用生物学启发的智能优化为UWSNs采用节能层次路由方法
Wei Chen1, Lina He1, Bingyu Cao1
1School of Information Science and Engineering, Xinjiang College of Science & Technology, Korla, 841000, Xinjiang, China.
Scientific reports
|October 1, 2025
概括
本研究介绍了一种改进的灰狼优化算法,用于水下无线传感器网络 (UWSNs). 新方法通过优化集群头选择和路由来提高能源效率和网络寿命.
科学领域:
- 计算机科学 计算机科学
- 网络工程 网络工程
- 人工智能的人工智能
背景情况:
- 水下无线传感器网络 (UWSNs) 面临着能源消耗不均和集群头选择不足的挑战.
- 现有的路由算法经常难以平衡能源效率和网络寿命.
研究的目的:
- 为UWSNs提出一个改进的灰狼优化算法 (CTRGWO-CRP).
- 解决能源消耗不平衡问题,优化UWSN中的集群头部选择.
主要方法:
- 在灰狼优化框架内实施了克隆策略,t分布扰动突变和基于对立的学习.
- 设计了一个动态加权的健身功能,结合了网络能量和通信距离.
- 采用精英保留策略来选择集群头和多跳转中继机制来传输数据.
主要成果:
- 与LEACH,DMaOWOA和GSHFA-HCP相比,CTRGWO-CRP算法显著延长了至少23.5%的网络寿命.
- 通过多目标优化,证明了能源平衡和传输效率的改善.
- 验证了多策略融合在路由优化中的有效性.
结论:
- 拟议的CTRGWO-CRP算法为UWSN性能提供了显著的改进.
- 多种策略的融合有效地优化了路由,并延长了网络寿命.
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