基于K-means聚类算法实现无线传感器网络分簇路由协议

Posted 2021-06-29 博主QQ2449341593

文章目录

• 一、算法设计
• 二、仿真分析
• 三、参考文献

 

一、算法设计

二、仿真分析

图1 K-means分簇

如图1所示，使用MATLAB R2018b进行了100个节点的仿真，黑色十字表示选择到的簇头节点，每个颜色代表簇。可见，网络的拓扑结构合理，簇头节点位置在族的中心，这样节约了簇内节点信息汇集的传输成本。
对于仿真中节点的参数设定则如表1所示：

表1 仿真参数

存活节点与轮数的关系如图2所示：

 

图2 存活节点与轮数的关系

系统剩余总能量与轮数的关系如图3所示：

图3 系统剩余总能量与轮数的关系

系统消耗总能量与轮数的关系如图4所示：

图3 系统剩余总能量与轮数的关系

代码如下：

%% 清空环境变量
close all;
clear;
clc;
%% % 网络建立参数
%% 网络参数
xm = 100;
ym = 100;                     % 区域范围
n = 100;                      % 节点总个数
sinkx = 50;
sinky = 50;                   % 基站位置
p = 0.2;                      % 簇头选择概率
%% 能量参数
Eo = 1;                       % 初始能量（单位：焦耳J）
% 所需的能量（发射器和接收器）
Eelec = 50*10^(-9);
Efs = 10*10^(-12);
Eamp = 0.0015*10^(-12);
d0 = sqrt(Efs/Eamp);
EDA = 5*10^(-9);              % 数据聚合能量
packetLength = 4000;          % 数据包大小
ctrPacketLength = 100;        % 控制数据包大小
rmax = 7000;                  % 最大循环轮数
%% % Creation of the Wireless Sensor Network
%% 画出WSN
figure
for i = 1:n
    Node(i).id = i;              % 节点的ID
    Node(i).x = rand(1,1)*xm;	 % 节点X坐标
    Node(i).y = rand(1,1)*ym;	 % 节点Y坐标
    Node(i).E = Eo;              % 节点当前能量 (初始值为Eo）
    Node(i).cond = 1;            % 节点的当前状态：存活   1；死亡  0
    Node(i).dts = sqrt((Node(i).x-sinkx)^2+(Node(i).y-sinky)^2);  % 节点到基站的距离
    Node(i).role = 0;            % 节点的角色：普通节点   0；簇头节点  1
    Node(i).CH = 0;              % 簇头节点：-1  自己是簇头
    Node(i).G = 0;               % 候选集标志
    plot(Node(i).x, Node(i).y, 'ob', sinkx, sinky, '*r');
    hold on;
    title 'Wireless Sensor Network';
    xlabel '(m)';
    ylabel '(m)';
    X(i, :) = [Node(i).x, Node(i).y];
end

