云环境中使用飞蛾火焰和萨尔普群算法组合的工作流调度(Matlab代码实现）

%Define problem parameters
search_agents_number=50; % Number of search agents
maxLoop=100; % Maximum numbef of iterations
%-------------------------------------------------------------------------%
% MIPS (Millions of Instructions Per Second)
% Expect Complete Time (ECT) 
% A cloud server(Node) can execute several separate VM samples, and each VM sample includes various resources such as CPU and memory
% the CPU (cpu_i (t)) and memory (mem_i (t))) usage of the cloud server are between [0, 100], i.e.  0鈮pu_i (t), mem_i (t)鈮�100
% ECT (k,j) represents the expected time of execution of task T(k,1) on vm(:, j)
Node1=randi([0 100],2,3);%vm1, vm2, vm3----> each vm incloud 2 feature(cpu capacity(mips), memory)...0鈮pu_i (t), mem_i (t)鈮�100
Node2=randi([0 100],2,4);%vm1, vm2, vm3, vm4----> each vm incloud 2 feature(cpu capacity(mips), memory)...0鈮pu_i (t), mem_i (t)鈮�100
Node3=randi([0 100],2,5);%vm1, vm2, vm3, vm4, vm5----> each vm incloud 2 feature(cpu capacity(mips), memory)...0鈮pu_i (t), mem_i (t)鈮�100
Node4=randi([0 100],2,6);%vm1, vm2, vm3, vm4, vm5, vm6, vm7----> each vm incloud 2 feature(cpu capacity(mips), memory)...0鈮pu_i (t), mem_i (t)鈮�100
Node5=randi([0 100],2,8);
Node6=randi([0 100],2,10);
Node7=randi([0 100],2,9);
Node8=randi([0 100],2,12);
%-------------------------------------------------------------------------%
failure_Rate1 = [9e-5, 7e-5, 8e-5, 6e-5, 5e-5, 6e-5]; %failure_Rate of each processor(deadline failure rate of the tasks at time t)
num_core = [15, 10, 15, 20, 25, 20]; %number of cores
for jj=1:size(Node1, 2)
    s=randi(size(failure_Rate1, 2));
    Node1(3, jj)=failure_Rate1(1, s);
    Node1(4, jj)=num_core(1, s);%number of cores
    Node1(5, jj)=num_core(1, s)*Node1(2, jj);% capacity of the VM instance
end
for jj=1:size(Node2, 2)
    s=randi(size(failure_Rate1, 2));
    Node2(3, jj)=failure_Rate1(1, s);
    Node2(4, jj)=num_core(1, s);
    Node2(5, jj)=num_core(1, s)*Node2(2, jj);% capacity of the VM instance
end
for jj=1:size(Node3, 2)
    s=randi(size(failure_Rate1, 2));
    Node3(3, jj)=failure_Rate1(1, s);
    Node3(4, jj)=num_core(1, s);
    Node3(5, jj)=num_core(1, s)*Node3(2, jj);% capacity of the VM instance
end
for jj=1:size(Node4, 2)
    s=randi(size(failure_Rate1, 2));
    Node4(3, jj)=failure_Rate1(1, s);
    Node4(4, jj)=num_core(1, s);
    Node4(5, jj)=num_core(1, s)*Node4(2, jj);% capacity of the VM instance
end
for jj=1:size(Node5, 2)
    s=randi(size(failure_Rate1, 2));
    Node5(3, jj)=failure_Rate1(1, s);
    Node5(4, jj)=num_core(1, s);
    Node5(5, jj)=num_core(1, s)*Node5(2, jj);% capacity of the VM instance
end
for jj=1:size(Node6, 2)
    s=randi(size(failure_Rate1, 2));
    Node6(3, jj)=failure_Rate1(1, s);
    Node6(4, jj)=num_core(1, s);
    Node6(5, jj)=num_core(1, s)*Node6(2, jj);% capacity of the VM instance
end
for jj=1:size(Node7, 2)
    s=randi(size(failure_Rate1, 2));
    Node7(3, jj)=failure_Rate1(1, s);
    Node7(4, jj)=num_core(1, s);
    Node7(5, jj)=num_core(1, s)*Node7(2, jj);% capacity of the VM instance
end
for jj=1:size(Node8, 2)
    s=randi(size(failure_Rate1, 2));
    Node8(3, jj)=failure_Rate1(1, s);
    Node8(4, jj)=num_core(1, s);
    Node8(5, jj)=num_core(1, s)*Node8(2, jj);% capacity of the VM instance
end
% save vm_info.mat Node1 Node2 Node3 Node4 Node5 Node6 Node7 Node8;
%=========================================================================%
total_Node={Node1, Node2, Node3, Node4, Node5, Node6, Node7, Node8};
%=========================================================================%
total_vm=zeros(size(Node1, 1), size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2)+size(Node5, 2)+size(Node6, 2)+size(Node7, 2)+size(Node8, 2));
total_vm(:, 1:size(Node1, 2))=Node1(:, :);
total_vm(:, size(Node1, 2)+1:size(Node1, 2)+size(Node2, 2))=Node2(:, :);
total_vm(:, size(Node1, 2)+size(Node2, 2)+1:size(Node1, 2)+size(Node2, 2)+size(Node3, 2))=Node3(:, :);
total_vm(:, size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+1:size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2))=Node4(:, :);
