Showing posts with label WSN protocol implementation leach program. Show all posts
Showing posts with label WSN protocol implementation leach program. Show all posts

Saturday, November 7, 2015

WSN protocol implementation leach program GUI

close all;
clear;
clc;
%-------------------------------
%Number of Nodes in the field
 n=200;
%n=input('Enter the number of nodes in the space : '); 
%Energy Model (all values in Joules)
%Initial Energy 
Eo=0.1;
%Eo=input('Enter the initial energy of sensor nJ : ');
%Field Dimensions - x and y maximum (in meters)
% xm=input('Enter x value for area plot : ');
% ym=input('Enter y value for area plot : ');  
xm=100;
ym=100;

%x and y Coordinates of the Sink
sink.x=1.5*xm;
sink.y=0.5*ym;

%Optimal Election Probability of a node
%to become cluster head
p=0.2;

%Eelec=Etx=Erx
ETX=50*0.000000001;
ERX=50*0.000000001;
%Transmit Amplifier types
Efs=10*0.000000000001;
Emp=0.0013*0.000000000001;
%Data Aggregation Energy
EDA=5*0.000000001;

%Values for Hetereogeneity
%Percentage of nodes than are advanced
m=0.5;
%\alpha
a=1;

%maximum number of rounds
%rmax=input('enter the number of iterations you want to run : '); 
rmax=50;
%------------------

%Computation of do
do=sqrt(Efs/Emp);

%Creation of the random Sensor Network
figure(1);
hold off;
for i=1:1:n
    S(i).xd=rand(1,1)*xm;
    XR(i)=S(i).xd;
    S(i).yd=rand(1,1)*ym;
    YR(i)=S(i).yd;
    S(i).G=0;
    %initially there are no cluster heads only nodes
    S(i).type='N';
   
    temp_rnd0=i;
    %Random Election of Normal Nodes
    if (temp_rnd0>=m*n+1) 
        S(i).E=Eo;
        S(i).ENERGY=0;
       plot(S(i).xd,S(i).yd,'o-r');
        hold on;
    end
    %Random Election of Advanced Nodes
    if (temp_rnd0<m*n+1)  
        S(i).E=Eo*(1+a);
        S(i).ENERGY=1;
       plot(S(i).xd,S(i).yd,'+');
        hold on;
    end
end

S(n+1).xd=sink.x;
S(n+1).yd=sink.y;
plot(S(n+1).xd,S(n+1).yd,'o', 'MarkerSize', 12, 'MarkerFaceColor', 'r');
figure(1);  
% figure(1)
%  plot(o1,o2,'^','LineWidth',1, 'MarkerEdgeColor','k', 'MarkerFaceColor','y', 'MarkerSize',12);
%    hold on
%First Iteration
%counter for CHs
countCHs=0;
%counter for CHs per round
rcountCHs=0;
cluster=1;

countCHs;
rcountCHs=rcountCHs+countCHs;
flag_first_dead=0;

for r=0:1:rmax
    r;

  %Operation for epoch
  if(mod(r, round(1/p) )==0)
    for i=1:1:n
        S(i).G=0;
        S(i).cl=0;
    end
  end

hold off;

%Number of dead nodes
dead=0;
%Number of dead Advanced Nodes
dead_a=0;
%Number of dead Normal Nodes
dead_n=0;

%counter for bit transmitted to Bases Station and to Cluster Heads
packets_TO_BS=0;
packets_TO_CH=0;
%counter for bit transmitted to Bases Station and to Cluster Heads 
%per round
PACKETS_TO_CH(r+1)=0;
PACKETS_TO_BS(r+1)=0;

figure(1);

