matlab实现LEACH协议路由分簇算法
作者:互联网
文章目录
- 一、理论基础
- 二、方法描述
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- 1、节点分簇
- 2、节点能量消耗
- 三、仿真分析
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- 1、节点分簇
- 2、节点能量消耗
- 四、参考文献
一、理论基础
LEACH(Low-Energy Adaptive Clustering Hierarchy)是由Wendi Rabiner Heinzelman、Anantha Chandrakasan和Hari Balakrishnan三人于2000年提出的一种无线传感器网络路由协议,它利用簇头的随机轮换在网络中的传感器之间均匀地分配能量负载。LEACH使用局部协调来实现动态网络的可伸缩性和健壮性,并将数据融合纳入路由协议中,以减少必须传输到基站的信息量。仿真结果表明,与传统的路由协议相比,LEACH协议的能耗降低了8倍。此外,LEACH能够在传感器中均匀地分配能量耗散,使网络的有效系统的生命周期延长一倍。
二、方法描述1、节点分簇
2、节点能量消耗
三、仿真分析节点分布如图1所示。
图1 100节点随机分布图
1、节点分簇
仿真程序如下:
%% 清空环境变量 clear; clc; %% 初始化参数 xm = 100; % x轴范围 ym = 100; % y轴范围 sink.x = 50; % 基站x轴 50 sink.y = 200; % 基站y轴 200 n = 100; % 节点总数 p = 0.05; % 簇头概率 Eelec = 50*10^(-9); Efs=10*10^(-12); Emp=0.0013*10^(-12); ED=5*10^(-9); d0 = sqrt(Efs/Emp); packetLength = 4000; ctrPacketLength = 100; rmax = 2000; figure; %% 节点随机分布 for i = 1:n Node(i).xd = rand(1,1)*xm; Node(i).yd = rand(1,1)*ym; % 随机产生100个点 Node(i).type = 'N'; % 进行选举簇头前先将所有节点设为普通节点 Node(i).E = 0.5; % 初始能量 Node(i).CH = 0; % 保存普通节点的簇头节点,-1代表自己是簇头 Node(i).d = sqrt((Node(i).xd-sink.x)^2+(Node(i).yd-sink.y)^2); Node(i).G = 0; % 候选集标志 plot(Node(i).xd, Node(i).yd, 'o', sink.x, sink.y, 'p', 'LineWidth', 2); hold on; end legend('节点', '基站'); xlabel 'x'; ylabel 'y'; title 'WSN分布图'; %% alive = zeros(rmax, 1); % 每轮存活节点数 re = zeros(rmax, 1); % 每轮节点总能量 ce = zeros(rmax, 1); % 每轮节点消耗总能量 for r = 1:10 figure; if mod(r, round(1/p)) == 0 for i = 1:n Node(i).G=0; end end for i = 1:n if Node(i).E > 0 Node(i).type = 'N'; Node(i).CH = 0; alive(r) = alive(r)+1; re(r) = re(r)+Node(i).E; end end if alive(r) == 0 break; end %% 簇头选举 cluster = 0; for i = 1:n if Node(i).E > 0 temp_rand = rand; if Node(i).G <= 0 && temp_rand < p/(1-p*mod(r,round(1/p))) Node(i).type = 'C'; % 节点类型为簇头 Node(i).G = 1; cluster = cluster + 1; % 簇头节点存入C数组 C(cluster).xd = Node(i).xd; C(cluster).yd = Node(i).yd; C(cluster).dist = Node(i).d; C(cluster).id = i; plot(C(cluster).xd, C(cluster).xd, '*'); text(Node(i).xd, Node(i).yd, num2str(i)); hold on; CH = C; Node(i).CH = -1; % 广播自成为簇头 distanceBroad = sqrt(xm*xm+ym*ym); if distanceBroad > d0 Node(i).E = Node(i).E- (Eelec*ctrPacketLength + Emp*ctrPacketLength*distanceBroad^4); ce(r) = ce(r)+Eelec*ctrPacketLength + Emp*ctrPacketLength*distanceBroad^4; else Node(i).E = Node(i).E- (Eelec*ctrPacketLength + Efs*ctrPacketLength*distanceBroad^2); ce(r) = ce(r)+Eelec*ctrPacketLength + Efs*ctrPacketLength*distanceBroad^2; end % 簇头自己发送数据包能量消耗 if Node(i).d > d0 Node(i).E = Node(i).E- ((Eelec+ED)*packetLength+Emp*packetLength*Node(i).d^4); ce(r) = ce(r)+(Eelec+ED)*packetLength+Emp*packetLength*Node(i).d^4; else Node(i).E = Node(i).E- ((Eelec+ED)*packetLength+Efs*packetLength*Node(i).d^2); ce(r) = ce(r)+(Eelec+ED)*packetLength+Efs*packetLength*Node(i).d^2; end end end end % 判断最近的簇头结点,如何去判断,采用距离矩阵 for i = 1:n if Node(i).type == 'N' && Node(i).E > 0 if cluster > 0 Length = zeros(cluster, 1); for c = 1:cluster Length(c) = sqrt((Node(i).xd - C(c).xd)^2+(Node(i).yd-C(c).yd)^2); end [min_dis, min_dis_cluster] = min(Length); % 找到距离簇头最近的簇成员节点 plot(Node(i).xd, Node(i).yd, 'o'); text(Node(i).xd, Node(i).yd, num2str(i)); hold on; plot([Node(i).xd; Node(C(min_dis_cluster).id).xd], [Node(i).yd; Node(C(min_dis_cluster).id).yd]); hold on; % 接收簇头发来的广播的消耗 Node(i).E = Node(i).E - Eelec*ctrPacketLength; ce(r) = ce(r)+Eelec*ctrPacketLength; % 加入这个簇,并发送数据给簇头 if min_dis < d0 Node(i).E = Node(i).E-(Eelec*(ctrPacketLength+packetLength)+Efs*(ctrPacketLength+packetLength)*min_dis^2); ce(r) = ce(r)+Eelec*(ctrPacketLength+packetLength)+Efs*(ctrPacketLength+packetLength)*min_dis^2; else Node(i).E = Node(i).E-(Eelec*(ctrPacketLength+packetLength)+Emp*(ctrPacketLength+packetLength)*min_dis^4); ce(r) = ce(r)+Eelec*(ctrPacketLength+packetLength)+Emp*(ctrPacketLength+packetLength)*min_dis^4; end Node(i).CH = C(min_dis_cluster).id; % 簇头接收簇成员数据包消耗能量,接收加入消息和确认加入消息 if min_dis > 0 Node(C(min_dis_cluster).id).E = Node(C(min_dis_cluster).id).E - (Eelec+ED)*packetLength; %接受簇成员发来的数据包 Node(C(min_dis_cluster).id).E = Node(C(min_dis_cluster).id).E - Eelec*ctrPacketLength; %接收加入消息 ce(r) = ce(r)+(Eelec+ED)*packetLength+Eelec*ctrPacketLength; if min_dis > d0 % 簇头向簇成员发送确认加入的消息 Node(C(min_dis_cluster).id).E = Node(C(min_dis_cluster).id).E - (Eelec*ctrPacketLength+Emp*ctrPacketLength*min_dis^4); ce(r) = ce(r)+Eelec*ctrPacketLength+Emp*ctrPacketLength*min_dis^4; else Node(C(min_dis_cluster).id).E = Node(C(min_dis_cluster).id).E - (Eelec*ctrPacketLength+Efs*ctrPacketLength*min_dis^2); ce(r) = ce(r)+Eelec*ctrPacketLength+Efs*ctrPacketLength*min_dis^2; end end else if Node(i).d < d0 Node(i).E = Node(i).E-(Eelec*packetLength+Efs*packetLength*Node(i).d^2); ce(r) = ce(r)+Eelec*packetLength+Efs*packetLength*Node(i).d^2; else Node(i).E = Node(i).E-(Eelec*packetLength+Emp*packetLength*Node(i).d^4); ce(r) = ce(r)+Eelec*packetLength+Emp*packetLength*Node(i).d^4; end end end end clear C; end
随机选取4幅分簇图,如图2~5所示。
