Uses of Package
org.cloudbus.cloudsim.distributions
Package
Description
Provides classes that implement policies for a
Datacenter
to select a Host to place or migrate a VM, based on some criteria defined by each class.Provides Pseudo-Random Number Generators (PRNG) following several statistical
distributions used by the simulation API.
Provides classes that represent different physical and logical
Resource
used by simulation
objects such as Hosts and VMs.Provides
VmSelectionPolicy
implementations that define policies to be used by a Host
to select a Vm
to migrate from a list of VMs.Provides classes to inject random faults during simulation runtime.
Provides a set of interfaces and classes to develop heuristics to
find sub-optimal solutions for problems, considering some
utility function that has to be minimized or maximized.
Provides base classes to enable implementing testbeds in a repeatable manner,
allowing a researcher to execute several simulation runs
for a given experiment and collect statistical data using a scientific approach.
-
ClassDescriptionInterface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows a defined statistical continuous distribution.
-
ClassDescriptionInterface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows a defined statistical continuous distribution.Interface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows a defined statistical discrete distribution.A Pseudo-Random Number Generator following the Exponential distribution.A Pseudo-Random Number Generator following the Gamma distribution.A
RandomGenerator
that internally uses theThreadLocalRandom
, a very fast Pseudo-Random Number Generator (PRNG) with higher performance thanRandom
, mainly in concurrent environments.A Pseudo-Random Number Generator following the Log-normal distribution.A Pseudo-Random Number Generator following the Normal (Gaussian) distribution.A Pseudo-Random Number Generator following the Pareto distribution.A Pseudo-Random Number Generator which returns numbers following a Poisson Distribution, modeling the probability of an event to happen a number of times in a given time interval.Interface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows some statistical distribution, even discrete or continuous.A Pseudo-Random Number Generator (RNG) following the Uniform continuous distribution.A Pseudo-Random Number Generator following the Weibull distribution.A Pseudo-Random Number Generator following the Zipf distribution. -
ClassDescriptionInterface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows a defined statistical continuous distribution.
-
ClassDescriptionInterface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows a defined statistical continuous distribution.
-
ClassDescriptionInterface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows a defined statistical continuous distribution.
-
ClassDescriptionInterface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows some statistical distribution, even discrete or continuous.
-
ClassDescriptionInterface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows a defined statistical continuous distribution.
-
ClassDescriptionInterface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows a defined statistical continuous distribution.Interface to be implemented by a Pseudo-Random Number Generator (PRNG) that follows some statistical distribution, even discrete or continuous.