Can anyone help me in simulating a Wireless sensor Network with 100 nodes in it.

I want to implement Wireless Sensor Network with following specifications

-> Sensors are sensing data and are at fixed locations. Sensors are to sense signals from body(Wireless Body Area Sensors)

-> Here the spectrum is ISM band, hence we need to have an efficient channel access mechanism ie I have to use CSMA/CA and don't know how to simulate one.

-> Sensors should work at 20Kbps and also the effect of energy needs to be included in the simulation.

-> There cannot be forwarding of data from one sensor to another sensor as each one has their own data to transmit.

-> I am essentially trying to simulate only the MAC and the physical layer.

-> I am also struck up with how to do this synchronization between the nodes, as I want to implement TDM and also FDM if possible between these nodes.

Please let me know if someone can help me. With Reagrds, Shravan

[Avinash Chaudhary]

I want to complete my matlab code and want to get those results

[Avinash Chaudhary]

My code is this.....

clear; %Field Dimensions - x and y maximum (in meters)/ Tarife Size mohite shabake(m) xm=100; ym=100; p=1; %x and y Coordinates of the Sink / sink.x=0.5*xm; sink.y=0.5*ym; %Number of Nodes in the field / Tedade Node haye shabake n=100; number_of_ch=0.1*n; %Optimal Election Probability of a node to become cluster head/ Ehtemale Entekhab Node be onvane Cluster Head %p=0.1; %Energy Model (all values in Joules)/ Energy ha bar hasbe Joule %Initial Energy / Energy Avaliye Eo=0.5; %maximum number of rounds %rmax=input('enter the number of iterations you want to run : '); rmax=3000;

figure(1); 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;

    S(i).E=Eo;

    % Calculation of distance from sink node to normal node %
     D(i)=sqrt(((S(i).xd-50)^2)+ ((S(i).yd-50)^2)); 

     R(i)=(D(i)+Eo*150)*3;

    %initially there are no cluster heads only nodes/ Dar ebteda hich Cluster Head i mojud nist
    S(i).type='N';
    S(i).e=Eo

    %temp_rnd0=i;
    %Random Election of Normal Nodes/ Entekhabe Tasadofi Node ha 
        plot(S(i).xd,S(i).yd,'o',...
            'markerFace','b');
        hold on;

end S(n+1).xd=sink.x; S(n+1).yd=sink.y; plot(sink.x,sink.y,'o', ... 'markerSize',15,'markerFace','r'); hold on;

%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;

%Computation of do do=sqrt(Efs/Emp); S3=S; totalclust=10; %First Iteration %counter for CHs LcountCHs=0; %counter for CHs per round LrcountCHs=0; Lcluster=1;

%LcountCHs; LrcountCHs=LrcountCHs+LcountCHs; Lflag_first_dead=0;

figure(3) for r=1:rmax r hold off;

clust = randperm(n,totalclust); for i=1:totalclust

% clust=randi(n,1); S3(clust(i)).type='C'; cluster(i)=clust(i); end

 for i=1:totalclust
     plot(S3(cluster(i)).xd,S3(cluster(i)).yd,'*-g');
     hold on;
 end
  plot(S3(n+1).xd,S3(n+1).yd,'o', 'MarkerSize', 12, 'MarkerFaceColor', 'r');  
  hold on;

 for i=1:totalclust
     clster_count(i)=0;
 end
 for i=1:n
%      if(S3(i).type=='N')
%          min_dis=sqrt( (S3(i).xd-S3(n+1).xd)^2 + (S3(i).yd-S3(n+1).yd)^2 );
         min_dis=999999;
         k=n+1;
         k1=totalclust+1;
        for j=1:totalclust
             min_dis2=sqrt( (S3(i).xd-S3(cluster(j)).xd)^2 + (S3(i).yd-S3(cluster(j)).yd)^2 );
             if(min_dis2<min_dis)
                 min_dis=min_dis2;

                 k=cluster(j);
                 k1=j;
             end

        end
%        node_number(k1,i)=cluster(j); 
      S3(i).clustnum= k1;
      S3(i).clustnode= k;
      line([S3(i).xd, S3(k).xd], [S3(i).yd, S3(k).yd], 'Color', 'b', 'LineWidth', 0.5);
       hold on;
      clster_count(k1)=clster_count(k1)+1;
%             line([S3(i).xd, S3(k).xd], [S3(i).yd, S3(k).yd], 'Color', 'b', 'LineWidth', 0.5);
%        hold on;

% end end for j=1:totalclust total_node(j)=0; incre(j)=1; end for i=1:n % if (S3(i).type=='N') for j=1:totalclust if (S3(i).clustnum==j) total_node(j)=total_node(j)+1; node_no(j,incre(j))=i; res_energy(j,incre(j))=S3(i).E; incre(j)=incre(j)+1; end end % end end

