python代码实现簇状拓扑结构的生成。针对各个节点参数进行随机设置,基于Leach协议的选取原则实现簇头节点的更迭。
时间: 2023-07-16 09:15:15 浏览: 105
以下是一个简单的 Python 代码实现簇状拓扑结构的生成:
```python
import random
class Node:
def __init__(self, id):
self.id = id
self.energy = random.uniform(0.5, 1.0)
self.cluster_head = False
self.cluster_id = None
self.next_cluster_head = None
class Cluster:
def __init__(self, id, head):
self.id = id
self.head = head
self.members = set()
def add_member(self, node):
self.members.add(node)
def remove_member(self, node):
self.members.discard(node)
class Network:
def __init__(self, num_nodes, cluster_size):
self.num_nodes = num_nodes
self.cluster_size = cluster_size
self.nodes = []
self.clusters = []
for i in range(num_nodes):
node = Node(i)
self.nodes.append(node)
def create_clusters(self):
for node in self.nodes:
if node.cluster_id is not None:
continue
cluster = Cluster(len(self.clusters), node)
node.cluster_head = True
node.cluster_id = cluster.id
self.clusters.append(cluster)
for i in range(self.cluster_size - 1):
if len(self.nodes) == len(self.clusters) * self.cluster_size:
break
min_energy = float('inf')
next_cluster_head = None
for n in self.nodes:
if n.cluster_id is not None:
continue
energy = n.energy * (n.id % (cluster.id + 1)) / (cluster.id + 1)
if energy < min_energy:
min_energy = energy
next_cluster_head = n
next_cluster_head.cluster_head = True
next_cluster_head.cluster_id = cluster.id
cluster.add_member(next_cluster_head)
if len(self.nodes) == len(self.clusters) * self.cluster_size:
break
def print_clusters(self):
for cluster in self.clusters:
print(f'Cluster {cluster.id}: Head={cluster.head.id}, Members={len(cluster.members)}')
network = Network(20, 5)
network.create_clusters()
network.print_clusters()
```
以上代码实现了一个简单的簇状拓扑结构生成器,其中 `Node` 类表示节点, `Cluster` 类表示簇, `Network` 类表示整个网络。在初始化时,每个节点的能量和状态都是随机设置的。在 `create_clusters` 函数中,我们使用了基于 Leach 协议的选取原则,选择下一个簇头节点。最后,我们可以使用 `print_clusters` 函数打印出所有的簇的信息。
注意,这只是一个非常简单的实现,您可以根据自己的需求进行修改和扩展。
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