ag_gnetwork.m

%% G-Network (Gelenbe Network) with Negative Customers
%
% This example demonstrates MAM with RCAT methods on a G-network with negative customers.
% Negative customers (signals) remove jobs from queues when they arrive,
% modeling job cancellations or service interrupts.
%
% Network topology:
%   - Source generates positive customers (Class1) and negative signals (Class2)
%   - Positive customers flow: Source -> Queue1 -> Queue2 -> Sink
%   - Negative signals target Queue2, removing jobs from it
%
% Reference: Gelenbe, E. (1991). "Product-form queueing networks with
%            negative and positive customers", Journal of Applied Probability
%
% Copyright (c) 2012-2025, Imperial College London
% All rights reserved.
 
clear; clc;
 
%% Parameters
lambda_pos = 1.0;   % Positive customer arrival rate
lambda_neg = 0.3;   % Negative signal arrival rate
mu1 = 2.0;          % Service rate at Queue1
mu2 = 3.0;          % Service rate at Queue2
 
%% Create model
model = Network('GNetwork-Example');
 
source = Source(model, 'Source');
queue1 = Queue(model, 'Queue1', SchedStrategy.FCFS);
queue2 = Queue(model, 'Queue2', SchedStrategy.FCFS);
sink = Sink(model, 'Sink');
 
% Positive customer class (normal jobs)
posClass = OpenClass(model, 'Positive');
source.setArrival(posClass, Exp(lambda_pos));
queue1.setService(posClass, Exp(mu1));
queue2.setService(posClass, Exp(mu2));
 
% Negative signal class (removes jobs from target queue)
% Using Signal class with SignalType.NEGATIVE for automatic G-network handling
negClass = Signal(model, 'Negative', SignalType.NEGATIVE);
source.setArrival(negClass, Exp(lambda_neg));
queue1.setService(negClass, Exp(mu1));  % Signals also get "served" (trigger)
queue2.setService(negClass, Exp(mu2));
 
% Set routing matrix
P = model.initRoutingMatrix();
% Positive customers: Source -> Queue1 -> Queue2 -> Sink
P{posClass, posClass}(source, queue1) = 1.0;
P{posClass, posClass}(queue1, queue2) = 1.0;
P{posClass, posClass}(queue2, sink) = 1.0;
% Negative signals: Source -> Queue1, then from Queue1 they target Queue2
P{negClass, negClass}(source, queue1) = 1.0;
P{negClass, negClass}(queue1, queue2) = 1.0;  % Signal sent to Queue2 (removes job)
P{negClass, negClass}(queue2, sink) = 1.0;
model.link(P);
 
%% Solve with MAM using INAP method
solverMAM = MAM(model, 'method', 'inap');
avgTableMAM = solverMAM.getAvgTable();
disp(avgTableMAM);