for i=1:1:n
    %checking if there is a dead node
    if (S(i).E<=0)
       plot(S(i).xd,S(i).yd,'^','LineWidth',1, 'MarkerEdgeColor','k', 'MarkerFaceColor','y', 'MarkerSize',8);
        dead=dead+1;
        if(S(i).ENERGY==1)
            dead_a=dead_a+1;
        end
        if(S(i).ENERGY==0)
            dead_n=dead_n+1;
        end
        hold on;    
    end
    if S(i).E>0
        S(i).type='N';
        if (S(i).ENERGY==0)  
     plot(S(i).xd,S(i).yd,'o','LineWidth',1, 'MarkerEdgeColor','k', 'MarkerFaceColor','g', 'MarkerSize',8);
        end
        if (S(i).ENERGY==1)  
        plot(S(i).xd,S(i).yd,'+','LineWidth',3, 'MarkerEdgeColor','k', 'MarkerFaceColor','r', 'MarkerSize',8);
        end
        hold on;
    end
end
plot(S(n+1).xd,S(n+1).yd,'x','LineWidth',1, 'MarkerEdgeColor','k', 'MarkerFaceColor','r', 'MarkerSize',8); 


STATISTICS(r+1).DEAD=dead;
DEAD(r+1)=dead;
DEAD_N(r+1)=dead_n;
DEAD_A(r+1)=dead_a;
%          plot(S(n+1).xd,S(n+1).yd,'o', 'MarkerSize', 12, 'MarkerFaceColor', 'r');
%          plot(S(n+1).xd,S(n+1).yd,'x','LineWidth',1, 'MarkerEdgeColor','k', 'MarkerFaceColor','r', 'MarkerSize',8);  
%When the first node dies
if (dead==1)
    if(flag_first_dead==0)
        first_dead=r;
        flag_first_dead=1;
    end
end

countCHs=0;
cluster=1;
for i=1:1:n
   if(S(i).E>0)
   temp_rand=rand;     
   if ( (S(i).G)<=0)

 %Election of Cluster Heads
 if(temp_rand<= (p/(1-p*mod(r,round(1/p)))))
            countCHs=countCHs+1;
            packets_TO_BS=packets_TO_BS+1;
            PACKETS_TO_BS(r+1)=packets_TO_BS;
            
            S(i).type='C';
            S(i).G=round(1/p)-1;
            C(cluster).xd=S(i).xd;
            C(cluster).yd=S(i).yd;
             plot(S(i).xd,S(i).yd,'k*');
            
            distance=sqrt( (S(i).xd-(S(n+1).xd) )^2 + (S(i).yd-(S(n+1).yd) )^2 );
            C(cluster).distance=distance;
            C(cluster).id=i;
            X(cluster)=S(i).xd;
            Y(cluster)=S(i).yd;
            cluster=cluster+1;
            
            %Calculation of Energy dissipated
            distance;
            if (distance>do)
                S(i).E=S(i).E- ( (ETX+EDA)*(4000) + Emp*4000*( distance*distance*distance*distance )); 
            %S(i).E=S(i).E- ( (ETX+EDA)*(4000) + Emp*4000*( distance*distance*distance*distance )); 
            end
            if (distance<=do)
                S(i).E=S(i).E- ( (ETX+EDA)*(4000)  + Efs*4000*( distance * distance )); 
            %S(i).E=S(i).E- ( (ETX+EDA)*(4000)  + Efs*4000*( distance * distance )); 
            end
            Energy_disp(r+1) =  S(i).E;
        end     
    
    end
  end 
end

STATISTICS(r+1).CLUSTERHEADS=cluster-1;
CLUSTERHS(r+1)=cluster-1;

%Election of Associated Cluster Head for Normal Nodes
for i=1:1:n
   if ( S(i).type=='N' && S(i).E>0 )
     if(cluster-1>=1)
       min_dis=sqrt( (S(i).xd-S(n+1).xd)^2 + (S(i).yd-S(n+1).yd)^2 );
       min_dis_cluster=1;
       for c=1:1:cluster-1
           temp=min(min_dis,sqrt( (S(i).xd-C(c).xd)^2 + (S(i).yd-C(c).yd)^2 ) );
           if ( temp<min_dis )
               min_dis=temp;
               min_dis_cluster=c;
           end
       end
       
