public void TestCECountermeasureSelectionFDS()
{
var input = File.ReadAllText("/Users/acailliau/Google Drive/PhD/Dissertation/running-example-fds/model2.kaos");
ModelBuilder parser = new ModelBuilder();
var model = parser.Parse(input);
var optimizer = new MOCECountermeasureSelectionOptimizer(model);
var propagator = new BDDBasedPropagator(model);
var root = model.Goal("locals_warned_when_risk_imminent");
var sr = (DoubleSatisfactionRate)propagator.GetESR(root);
Console.WriteLine("Satisfaction Rate without countermeasures: " + sr.SatisfactionRate);
Console.WriteLine("Required Satisfaction Rate: " + root.RDS);
var optimalSelections = optimizer.GetOptimalSelections(root, propagator);
if (optimalSelections.Count() == 0)
{
Console.WriteLine("Optimal selections: No countermeasure to select.");
Console.WriteLine();
}
else
{
Console.WriteLine($"Optimal selections ({optimalSelections.Count()}):");
foreach (var o in optimalSelections.Distinct().OrderBy(x => x.Cost).ThenBy(x => x.SatisfactionRate))
{
Console.WriteLine("* " + o);
}
}
}
public void TestCECountermeasureSelection2()
{
const string Path1 = "/Users/acailliau/Google Drive/PhD/Dissertation/case-studies/ambulance-dispatching-system/Models/runtime.kaos";
var input = File.ReadAllText(Path1);
//input = @"declare goal [ root ] rsr .75 refinedby child1, child2 end
//declare goal [ child1 ] obstructedby o1 end
//declare goal [ child2 ] obstructedby o2 end
//declare obstacle [ o1 ]
// probability .2
// resolvedby [substitution:root] cm1
//end
//declare obstacle [ o2 ]
// refinedby so1
// refinedby so2
//end
//declare obstacle [ so1 ]
// probability .1
// resolvedby [substitution:root] cm2
//end
//declare obstacle [ so2 ]
// probability .3
// resolvedby [substitution:root] cm3
//end";
ModelBuilder parser = new ModelBuilder();
var model = parser.Parse(input, Path1);
var optimizer = new MOCECountermeasureSelectionOptimizer(model);
var propagator = new BDDBasedPropagator(model);
var root = model.Goal("achieve_incident_resolved");
var sr = (DoubleSatisfactionRate)propagator.GetESR(root);
Console.WriteLine("Satisfaction Rate without countermeasures: " + sr.SatisfactionRate);
Console.WriteLine("Required Satisfaction Rate: " + root.RDS);
//var minCost = optimizer.GetMinimalCost(root, propagator);
//Console.WriteLine("Minimal cost: " + minCost);
var optimalSelections = optimizer.GetOptimalSelections(root, propagator);
if (optimalSelections.Count() == 0)
{
Console.WriteLine("Optimal selections: No countermeasure to select.");
Console.WriteLine();
}
else
{
Console.WriteLine($"Optimal selections ({optimalSelections.Count()}):");
foreach (var o in optimalSelections.Distinct().OrderBy(x => x.Cost).ThenBy(x => x.SatisfactionRate))
{
Console.WriteLine("* " + o);
}
}
}
static void OptimizeLoop()
{
var factory = new ConnectionFactory()
{
HostName = "localhost"
};
var currentSelection = new HashSet <string> ();
using (var connection = factory.CreateConnection())
using (var channel = connection.CreateModel())
{
channel.QueueDeclare(queue: kaos_cm_selection_queue_name,
durable: false,
exclusive: false,
autoDelete: false,
arguments: null);
var _propagator_optimization = new BDDBasedPropagator(model);
while (!stop)
{
Thread.Sleep(TimeSpan.FromMinutes(1));
bool optimization_required = false;
foreach (var root in roots)
{
var doubleSatisfactionRate = modelMonitor.RootSatisfactionRates[root.Identifier];
if (doubleSatisfactionRate == null)
{
logger.Info($"Ignoring '{root.Identifier}', no satisfaction rate monitored.");
continue;
}
logger.Info($"RSR = " + root.RDS);
if (doubleSatisfactionRate.SatisfactionRate >= root.RDS)
{
logger.Info("Current configuration is above RSR for " + root.FriendlyName + ".");
}
else
{
logger.Info("Current configuration is below RSR for " + root.FriendlyName + ".");
optimization_required = true;
}
}
if (!optimization_required)
{
continue;
}
//var minimalcost = optimizer.GetMinimalCost(roots, _propagator_optimization);
//var optimalSelections = optimizer.GetOptimalSelections(minimalcost, roots, _propagator_optimization).FirstOrDefault();
var optimizer = new MOCECountermeasureSelectionOptimizer(optimization_model);
optimization_model.satisfactionRateRepository = modelMonitor._model_running.satisfactionRateRepository;
Console.WriteLine("Computing optimization");
