/*
*
*/
package org.cloudbus.cloudsim.examples.power.random;
import java.util.ArrayList;
import java.util.List;
import org.cloudbus.cloudsim.Cloudlet;
import org.cloudbus.cloudsim.UtilizationModel;
import org.cloudbus.cloudsim.UtilizationModelNull;
import org.cloudbus.cloudsim.UtilizationModelStochastic;
import org.cloudbus.cloudsim.examples.power.Constants;
/**
* The Helper class for the random workload.
*
* If you are using any algorithms, policies or workload included in the power package please cite
* the following paper:
*
* Anton Beloglazov, and Rajkumar Buyya, "Optimal Online Deterministic Algorithms and Adaptive
* Heuristics for Energy and Performance Efficient Dynamic Consolidation of Virtual Machines in
* Cloud Data Centers", Concurrency and Computation: Practice and Experience (CCPE), Volume 24,
* Issue 13, Pages: 1397-1420, John Wiley & Sons, Ltd, New York, USA, 2012
*
* @author Anton Beloglazov
* @since Jan 5, 2012
*/
public class RandomHelper {
/**
* Creates the cloudlet list.
*
* @param brokerId the broker id
* @param cloudletsNumber the cloudlets number
*
* @return the list< cloudlet>
*/
public static List<Cloudlet> createCloudletList(int brokerId, int cloudletsNumber) {
List<Cloudlet> list = new ArrayList<Cloudlet>();
long fileSize = 300;
long outputSize = 300;
long seed = RandomConstants.CLOUDLET_UTILIZATION_SEED;
UtilizationModel utilizationModelNull = new UtilizationModelNull();
for (int i = 0; i < cloudletsNumber; i++) {
Cloudlet cloudlet = null;
if (seed == -1) {
cloudlet = new Cloudlet(
i,
Constants.CLOUDLET_LENGTH,
Constants.CLOUDLET_PES,
fileSize,
outputSize,
new UtilizationModelStochastic(),
utilizationModelNull,
utilizationModelNull);
} else {
cloudlet = new Cloudlet(
i,
Constants.CLOUDLET_LENGTH,
Constants.CLOUDLET_PES,
fileSize,
outputSize,
new UtilizationModelStochastic(seed * i),
utilizationModelNull,
utilizationModelNull);
}
cloudlet.setUserId(brokerId);
cloudlet.setVmId(i);
list.add(cloudlet);
}
return list;
}
}