       %Energy dissipated by associated Cluster Head
            min_dis;
            if (min_dis>do)
                S(i).E=S(i).E- ( ETX*(4000) + Emp*4000*( min_dis * min_dis * min_dis * min_dis)); 
            end
            if (min_dis<=do)
                S(i).E=S(i).E- ( ETX*(4000) + Efs*4000*( min_dis * min_dis)); 
            end
        %Energy dissipated
        if(min_dis>0)
         distance=sqrt( (S(C(min_dis_cluster).id).xd-(S(n+1).xd) )^2 + (S(C(min_dis_cluster).id).yd-(S(n+1).yd) )^2 );
          S(C(min_dis_cluster).id).E = S(C(min_dis_cluster).id).E- ( (ERX + EDA)*4000 ); 
if (distance>do)
                S(C(min_dis_cluster).id).E=S(C(min_dis_cluster).id).E- ( (ETX+EDA)*(4000) + Emp*4000*( distance*distance*distance*distance )); 
            end
            if (distance<=do)
                S(C(min_dis_cluster).id).E=S(C(min_dis_cluster).id).E- ( (ETX+EDA)*(4000)  + Efs*4000*( distance * distance )); 
            end
          PACKETS_TO_CH(r+1)=n-dead-cluster+1; 
        end

       S(i).min_dis=min_dis;
       S(i).min_dis_cluster=min_dis_cluster;
           
   end
 end
end
hold on;

countCHs;
rcountCHs=rcountCHs+countCHs;
sum=0;
for i=1:1:n
if(S(i).E>0)
    sum=sum+S(i).E;
end
end
avg=sum/n;
STATISTICS(r+1).AVG=avg;
sum;


%Code for Voronoi Cells
%Unfortynately if there is a small
%number of cells, Matlab's voronoi
%procedure has some problems
warning('OFF');
[vx,vy]=voronoi(X(:),Y(:));
plot(X,Y,'g+',vx,vy,'m-');
hold on;
voronoi(X,Y);
axis([10 xm 0 ym]);

end
% figure1 = figure11;
% % Create axes
% axes1 = axes('Parent',figure1,'YGrid','on','XGrid','on','GridLineStyle','--');
% box(axes1,'on');
% hold(axes1,'all');
figure(2);
for r=0:1:24
    ylabel('Average Energy of Each Node');
    xlabel('Round Number');
    plot([r r+1],[STATISTICS(r+1).AVG STATISTICS(r+2).AVG],'red');
    hold on;
end
figure(3);
for r=0:1:49
    ylabel('Average Energy of Each Node');
    xlabel('Round Number');
    plot([r r+1],[STATISTICS(r+1).AVG STATISTICS(r+2).AVG],'red');
    hold on;
end
figure(4);
for r=0:1:74
    ylabel('Average Energy of Each Node');
    xlabel('Round Number');
    plot([r r+1],[STATISTICS(r+1).AVG STATISTICS(r+2).AVG],'red');
    hold on;
end
figure(5);
for r=0:1:99
    ylabel('Average Energy of Each Node');
    xlabel('Round Number');
    plot([r r+1],[STATISTICS(r+1).AVG STATISTICS(r+2).AVG],'red');
    hold on;
end
figure(6);
for r=0:1:24
    ylabel('Number of Dead Nodes');
    xlabel('Round Number');
    plot([r r+1],[STATISTICS(r+1).DEAD STATISTICS(r+2).DEAD],'red');
    hold on;
end
figure(7);
for r=0:1:49
        ylabel('Number of Dead Nodes');
    xlabel('Round Number');
    plot([r r+1],[STATISTICS(r+1).DEAD STATISTICS(r+2).DEAD],'red');
    hold on;
end
figure(8);
for r=0:1:74
        ylabel('Number of Dead Nodes');
    xlabel('Round Number');
    plot([r r+1],[STATISTICS(r+1).DEAD STATISTICS(r+2).DEAD],'red');
    hold on;
end
figure(9);
for r=0:1:99
        ylabel('Number of Dead Nodes');
    xlabel('Round Number');
    plot([r r+1],[STATISTICS(r+1).DEAD STATISTICS(r+2).DEAD],'red');
    hold on;
end