var propagator = new BDDBasedPropagator(optimization_model);
var enumerable = new HashSet <Goal> (optimization_model.Goals(x => roots.Select(y => y.Identifier).Contains(x.Identifier)));
var optimalSelections = optimizer.GetOptimalSelections(enumerable, propagator);
if (optimalSelections.Count() == 0)
{
Console.WriteLine("Optimal selections: No countermeasure to select.");
Console.WriteLine();
}
else
{
Console.WriteLine($"Optimal selections ({optimalSelections.Count()}):");
foreach (var o in optimalSelections.Distinct().OrderBy(x => x.Cost).ThenBy(x => x.SatisfactionRate))
{
Console.WriteLine("* " + o);
}
}
if (optimalSelections.Count() > 0)
{
var optimalSelection = optimalSelections
.Where(x => x.SatRoots.SetEquals(roots.Select(y => y.Identifier)))
.OrderBy(x => x.Cost)
.ThenByDescending(x => x.SatisfactionRate)
.FirstOrDefault();
if (optimalSelection == null)
{
optimalSelection = optimalSelections
.OrderByDescending(x => x.SatRoots.Count)
.ThenBy(x => x.Cost)
.ThenByDescending(x => x.SatisfactionRate)
.FirstOrDefault();
}
if (optimalSelection == null)
{
logger.Info("No optimal selection found!");
return;
}
// Update the model
var deployment_methods = new List <string>();
foreach (var resolution in optimalSelection.Resolutions.Except(_active_resolutions))
{
_integrator_model.Integrate(resolution);
deployment_methods.Add(resolution.ResolvingGoal().CustomData["ondeploy"]);
}
foreach (var resolution in optimalSelection.Resolutions.Intersect(_active_resolutions))
{
_integrator_model.Remove(resolution);
deployment_methods.Add(resolution.ResolvingGoal().CustomData["onwithold"]);
}
modelMonitor.ModelChanged();
_active_resolutions = optimalSelection.Resolutions.ToHashSet();
// Deploy the countermeasures in the running system
var json = new JavaScriptSerializer().Serialize(deployment_methods);
logger.Info(json);
var body = Encoding.UTF8.GetBytes(json);
channel.BasicPublish(exchange: "",
routingKey: kaos_cm_selection_queue_name,
basicProperties: null,
body: body);
}
else
{
logger.Info("No selection found!");
}
}
}
}
public void TestCECountermeasureSelection()
{
var input = @"declare goal [ root ] rsr .75 refinedby child1, child2 end
declare goal [ child1 ] obstructedby o1 end
declare goal [ child2 ] obstructedby o2 end
declare obstacle [ o1 ]
probability .2
refinedby so4
refinedby so5, so6
end
declare obstacle [ so4 ]
probability .1
end
declare obstacle [ so5 ]
probability .4
resolvedby [substitution:root] cm5
end
declare obstacle [ so6 ]
probability .4
resolvedby [substitution:root] cm4
end
declare obstacle [ o2 ]
refinedby so1
refinedby so2
end
declare obstacle [ so1 ]
probability .1
resolvedby [substitution:root] cm2
end
declare obstacle [ so2 ]
probability .3
resolvedby [substitution:root] cm3
end
declare obstacle [ so3 ]
probability .4
resolvedby [substitution:root] cm4
end
";
//input = @"declare goal [ root ] rsr .75 refinedby child1, child2 end
//declare goal [ child1 ] obstructedby o1 end
//declare goal [ child2 ] obstructedby o2 end
//declare obstacle [ o1 ]
// probability .2
// resolvedby [substitution:root] cm1
//end
//declare obstacle [ o2 ]
// refinedby so1
// refinedby so2
//end
//declare obstacle [ so1 ]
// probability .1
// resolvedby [substitution:root] cm2
//end
//declare obstacle [ so2 ]
// probability .3
// resolvedby [substitution:root] cm3
//end";
ModelBuilder parser = new ModelBuilder();
var model = parser.Parse(input);
var optimizer = new MOCECountermeasureSelectionOptimizer(model);
var propagator = new BDDBasedPropagator(model);
var root = model.Goal("root");
var sr = (DoubleSatisfactionRate)propagator.GetESR(root);
Console.WriteLine("Satisfaction Rate without countermeasures: " + sr.SatisfactionRate);
Console.WriteLine("Required Satisfaction Rate: " + root.RDS);
//var minCost = optimizer.GetMinimalCost(root, propagator);
//Console.WriteLine("Minimal cost: " + minCost);
var optimalSelections = optimizer.GetOptimalSelections(root, propagator);
if (optimalSelections.Count() == 0)
{
Console.WriteLine("Optimal selections: No countermeasure to select.");
Console.WriteLine();
}
else
{
Console.WriteLine($"Optimal selections ({optimalSelections.Count()}):");
foreach (var o in optimalSelections.Distinct().OrderBy(x => x.Cost).ThenBy(x => x.SatisfactionRate))
{
Console.WriteLine("* " + o);
}
}
}