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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
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物联网物联网物流物流物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联网物联

Asif Umer1, Mushtaq Ali1, Ali Imran Jehangiri1

  • 1Department of Computer Science & Information Technology, Hazara University, Mansehra 21130, Pakistan.

Sensors (Basel, Switzerland)
|April 27, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了物联网 (IoT) 物流的新框架,优化任务卸载和调度,以减少响应时间和能源消耗. 拟议的系统通过优先考虑任务和选择最佳节点来提高智能运输的效率和可靠性.

关键词:
物联网任务卸载和调度分析层次过程 (AHP)计算密集型的任务需要大量的计算.对延迟敏感的任务.能源消耗 能源消耗是指能源的消耗.能容忍错误的管理者物流的智能运输物流的智能运输任务意识的调度人员

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科学领域:

  • * 物联网 (IoT) 是物联网的组成部分.
  • * 智能交通运输系统
  • * 云计算和雾计算

背景情况:

  • *智能运输中的物联网设备具有有限的计算能力,需要将任务卸载到远程服务器.
  • *现有的任务卸载机制往往忽视了容错性,数据意识和物流多参数节点选择.
  • * 这种差距阻碍了物联网物流卡车在能源消耗和响应时间方面的最佳性能.

研究的目的:

  • * 提出一个新的物联网物流多目标任务意识卸载和调度框架 (MT-OSF).
  • * 解决故障容忍,任务/数据意识,基于优先级的卸载和多参数雾节点选择的局限性.
  • * 提高基于物联网的智能运输的效率和可靠性.

主要方法:

  • * 开发了一个基于优先级的下载器,将任务分类为对延迟敏感和计算密集的任务.
  • * 实现了使用分析层次过程 (AHP) 的任务意识调度器 (TAS),用于多标准的雾节点选择 (能量,带宽,RAM,MIPS).
  • * 集成了一个容错管理器,用于任务重新执行和节点故障处理,使用先到先得 (FCFS) 算法进行调度.

主要成果:

  • * 与现有方法相比,实现了7%的响应时间缩短.
  • * 显示能耗下降了16%.
  • * 任务失败率显著降低22%.

结论:

  • * MT-OSF框架有效地优化了物联网物流中的任务卸载和调度.
  • * 拟议的系统显著改善了性能指标,包括响应时间,能源效率和故障耐受性.
  • *MT-OSF提供了一个强大的解决方案,可以提高智能运输系统的可靠性和效率.