public static void main(String args[]) {
int NU = 0;
int NL = 0;
int num_tests = 0;
int num_trials = 0;
long seed = 0;
// Argument Validation
if (args.length != 5) {
System.out.println("Usage: java PingOverheadDecayTest <NU> <NL> <tests> <trials> <seed>");
System.exit(1);
}
try {
NU = Integer.parseInt(args[0]);
NL = Integer.parseInt(args[1]);
num_tests = Integer.parseInt(args[2]);
num_trials = Integer.parseInt(args[3]);
seed = Long.parseLong(args[4]);
} catch (Exception e) {
System.out.println("Error - All arguments must be numerical.");
System.exit(1);
}
if (NL < 1) {
System.out.println("Error - NL must be a positive number.");
System.exit(1);
}
if (NU <= NL) {
System.out.println("Error - NU must be greater than NL.");
System.exit(1);
}
Random seed_generator = new Random(seed);
ArrayList<ArrayList<Double>> tora_results = new ArrayList<ArrayList<Double>>(num_tests);
ArrayList<ArrayList<Double>> olsr_results = new ArrayList<ArrayList<Double>>(num_tests);
for (int test = 0; test < num_tests; test++) {
System.out.println("Test " + (test + 1) + "...");
tora_results.add(test, new ArrayList<Double>());
olsr_results.add(test, new ArrayList<Double>());
// make the MANET
Manet network = new UniformManet(seed_generator.nextLong());
network.generateNode();
for (int i = 1; i <= NU; i++) {
network.generateNode();
}
// Wrap it with the protocols
TORAWrapper tora = new TORAWrapper(network, seed_generator.nextLong());
OLSRWrapper olsr = new OLSRWrapper(network, seed_generator.nextLong());
for (int i = NU; i >= NL; i--) {
network.removeLastNode();
// GET OVERHEAD HERE
ListSeries toraBSeries = new ListSeries();
ListSeries olsrBSeries = new ListSeries();
for (int trial = 0; trial < num_trials; trial++) {
olsr.clearMetrics();
tora.clearMetrics();
Node source = olsr.getRandomNode();
Node destination = olsr.getRandomNode();
LinkedList<Node> olsr_path = olsr.ping(source, destination);
LinkedList<Node> tora_path = tora.ping(source, destination);
toraBSeries.add(tora_path.size());
olsrBSeries.add(olsr_path.size());
}
Series.Stats toraTrialsStats = toraBSeries.stats();
Series.Stats olsrTrialsStats = olsrBSeries.stats();
tora_results.get(test).add(toraTrialsStats.mean);
olsr_results.get(test).add(olsrTrialsStats.mean);
}
}
ListXYSeries tora_averages = new ListXYSeries();
ListXYSeries olsr_averages = new ListXYSeries();
System.out.println(" Throughput Averages ");
System.out.println("N Nodes TORA OLSR ");
int i = 0;
for (int n = NU; n >= NL; n--) {
if (n == 0) {
tora_averages.add(n, 0);
olsr_averages.add(n, 0);
continue;
}
ListSeries toraBSeries = new ListSeries();
ListSeries olsrBSeries = new ListSeries();
for (int t = 0; t < num_tests; t++) {
toraBSeries.add(tora_results.get(t).get(i));
olsrBSeries.add(olsr_results.get(t).get(i));
}
Series.Stats toraTestStats = toraBSeries.stats();
Series.Stats olsrTestStats = olsrBSeries.stats();
tora_averages.add(n, toraTestStats.mean);
olsr_averages.add(n, olsrTestStats.mean);
System.out.printf("%3d %7.2f %7.2f %n", n, toraTestStats.mean, olsrTestStats.mean);
i++;
}
System.out.println("-----------------------------------------");
double[] ttest =
Statistics.tTestUnequalVariance(tora_averages.ySeries(), olsr_averages.ySeries());
System.out.printf("T Value: %.3f P Value: %.3f %n", ttest[0], ttest[1]);
// Now that we ran through the tests, time to do some stats
new Plot()
.plotTitle("Throughput during Pings (Decay)")
.xAxisTitle("Nodes N in Network")
.yAxisTitle("Number of Hops")
