LEACH协议代码(MATLAB)

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% % % SEP: A Stable Election Protocol for clustered % % heterogeneous wireless sensor networks %

% %

% (c) Georgios

Smaragdakis % % WING group, Computer Science Department, Boston University % % %

% You can find full documentation and related information at: % %

http://csr.bu.edu/sep %

% %

% To report your comment or any bug please send e-mail to: % %

gsmaragd@cs.bu.edu %

% %

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% %

% This is the LEACH [1] code we have used. % % The same code can be used for FAIR if m=1 % % %

% [1] W.R.Heinzelman, A.P.Chandrakasan and H.Balakrishnan, %

% \"An application-specific protocol architecture for wireless % % microsensor

networks\" %

% IEEE Transactions on Wireless Communications, 1(4):660-670,2002 %

% %

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clear;

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PARAMETERS %%%%%%%%%%%%%%%%%%%%%%%%%%%%

%Field Dimensions - x and y maximum (in meters) xm=100; ym=100;

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

%Number of Nodes in the field n=100

%Optimal Election Probability of a node %to become cluster head p=0.1;

%Energy Model (all values in Joules) %Initial Energy Eo=0.5;

%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=0.1; %\\alpha a=1;

%maximum number of rounds rmax=9999

%%%%%%%%%%%%%%%%%%%%%%%%% END OF PARAMETERS %%%%%%%%%%%%%%%%%%%%%%%%

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

%Creation of the random Sensor Network 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;

%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_rnd0plot(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;

%Calculation of Energy dissipated distance;

if (distance>do)

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 )); end 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 ( tempmin_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)

S(C(min_dis_cluster).id).E = S(C(min_dis_cluster).id).E- ( (ERX + EDA)*4000 );

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;

%Code for Voronoi Cells

%Unfortynately if there is a small %number of cells, Matlab's voronoi %procedure has some problems

%[vx,vy]=voronoi(X,Y);

%plot(X,Y,'r*',vx,vy,'b-'); % hold on;

% voronoi(X,Y);

% axis([0 xm 0 ym]); end

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STATISTICS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% %

% DEAD : a rmax x 1 array of number of dead nodes/round

% DEAD_A : a rmax x 1 array of number of dead Advanced nodes/round % DEAD_N : a rmax x 1 array of number of dead Normal nodes/round % CLUSTERHS : a rmax x 1 array of number of Cluster Heads/round % PACKETS_TO_BS : a rmax x 1 array of number packets send to Base Station/round

% PACKETS_TO_CH : a rmax x 1 array of number of packets send to ClusterHeads/round

% first_dead: the round where the first node died % %

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