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相关概念视频

Propagation of Action Potentials01:23

Propagation of Action Potentials

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The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
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相关实验视频

Updated: Jan 9, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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在wsn中基于睡眠和唤醒的安全多路径路由使用fennec fox优化的深度学习框架.

Mohammad Bilal J1, D Suresh2, R Karthikeyan3

  • 1Department of Information Technology, Annamalai University, Chidambaram, India. mohammadbilal1987@gmail.com.

Scientific reports
|December 4, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了无线传感器网络 (WSN) 的新框架,以节省能源和延长网络寿命. 基于安全聚类和睡眠唤醒的能源高效路由 (SCS-EEF) 框架显著降低了能源消耗和延迟.

关键词:
深度学习是一种深度学习.芬尼克·福克斯优化优化模糊的C意味着模糊的C.确保安全的路由.时间卷积网络的时间卷积网络.

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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) 对环境监测和智能城市等应用至关重要.
  • WSN 的高能耗限制了其运行寿命和数据完整性.
  • 现有的路由方法往往会导致拥堵和由于冗余传输和碰撞而快速耗尽能源.

研究的目的:

  • 为WSNs提出一个基于安全聚类和睡眠唤醒的新能源高效路由 (SCS-EEF) 框架.
  • 提高能源效率并延长WSNs的网络寿命.
  • 为应对WSN数据路由中冗余转发和碰撞的挑战.

主要方法:

  • 实现基于 Fuzzy C 平均值的平衡代缩减和使用层次结构的集群 (Fuzzy-BIRCH),以改进集群形成.
  • 使用Fennec Fox优化 (FFO) 进行最佳集群头选择 (CHS) 和平衡的能量分配.
  • 开发了一个节能的动态睡眠-觉醒时间表,以尽量减少冗余的传输.
  • 采用混合时间卷积网络-BiGRU (TCN-BiGRU) 基于数据紧迫性的多路线预测.

主要成果:

  • 在SCS-EEF框架中,能源消耗显著减少:比HBWCO减少39.3%,比IBORSDFFNL减少29.2%,比EER-CGHHOA减少26.1%.
  • 与HBWCO相比,延迟时间减少了10.7%,与IBORSDFFNL相比减少了9.42%,与EER-CGHHOA相比减少了7.4%.
  • 提出的方法有效地改善了集群形成,能量分配,并减少了节点过早故障.

结论:

  • SCS-EEF框架为WSN提供了能源效率和网络寿命的大幅改善.
  • 融合了Fuzzy-BIRCH,FFO和TCN-BiGRU,有效地解决了WSN的能源消耗和延迟问题.
  • 这项研究为各种应用中可持续和高效的WSN运行提供了有希望的解决方案.