     for i=1:totalclust
         for j=1:total_node(i)
             dist_bs(i,j)=sqrt( (S3(node_no(i,j)).xd-S3(n+1).xd)^2 + (S3(node_no(i,j)).yd-S3(n+1).yd)^2 );
         end
         j=j+1;
         dist_bs(i,j)=sqrt( (S3(cluster(i)).xd-S3(n+1).xd)^2 + (S3(cluster(i)).yd-S3(n+1).yd)^2 );
     end
      for i=1:totalclust
         for j=1:total_node(i)
             max_dist(i,j)=0;
             total_dist(i,j)=0;
            for k=1:total_node(i)
                 max_dis2=sqrt( (S3(node_no(i,j)).xd-S3(node_no(i,k)).xd)^2 + (S3(node_no(i,j)).yd-S3(node_no(i,k)).yd)^2 );
             total_dist(i,j)=total_dist(i,j)+ max_dis2;
              if(max_dis2>max_dist(i,j))
                 max_dist(i,j)=max_dis2;
              end
            end
         end
      end
        for i=1:totalclust
         for j=1:total_node(i)
               avg_dist(i,j)=total_dist(i,j)/total_node(i);
                distance1=sqrt((S3(node_no(i,j)).xd-S3(n+1).xd)^2 + (S3(node_no(i,j)).yd-S3(n+1).yd)^2 );
                if(distance1>do)
                min_energy(i,j)=4000* total_node(i) * ERX+ 4000* Emp* ETX * distance1*distance1*distance1*distance1;
                else
                     min_energy(i,j)=4000* total_node(i) * ERX+ 4000* Emp* ETX *distance1*distance1;
                end
         end
        end
       for i=1:totalclust
         for j=1:total_node(i)
             delay(i,j)=res_energy(i,j);
         end
       end
     alpha=0.33;
     beta=0.33;
     gama=0.33;
     for i=1:totalclust
         for j=1:total_node(i)
             fitness(i,j)=delay(i,j);
         end
     end
      [B I]=sort(fitness,2,'descend');

      for i=1:totalclust
     selected_ch(i)=node_no(i,I(i,total_node(i)));
     if (selected_ch(i)==0)
         selected_ch(i)=node_no(i,I(i,total_node(i))-1);
     end
     if (selected_ch(i)==0)
         selected_ch(i)=node_no(i,I(i,total_node(i))-2);
     end
      end

     for i=1:n
         S3(i).type='N';
     end

     for j=1:n
         for i=1:totalclust
         if (j==selected_ch(i))
         S3(i).type='C';
         end
         end
     end

     % Same for all algorithms
     for i=1:n
         if (S3(i).type=='N')
             for j=1:totalclust
                 if (S3(i).clustnum==j)
              min_dis=sqrt( (S3(i).xd-S3(selected_ch(j)).xd)^2 + (S3(i).yd-S3(selected_ch(j)).yd)^2 );
              if (min_dis>do)
                S3(i).E=S3(i).E - ( ETX *(4000) + Emp*4000*( min_dis * min_dis * min_dis * min_dis)); 
            end
            if (min_dis<=do)
                S3(i).E=S3(i).E - ( ETX *(4000) + Efs*4000*( min_dis * min_dis)); 
            end
                 end
             end
         else
            Ldistance=sqrt( (S3(i).xd-S3(n+1).xd)^2 + (S3(i).yd-S3(n+1).yd)^2 );
              if (Ldistance>do)
                S3(i).E=S3(i).E- ( (ETX+EDA)*(4000) + Emp*4000*( Ldistance*Ldistance*Ldistance*Ldistance )); 

            %S2(i).E=S2(i).E- ( (ETX+EDA)*(4000) + Emp*4000*( Ldistance*Ldistance*Ldistance*Ldistance )); 
            end
            if (Ldistance<=do)
                S3(i).E=S3(i).E - ( (ETX+EDA)*(4000)  + Efs*4000*( Ldistance * Ldistance )); 
            %S2(i).E=S2(i).E- ( (ETX+EDA)*(4000)  + Efs*4000*( Ldistance * Ldistance )); 
            end
         end
     end

     % Same for all algorithms
    for i=1:n
         if(S3(i).E>0)
         Eres(r,i)=S3(i).E;
         else
             Eres(r,i)=0;
             S3(i).E=0;
         end
    end

      deadnode=0;
     %figure(4);
     %Same for all algoriths.
     for i=1:n
         dead(i)=0;
        if(S3(i).E<=0)
            dead(i)=dead(i)+1;
            deadnode=deadnode+1;
            %S3(i).type='D'
            %plot(S(i).xd,p,'o',...
             %   'markerFace','b');

            % hold on;
            % p=p+1;
        end
     end
     d(r)=deadnode;

end

 % no of nodes remaining after each rounds
 for r=1:rmax
     figure(4);
     plot(p,n-d(r),'o',...
      'markerSize',5,'markerFace','g');
     hold on;
     p=p+1;
 end

[Avinash Chaudhary]

Please help me soon

[Walter Roberson]

you posted your own Question about this. People should look there rather than working on it here.

Answer 1

[Thomas]

Do you have any paper that you are following. This work is equivalent to a Thesis or dissertation.

Anyways since you asked, here are the steps: (assuming you are performing energy based simulations)

1. Model the network (something like a meshgrid) 2. Model the channel (depending on the quantization) 3. Model individual sensors (as a cost of energy efficiency and communication) 4. add random noise to the system 5. For a particular target in the network (particular position, power, start with initial conditions and run monte carlo simulations)

OR follow the protocol given in the following paper: www.isi.edu/~johnh/PAPERS/Ye02a.pdf

[Shravan Kumar Pasupuleti]

Can u be more specific in how to create the network.

[Thomas]

[x,y]=meshgrid(-10:2:10,-10:2:10);

plot(x,y,'Marker','o','LineStyle','none')

[Asma']

thank you for your question and answer

really, I need to build my routing protocol for WSN in Matlab and I found good Demoes and examples and simulink tools I expect it do the best more than any network simulator. But from where to start, how to build and connect? your answer is a good quick reference but I suggest to have complete tutorial or demo to build WSN in details and step by step

this will be a good support to any researcher to use Matlab for simulation.