Energy-Efficient Communication Protocol for Wireless Microsensor Networks
文章目录
- 一、理论基础
- 二、方法描述
- 1、节点分簇
- 2、节点能量消耗
- 三、仿真分析
- 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
簇头选举初始阶段，每个节点根据所建议网络簇头的百分比（事先确定）和节点已经成为簇头的次数来确定自己是否当选为簇头。每个节点产生一个0-1的随机数字，如果该数字小于阈值，节点成为当前轮的簇头。阈值定义为：
T(n)={p1−p×(rmod1p),n∈G0,else(1)T(n)=\begin{dcases} \frac{p}{1-p×(r mod \frac1p)},\quad n∈G\\0, \quad \quad \quad \quad \quad \quad \quad \quad else\end{dcases}\tag{1}T(n)=⎩⎨⎧1−p×(rmodp1)p,n∈G0,else(1)其中，nnn为当前节点，ppp为预期的簇头百分比，rrr为当前轮数，GGG是最近1/p1/p1/p轮里没有成为簇头的节点的集合。
2、节点能量消耗
传感器节点在传输kkkbit数据到距离该传感器节点ddd的邻接传感器节点时需消耗的能量如式（2）所示：ETx(k,d)={Eelec⋅k+εfs⋅k⋅d2,d<d0Eelec⋅k+εmp⋅k⋅d4,d≥d0(2)E_{Tx}(k,d)=\begin{dcases} E_{elec}\boldsymbol ·k+\varepsilon_{fs}\boldsymbol ·k\boldsymbol ·d^2,d<d_{0}\\E_{elec}\boldsymbol ·k+\varepsilon_{mp}\boldsymbol ·k\boldsymbol ·d^4,d\geq d_0\end{dcases}\tag{2}ETx(k,d)={Eelec⋅k+εfs⋅k⋅d2,d<d0Eelec⋅k+εmp⋅k⋅d4,d≥d0(2)节点接收到kkkbit数据需消耗的能量如式（3）所示：ERx(k)=Eelec⋅k(3)E_{Rx}(k)=E_{elec}\boldsymbol ·k\tag{3}ERx(k)=Eelec⋅k(3)其中，EelecE_{elec}Eelec是传感器处理单位bit的数据时所需要的能量值，εfs\varepsilon_{fs}εfs和εmp\varepsilon_{mp}εmp是通信能量参数，d0d_0d0是阈值。如果距离ddd小于d0d_0d0，则使用自由空间传播（free space communication）模型； 否则，使用多路径衰减信道（multipath fading channel）模型。阈值d0d_0d0的计算方法如式（4） 所示：d0=εfsεmp(4)d_0=\sqrt {\frac {\varepsilon_{fs}}{\varepsilon_{mp}}}\tag{4}d0=εmpεfs(4)
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
xmin = 0; xmax = 100; % 区域x轴范围
ymin = 0; ymax = 100; % 区域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:nNode(i).xd = rand*(xmax-xmin)+xmin;Node(i).yd = rand*(ymax-ymin)+ymin; % 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 = 1:10figure;if mod(r, round(1/p)) == 0for i = 1:nNode(i).G=0;endendfor i = 1:nif Node(i).E > 0Node(i).type = 'N';Node(i).CH = 0;alive(r) = alive(r)+1;re(r) = re(r)+Node(i).E;endendif alive(r) == 0break;end%% 簇头选举cluster = 0;for i = 1:nif Node(i).E > 0temp_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).yd, '*');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((xmax-xmin)^2+(ymax-ymin)^2);if distanceBroad > d0Node(i).E = Node(i).E- (Eelec*ctrPacketLength + Emp*ctrPacketLength*distanceBroad^4);ce(r) = ce(r)+Eelec*ctrPacketLength + Emp*ctrPacketLength*distanceBroad^4;elseNode(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 > d0Node(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;elseNode(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;endendendend% 判断最近的簇头结点，如何去判断，采用距离矩阵for i = 1:nif Node(i).type == 'N' && Node(i).E > 0if cluster > 0Length = zeros(cluster, 1);for c = 1:clusterLength(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 < d0Node(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;elseNode(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;endNode(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 > 0Node(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;elseNode(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;endendelseif Node(i).d < d0Node(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;elseNode(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;endendendendclear 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;xmin = 0; xmax = 100; % 区域x轴范围
ymin = 0; ymax = 100; % 区域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:nNode(i).xd = rand*(xmax-xmin)+xmin;Node(i).yd = rand*(ymax-ymin)+ymin; % 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:rmaxif mod(r, round(1/p)) == 0for i = 1:nNode(i).G=0;endendfor i = 1:nif Node(i).E > 0Node(i).type = 'N';Node(i).CH = 0;alive(r) = alive(r)+1;re(r) = re(r)+Node(i).E;endendif alive(r) == 0break;end%% 簇头选举cluster = 0;for i = 1:nif Node(i).E > 0temp_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((xmax-xmin)^2+(ymax-ymin)^2);if distanceBroad > d0Node(i).E = Node(i).E- (Eelec*ctrPacketLength + Emp*ctrPacketLength*distanceBroad^4);ce(r) = ce(r)+Eelec*ctrPacketLength + Emp*ctrPacketLength*distanceBroad^4;elseNode(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 > d0Node(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;elseNode(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;endendendend% 判断最近的簇头结点，如何去判断，采用距离矩阵for i = 1:nif Node(i).type == 'N' && Node(i).E > 0if cluster > 0Length = zeros(cluster, 1);for c = 1:clusterLength(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 < d0Node(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;elseNode(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;endNode(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 > 0Node(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;elseNode(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;endendelse % 无簇头选出，直接发送数据包到基站if Node(i).d < d0Node(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;elseNode(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;endendendendclear 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
[1] W. R. Heinzelman, A. Chandrakasan, H. Balakrishnan. Energy-efficient communication protocol for wireless microsensor networks[C]. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, 2000, 2: 1-10.
[2] kkzhang. LEACH分簇算法实现和能量控制算法实现. 博客园.
[3] 喻小惠, 张晶, 陶涛, 等. 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(7): 1197-1202.
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