一个能源意识的集群启发了使用多策略的路由协议,改进了鱼优化算法,以保证物联网中的绿色通信.
R Chithra1, C K Sarumathiy2, E Padma3
1Department of Information Technology, K. S. Rangasamy College of Technology, Tiruchengode, Namakkal, Tamil Nadu, 637 215, India. chithra@ksrct.ac.in.
Scientific reports
|October 6, 2025
概括
本研究介绍了一种用于物联网 (IoT) 的新型智能集群机制,以提高能源效率和网络寿命. 拟议的方法优化了集群头的选择,大大提高了吞吐量,减少了物联网网络中的传输延迟.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 环境科学 环境科学
背景情况:
- 物联网 (IoT) 连接了数十亿台设备,导致了重大的环境和经济影响.
- 能源消耗对于物联网传感器运行至关重要,但快速耗尽能源会威胁到性能和稳定性.
- 使用元启发式技术进行聚类为物联网中的能源管理和服务质量提供了一个有希望的方法.
研究的目的:
- 为物联网中绿色通信提出智能集群机制,最大限度地提高网络寿命.
- 在大规模物联网部署中解决能源管理的NP难题.
- 通过优化能源利用和集群头部选择,提高物联网网络的性能.
主要方法:
- 开发了一个基于多策略改进的鱼优化算法智能集群机制 (MSCFOAICM).
- 实现了一个考虑延迟,能量,距离,动和数据包转发潜力的多目标健身功能.
- 使用混合BWM-TOPSIS多标准决策模型进行信任评估和选择高能耗,非恶意集群头.
主要成果:
- 该MSCFOAICM计划实现了最佳的集群形成,保持最大限度的能量和延长网络寿命.
- 显示吞吐量提高了18.14%,运行物联网节点增加了19.42%.
- 与基线方案相比,实现了平均传输延迟减少18.42%.
结论:
- 拟议的MSCFOAICM通过优化能源效率和网络寿命,有效地增强物联网中的绿色通信.
- 智能集群机制为管理大规模物联网网络中的能源稳定性和性能提供了强大的解决方案.
- 在吞吐量,运营节点和传输延迟方面,MSCFOAICM显著优于现有方法.
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