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相关概念视频

Short-distance Transport of Resources02:12

Short-distance Transport of Resources

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Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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在软件定义的无线传感器网络中使用强化学习的节能路由协议.

Daniel Godfrey1, BeomKyu Suh1, Byung Hyun Lim1

  • 1Department of Computer Science and Engineering, Chungnam National University, Daejeon 34134, Republic of Korea.

Sensors (Basel, Switzerland)
|October 28, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了物联网 (IoT) 网络的新型路由协议,以优化能源效率和网络适应性. 动态目标选择与强化学习 (DOS-RL) 协议提高了动态无线环境中的性能.

关键词:
在 SDWSN-IoT 系统中.节能路由是节能的路由方式.多目的路由多目标路由.强化学习是一种强化学习.

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科学领域:

  • 计算机科学 计算机科学
  • 网络化 网络化 网络化
  • 无线通信无线通信

背景情况:

  • 物联网 (IoT) 系统面临着异质设备,可靠性和可扩展性的挑战.
  • 现有的软件定义无线传感器网络 (SDWSN) 与物联网集成,与设备能量限制,网络不可预测性和服务质量 (QoS) 斗争.
  • 不有效的路由协议会导致网络断开连接,并且在无线物联网部署中表现不佳.

研究的目的:

  • 为物联网网络开发一个智能,节能,多目标的路由协议.
  • 提高网络适应突然变化的能力,优化能源消耗.
  • 改善整体网络性能,包括数据包交付比率和降低延迟.

主要方法:

  • 实施了一种新的路由协议,即动态目标选择与强化学习 (DOS-RL).
  • 利用强化学习 (RL) 通过动态的目标选择和信息形式的奖励.
  • 进行各种模拟以评估与传统路由方法相比的协议性能.

主要成果:

  • 在无线物联网设备的能源效率方面取得了显著的改进.
  • 展示了快速适应意想不到的网络变化的能力.
  • 与OSPF和SDN-Q相比,提高了数据包交付比率和减少了数据交付延迟.

结论:

  • 拟议的DOS-RL路由方案有效地解决了物联网中的能源限制和网络动态.
  • DOS-RL为优化异质无线物联网环境中的性能提供了卓越的解决方案.
  • 该协议促进了无适应,减轻了中断,提高了网络可靠性.