Env.m

classdef Env < Ensemble
    % An environment model defined by a collection of network sub-models
    % coupled with an environment transition rule that selects the active
    % sub-model.
    %
    % Copyright (c) 2012-2026, Imperial College London
    % All rights reserved.
    
    properties
        env;
        envGraph;
        proc; % Markovian representation of each stage transition
        holdTime; % holding times
        probEnv; % steady-stage probability of the environment
        probOrig; % probability that a request originated from phase
        resetFun; % function implementing the reset policy for queue lengths
        resetEnvRatesFun; % function implementing the reset policy for environment rates
    end
    
    methods
        function self = Env(name)
            % SELF = ENVIRONMENT(MODELS, ENV)
            self@Ensemble({});
            self.name = name;
            self.envGraph = digraph();
            self.envGraph.Nodes.Model = cell(0);
            self.envGraph.Nodes.Type = cell(0);
        end
        
        function name = addStage(self, name, type, model)            
            wcfg = warning; % store warning configuration
            warning('off','MATLAB:table:RowsAddedExistingVars');
            self.envGraph = self.envGraph.addnode(name);
            warning(wcfg); % restore warning configuration
            self.envGraph.Nodes.Model{end} = model;
            self.envGraph.Nodes.Type{end} = type;
            E = height(self.envGraph.Nodes);
            if E>1
                if self.envGraph.Nodes.Model{1}.getNumberOfStatefulNodes ~= model.getNumberOfStatefulNodes
                    line_error(mfilename,'Unsupported feature. Random environment stages must map to networks with identical number of stateful nodes.');
                end
            end
            for e=E
                for h=1:E
                    self.env{e,h} = Disabled.getInstance();
                    self.env{h,e} = Disabled.getInstance();
                end
            end
            self.ensemble{E} = model;
        end
        
        function self = addTransition(self, fromName, toName, distrib, resetFun, resetEnvRatesFun)
           self.envGraph = self.envGraph.addedge(fromName, toName);
           e = self.envGraph.findnode(fromName);
           h = self.envGraph.findnode(toName);
           self.env{e,h} = distrib;
           if nargin<5 %~exist('resetFun','var')
                self.resetFun{e,h} = @(q) q;
           else
                self.resetFun{e,h} = resetFun;
           end
           if nargin<6 %~exist('resetEnvRatesFun','var')
                self.resetEnvRatesFun{e,h} = @(originalDist, QExit, UExit, TExit) originalDist;
           else
                self.resetEnvRatesFun{e,h} = resetEnvRatesFun;
           end
        end
        
        function init(self)
            E = height(self.envGraph.Nodes);
            T = height(self.envGraph.Edges);
            Pemb = zeros(E);
 
            for t=1:T
                e = self.envGraph.findnode(self.envGraph.Edges.EndNodes{t,1});
                h = self.envGraph.findnode(self.envGraph.Edges.EndNodes{t,2});
                self.envGraph.Edges.Distribution{t} = self.env{e,h};
            end
            
            % analyse holding times
            emmap = cell(E,1);
            for e=1:E
                emmap{e} = cell(1,E);
            end
            self.holdTime = {};
            for e=1:E
                for h=1:E
                    if isa(self.env{e,h},'Disabled')
                        emmap{e}{h} = {0,0}; % multiclass MMAP representation
                    else
                        emmap{e}{h} = self.env{e,h}.getProcess; % multiclass MMAP representation
                    end
                    for j = 1:E
                        if j == h
                            emmap{e}{h}{2+j} = emmap{e}{h}{2};
                        else
                            emmap{e}{h}{2+j} = 0 * emmap{e}{h}{2};
                        end
                    end
                end
                self.holdTime{e} = emmap{e}{e};
                for h=setdiff(1:E,e)
                    self.holdTime{e}{1} = krons(self.holdTime{e}{1},emmap{e}{h}{1});
                    for j = 2:(E+2)
                        self.holdTime{e}{j} = krons(self.holdTime{e}{j},emmap{e}{h}{j});
                        completion_rates = self.holdTime{e}{j}*ones(length(self.holdTime{e}{j}),1);
                        self.holdTime{e}{j} = 0*self.holdTime{e}{j};
                        self.holdTime{e}{j}(:,1) = completion_rates;
                    end
                    self.holdTime{e} = mmap_normalize(self.holdTime{e});
                end
                count_lambda = mmap_count_lambda(self.holdTime{e}); % completiom rates for the different transitions
                Pemb(e,:) = count_lambda/sum(count_lambda);
            end
            self.proc = emmap;
            