.xAxisStart(NU)
.xAxisEnd(NL)
.seriesStroke(Strokes.solid(1))
.seriesDots(null)
.seriesColor(Color.RED)
.xySeries(tora_averages)
.seriesStroke(Strokes.solid(1))
.seriesColor(Color.BLUE)
.xySeries(olsr_averages)
.getFrame()
.setVisible(true);
}
public static void main(String args[]) {
int NL = 0;
int NU = 0;
int num_tests = 0;
long seed = 0;
if (args.length != 4) {
System.out.println("Usage: java DecayOverheadTest <NU> <NL> <tests> <seed>");
System.exit(1);
}
try {
NU = Integer.parseInt(args[0]);
NL = Integer.parseInt(args[1]);
num_tests = Integer.parseInt(args[2]);
seed = Long.parseLong(args[3]);
} catch (Exception e) {
System.out.println("Error - All arguments must be numerical.");
System.exit(1);
}
if (NL < 1) {
System.out.println("Error - NL must be a positive number.");
System.exit(1);
}
if (NU <= NL) {
System.out.println("Error - NU must be greater than NL.");
System.exit(1);
}
Random seed_generator = new Random(seed);
ArrayList<ArrayList<Integer>> tora_results = new ArrayList<ArrayList<Integer>>(num_tests);
ArrayList<ArrayList<Integer>> olsr_results = new ArrayList<ArrayList<Integer>>(num_tests);
for (int test = 0; test < num_tests; test++) {
System.out.println("Test " + (test + 1) + "...");
tora_results.add(test, new ArrayList<Integer>(NU - NL));
olsr_results.add(test, new ArrayList<Integer>(NU - NL));
ArrayList<Integer> tora_test_results = tora_results.get(test);
ArrayList<Integer> olsr_test_results = olsr_results.get(test);
// make the MANET
Manet network = new UniformManet(seed_generator.nextLong());
network.generateNode();
for (int i = NL; i <= NU; i++) {
network.generateNode();
}
// Wrap it with the protocols
TORAWrapper tora = new TORAWrapper(network, seed_generator.nextLong());
OLSRWrapper olsr = new OLSRWrapper(network, seed_generator.nextLong());
for (int i = NU; i >= NL; i--) {
network.removeLastNode();
// GET OVERHEAD HERE
int tora_overhead = tora.getTotalPacketsRecieved();
int olsr_overhead = olsr.getTotalPacketsRecieved();
tora_test_results.add(tora_overhead);
olsr_test_results.add(olsr_overhead);
}
}
// Now that we ran through the tests, time to do some stats
ListXYSeries tora_averages = new ListXYSeries();
ListXYSeries olsr_averages = new ListXYSeries();
System.out.println(" Overhead Averages ");
System.out.println("N Nodes TORA OLSR ");
int i = 0;
for (int n = NU; n >= NL; n--) {
double n_tora_average = 0.0;
double n_olsr_average = 0.0;
for (int j = 0; j < num_tests; j++) {
n_tora_average = n_tora_average + tora_results.get(j).get(i);
n_olsr_average = n_olsr_average + olsr_results.get(j).get(i);
}
n_tora_average = n_tora_average / num_tests;
n_olsr_average = n_olsr_average / num_tests;
tora_averages.add(n, n_tora_average);
olsr_averages.add(n, n_olsr_average);
System.out.printf("%3d %7.2f %7.2f %n", n, n_tora_average, n_olsr_average);
i++;
}
System.out.println("-----------------------------------------");
double[] ttest =
Statistics.tTestUnequalVariance(tora_averages.ySeries(), olsr_averages.ySeries());
System.out.printf("T Value: %.3f P Value: %.3f %n", ttest[0], ttest[1]);
new Plot()
.plotTitle("Message Overhead during Network Decay")
.xAxisTitle("Nodes N in Network")
.yAxisTitle("Number of Messages Recieved")
.xAxisStart(NU)
.xAxisEnd(NL)
.seriesStroke(Strokes.solid(1))
.seriesDots(null)
.seriesColor(Color.RED)
.xySeries(tora_averages)
.seriesStroke(Strokes.solid(1))
.seriesColor(Color.BLUE)
.xySeries(olsr_averages)
.getFrame()
.setVisible(true);
}