matlab-无线传感器网络WSN中LEACH和EAMMH两种节能协议的性能仿真-源码

clc; clear; close all; warning off; addpath(genpath(pwd)); xm=100; ym=100; %x and y Coordinates of the Sink sink.x=1.5*xm; sink.y=0.5*ym; %Number of Nodes in the field n=200; p=0.2; intermediate=1; Eo=0.1; %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; m=0.0; %\alpha a=1; %maximum number of rounds rmax=100; 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'); 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,'x'); %First Iteration figure(1); %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,'red .'); 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'); end if (S(i).ENERGY==1) % plot(S(i).xd,S(i).yd,'+'); end hold on; end end %plot(S(n+1).xd,S(n+1).yd,'x'); STATISTICS(r+1).DEAD=dead; DEAD(r+1)=dead; DEAD_N(r+1)=dead_n; DEAD_A(r+1)=dead_a; %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; end end end end STATISTICS(r+1).CLUSTERHEADS=cluster-1; CLUSTERHS(r+1)=cluster-1; Ecalc=0;d1=0;d2=0;E1=0;E2=0;min=0;distance1=0;distance2=0; %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=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 if(min_dis>do) Esmall=( ETX*(4000) + Emp*4000*( min_dis * min_dis * min_dis * min_dis)); else Esmall=( ETX*(4000) + Efs*4000*( min_dis * min_dis)); end for j=1:1:n if(i~=j && S(j).E>0) d1=sqrt( (S(i).xd-S(j).xd)^2 + (S(i).yd-S(j).yd)^2 ) ; d2=sqrt( (S(j).xd-C(min_dis_cluster).xd)^2 + (S(j).yd-C(min_dis_cluster).yd)^2 ) ; if(d1>do) E1=( ETX*(4000) + Emp*4000*( d1 * d1 * d1 * d1)); else E1=( ETX*(4000) + Emp*4000*( d1 * d1)); end if(d2>do) E2=( ETX*(4000) + Emp*4000*( d2 * d2 * d2 * d2)); else E2=( ETX*(4000) + Emp*4000*( d2 * d2)); end Ecalc=E1+E2; if(Ecalc<min) min=Ecalc; intermediate=j; distance1=d1; distance2=d2; end end end if(Ecalc<Esmall) if(distance1>do) S(i).E=S(i).E- ( ETX*(4000) + Emp*4000*( distance1 * distance1 * distance1 * distance1)); S(intermediate).E=S(intermediate).E-( (ERX + EDA)*4000 ); else S(i).E=S(i).E- ( ETX*(4000) + Emp*4000*( distance1 * distance1)); S(intermediate).E=S(intermediate).E-( (ERX + EDA)*4000 ); end if(distance2>do) S(intermediate).E=S(intermediate).E-( ETX*(4000) + Emp*4000*( distance2 * distance2 * distance2 * distance2)); else S(intermediate).E=S(intermediate).E-( ETX*(4000) + Emp*4000*( distance2 * distance2)); end else 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 end 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; end 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],'blue'); 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],'blue'); 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],'blue'); 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],'blue'); 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],'blue'); 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],'blue'); 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],'blue'); 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],'blue'); hold on; end