Cloudsim Tutorials

Cloudlet in Cloudsim Simulation

Anupinder Singh

Cloudlet in Cloudsim defined the workload, which is to be executed during the simulation run of the cloudsim simulation engine.

Cloudlet in Cloudsim is a model class that exists inside the package ‘org.cloudbus.cloudsim‘.

A cloudlet is one of the most important models which defined the specifications for a simulation engine corresponding to the real-life candidate application to be considered for moving to a Cloud-based system.

In contrast, we can also define this cloudlet as a single process or task being executed on the cloud-based system which is to be simulated through a Cloudsim simulation engine.

The cloudlet model class defines four different constructors for its initialization, its method signatures are as follows:

/*
First method signature with 8 parameters with simplest cloudlet execution with out maintaining its history or additional files
*/
public Cloudlet(
			final int cloudletId,
			final long cloudletLength,
			final int pesNumber,
			final long cloudletFileSize,
			final long cloudletOutputSize,
			final UtilizationModel utilizationModelCpu,
			final UtilizationModel utilizationModelRam,
			final UtilizationModel utilizationModelBw)

/*
Second method signature with 10 parameters with support for cloudlet execution history maintenance as well as additionl list of file requirements for execution.
*/
public Cloudlet(
			final int cloudletId,
			final long cloudletLength,
			final int pesNumber,
			final long cloudletFileSize,
			final long cloudletOutputSize,
			final UtilizationModel utilizationModelCpu,
			final UtilizationModel utilizationModelRam,
			final UtilizationModel utilizationModelBw,
			final boolean record,
			final List<String> fileList)

/*
Third method signature with 9 parameters with support for cloudlet execution additionl list of file requirements for execution.
*/
public Cloudlet(
			final int cloudletId,
			final long cloudletLength,
			final int pesNumber,
			final long cloudletFileSize,
			final long cloudletOutputSize,
			final UtilizationModel utilizationModelCpu,
			final UtilizationModel utilizationModelRam,
			final UtilizationModel utilizationModelBw,
			final List<String> fileList)

/*
Fourth method signature with 9 parameters with support for cloudlet execution history maintenance.
*/
public Cloudlet(
			final int cloudletId,
			final long cloudletLength,
			final int pesNumber,
			final long cloudletFileSize,
			final long cloudletOutputSize,
			final UtilizationModel utilizationModelCpu,
			final UtilizationModel utilizationModelRam,
			final UtilizationModel utilizationModelBw,
			final boolean record)

Cloudlet in Cloudsim defines following are the attributes that are being by the cloudsim simulation engine:

Following are the states that each cloudlet can sustain during the simulation flow:

The cloudlets would shuffle between these states any number of times depending upon the simulation scenario under consideration.

One of the most important behaviors of the Cloudlet model class is that it may be moved from one resource to another resource due to any implicit/explicit reasons.

Therefore, the track is to be maintained for its movement during the simulation flow. To support this a nested class named ‘Resource’ is defined which contains the following attributes:

The instance of this ‘Resource’ model class is defined and utilized through the setResourceParameter() method of cloudlet class. Which is further utilized in the processCloudletSubmit() method(line no 715) of DataCenter class available under the same package i.e. ‘org.cloudbus.cloudsim’.

This class plays a very important role in simulated distributed network applications.

Frequently Asked Questions on Cloudlet

What does the Cloudlet length represent?

The Cloudlet length in CloudSim represents the size or amount of processing (in Million Instructions – MI) that a Cloudlet needs to execute. It can be adjusted to simulate different workloads in a cloud environment.

How does the number of processing elements (Pe’s) affect a Cloudlet?

The number of Pe’s required to execute a Cloudlet affects its execution time. If a Cloudlet requires multiple Pe’s, it means it can take advantage of parallel execution, potentially reducing its overall execution time. However, the availability of the required number of Pe’s is determined by the scheduling and resource allocation policies in place.

What is the role of file size parameters in a Cloudlet?

The file size parameters in a Cloudlet (input and output) represent the size of data to be transferred over the network before and after the execution of the Cloudlet. These parameters are important as they can affect the total execution time, especially in network-constrained environments.

Can I create a custom Cloudlet with specific behavior?

Yes, the CloudSim simulation toolkit is a highly extensible framework. You can extend the Cloudlet class to create custom Cloudlets with specific behaviors, such as varying instruction length or dynamic priority changes etc.

How are Cloudlets executed in parallel in CloudSim?

Parallel execution of Cloudlets is achieved by distributing them across multiple Pe’s. If a Cloudlet is defined with multiple required Pe’s, and a VM has sufficient Pe’s available, the Cloudlet’s execution can occur in parallel, reducing the overall completion time.

What does the status of a Cloudlet signify?

The status of a Cloudlet represents its current state in the simulation. It could be one of the following:
CREATED: just instantiated,
READY: ready to be executed,
INEXEC: in execution,
PAUSED: execution has been paused,
SUCCESS: successfully completed,
QUEUED: in the queue waiting for execution,
FAILED, and CANCELED: title speaks for itself.

How do I handle failed or canceled Cloudlets?

CloudSim does not automatically handle failed or canceled Cloudlets. The user must explicitly check the status of Cloudlets at the end of the simulation and implement any necessary recovery or fallback procedures.

How can I measure the performance of Cloudlets?

The performance of Cloudlets can be measured in terms of various metrics like execution time, waiting time in the queue, start and finish times, and data transfer time. CloudSim provides methods to retrieve these metrics for each Cloudlet at the end of the simulation.

Learn More

Also, To quickly get started with the Cloudsim Simulation Toolkit, Feel free to join our learners community for an online self-paced course named “Essential Cloudsim Tutorials” I would be interested in interacting with you. for further discussion.

Exit mobile version