Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

685
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...
685
Distributed Loads01:19

Distributed Loads

564
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...
564
Relation Between the Distributed Load and Shear01:23

Relation Between the Distributed Load and Shear

722
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.
722
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

147
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.
147
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

249
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:
249
The Delta-to-Delta Circuit01:17

The Delta-to-Delta Circuit

684
In a delta-delta configuration, the source and the load are connected in a delta manner, forming a closed loop that divides the network into three distinct phases. This configuration makes the phase voltages identical to line voltages. Assuming the sources are in positive sequence, the phase voltages can be expressed directly without having a neutral wire.
684

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A deep learning-based automated Solar-Powered Fish Monitoring System.

PloS one·2026
Same author

A systematic review of machine learning techniques for real-time speech and noise classification in hearing aids.

Disability and rehabilitation. Assistive technology·2026
See all related articles

Related Experiment Video

Updated: Aug 2, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

611

Enhanced network load balancing technique for efficient performance in software defined network.

Evans Osei Kofi1, Emmanuel Ahene1

  • 1Department of Computer Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ashanti Region, Ghana.

Plos One
|April 13, 2023
PubMed
Summary
This summary is machine-generated.

We introduce the HDW algorithm for network load balancing (NLB) to enhance efficiency and scalability. This novel approach merges weighted scheduling and dynamic path switching, outperforming existing methods in software-defined networks.

More Related Videos

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.1K
Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.8K

Related Experiment Videos

Last Updated: Aug 2, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

611
Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.1K
Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.8K

Area of Science:

  • Computer Science
  • Network Engineering

Background:

  • Hash collisions and load redirection limit current Hash IP algorithms.
  • Network load balancing (NLB) is crucial for efficiency, availability, and scalability.

Purpose of the Study:

  • To propose a new Hash IP algorithm, HDW, for improved network load balancing.
  • To enhance network efficiency, availability, and scalability using the HDW algorithm.

Main Methods:

  • Developed the HDW algorithm by integrating weighted scheduler (WS) and dynamic switching of routing path (DSP).
  • Conducted comprehensive simulations and performance evaluations.

Main Results:

  • The HDW algorithm effectively reduces delays and jitters.
  • HDW demonstrates improved network efficiency compared to existing load balancing algorithms.
  • The hashing process in HDW offers a degree of security.

Conclusions:

  • The proposed HDW algorithm offers a significant improvement over traditional Hash IP algorithms.
  • HDW enhances network performance metrics like efficiency, availability, and scalability in software-defined networks.