Python代码实现基于K-MEANS的LEACH协议构建

以下是基于Python实现基于K-MEANS的LEACH协议构建的代码样例：

import random
import math

# 定义节点类
class Node:
    def __init__(self, x, y, energy):
        self.x = x  # 节点的x坐标
        self.y = y  # 节点的y坐标
        self.energy = energy  # 节点的能量
        self.cluster = None  # 节点所在的簇
        self.is_cluster_head = False  # 是否是簇首节点

# 定义LEACH协议类
class LEACH:
    def __init__(self, node_list, k):
        self.node_list = node_list  # 节点列表
        self.k = k  # 簇的个数
        self.cluster_head_list = []  # 簇首节点列表

    # K-MEANS聚类算法
    def k_means(self):
        # 随机选择k个节点作为初始簇首节点
        cluster_head_index_list = random.sample(range(len(self.node_list)), self.k)
        for i in range(len(self.node_list)):
            node = self.node_list[i]
            min_distance = float('inf')
            for j in range(self.k):
                cluster_head = self.node_list[cluster_head_index_list[j]]
                distance = math.sqrt((node.x - cluster_head.x) ** 2 + (node.y - cluster_head.y) ** 2)
                if distance < min_distance:
                    min_distance = distance
                    node.cluster = j
            if node.cluster_head == None:
                node.cluster_head = self.node_list[cluster_head_index_list[node.cluster]]
        # 更新簇首节点
        for i in range(self.k):
            cluster_head = None
            min_energy = float('inf')
            for node in self.node_list:
                if node.cluster == i and node.energy < min_energy:
                    cluster_head = node
                    min_energy = node.energy
            if cluster_head != None:
                cluster_head.is_cluster_head = True
                self.cluster_head_list.append(cluster_head)

    # LEACH协议
    def leach(self):
        # 第一轮选举簇首节点
        for node in self.node_list:
            if node.is_cluster_head == False:
                if random.random() < node.energy / 10:
                    node.is_cluster_head = True
                    self.cluster_head_list.append(node)
        # 其他轮选举簇首节点
        for t in range(2, 100):
            for node in self.node_list:
                if node.is_cluster_head == False:
                    p = 0.1 * (1 - float(t % (1 / 0.1)) / (1 / 0.1))
                    if random.random() < p:
                        node.is_cluster_head = True
                        self.cluster_head_list.append(node)
            # 簇首节点收集数据
            for cluster_head in self.cluster_head_list:
                for node in self.node_list:
                    if node.cluster_head == cluster_head and node.is_cluster_head == False:
                        # 进行数据传输等操作
                        pass
            # 簇首节点更新
            for node in self.node_list:
                if node.is_cluster_head == True:
                    node.is_cluster_head = False
            self.cluster_head_list = []

以上是一个简单的基于Python实现基于K-MEANS的LEACH协议构建的代码样例，仅供参考。具体实现需要根据实际情况进行修改和优化。