Journal of Cloud Computing Advances Systems and Applications,
Journal Year:
2020,
Volume and Issue:
9(1)
Published: July 21, 2020
Abstract
With
the
application
and
comprehensive
development
of
big
data
technology,
need
for
effective
research
on
cloud
workflow
management
scheduling
is
becoming
increasingly
urgent.
However,
there
are
currently
suitable
methods
analysis.
To
determine
how
to
effectively
manage
schedule
smart
workflows,
this
article
studies
from
various
aspects
draws
following
conclusions:
Compared
with
original
JStorm
system,
response
time
shortened
by
a
maximum
58.26%
an
average
23.18%,
CPU
resource
utilization
increased
17.96%
11.39%,
memory
88.7%
71.16%.
In
terms
optimizing
dynamic
combination
web
services,
overall
performance
both
MOACO
CCA
algorithms
better
than
that
GA
algorithm,
algorithm
algorithm.
This
paper
also
proposes
strategy
based
intelligent
realizes
two-tier
tasks
adjusting
service
resources.
We
have
studied
three
representative
(ACO,
PSO
GA)
improved
them
optimization.
It
can
be
clearly
seen
in
same
scenario,
optimal
values
different
vary
greatly
test
cases.
solution
curve
substantially
consistent
trend
mean
curve.
IEEE Access,
Journal Year:
2022,
Volume and Issue:
10, P. 16408 - 16423
Published: Jan. 1, 2022
Container
virtualization
methods
based
on
application
deployment
levels
have
been
widely
adopted
in
cloud-computing
environments
to
implement
construction,
deployment,
and
migration.
However,
most
containers
focus
the
interface
between
applications
hosts
lack
collaboration
containers.
This
study
proposes
a
new
container
model
that
contains
users,
services,
documents,
messages,
called
Band-area
Application
Container.
A
salient
feature
of
is
it
can
express
variety
things
reality,
such
as
organizations
or
individuals.
End
users
build
complex
changeable
system
through
cooperation
Band-areas.
resource
allocation
non
Internet-of-Thing
tasks
from
an
open
issue.
The
method
should
not
only
improve
quality
user
experience,
but
also
reduce
energy
consumption
by
improving
utilization
server.
To
solve
this
problem,
artificial
fish
swarm
algorithm
proposed
optimize
container-based
task
scheduling.
considers
reliability,
processing
time
overhead,
task,
servers.
Experimental
evaluation
shows
that,
compared
with
existing
three
algorithms,
obtains
better
improvement
rate
consumption,
cluster
load
balancing.
Journal of Cloud Computing Advances Systems and Applications,
Journal Year:
2020,
Volume and Issue:
9(1)
Published: July 21, 2020
Abstract
With
the
application
and
comprehensive
development
of
big
data
technology,
need
for
effective
research
on
cloud
workflow
management
scheduling
is
becoming
increasingly
urgent.
However,
there
are
currently
suitable
methods
analysis.
To
determine
how
to
effectively
manage
schedule
smart
workflows,
this
article
studies
from
various
aspects
draws
following
conclusions:
Compared
with
original
JStorm
system,
response
time
shortened
by
a
maximum
58.26%
an
average
23.18%,
CPU
resource
utilization
increased
17.96%
11.39%,
memory
88.7%
71.16%.
In
terms
optimizing
dynamic
combination
web
services,
overall
performance
both
MOACO
CCA
algorithms
better
than
that
GA
algorithm,
algorithm
algorithm.
This
paper
also
proposes
strategy
based
intelligent
realizes
two-tier
tasks
adjusting
service
resources.
We
have
studied
three
representative
(ACO,
PSO
GA)
improved
them
optimization.
It
can
be
clearly
seen
in
same
scenario,
optimal
values
different
vary
greatly
test
cases.
solution
curve
substantially
consistent
trend
mean
curve.
