无线传感器网络中LEACH路由协议的MATLAB仿真

LEACH协议 全称是“低功耗自适应集簇分层型协议” Low Energy Adaptive Clustering Hierarchy 是一种无线传感器网络路由协议 基于LEACH协议的算法 称为LEACH算法

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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）:660-6702002  %
%                                                                      %
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clear;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 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（11）*xm;
    XR（i）=S（i）.xd;
    S（i）.yd=rand（11）*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 （te