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相关概念视频

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

647
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...
647
Distributed Loads01:19

Distributed Loads

539
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.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
539
Relation Between the Distributed Load and Shear01:23

Relation Between the Distributed Load and Shear

644
Understanding the relationship between the distributed load and shear force in structural analysis is crucial for analyzing beams subjected to various loading conditions. Consider the case of a beam experiencing a distributed load, two concentrated loads, and a couple moment.
644
Load-frequency control01:28

Load-frequency control

166
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
166
Energy Budgets00:51

Energy Budgets

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Organisms must balance energy intake with the energy required for growth, maintenance and reproduction. These trade-offs result in a variety of survivorship and reproductive strategies, including semelparity and iteroparity. Semelparous species, like annual plants, have only one reproductive episode in their lifetimes and consequently have short lifespans. Iteroparous species, by contrast, have many reproductive events during their lifetimes but have relatively few offspring. These two...
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Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

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Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
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相关实验视频

Updated: Jul 10, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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为网络意识和联合边缘计算提供最佳的资源配置和任务卸载.

Avilia Kusumaputeri Nugroho1, Shigeo Shioda2, Taewoon Kim1

  • 1School of Computer Science and Engineering, Pusan National University, Busan 46241, Republic of Korea.

Sensors (Basel, Switzerland)
|November 25, 2023
PubMed
概括

移动边缘计算 (MEC) 为延迟敏感的应用提供了更好的性能. 我们的NAFEOS解决方案优化了联合边缘服务器的用户关联和资源扩展,改善了利用率.

关键词:
横向缩放尺度是指水平缩放尺度.移动边缘计算移动边缘计算最佳的关联是最优的关联.任务卸载 任务卸载垂直缩放的垂直缩放方式

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科学领域:

  • 计算机科学 计算机科学
  • 分布式系统 分布式系统
  • 网络工程 网络工程

背景情况:

  • 移动边缘计算 (MEC) 通过处理更接近用户的任务来提高对延迟敏感应用程序的响应能力.
  • 最佳的MEC利用需要在用户协会,资源配置和任务分配方面仔细设计.
  • 联邦边缘服务器对资源分配和管理的影响尚未得到充分研究.

研究的目的:

  • 在联邦边缘环境中解决网络和MEC资源调度问题.
  • 调查网络和MEC资源管理的整合,以实现最佳性能.
  • 提出一个平衡用户协会,联合分配和动态资源扩展的解决方案.

主要方法:

  • 开发了NAFEOS,这是一个两阶段算法,用于优化用户基站协会和联邦分配.
  • 阶段-1优化了用户协会和联邦分配,以实现平衡的边缘服务器利用.
  • 第二阶段动态安排垂直和水平扩展,以满足波动的任务卸载需求.

主要成果:

  • 拟议的NAFEOS算法有效地将关联优化与垂直和水平扩展集成在一起.
  • 第1阶段确保了联邦边缘服务器的平衡利用.
  • 第二阶段成功管理动态资源扩展以满足用户需求,实现最佳的资源利用.

结论:

  • 在联邦环境中,NAFEOS为网络和MEC资源调度提供了有效的解决方案.
  • 对网络和MEC资源管理的联合方法对于提高服务质量至关重要.
  • 该研究表明,通过优化关联和动态扩展,资源利用得到了显著改善.