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相关概念视频

Distributed Loads01:19

Distributed Loads

509
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...
509
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

623
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...
623
Relation Between the Distributed Load and Shear01:23

Relation Between the Distributed Load and Shear

603
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.
603
Load along a Single Axis01:29

Load along a Single Axis

283
In structural engineering, the analysis of beams subjected to varying loads is a critical aspect of understanding the behavior and performance of these structural elements. A common scenario involves a beam subjected to a combination of different load distributions.
Consider a beam of length L subjected to a varying load, which is a combination of parabolic and trapezoidal load distribution along the x-axis. In this case, it is essential to determine the resultant loads, their locations, and...
283
Design Consideration01:22

Design Consideration

180
Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
180

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相关实验视频

Updated: Jun 3, 2025

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes
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基于资源需求预测的负载平衡动态SFC迁移.

Tian Sun1, Hefei Hu1, Sirui Zhang1

  • 1School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Sensors (Basel, Switzerland)
|January 8, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一个资源预测负载平衡SFC迁移 (RP-LBM) 算法用于网络功能虚拟化. 它通过预测资源需求和优化迁移策略来最大限度地减少服务中断和迁移时间.

关键词:
深度强化学习的学习.网络功能虚拟化 网络功能虚拟化网络负载平衡 网络负载平衡资源需求预测 资源需求预测服务功能链接服务功能链接

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科学领域:

  • 计算机科学 计算机科学
  • 网络工程 网络工程
  • 人工智能的人工智能

背景情况:

  • 网络功能虚拟化 (NFV) 服务由于网络流量波动而面临动态资源需求.
  • 服务功能链 (SFC) 迁移对于保持服务质量至关重要,但在负载管理方面面临着挑战,需求的时间变化.
  • 现有的方法缺乏在SFC迁移期间主动负载平衡的有效策略.

研究的目的:

  • 提出一种新的算法来管理网络负载,并确保在NFV中的动态资源需求下确保服务级协议.
  • 优化SFC迁移时间和策略,以提高网络性能和可靠性.
  • 在虚拟化网络环境中降低服务中断率和迁移成本.

主要方法:

  • 开发了资源预测负载平衡SFC迁移 (RP-LBM) 算法.
  • 利用带有注意力和长期短期记忆的卷积神经网络 (CNN-AT-LSTM) 来预测虚拟网络功能 (VNF) 资源需求.
  • 采用近接政策优化 (PPO) 算法来开发SFC迁移策略并确保网络负载平衡.

主要成果:

  • 与被动迁移方法相比,RP-LBM算法显示服务中断率平均低27.3%.
  • 基于PPO的迁移策略导致SFC迁移时间和服务中断率相比DQN算法减少.
  • 拟议的方法有效地将后续迁移降到最低,并确保低迁移成本的服务连续性.

结论:

  • RP-LBM算法有效地解决了NFV中负载管理的挑战,随着时间变化的资源需求.
  • 预测性VNF资源需求预测和基于PPO的迁移策略显著提高了网络服务的可靠性和效率.
  • 这些发现表明,在动态网络环境中优化SFC迁移是一个有希望的方法.