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Related Concept Videos

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...
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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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Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

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The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
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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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Elastic Curve from the Load Distribution01:16

Elastic Curve from the Load Distribution

180
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.
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Beams with Symmetric Loadings01:15

Beams with Symmetric Loadings

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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.
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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An improved energy-efficient cloud-optimized load-balancing for IoT frameworks.

Nageswara Rao Moparthi1, G Balakrishna2, Premkumar Chithaluru3

  • 1Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, 522302, India.

Heliyon
|December 6, 2023
PubMed
Summary
This summary is machine-generated.

A new cloud-based load balancer algorithm enhances Internet of Things (IoT) networks by improving response time and reducing energy consumption. This solution addresses challenges in cloud-integrated IoT architectures for better performance and efficiency.

Keywords:
CloudEnergy consumptionIoTLoad balancerResponse timeWSN

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Area of Science:

  • Computer Science
  • Network Engineering
  • Cloud Computing

Background:

  • The proliferation of wireless communication and the Internet of Things (IoT) necessitates efficient network solutions.
  • Existing IoT networks face challenges with communication overheads and data management, driving the need for advanced load-balancing techniques.
  • Migrating IoT data and applications to the cloud requires specialized load balancing algorithms tailored for cloud-integrated IoT architectures.

Purpose of the Study:

  • To design a novel cloud-based load balancer algorithm specifically for IoT networks.
  • To improve network response time and reduce energy consumption in cloud-integrated IoT environments.
  • To develop a load balancing solution that is easily integrable with existing IoT frameworks.

Main Methods:

  • Analysis of actual and virtual host machine requirements in cloud computing environments.
  • Development of a unique method for load control in cloud-integrated IoT networks.
  • Integration of the proposed load balancer algorithm with existing IoT frameworks.

Main Results:

  • The proposed load balancer significantly boosts IoT network response time by 60%.
  • Demonstrated reductions in energy consumption (31%), execution time (24%), node shutdown time (45%), and infrastructure cost (48%).
  • Simulation results confirm the effectiveness of the proposed framework in addressing IoT-based cloud load-balancing issues.

Conclusions:

  • The developed cloud-based load balancer offers a superior solution for managing loads in cloud-integrated IoT architectures.
  • The algorithm effectively enhances network performance metrics, including response time and energy efficiency.
  • The proposed framework provides significant cost and time savings compared to existing solutions.