Concurrency and Computation Practice and Experience,
Год журнала:
2022,
Номер
34(28)
Опубликована: Сен. 29, 2022
Summary
Data
sharing
in
cloud
computing
happens
with
multiple
participants
to
freely
distribute
the
group
data,
which
focuses
on
advancing
effectiveness
of
work
cooperative
backgrounds
and
has
attained
widespread
benefits.
The
main
intent
this
article
is
accomplish
a
virtual
machines
(VMs)
placement
migration
model
using
hybrid
meta‐heuristic
concept.
A
new
algorithm
named
DJ‐HA
developed
for
optimal
VM
reduce
count
active
servers,
minimization
makespan,
energy
consumption
faster
convergence
rate
background.
Then,
done
based
multi‐objective
function
concerning
makespan
same
DJ‐HA.
From
result
analysis,
correspondingly
secured
at
4.3%,
3.5%,
31%,
33%
more
advanced
than
PSO,
GWO,
DHOA,
JA,
100th
iteration
Experiment
1.
Accordingly,
cost
suggested
88.8%,
89.4%,
33.3%,
50%
increased
JA
4.
Hence,
it
proved
that
enriched
other
conventional
algorithms.
IEEE Systems Journal,
Год журнала:
2020,
Номер
15(2), С. 2571 - 2582
Опубликована: Июнь 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