total_vm(:, size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2)+1:size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2)+size(Node5, 2))=Node5(:, :);
total_vm(:, size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2)+size(Node5, 2)+1:size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2)+size(Node5, 2)+size(Node6, 2))=Node6(:, :);
total_vm(:, size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2)+size(Node5, 2)+size(Node6, 2)+1:size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2)+size(Node5, 2)+size(Node6, 2)+size(Node7, 2))=Node7(:, :);
total_vm(:, size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2)+size(Node5, 2)+size(Node6, 2)+size(Node7, 2)+1:size(Node1, 2)+size(Node2, 2)+size(Node3, 2)+size(Node4, 2)+size(Node5, 2)+size(Node6, 2)+size(Node7, 2)+size(Node8, 2))=Node8(:, :);
%=========================================================================%
% DAG
job_uses=row(:, 22); %task size
child_ref=text(:, 23);
child_parent=text(:, 24);
% child_parent1=child_parent;
% child_ref1=child_ref;
% index1 = find(contains(child_parent, 'ID00000'));
% index2 = find(contains(child_ref, 'ID00000'));
for jj=2:size(child_parent, 1)
    job_uses1(jj, 1)=cell2mat(job_uses(jj, 1));
end
B1=unique(child_parent);% hazf anasor tekrari
B2=unique(child_ref);
ff=zeros(size(B1, 1), size(B1, 1));
for k1=2:size(B1, 1)-1
    for k2=2:size(B2, 1)-1
    aa = find(contains(child_parent, B1(k1)));
    for i3=1:size(aa, 1)
        m1=child_ref(aa(i3, 1), 1);
        bb = find(contains(B2, m1));
        m2=child_parent(aa(i3, 1), 1);
        h1=strcmp(m1, m2);
        if h1==1
           ff(k1-1, bb)=-1;
        else
           ff(k1-1, bb)=job_uses1(aa(i3, 1), 1);
        end
    end
end
end
fff=ff;
for i=1:size(fff, 1)
    for j=1:size(fff, 2)
        if fff(i, j)==0
        fff(i, j)=-1;
        end
    end
end
fff=fff(1:size(fff, 1)-2, 2:size(fff, 2)-1);
%=========================================================================%
taskNum = size(B1, 1)-2; % 
% taskNum = size(fff, 1); % 
nvar = taskNum;
% nvar=size(DataSet, 1);    % number of tasks for scheduling.
nvms=size(total_vm, 2);  % number of virtual machine.
dim=nvar;
xmin=1;
xmax=nvms;
lowerBound=xmin;
upperBound=xmax;
%=========================================================================%
% ECT=zeros(nvar,nvms);
% for i1=1:nvar
%     for j1=1:nvms
%         ECT(i1, j1)=DataSet(i1,:)./total_vm(1, j1);
%     end
% end
%=========================================================================% 
DAG = FunctionClass; %produce the structure
DAG.E=fff;%Communication cost between Ti and Tj/set of those task dependencies
DAG.arrivalTime = 0;
%=========================================================================%
% for workflow with 6 tasks
taskNum = 6;
DAG.Wcet = randi([1 100],size(total_vm, 2), taskNum+1);%Computation cost of Ti on pj/the task execution time matrix
DAG.E = [-1 20 24 -1 -1 -1;-1 -1 -1 12 -1 -1;-1 -1 -1 -1 43 -1;-1 -1 -1 -1 -1 70;-1 -1 -1 -1 -1 93;-1 -1 -1 -1 -1 -1];  
%=========================================================================%
energy_Spec =abs(rand(size(total_vm, 2), taskNum));%(NUM Of PROCESSOR)x(num task)
%=========================================================================%
%MFO_SSA
%avg 30 runs
% for i=1:30% 30 Runs
[Resourse_utilization_MFSSA, Throughput_MFSSA, Reliability_MFSSA, Fitnes_value_MFSSA, MakeSpanMax_MFSSA, index_server_MFSSA, pos_best_MFSSA, Leader_pos_MFSSA] = forLoopFuc_MFSSA(taskNum, DAG, energy_Spec, search_agents_number, maxLoop, Node1, Node2, Node3, Node4, Node5, Node6, Node7, Node8, total_vm, nvar, dim, lowerBound,upperBound);
% end
%=========================================================================%
fprintf('1-Resourse_utilization_MFSSA is %f\n', Resourse_utilization_MFSSA);
fprintf('1-Throughput_MFSSA is %f\n', Throughput_MFSSA);%
fprintf('1-Reliability_MFSSA is %f\n', Reliability_MFSSA);%
fprintf('1-MakeSpanMax_MFSSA is %f\n', MakeSpanMax_MFSSA);%
fprintf('1-Fitnes_value_MFSSA is %f\n', Fitnes_value_MFSSA);
%========================================================================