图2~5 LEACH分簇图
2、节点能量消耗
代码如下:
%% 清空环境变量 clear; clc; %% 初始化参数 xm = 100; % x轴范围 ym = 100; % y轴范围 sink.x = 50; % 基站x轴 50 sink.y = 200; % 基站y轴 200 n = 100; % 节点总数 p = 0.05; % 簇头概率 Eelec = 50*10^(-9); Efs=10*10^(-12); Emp=0.0013*10^(-12); ED=5*10^(-9); d0 = sqrt(Efs/Emp); packetLength = 4000; ctrPacketLength = 100; rmax = 1500; figure; %% 节点随机分布 for i = 1:n Node(i).xd = rand(1,1)*xm; Node(i).yd = rand(1,1)*ym; % 随机产生100个点 Node(i).type = 'N'; % 进行选举簇头前先将所有节点设为普通节点 Node(i).E = 0.5; % 初始能量 Node(i).CH = 0; % 保存普通节点的簇头节点,-1代表自己是簇头 Node(i).d = sqrt((Node(i).xd-sink.x)^2+(Node(i).yd-sink.y)^2); Node(i).G = 0; % 候选集标志 plot(Node(i).xd, Node(i).yd, 'o', sink.x, sink.y, 'p', 'LineWidth', 2); hold on; end legend('节点', '基站'); xlabel 'x'; ylabel 'y'; title 'WSN分布图'; %% alive = zeros(rmax, 1); % 每轮存活节点数 re = zeros(rmax, 1); % 每轮节点总能量 ce = zeros(rmax, 1); % 每轮节点消耗总能量 for r = 1:rmax if mod(r, round(1/p)) == 0 for i = 1:n Node(i).G=0; end end for i = 1:n if Node(i).E > 0 Node(i).type = 'N'; Node(i).CH = 0; alive(r) = alive(r)+1; re(r) = re(r)+Node(i).E; end end if alive(r) == 0 break; end %% 簇头选举 cluster = 0; for i = 1:n if Node(i).E > 0 temp_rand = rand; if Node(i).G <= 0 && temp_rand < p/(1-p*mod(r,round(1/p))) Node(i).type = 'C'; % 节点类型为簇头 Node(i).G = 1; cluster = cluster + 1; % 簇头节点存入C数组 C(cluster).xd = Node(i).xd; C(cluster).yd = Node(i).yd; C(cluster).dist = Node(i).d; C(cluster).id = i; CH = C; Node(i).CH = -1; % 广播自成为簇头 distanceBroad = sqrt(xm*xm+ym*ym); if distanceBroad > d0 Node(i).E = Node(i).E- (Eelec*ctrPacketLength + Emp*ctrPacketLength*distanceBroad^4); ce(r) = ce(r)+Eelec*ctrPacketLength + Emp*ctrPacketLength*distanceBroad^4; else Node(i).E = Node(i).E- (Eelec*ctrPacketLength + Efs*ctrPacketLength*distanceBroad^2); ce(r) = ce(r)+Eelec*ctrPacketLength + Efs*ctrPacketLength*distanceBroad^2; end % 簇头自己发送数据包能量消耗 if Node(i).d > d0 Node(i).E = Node(i).E- ((Eelec+ED)*packetLength+Emp*packetLength*Node(i).d^4); ce(r) = ce(r)+(Eelec+ED)*packetLength+Emp*packetLength*Node(i).d^4; else Node(i).E = Node(i).E- ((Eelec+ED)*packetLength+Efs*packetLength*Node(i).d^2); ce(r) = ce(r)+(Eelec+ED)*packetLength+Efs*packetLength*Node(i).d^2; end end end end % 判断最近的簇头结点,如何去判断,采用距离矩阵 for i = 1:n if Node(i).type == 'N' && Node(i).E > 0 if cluster > 0 Length = zeros(cluster, 1); for c = 1:cluster Length(c) = sqrt((Node(i).xd - C(c).xd)^2+(Node(i).yd-C(c).yd)^2); end [min_dis, min_dis_cluster] = min(Length); % 找到距离簇头最近的簇成员节点 % 接收簇头发来的广播的消耗 Node(i).E = Node(i).E - Eelec*ctrPacketLength; ce(r) = ce(r)+Eelec*ctrPacketLength; % 加入这个簇,并发送数据给簇头 if min_dis < d0 Node(i).E = Node(i).E-(Eelec*(ctrPacketLength+packetLength)+Efs*(ctrPacketLength+packetLength)*min_dis^2); ce(r) = ce(r)+Eelec*(ctrPacketLength+packetLength)+Efs*(ctrPacketLength+packetLength)*min_dis^2; else Node(i).E = Node(i).E-(Eelec*(ctrPacketLength+packetLength)+Emp*(ctrPacketLength+packetLength)*min_dis^4); ce(r) = ce(r)+Eelec*(ctrPacketLength+packetLength)+Emp*(ctrPacketLength+packetLength)*min_dis^4; end Node(i).CH = C(min_dis_cluster).id; % 簇头接收簇成员数据包消耗能量,接收加入消息和确认加入消息 if min_dis > 0 Node(C(min_dis_cluster).id).E = Node(C(min_dis_cluster).id).E - (Eelec+ED)*packetLength; %接受簇成员发来的数据包 Node(C(min_dis_cluster).id).E = Node(C(min_dis_cluster).id).E - Eelec*ctrPacketLength; %接收加入消息 ce(r) = ce(r)+(Eelec+ED)*packetLength+Eelec*ctrPacketLength; if min_dis > d0 % 簇头向簇成员发送确认加入的消息 Node(C(min_dis_cluster).id).E = Node(C(min_dis_cluster).id).E - (Eelec*ctrPacketLength+Emp*ctrPacketLength*min_dis^4); ce(r) = ce(r)+Eelec*ctrPacketLength+Emp*ctrPacketLength*min_dis^4; else Node(C(min_dis_cluster).id).E = Node(C(min_dis_cluster).id).E - (Eelec*ctrPacketLength+Efs*ctrPacketLength*min_dis^2); ce(r) = ce(r)+Eelec*ctrPacketLength+Efs*ctrPacketLength*min_dis^2; end end else % 无簇头选出,直接发送数据包到基站 if Node(i).d < d0 Node(i).E = Node(i).E-(Eelec*packetLength+Efs*packetLength*Node(i).d^2); ce(r) = ce(r)+Eelec*packetLength+Efs*packetLength*Node(i).d^2; else Node(i).E = Node(i).E-(Eelec*packetLength+Emp*packetLength*Node(i).d^4); ce(r) = ce(r)+Eelec*packetLength+Emp*packetLength*Node(i).d^4; end end end end clear C; end %% 绘图显示 figure; plot(1:rmax, alive, 'r', 'LineWidth', 2); xlabel '轮数'; ylabel '每轮存活节点数'; figure; plot(1:rmax, re, 'b', 'LineWidth', 2); xlabel '轮数'; ylabel '每轮剩余总能量'; figure; plot(1:rmax, ce, 'm', 'LineWidth', 1); xlabel '轮数'; ylabel '每轮消耗总能量';
每轮节点存活个数如图6所示。
图6 每轮节点存活个数
每轮节点总剩余能量如图7所示。
图7 每轮节点总剩余能量
每轮节点总消耗能量如图8所示。
图8 每轮节点总消耗能量
四、参考文献代码下载或者仿真咨询添加QQ1575304183
[1] kkzhang .LEACH分簇算法实现和能量控制算法实现. 博客园
[2] HEINZELMAN W, CHANDRAKASAN A, BALAKRISHNAN H. Energy- efficient communication protocol for wireless micro- sensor networks[C]/ /Proc of the 33rd Hawaii International Conference on System Sciences. Washington:IEEE Computer Society, 2000:3005- 3014.
[3] 喻小惠,张晶,陶涛,龚力波,黄云明,傅铁威.基于蚁群策略的无线传感器网络能耗均衡分簇算法[J].计算机工程与科学,2019,41(07):1197-1202.
标签:Node,packetLength,LEACH,min,ctrPacketLength,ce,matlab,分簇,Eelec 来源: https://blog.51cto.com/u_15287693/2960378