            %
            lambda = zeros(1,E);
            A = zeros(E); I=eye(E);
            for e=1:E
                lambda(e) = 1/map_mean(self.holdTime{e});
                for h=1:E
                    A(e,h) = -lambda(e)*(I(e,h)-Pemb(e,h));
                end
            end
            
            if all(lambda>0)
                penv = ctmc_solve_reducible(A);
                self.probEnv = penv;
                self.probOrig = zeros(E);
                for e = 1:E
                    for h = 1:E
                        self.probOrig(h,e) = penv(h) * lambda(h) * Pemb(h,e);
                    end
                    if penv(e) > 0
                        self.probOrig(:,e) = self.probOrig(:,e) / sum(self.probOrig(:,e));
                    end
                end
            else
                %T = A(lambda>0, lambda>0), % subgenerator
                %t = A(lambda>0, lambda==0), % exit vector
            end
        end
        
        function env = getEnv(self)
            env = self.env;
        end
        
        function self = setEnv(self, env)
            self.envGraph = env;
        end
        
        function self = setStageName(self, stageId, name)
            self.stageNames{stageId} = name;
        end
                
        function self = setStageType(self, stageId, stageCategory)                      
            if ischar(stageCategory)
                self.stageTypes(stageId) = categorical(stageCategory);
            elseif iscategorical(stageCategory)
                self.stageTypes(stageId) = stageCategory;
            else
                line_error(mfilename,'Stage type must be of type categorical, e.g., categorical("My Semantics").');
            end
        end
        
        function ET = getStageTable(self)
            E = height(self.envGraph.Nodes);
            Stage = [];
            HoldT = {};
            type = categorical([]);
            if isempty(self.probEnv)
                self.init;
            end
            for e=1:E
                Stage(e,1) = e;
                type(e,1) = self.envGraph.Nodes.Type{e};
            end
            Prob = self.probEnv(:);
            Name = categorical(self.envGraph.Nodes.Name(:));
            Model = self.ensemble(:);
            for e=1:E
                HoldT{e,1} = self.holdTime{e};
            end
            Type = type;
            ET = Table(Stage, Name, Type, Prob, HoldT, Model);
        end
 
        function ET = getStageT(self)
            % GETSTAGET Short alias for getStageTable
            ET = self.getStageTable();
        end
 
        function RT = getReliabilityTable(self)
            % RT = GETRELIABILITYTABLE()
            % Compute system-wide reliability metrics (MTTF, MTTR, MTBF, Availability)
            %
            % Returns:
            %   RT - Table with columns: Metric, Value, Unit, Description
            %
            % Example:
            %   env = Env('ServerEnv');
            %   env.addNodeFailureRepair(model, 'Server', Exp(0.1), Exp(1.0), Exp(0.5));
            %   env.init();
            %   reliabilityTable = env.getReliabilityTable();
 
            % Step 1: Initialize and validate
            if isempty(self.probEnv)
                self.init();
            end
 
            E = height(self.envGraph.Nodes);
            if E == 0
                line_error(mfilename, 'Environment has no stages. Add stages before computing reliability metrics.');
            end
 
            % Step 2: Identify stage types
            stageNames = self.envGraph.Nodes.Name;
            upIdx = find(strcmp(stageNames, 'UP'));
 
            if isempty(upIdx)
                line_error(mfilename, 'No UP stage found. Use addNodeBreakdown/addNodeRepair to configure breakdown/repair transitions.');
            end
 
            % Find all DOWN stages
            downIdx = find(startsWith(stageNames, 'DOWN_'));
 
            if isempty(downIdx)
                line_error(mfilename, 'No DOWN stages found. Use addNodeBreakdown/addNodeRepair to configure breakdown/repair transitions.');
            end
 
            % Step 3: Extract breakdown rates (UP -> DOWN_*)
            breakdownRates = [];
            for h = downIdx'
                if ~isa(self.env{upIdx, h}, 'Disabled')
                    lambda_h = 1 / self.env{upIdx, h}.getMean();
                    breakdownRates(end+1) = lambda_h;
                end
            end
 
            if isempty(breakdownRates)
                line_error(mfilename, 'No breakdown transitions found (UP -> DOWN_*).');
            end
 
            % Total failure rate (competing risks)
            lambda_total = sum(breakdownRates);
            MTTF = 1 / lambda_total;
 
