Balancing Performance and Cost in EC2 Instance Selection for Energy-Efficient Cloud Computing
Abstract
This
paper
introduces
a
dynamic
decision-making
framework
designed
to
optimize
cloud
resource
allocation
through
the
selection
of
most
suitable
Amazon
EC2
instance
types
based
on
specific
workload
demands.
The
system
categorizes
workloads
into
general-purpose,
memory-intensive,
and
compute-intensive
types,
allowing
user
input
be
translated
detailed
technical
requirements,
such
as
necessary
virtual
CPUs,
RAM,
expected
usage
duration,
performance
needs.
Leveraging
cost-performance
scoring
algorithm,
filters
evaluates
various
instances
recommend
optimal
configurations
that
balance
computational
with
budgetary
constraints.
method
not
only
maximizes
cost-effectiveness
but
also
reduces
unnecessary
utilization,
minimizing
operational
inefficiencies
environmental
impact
associated
over-provisioning.
proposed
is
particularly
relevant
in
context
scalable,
energy-efficient
computing
environments,
it
aligns
infrastructure
application
thereby
supporting
more
sustainable
operations.
By
helping
users
effectively
match
their
investment
necessities,
this
offers
valuable
solution
for
organizations
looking
achieve
both
economic
ecological
benefits
deployments.
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 18, 2024
Language: Английский