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
%% % 迭代
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).cond ~= 0
            Node(i).type = 'N';
            Node(i).role = 0;
            re(r) = re(r)+Node(i).E;
            alive(r) = alive(r)+1;
        end
    end
    f = 0;
    if alive(r) == 0
        break;
    end
    %% 簇头选举
    k = 0;              % 质心个数
    % 确定质心个数
    for i = 1:n
        if Node(i).role == 0 && Node(i).cond ~= 0
            temp_rand = rand;
            if Node(i).G <= 0 && temp_rand < p/(1-p*mod(r,round(1/p)))
                k = k + 1;
                Node(i).G = 1;
            end
        end
    end
    %%% k-means聚类
    center = zeros(k, 2);
    Idx = zeros(n, 1);
    % 随机选择k个质心
    for i = 1:k
        center(i, :) = rand(1, 2)*xm;
    end
    while 1
        distance = zeros(1, k);             % 最小距离矩阵
        num = zeros(1, k);                  % 聚类簇数矩阵
        new_center = zeros(k, 2);           % 聚类中心矩阵
        for i = 1:n
            for j = 1:k
                distance(j) = norm(X(i, :)-center(j, :));       % 计算到每个簇的距离
            end
            [~, min_index] = min(distance);     % 求最小的距离
            Idx(i) = min_index;                 % 划分所有对象点到最近的聚类中心
        end
        q = 0;
        for i = 1:k
            for j = 1:n
                if Idx(j) == i
                    new_center(i, :) = new_center(i, :)+X(j, :);
                    num(i) = num(i)+1;
                end
            end
            if num(i) > 0
                new_center(i, :) = new_center(i, :)/num(i);    % 求均值，即新的聚类中心
            else
                new_center(i, :) = center(i, :);
            end
            if norm(new_center(i, :)-center(i, :)) < 0.1    % 检查集群中心是否已收敛。如果是则终止。
                q = q+1;
            end
        end
        if q >= k
            break;
        else
            center = new_center;
        end
    end
    %     figure;
    %     plot(sinkx, sinky, 'rp', 'MarkerSize', 14)
    %     hold on
    %     plot(center(:, 1), center(:, 2), 'kx', 'MarkerSize', 14, 'LineWidth', 4)
    %     hold on
    %     plot(X(Idx==1,1),X(Idx==1,2),'r.','MarkerSize',14)
    %     hold on
    %     plot(X(Idx==2,1),X(Idx==2,2),'b.','MarkerSize',14)
    %     hold on
    %     plot(X(Idx==3,1),X(Idx==3,2),'g.','MarkerSize',14)
    %     hold on
    %     plot(X(Idx==4,1),X(Idx==4,2),'k.','MarkerSize',14)
    %     hold on
    %     plot(X(Idx==5,1),X(Idx==5,2),'y.','MarkerSize',14)
    %     hold on
    %     plot(X(Idx==6,1),X(Idx==6,2),'c.','MarkerSize',14)
    %     hold on
    %     plot(X(Idx==7,1),X(Idx==7,2),'m.','MarkerSize',14)
    %     hold on
    % 找出离质心最近的节点作为簇头
    if k ~= 0
        for i = 1:k
            len = sqrt((X(Idx==i, 1)-center(i, 1)).^2+(X(Idx==i, 2)-center(i, 2)).^2);
            if ~isempty(len)
                [~, min_index] = min(len);
                count = 0;
                for j = 1:n
                    if Idx(j) == i
                        count = count + 1;
                    end
                    if count == min_index
                        min_index = j;
                        break;
                    end
                end
                if Node(min_index).E > 0
                    Node(min_index).role = 1;
                    Node(min_index).CH = -1;
                    % 簇头广播
                    distanceBroad = sqrt(xm*xm+ym*ym);
                    if distanceBroad > d0
                        Node(min_index).E = Node(min_index).E- (Eelec*ctrPacketLength + Eamp*ctrPacketLength*distanceBroad^4);
                        ce(r) = ce(r)+Eelec*ctrPacketLength + Eamp*ctrPacketLength*distanceBroad^4;
                    else
                        Node(min_index).E = Node(min_index).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(min_index).dts > d0
                        Node(min_index).E = Node(min_index).E- ((Eelec+EDA)*packetLength+Eamp*packetLength*Node(i).dts^4);
                        ce(r) = ce(r)+(Eelec+EDA)*packetLength+Eamp*packetLength*Node(i).dts^4;
                    else
                        Node(min_index).E = Node(min_index).E- ((Eelec+EDA)*packetLength+Efs*packetLength*Node(i).dts^2);
                        ce(r) = ce(r)+(Eelec+EDA)*packetLength+Efs*packetLength*Node(i).dts^2;
                    end
                    for j = 1:n
                        if Idx(j) == i && min_index ~= j
