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使用基于神经模糊的数据路由机制进行节能数据路由,用于支持物联网的WSN
Sakthi Shunmuga Sundaram Paulraj1, T Deepa2
1Department of Electronics and Communication Engineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India. sp8941@srmist.edu.in.
Scientific reports
|December 3, 2024
概括
本研究介绍了一种基于神经模糊的数据路由 (NFDR) 机制,用于物联网 (IoT) 无线传感器网络 (WSN) 的高效数据路由和集群形成. 通过提高能量保留和减少延迟和死节点,NFDR提高了网络性能.
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:
- 通过物联网 (IoT) 实现的无线传感器网络 (WSN) 在高效的数据路由和动态集群形成方面面临挑战.
- 现有的机制往往在可扩展性和维护网络参数值方面扎.
研究的目的:
- 提出一种新的基于神经模糊的数据路由 (NFDR) 机制,用于在支持物联网的WSN中增强数据路由和集群形成.
- 提高网络效率,节能,减少端到端延迟和节点死亡率.
主要方法:
- NFDR机制使用神经网络来满足集群形成的要求,以及用于目标功能调整的模糊逻辑.
- 从历史和当前的网络参数计算出最佳的可扩展性因素,以维持集群内的节点.
- 使用动态集群形成方法,选择超级头和调整集群成员大小.
主要成果:
- 根据NFDR机制,集群范围得到了增强,集群成员数量增加.
- 模拟结果显示,75%的能量保留,20%的端到端延迟减少,15%的死亡节点减少.
- 拟议的机制有效地维持数据传输期间的网络参数值.
结论:
- 基于神经模糊的数据路由 (NFDR) 机制为支持物联网的WSN提供了高效和强大的解决方案.
- NFDR显著改善了关键性能指标,为更可靠和可持续的WSN运营做出了贡献.
- 这种方法为在资源有限的物联网环境中开发先进的路由策略提供了基础.
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