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Related Concept Videos

Distributed Loads01:19

Distributed Loads

576
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...
576
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

692
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...
692
Elastic Curve from the Load Distribution01:16

Elastic Curve from the Load Distribution

246
The structural behavior of beams under distributed loads is critical for engineering analysis, which focuses on predicting how beams bend and react under such conditions. Different types of beams (e.g., cantilever, supported, or overhanging) behave differently under distributed load conditions.
For all beams, the analysis of the beam's reaction to distributed loads begins by understanding the relationship between a beam's load and the resulting shear forces and bending moments.
246
Relation Between the Distributed Load and Shear01:23

Relation Between the Distributed Load and Shear

737
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.
737
Beams with Symmetric Loadings01:15

Beams with Symmetric Loadings

231
The moment-area method is an analytical tool used in structural engineering to determine the slope and deflection of beams under various loads. Consider a cantilever with a concentrated load and moment at the free end. The first step is constructing a free-body diagram to calculate the reactions at the fixed end. Next, the bending moment diagram is plotted to visualize how the bending moment varies along the beam's length, focusing on points where the bending moment equals zero.
The M/EI...
231
Beams with Unsymmetric Loadings01:17

Beams with Unsymmetric Loadings

154
Analyzing a supported beam under unsymmetrical loadings is essential in structural engineering to understand how beams respond to varied force distributions. This analysis involves calculating the deflection and identifying points where the slope of the beam is zero, which are crucial for ensuring structural stability and functionality.
The first moment-area theorem determines the slope at any point on the beam. This theorem indicates that the change in slope between two points on a beam...
154

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Cloud-edge load balancing distributed protocol for IoE services using swarm intelligence.

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This summary is machine-generated.

This study introduces a secure data management protocol for the Internet of Everything (IoE) and cloud computing. The particle swarm optimization-based approach enhances network communication security and reduces response times for smart applications.

Keywords:
Cloud-edgeInternet of everythingParticle swarm optimizationSecurity analysisTechnological development

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Area of Science:

  • Computer Science
  • Network Engineering
  • Distributed Systems

Background:

  • The Internet of Everything (IoE) and cloud services are crucial for smart applications, offering scalability and data handling capabilities.
  • Edge computing optimizes bandwidth and latency for embedded systems but faces challenges in data aggregation and security.
  • Distributed systems are essential for data access and storage, requiring robust security against unpredictable events.

Purpose of the Study:

  • To propose a secured data management protocol with distributed load balancing for IoE and cloud environments.
  • To decrease response time for cloud users and maintain network communication integrity.
  • To protect communicating machines from malicious devices through trust evaluation.

Main Methods:

  • Developed a distributed load balancing protocol integrated with particle swarm optimization.
  • Combined distributed computing principles with edge computing to reduce latency and transmission overhead.
  • Implemented a trust evaluation mechanism to secure machine-to-machine communication.

Main Results:

  • The proposed protocol demonstrated significant performance improvements compared to existing solutions.
  • Achieved an average reduction of 20% in energy consumption.
  • Improved success rate by 17% and reduced end-to-end delay by 14%.

Conclusions:

  • The novel protocol effectively manages data securely in IoE and cloud systems.
  • Particle swarm optimization enhances load balancing and reduces network costs by 19%.
  • The trust evaluation mechanism provides robust security against malicious entities in distributed networks.