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相关概念视频

Parallel Processing01:20

Parallel Processing

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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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Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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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 Loads01:19

Distributed Loads

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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.
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...
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Multimachine Stability01:25

Multimachine Stability

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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
188
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

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The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
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相关实验视频

Updated: Jul 18, 2025

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
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微服务应用程序调度在多层雾计算-启用物联网的物联网.

Maria Ashraf1, Muhammad Shiraz2, Almas Abbasi1

  • 1Department of Computer Science, Faculty of Computing and Information Technology, International Islamic University, Islamabad 44000, Pakistan.

Sensors (Basel, Switzerland)
|August 26, 2023
PubMed
概括
此摘要是机器生成的。

这项研究通过将微服务迁移到网络边缘来优化对低延迟应用程序的雾计算. 拟议的调度方法显著提高了应用程序性能,网络使用率和能源效率.

关键词:
物联网的物联网,就是物联网.受到限制的设备.分布式应用程序的执行.雾计算 雾计算 雾计算微服务应用程序调度服务延迟服务延迟

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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

背景情况:

  • 雾计算将云计算功能扩展到网络边缘,以减少延迟.
  • 微服务架构通过可扩展性和可维护性来增强物联网应用程序.
  • 利用未充分利用的边缘资源对于满足应用需求至关重要.

研究的目的:

  • 调查网络边缘的置资源以执行应用程序.
  • 为在雾计算中提供最佳微服务迁移的调度方法.
  • 为解决边缘应用程序的延迟和带宽要求.

主要方法:

  • 在多层雾基础设施中开发了用于上升微服务迁移的调度技术.
  • 利用微服务架构进行细分服务分解.
  • 使用iFogSim2模拟器验证了方法.

主要成果:

  • 提出的技术显著提高了应用程序延迟66.92%.
  • 与边缘化方法相比,网络使用量减少了69.83%.
  • 能源消耗减少了4.16%.

结论:

  • 拟议的调度方法有效地优化了网络边缘资源的利用.
  • 这种方法满足了边缘应用程序的严格延迟要求.
  • 该技术在性能,网络效率和节能方面提供了实质性的改进.