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相关概念视频

Distributed Loads: Problem Solving01:21

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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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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).
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Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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智能城市中分布式云的任务调度算法,具有截止日期限制.

Jincheng Zhou1,2, Bo Liu3, Jian Gao4

  • 1School of Computer and Information, Qiannan Normal University for Nationalities, Duyun, Guizhou, China.

PeerJ. Computer science
|June 22, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种高效的本地搜索算法,用于智能城市云网络中的任务调度. 该算法减少了数据负载和延迟,优于GA和PSO等基于群体的方法,以提高云服务效率.

关键词:
分布式云是分布式的云.当地搜索算法本地搜索算法智慧城市是智慧城市.任务安排 任务安排

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科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 云计算 云计算 云计算 云计算

背景情况:

  • 智能城市利用计算技术和5G进行基础设施管理.
  • 云计算将物联网设备,传感器和摄像头的数据集成到智能城市运营中.
  • 具有微型和核心云的层次分布式云模型增强了网络架构.

研究的目的:

  • 解决智能城市分布式云模型中具有截止日期约束的任务安排.
  • 为了减少通信网络的数据负载,并提供低延迟的云服务.
  • 为当地用户提高云计算服务的效率.

主要方法:

  • 开发一个高效的本地搜索算法,用于任务安排.
  • 实施一个贪的搜索策略,用于代解决方案的改进.
  • 使用随机化方法来重新分配任务和虚拟机.

主要成果:

  • 拟议的本地搜索算法在任务安排方面表现出卓越的性能.
  • 该算法有效地减少了通信网络数据负载和延迟.
  • 实验结果显示,该算法的性能优于遗传算法 (GA) 和粒子集群优化 (PSO).

结论:

  • 介绍的本地搜索算法是智能城市分布式云中的有限期限任务调度的高效解决方案.
  • 这种方法通过最小化数据负载和延迟来提高云计算效率.
  • 这种方法为优化智能城市云基础设施提供了一个有希望的策略.