- rewritten all the sim code in a way to make easier to read and collect stats
This commit is contained in:
2025-01-17 12:29:47 +01:00
parent f0b6cbfba3
commit 0d541f7737
5 changed files with 302 additions and 1 deletions

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package net.berack.upo.valpre;
public class Event implements Comparable<Event> {
public final double time;
public final Type type;
public final ServerNode node;
private Event(Type type, ServerNode node, double time) {
this.type = type;
this.time = time;
this.node = node;
}
public int compareTo(Event other) {
if (this.time < other.time)
return -1;
if (this.time == other.time)
return 0;
return 1;
}
public static Event newArrival(ServerNode node, double time) {
return new Event(Type.ARRIVAL, node, time);
}
public static Event newDeparture(ServerNode node, double time) {
return new Event(Type.DEPARTURE, node, time);
}
public static enum Type {
ARRIVAL,
DEPARTURE,
}
}

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@@ -1,7 +1,34 @@
package net.berack.upo.valpre;
import net.berack.upo.valpre.rand.Distribution;
public class Main {
public static void main(String[] args) {
System.out.println("Hello world!");
// Build the network
var node1 = ServerNode.createSource("Source", new Distribution.Exponential(1.0 / 4.5));
var node2 = ServerNode.createQueue("Queue", 1, new Distribution.NormalBoxMuller(3.2, 0.6));
node1.addChild(node2, 1.0);
/// Run the simulation
var sim = new NetSimulation(System.nanoTime());
sim.addNode(node1);
sim.addNode(node2);
var results = sim.run(1000, "Queue");
// Display the results
for (var entry : results.entrySet()) {
var stats = entry.getValue();
var size = (int) Math.ceil(Math.max(Math.log10(stats.numArrivals), Math.log10(stats.lastEventTime)));
var iFormat = "%" + size + "d";
var fFormat = "%" + (size + 4) + ".3f";
System.out.println("===== " + entry.getKey() + " =====");
System.out.printf(" Arrivals: \t" + iFormat + "\n", stats.numArrivals);
System.out.printf(" Departures:\t" + iFormat + "\n", stats.numDepartures);
System.out.printf(" Max Queue: \t" + iFormat + "\n", stats.maxQueueLength);
System.out.printf(" Response: \t" + fFormat + "\n", stats.responseTime / stats.numDepartures);
System.out.printf(" Busy %%: \t" + fFormat + "\n", stats.busyTime * 100 / stats.lastEventTime);
System.out.printf(" Last Event:\t" + fFormat + "\n", stats.lastEventTime);
}
}
}

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package net.berack.upo.valpre;
import java.util.ArrayDeque;
import java.util.HashMap;
import java.util.Map;
import java.util.PriorityQueue;
import net.berack.upo.valpre.rand.Rng;
public class NetSimulation {
public final long seed;
private final Rng rng;
private final Map<String, ServerNode> servers = new HashMap<>();
public NetSimulation(long seed) {
this.seed = seed;
this.rng = new Rng(seed);
}
public void addNode(ServerNode node) {
this.servers.put(node.name, node);
}
public Map<String, Statistics> run(long total, String untilDepartureNode) {
// Initialization
var timeNow = 0.0d;
var stats = new HashMap<String, Statistics>();
var fel = new PriorityQueue<Event>();
for (var node : this.servers.values()) {
var s = new Statistics(this.rng);
s.addArrivalIf(node.isSource, node, timeNow, fel);
stats.put(node.name, s);
}
// Main Simulation Loop
var nodeStop = stats.get(untilDepartureNode);
while (nodeStop.numDepartures < total) {
var event = fel.poll();
if (event == null) {
break;
}
timeNow = event.time;
var statsNode = stats.get(event.node.name);
switch (event.type) {
case ARRIVAL -> statsNode.processArrival(event, timeNow, fel);
case DEPARTURE -> statsNode.processDeparture(event, timeNow, fel);
}
}
return stats;
}
public static class Statistics {
public int numArrivals = 0;
public int numDepartures = 0;
public int maxQueueLength = 0;
public double busyTime = 0.0;
public double responseTime = 0.0;
public double lastEventTime = 0.0;
private int numServerBusy = 0;
private ArrayDeque<Double> queue = new ArrayDeque<>();
private final Rng rng;
public Statistics(Rng rng) {
this.rng = rng;
}
public void reset() {
this.numArrivals = 0;
this.numDepartures = 0;
this.numServerBusy = 0;
this.busyTime = 0.0;
this.responseTime = 0.0;
this.queue.clear();
}
private void processArrival(Event event, double timeNow, PriorityQueue<Event> fel) {
this.numArrivals++;
this.queue.add(event.time);
this.maxQueueLength = Math.max(this.maxQueueLength, this.queue.size());
if (event.node.maxServers > this.numServerBusy) {
this.numServerBusy++;
var time = event.node.distribution.sample(this.rng);
var departure = Event.newDeparture(event.node, timeNow + time);
fel.add(departure);
} else {
this.busyTime += timeNow - this.lastEventTime;
}
this.lastEventTime = timeNow;
this.addArrivalIf(event.node.isSource, event.node, timeNow, fel);
}
private void processDeparture(Event event, double timeNow, PriorityQueue<Event> fel) {
var startService = this.queue.poll();
var response = timeNow - startService;
if (this.queue.size() < this.numServerBusy) {
this.numServerBusy--;
} else {
var time = event.node.distribution.sample(this.rng);
var departure = Event.newDeparture(event.node, timeNow + time);
fel.add(departure);
}
this.numDepartures++;
this.responseTime += response;
this.busyTime += timeNow - this.lastEventTime;
this.lastEventTime = timeNow;
var next = event.node.getChild(rng);
this.addArrivalIf(!event.node.isSink, next, timeNow, fel);
}
private void addArrivalIf(boolean condition, ServerNode node, double timeNow, PriorityQueue<Event> fel) {
if (condition && node != null) {
var delay = node.distribution.sample(this.rng);
fel.add(Event.newArrival(node, timeNow + delay));
}
}
}
}

