
IoT-based
Big
Data
management
analysis
Cloud
environments.
Challenges
arise
from
fields
Machine
Learning
infrastructures,
A.I.
techniques
Analytics
environments,
Federated
systems
try
to
be
clarified.
Additionally,
Reinforcement
is
a
novel
technique
that
allows
large
data
centers
such
as
affect
more
energy-efficient
resource
allocation.
Moreover,
we
propose
an
architecture
tries
combine
features
offered
by
several
Providers
emerge
achieve
Energy-Efficient
Management
Framework
(EEIBDM)
established
outside
every
user,
Cloud.
IoT
could
integrated
with
Digital
Twin
scenario,
for
virtual
representation
machines
rooms
temperatures.
Furthermore,
algorithm
delivering
energy
consumption
infrastructure
through
evaluation
EEIBDM
framework.
Finally,
some
future
directions
expansion
our
research
are
illustrated.
International Journal of Communication Systems,
Journal Year:
2019,
Volume and Issue:
32(14)
Published: July 1, 2019
Summary
Cloud
computing
introduced
a
new
paradigm
in
IT
industry
by
providing
on‐demand,
elastic,
ubiquitous
resources
for
users.
In
virtualized
cloud
data
center,
there
are
large
number
of
physical
machines
(PMs)
hosting
different
types
virtual
(VMs).
Unfortunately,
the
centers
do
not
fully
utilize
their
and
cause
considerable
amount
energy
waste
that
has
great
operational
cost
dramatic
impact
on
environment.
Server
consolidation
is
one
techniques
provide
efficient
use
reducing
active
servers.
Since
VM
placement
plays
an
important
role
server
consolidation,
main
challenges
mapping
VMs
to
PMs.
Multiobjective
generating
interest
among
researchers
academia.
This
paper
aims
represent
detailed
review
recent
state‐of‐the‐art
multiobjective
mechanisms
using
nature‐inspired
metaheuristic
algorithms
environments.
Also,
it
gives
special
attention
parameters
approaches
used
placing
into
end,
we
will
discuss
explore
further
works
can
be
done
this
area
research.
IEEE Systems Journal,
Journal Year:
2020,
Volume and Issue:
15(2), P. 2571 - 2582
Published: June 30, 2020
Cloud
computing
efficiency
greatly
depends
on
the
of
virtual
machines
(VMs)
placement
strategy
used.
However,
VM
has
remained
one
major
challenging
issues
in
cloud
mainly
because
heterogeneity
both
and
physical
(PMs),
multidimensionality
resources,
increasing
scale
data
centers
(CDCs).
An
inefficiency
a
significant
influence
quality
service
provided,
amount
energy
consumed,
running
costs
CDCs.
To
address
these
issues,
this
article,
we
propose
greedy
randomized
(GRVMP)
algorithm
large-scale
CDC
with
heterogeneous
multidimensional
resources.
GRVMP
inspires
"power
two
choices"
model
places
VMs
more
power-efficient
PMs
to
jointly
optimize
usage
resource
utilization.
The
performance
is
evaluated
using
synthetic
real-world
production
scenarios
(Amazon
EC2)
several
matrices.
results
experiment
confirm
that
optimizes
power
overall
wastage
also
show
significantly
outperforms
baseline
schemes
terms
metrics
Applied Sciences,
Journal Year:
2023,
Volume and Issue:
13(16), P. 9165 - 9165
Published: Aug. 11, 2023
The
Internet
of
Things
(IoT)
was
introduced
as
a
recently
developed
technology
in
the
telecommunications
field.
It
is
network
made
up
real-world
objects,
things,
and
gadgets
that
are
enabled
by
sensors
software
can
communicate
data
with
one
another.
Systems
for
monitoring
gather,
exchange,
process
video
image
captured
cameras
across
network.
Furthermore,
novel
concept
Digital
Twin
offers
new
opportunities
so
proposed
systems
work
virtually,
but
without
differing
operation
from
“real”
system.
This
paper
meticulous
survey
IoT
to
illustrate
how
their
combination
will
improve
certain
types
Monitoring
Healthcare–IoT
Cloud.
To
achieve
this
goal,
we
discuss
characteristics
use
over
Multimedia
Transmission
System
also
discusses
some
technical
challenges
IoT,
based
on
Healthcare
data.
Finally,
it
shows
Mobile
Cloud
Computing
(MCC)
technology,
settled
base
enhances
functionality
has
an
impact
various
proposes
algorithm
approach
transmitting
processing
video/image
through
Cloud-based
gather
pertinent
about
validity
our
proposal
more
safe
useful
way,
have
implemented
scenario
Smart
suggested
sustainable
energy-efficient
system
experimental
findings
ultimately
demonstrate
reliable
secure.
Experimental
results
show
model
depicts
efficiency
usage
Management
operated
scenario,
using
real-time
large-scale
produced
connected
Through
these
scenarios,
observe
remains
best
choice
regardless
time
difference
or
energy
load.
ETRI Journal,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 18, 2025
Abstract
Cloud
computing
faces
challenges
in
energy
consumption
and
quality
of
service
(QoS).
Virtual
machine
(VM)
consolidation,
involving
relocation
between
hosts,
helps
reduce
power
usage
enhance
QoS.
OpenStack
Neat,
a
leading
VM
consolidation
framework,
uses
the
modified
best‐fit
decreasing
(MBFD)
strategy
but
QoS
issues.
To
address
these,
we
present
secure
efficient
(SEEVMC)
method,
introducing
unique
host
selection
criterion
based
on
incurred
loss
during
placement.
We
evaluated
SEEVMC
with
real‐time
workload
data
from
PlanetLab
Materna
over
ten
days
using
CloudSim.
For
PlanetLab,
reduced
by
78.33%,
57.74%,
19.57%,
6.30%
system‐level
agreement
(SLA)
violations
92.49%,
92.78%,
45.16%,
15.67%,
compared
MBFD,
power‐aware
best
fit
decreasing,
medium
power‐efficient
bit
decreasing.
Materna,
14.12%,
59.5%,
3.92%,
3.80%
fewer
SLA
74.85%,
86.95%,
11.40%,
46.60%.
also
migrations
time
per
active
host,
improving
cloud
efficiency.
