✅作者简介：热爱科研的Matlab仿真开发者，修心和技术同步精进，matlab项目合作可私信。
🍎个人主页：Matlab科研工作室
🍊个人信条：格物致知。
更多Matlab仿真内容点击👇
⛄ 内容介绍
提出并评估了一种称为异构无线传感器网络的开发分布式节能集群方案的集群技术。该技术基于动态变化且更高效的簇头选举概率。仿真结果表明，我们的协议在网络生命周期和第一个节点死亡方面比稳定选举协议 (SEP) 高约 30%，比分布式节能集群 (DEEC) 高约 15%。
⛄ 部分代码
clear all
xm=100;
ym=100;
sink.x=0.5*xm; %location of sink on x-axis
sink.y=0.5*ym; %location of sink on y-axis
n=100 %nodes
P=0.1; %probability of cluster heads
Eo=0.5;%initial energy
%
Echeck=Eo;
%
ETX=50*0.000000001; %tx energy
ERX=50*0.000000001; %rx energy
Efs=10*0.000000000001; %free space loss
Emp=0.0013*0.000000000001; %multipath loss
%Data Aggregation Energy
EDA=5*0.000000001; %compression energy
a=1; %fraction of energy enhancment of advance nodes
rmax=5000 %maximum number of rounds
do=sqrt(Efs/Emp); %distance do is measured
Et=0; %variable just use below
m=0;
mony=0;
c=0.02;
b=0.7;
talhar=0;
for i=1:1:n
S(i).xd=rand(1,1)*xm; %generates a random no. use to randomly distibutes nodes on x axis
XR(i)=S(i).xd;
S(i).yd=rand(1,1)*ym; %generates a random no. use to randomly distibutes nodes on y axis
YR(i)=S(i).yd;
S(i).G=0; %node is elegible to become cluster head
talhar=rand*a
S(i).E=Eo*(1+talhar);
S(i).A=talhar;
E(i)= S(i).E;
if (E(i)>Echeck)
mony=mony+1;
end
Et=Et+E(i); %estimating total energy of the network
%initially there are no cluster heads only nodes
S(i).type='N';
end
⛄ 运行结果
⛄ 参考文献