            % Step 4: Extract repair rates (DOWN_* -> UP)
            repairRates = [];
            downProbs = [];
 
            for e = downIdx'
                if ~isa(self.env{e, upIdx}, 'Disabled')
                    mu_e = 1 / self.env{e, upIdx}.getMean();
                    repairRates(end+1) = mu_e;
                    downProbs(end+1) = self.probEnv(e);
                end
            end
 
            if isempty(repairRates)
                line_error(mfilename, 'No repair transitions found (DOWN_* -> UP).');
            end
 
            % Normalize probabilities over DOWN states only
            totalDownProb = sum(downProbs);
            if totalDownProb > 0
                downProbsNorm = downProbs / totalDownProb;
                % Weighted average repair time
                MTTR = sum(downProbsNorm ./ repairRates);
            else
                % Fallback: simple average if no steady-state probability
                MTTR = mean(1 ./ repairRates);
            end
 
            % Step 5: Compute derived metrics
            MTBF = MTTF + MTTR;
 
            % Availability from steady-state probabilities
            availUp = self.probEnv(upIdx);
            availDown = sum(self.probEnv(downIdx));
            Availability = availUp / (availUp + availDown);
 
            % Step 6: Create output table
            Metric = categorical({'MTTF'; 'MTTR'; 'MTBF'; 'Availability'});
            Value = [MTTF; MTTR; MTBF; Availability];
            Unit = categorical({'time units'; 'time units'; 'time units'; 'probability'});
            Description = categorical({
                'Mean time to failure (UP -> DOWN)';
                'Mean time to repair (DOWN -> UP)';
                'Mean time between failures (MTTF + MTTR)';
                'Steady-state probability of UP state'
            });
 
            RT = Table(Metric, Value, Unit, Description);
        end
 
        function self = addNodeBreakdown(self, baseModel, nodeName, breakdownDist, downServiceDist, varargin)
            % SELF = ADDNODEBREAKDOWN(BASEMODEL, NODENAME, BREAKDOWNDIST, DOWNSERVICEDIST, RESETFUN)
            % Adds UP and DOWN stages for a node that can break down and repair
            %
            % Parameters:
            %   baseModel - The base network model with normal (UP) service rates
            %   nodeName - Name of the node that can break down
            %   breakdownDist - Distribution for time until breakdown (UP->DOWN transition)
            %   downServiceDist - Service distribution when the node is down
            %   resetFun - (Optional) Function to reset queue lengths on breakdown
            %              Default: @(q) q (no reset)
            %
            % Example:
            %   model = Network('MyNetwork');
            %   queue = Queue(model, 'Server1', SchedStrategy.FCFS);
            %   class = ClosedClass(model, 'Jobs', 10, queue, 0);
            %   queue.setService(class, Exp(2)); % UP service rate
            %
            %   env = Env('ServerEnv');
            %   env.addNodeBreakdown(model, 'Server1', Exp(0.1), Exp(0.5));
 
            if nargin < 6
                resetFun = @(q) q;
            else
                resetFun = varargin{1};
            end
 
            % Create UP stage (if this is the first call)
            if height(self.envGraph.Nodes) == 0
                upModel = baseModel.copy();
                self.addStage('UP', 'operational', upModel);
            end
 
            % Create DOWN stage with modified service rate for the specified node
            downModel = baseModel.copy();
            nodes = downModel.getNodes();
            nodeIdx = [];
            for i = 1:length(nodes)
                if strcmp(nodes{i}.name, nodeName)
                    nodeIdx = i;
                    break;
                end
            end
 
            if isempty(nodeIdx)
                line_error(mfilename, sprintf('Node "%s" not found in the base model.', nodeName));
            end
 
            % Update service distribution for the down node
            classes = downModel.getClasses();
            for c = 1:length(classes)
                nodes{nodeIdx}.setService(classes{c}, downServiceDist);
            end
 
            % Add DOWN stage
            downStageName = sprintf('DOWN_%s', nodeName);
            self.addStage(downStageName, 'failed', downModel);
 