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package net.berack.upo.valpre;
import java.util.ArrayList;
import java.util.List;
import net.berack.upo.valpre.rand.Distribution;
import net.berack.upo.valpre.rand.Rng;
public class ServerNode {
public final String name;
public final int maxServers;
public final Distribution distribution;
public final boolean isSink;
public final boolean isSource;
private final List<NodeChild> children = new ArrayList<>();
private double sumProbabilities = 0.0;
public static ServerNode createSource(String name, Distribution distribution) {
return new ServerNode(name, Integer.MAX_VALUE, distribution, false, true);
}
public static ServerNode createQueue(String name, int maxServers, Distribution distribution) {
return new ServerNode(name, maxServers, distribution, false, false);
}
public ServerNode(String name, int maxServers, Distribution distribution, boolean isSink, boolean isSource) {
this.name = name;
this.maxServers = maxServers;
this.distribution = distribution;
this.isSink = isSink;
this.isSource = isSource;
}
public void addChild(ServerNode node, double probability) {
this.children.add(new NodeChild(node, probability));
this.sumProbabilities += probability;
}
public ServerNode getChild(Rng rng) {
var random = rng.random();
for (var child : this.children) {
random -= child.probability / this.sumProbabilities;
if (random <= 0) {
return child.node;
}
}
return null;
}
public static class NodeChild {
public final ServerNode node;
public final double probability;
public NodeChild(ServerNode node, double probability) {
this.node = node;
this.probability = probability;
}
}
}

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package net.berack.upo.valpre.rand;
public interface Distribution {
public double sample(Rng rng);
public static class Exponential implements Distribution {
private final double lambda;
public Exponential(double lambda) {
this.lambda = lambda;
}
@Override
public double sample(Rng rng) {
return -Math.log(rng.random()) / lambda;
}
}
public static class Normal implements Distribution {
private final double mean;
private final double sigma;
public Normal(double mean, double sigma) {
this.mean = mean;
this.sigma = sigma;
}
@Override
public double sample(Rng rng) {
var sample = rng.random();
return mean + sigma * Math.sqrt(-2 * Math.log(sample)) * Math.cos(2 * Math.PI * sample);
}
}
public static class NormalBoxMuller implements Distribution {
private final double mean;
private final double sigma;
private double next = Double.NaN;
public NormalBoxMuller(double mean, double sigma) {
this.mean = mean;
this.sigma = sigma;
}
@Override
public double sample(Rng rng) {
if (!Double.isNaN(next)) {
var sample = next;
next = Double.NaN;
return sample;
}
var sample1 = rng.random();
var sample2 = rng.random();
next = mean + sigma * Math.sqrt(-2 * Math.log(sample1)) * Math.sin(2 * Math.PI * sample2);
return mean + sigma * Math.sqrt(-2 * Math.log(sample1)) * Math.cos(2 * Math.PI * sample2);
}
}
}