用MATLAB生成一个500500200的三维水下监测区域，共进行200个节点的部署。生成一个运行结果，然后再将这200个节点进行随机部署在三维水下监测区域，使用self-deployment算法将节点进行分簇，生成运行结果

生成500x500x200的三维水下监测区域：

x = 500;
y = 500;
z = 200;
monitoringArea = zeros(x,y,z);

将200个节点随机部署在监测区域中：

numNodes = 200;
nodePositions = randi([1 x],numNodes,1);
nodePositions(:,2) = randi([1 y],numNodes,1);
nodePositions(:,3) = randi([1 z],numNodes,1);

使用self-deployment算法将节点进行分簇：

% 定义簇的数量和半径
numClusters = 20;
radius = 20;

% 初始化每个节点的簇ID
clusterIDs = zeros(numNodes,1);

% 随机选择一个节点作为第一个簇的中心
clusterCenters = nodePositions(randi(numNodes),:);

% 将其他节点分配到簇中
for i = 1:numNodes
    distToCenters = sqrt(sum((nodePositions(i,:) - clusterCenters).^2,2));
    [minDist, minIndex] = min(distToCenters);
    if minDist <= radius
        clusterIDs(i) = minIndex;
        % 更新簇中心
        clusterCenters(minIndex,:) = mean(nodePositions(clusterIDs==minIndex,:),1);
    else
        % 创建新簇
        numClusters = numClusters + 1;
        clusterIDs(i) = numClusters;
        clusterCenters = [clusterCenters; nodePositions(i,:)];
    end
end

生成运行结果：

% 绘制监测区域和节点位置
figure;
plot3(nodePositions(:,1),nodePositions(:,2),nodePositions(:,3),'r.','MarkerSize',10);
hold on;
for i = 1:numClusters
    plot3(nodePositions(clusterIDs==i,1),nodePositions(clusterIDs==i,2),nodePositions(clusterIDs==i,3),'.','MarkerSize',10);
end
axis([1 x 1 y 1 z]);
grid on;
title('Self-deployment Results');
xlabel('X-axis');
ylabel('Y-axis');
zlabel('Z-axis');

运行结果如下图所示：