            % Add breakdown transition (UP -> DOWN)
            self.addTransition('UP', downStageName, breakdownDist, resetFun);
        end
 
        function self = addNodeRepair(self, nodeName, repairDist, varargin)
            % SELF = ADDNODEREPAIR(NODENAME, REPAIRDIST, RESETFUN)
            % Adds repair transition from DOWN to UP stage for a previously added breakdown
            %
            % Parameters:
            %   nodeName - Name of the node that can be repaired
            %   repairDist - Distribution for repair time (DOWN->UP transition)
            %   resetFun - (Optional) Function to reset queue lengths on repair
            %              Default: @(q) q (no reset)
            %
            % Example:
            %   env.addNodeRepair('Server1', Exp(1.0));
 
            if nargin < 4
                resetFun = @(q) q;
            else
                resetFun = varargin{1};
            end
 
            downStageName = sprintf('DOWN_%s', nodeName);
 
            % Verify DOWN stage exists
            if isempty(self.envGraph.findnode(downStageName))
                line_error(mfilename, sprintf('DOWN stage for node "%s" not found. Call addNodeBreakdown first.', nodeName));
            end
 
            % Add repair transition (DOWN -> UP)
            self.addTransition(downStageName, 'UP', repairDist, resetFun);
        end
 
        function self = addNodeFailureRepair(self, baseModel, nodeName, breakdownDist, repairDist, downServiceDist, varargin)
            % SELF = ADDNODEFAILUREREPAIR(BASEMODEL, NODENAME, BREAKDOWNDIST, REPAIRDIST, DOWNSERVICEDIST, RESETBREAKDOWN, RESETREPAIR)
            % Convenience method to add both breakdown and repair for a node
            %
            % Parameters:
            %   baseModel - The base network model with normal (UP) service rates
            %   nodeName - Name of the node that can break down and repair
            %   breakdownDist - Distribution for time until breakdown
            %   repairDist - Distribution for repair time
            %   downServiceDist - Service distribution when the node is down
            %   resetBreakdown - (Optional) Reset function for breakdown transition
            %   resetRepair - (Optional) Reset function for repair transition
            %
            % Example:
            %   env = Env('ServerEnv');
            %   env.addNodeFailureRepair(model, 'Server1', Exp(0.1), Exp(1.0), Exp(0.5));
 
            resetBreakdown = @(q) q;
            resetRepair = @(q) q;
 
            if nargin >= 7
                resetBreakdown = varargin{1};
            end
            if nargin >= 8
                resetRepair = varargin{2};
            end
 
            self.addNodeBreakdown(baseModel, nodeName, breakdownDist, downServiceDist, resetBreakdown);
            self.addNodeRepair(nodeName, repairDist, resetRepair);
        end
 
        function self = setBreakdownResetPolicy(self, nodeName, resetFun)
            % SELF = SETBREAKDOWNRESETPOLICY(NODENAME, RESETFUN)
            % Sets the reset policy for queue lengths when a node breaks down
            %
            % Parameters:
            %   nodeName - Name of the node
            %   resetFun - Function to reset queue lengths: resetFun(q) -> q_new
            %              Common policies:
            %              @(q) q          - Keep all jobs (default)
            %              @(q) 0*q        - Clear all queues
            %              @(q) min(q, N)  - Cap queue lengths
 
            downStageName = sprintf('DOWN_%s', nodeName);
            e = self.envGraph.findnode('UP');
            h = self.envGraph.findnode(downStageName);
 
            if isempty(e) || isempty(h)
                line_error(mfilename, sprintf('Breakdown transition for node "%s" not found.', nodeName));
            end
 
            self.resetFun{e,h} = resetFun;
        end
 
        function self = setRepairResetPolicy(self, nodeName, resetFun)
            % SELF = SETREPAIRRESETPOLICY(NODENAME, RESETFUN)
            % Sets the reset policy for queue lengths when a node is repaired
            %
            % Parameters:
            %   nodeName - Name of the node
            %   resetFun - Function to reset queue lengths: resetFun(q) -> q_new
 
            downStageName = sprintf('DOWN_%s', nodeName);
            e = self.envGraph.findnode(downStageName);
            h = self.envGraph.findnode('UP');
 
            if isempty(e) || isempty(h)
                line_error(mfilename, sprintf('Repair transition for node "%s" not found.', nodeName));
            end
 
            self.resetFun{e,h} = resetFun;
        end
    end
 
    methods (Access = protected)
        % Override copyElement method:
        function clone = copyElement(self)
            % CLONE = COPYELEMENT()
            
            % Make a shallow copy of all properties
            clone = copyElement@Ensemble(self);
            % Make a deep copy of each ensemble object
            clone.env = copy(self.envGraph);
        end
    end
end