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Add launch configuration for NetExamples; enhance NetExamples class with main method and improved network creation; refactor Result class for better stats handling

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This commit is contained in:
Giacomo Bertolazzi
2025-03-16 19:42:33 +01:00
parent 68687fa595
commit e4df5dab73
4 changed files with 94 additions and 22 deletions
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49
src/main/java/net/berack/upo/valpre/NetExamples.java
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@@ -1,8 +1,12 @@
package net.berack.upo.valpre;
import java.util.concurrent.ExecutionException;
import net.berack.upo.valpre.rand.Distribution;
import net.berack.upo.valpre.sim.Net;
import net.berack.upo.valpre.sim.ServerNode;
import net.berack.upo.valpre.sim.SimulationMultiple;
import net.berack.upo.valpre.sim.stats.Result;
/**
* This class provides two example networks.
@@ -10,37 +14,64 @@ import net.berack.upo.valpre.sim.ServerNode;
* The second network is composed of a terminal node and two queue nodes.
*/
public final class NetExamples {
/**
* Main method to test the example networks.
* It runs the fist network and prints the results.
* The network will have the distribution changed but the mean will be the same.
*
* @param args not needed
* @throws ExecutionException if the execution fails
* @throws InterruptedException if the execution is interrupted
*/
public static void main(String[] args) throws InterruptedException, ExecutionException {
var avg1 = 3.2;
var seed = 0l;
var nets = new Net[] {
getNet1("Normal", new Distribution.NormalBoxMuller(avg1, 0.6)),
getNet1("Exponential", new Distribution.Exponential(1 / avg1)),
getNet1("Erlang", new Distribution.Erlang(5, 5 / avg1)),
getNet1("Uniform", new Distribution.Uniform(avg1 - 1, avg1 + 1))
};
for (var net : nets) {
var summary = new SimulationMultiple(net).runParallel(seed, 1000);
var table = Result.getResultString(summary.getNodes(), summary.getStats());
System.out.println(table);
}
}
/**
* Return the first example network.
* The net is composed of a terminal node and a queue node.
* The terminal node generates 10000 jobs with an exponential distribution 4.5.
* The queue node has a capacity of 1 and a service time of 3.2 with a standard
* deviation of 0.6.
* The terminal node is connected to the queue node with a probability of 1.0.
*
* @return the first example network
*/
public static Net getNet1() {
var exp0_22 = new Distribution.Exponential(1.0 / 4.5);
var norm3_2 = new Distribution.NormalBoxMuller(3.2, 0.6);
var spawn = 10000;
return getNet1(spawn, exp0_22, norm3_2);
return getNet1("Queue", norm3_2);
}
/**
* Return the first example network.
* The net is composed of a terminal node and a queue node.
* The terminal node is connected to the queue node.
* The terminal node generates 10000 jobs with an exponential distribution 4.5.
*
* @param spawn the number of jobs to generate
* @param source the distribution of the source node
* @param queue the distribution of the queue node
* @param queue the distribution of the queue node
* @return the first example network
*/
public static Net getNet1(int spawn, Distribution source, Distribution queue) {
public static Net getNet1(String name, Distribution queue) {
var spawn = 10000;
var source = new Distribution.Exponential(1.0 / 4.5);
var net1 = new Net();
net1.addNode(ServerNode.Builder.terminal("Source", spawn, source));
net1.addNode(ServerNode.Builder.queue("Queue", 1, queue));
net1.addNode(ServerNode.Builder.queue(name, 1, queue));
net1.addConnection(0, 1, 1.0);
return net1;
}