                            % 普通节点接收簇头发来的广播的消耗
                            Node(j).E = Node(j).E - Eelec*ctrPacketLength;
                            ce(r) = ce(r)+Eelec*ctrPacketLength;
                            % 普通节点向簇头发送加入簇的控制消息，并发送数据给簇头
                            dist = sqrt((Node(j).x-Node(min_index).x)^2+(Node(j).y-Node(min_index).y)^2);
                            if dist < d0
                                Node(j).E = Node(j).E - (Eelec*(ctrPacketLength+packetLength)+Efs*(ctrPacketLength+packetLength)*dist^2);
                                ce(r) = ce(r)+Eelec*(ctrPacketLength+packetLength)+Efs*(ctrPacketLength+packetLength)*dist^2;
                            else
                                Node(j).E = Node(j).E - (Eelec*(ctrPacketLength+packetLength)+Eamp*(ctrPacketLength+packetLength)*dist^4);
                                ce(r) = ce(r)+Eelec*(ctrPacketLength+packetLength)+Eamp*(ctrPacketLength+packetLength)*dist^4;
                            end
                            Node(j).CH = min_index;
                            % 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
                            Node(min_index).E = Node(min_index).E - (Eelec+EDA)*packetLength; %接受簇成员发来的数据包
                            Node(min_index).E = Node(min_index).E - Eelec*ctrPacketLength; %接收加入消息
                            ce(r) = ce(r)+(Eelec+EDA)*packetLength+Eelec*ctrPacketLength;
                            if dist > d0      % 簇头向簇成员发送确认加入的消息
                                Node(min_index).E = Node(min_index).E - (Eelec*ctrPacketLength+Eamp*ctrPacketLength*dist^4);
                                ce(r) = ce(r)+Eelec*ctrPacketLength+Eamp*ctrPacketLength*dist^4;
                            else
                                Node(min_index).E = Node(min_index).E - (Eelec*ctrPacketLength+Efs*ctrPacketLength*dist^2);
                                ce(r) = ce(r)+Eelec*ctrPacketLength+Efs*ctrPacketLength*dist^2;
                            end
                        end
                    end
                else    % 此质心所在的簇成员直接发送数据包到基站
                    for j = 1:n
                        if Node(j).E > 0
                            if Idx(j) == i && min_index ~= j
                                if Node(j).dts > d0      % 簇头向簇成员发送确认加入的消息
                                    Node(j).E = Node(j).E - (Eelec*ctrPacketLength+Eamp*ctrPacketLength*Node(j).dts^4);
                                    ce(r) = ce(r)+Eelec*ctrPacketLength+Eamp*ctrPacketLength*Node(j).dts^4;
                                else
                                    Node(j).E = Node(j).E - (Eelec*ctrPacketLength+Efs*ctrPacketLength*Node(j).dts^2);
                                    ce(r) = ce(r)+Eelec*ctrPacketLength+Efs*ctrPacketLength*Node(j).dts^2;
                                end
                            end
                        end
                    end
                end
            end
        end
    else             % 无质心，直接发送数据包到基站
        for i = 1:n
            if Node(i).E > 0
                if Node(j).dts > d0      % 簇头向簇成员发送确认加入的消息
                    Node(j).E = Node(j).E - (Eelec*ctrPacketLength+Eamp*ctrPacketLength*Node(j).dts^4);
                    ce(r) = ce(r)+Eelec*ctrPacketLength+Eamp*ctrPacketLength*Node(j).dts^4;
                else
                    Node(j).E = Node(j).E - (Eelec*ctrPacketLength+Efs*ctrPacketLength*Node(j).dts^2);
                    ce(r) = ce(r)+Eelec*ctrPacketLength+Efs*ctrPacketLength*Node(j).dts^2;
                end
            end
        end
    end
    %     % 画出分簇图
    %     figure;
    %     for i = 1:n
    %         if Node(i).role == 1
    %             plot(Node(i).x, Node(i).y, '*');
    %             hold on
    %         else
    %             plot(Node(i).x, Node(i).y, 'o');
    %             hold on
    %             plot([Node(Node(i).CH).x; Node(i).x], [Node(Node(i).CH).y; Node(i).y]);
    %             hold on
    %         end
    %     end
    for i = 1:n
        if Node(i).E <= 0
            Node(i).cond = 0;
        end
    end
end
%% 绘图显示
figure;
plot(1:rmax, alive, 'r', 'LineWidth', 2);
xlabel '轮数'; ylabel '存活节点数';
figure;
plot(1:rmax, re, 'b', 'LineWidth', 2);
xlabel '轮数'; ylabel '剩余总能量';
figure;
plot(1:rmax, ce, 'm', 'LineWidth', 1);
xlabel '轮数'; ylabel '消耗总能量';

三、参考文献

[1] 王家深. 无线传感器路由协议优化研究[D].海南大学,2019.
[2] nineships. K-means算法的matlab实现. CSDN博客.