在无线传感器网络中使用游戏理论和进化策略的智能不平等集群
Yanhui Qu1, Yingyi Qu2, Zhiqiang Zhu3
1Wenzhou Institute of Industry & Science, Wenzhou, 325000, Zhejiang Province, China.
Scientific reports
|September 26, 2025
概括
本研究介绍了无线传感器网络 (WSN) 的智能不平等集群方法,以平衡能源消耗. 最优化的方法通过提高能源效率和可靠性,大大延长了网络运行时间.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 网络工程 网络工程
背景情况:
- 无线传感器网络 (WSN) 中的传统集群导致能量分布不均和网络过早故障.
- 不统一的集群头分布无法适应不同的节点密度和流量,导致某些节点的能量迅速耗尽,而另一些节点则保持置.
研究的目的:
- 为WSN开发智能不平等集群技术,以提高能源效率和网络寿命.
- 解决能源不平衡问题,改善WSN中的负载分布.
主要方法:
- 利用Coyote优化算法 (COA) 进行自适应集群头部选择.
- 实现模糊逻辑,根据网络条件动态调整集群半径.
- 在节能数据路由方面采用了游戏理论方法.
主要成果:
- 拟议的方法明显优于传统的EE-LEACH,将网络寿命延长了124.5%.
- 在能源效率,网络可靠性和整体运行持续时间方面取得了显著的改进.
- 在各种网络条件下展示了有效的负载平衡.
结论:
- 智能不平等集群方法为改善WSN性能提供了强大的解决方案.
- 动态聚类与优化路由相结合,提高了能源效率,可靠性和网络寿命.
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