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

Reinforcement Schedules01:24

Reinforcement Schedules

135
Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
Once a behavior is learned,...
135
Virtual Work01:20

Virtual Work

804
The principle of virtual work states that if a body is in static and dynamic equilibrium, then the sum of all the virtual work done by all external forces and couple moments for any given virtual displacement must be zero.
In static equilibrium, a body can experience an imaginary or virtual movement, such as displacement or rotation. The virtual work done by a force is equal to the dot product of force and virtual displacement in the direction of the force. When it comes to virtually rotating a...
804
Parallel Processing01:20

Parallel Processing

145
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...
145
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

4.3K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.3K
Energy Conservation and Bernoulli's Equation01:16

Energy Conservation and Bernoulli's Equation

8.8K
Applying the conservation of energy principle or the work-energy theorem to an incompressible, inviscid fluid in laminar, steady, irrotational flow leads to Bernoulli's equation. It states that the sum of the fluid pressure, potential, and kinetic energy per unit volume is constant along a streamline.
All the terms in the equation have the dimension of energy per unit volume. The kinetic energy per unit volume is called the kinetic energy density, and the potential energy per unit volume is...
8.8K
Energy Budgets00:51

Energy Budgets

9.2K
Organisms must balance energy intake with the energy required for growth, maintenance and reproduction. These trade-offs result in a variety of survivorship and reproductive strategies, including semelparity and iteroparity. Semelparous species, like annual plants, have only one reproductive episode in their lifetimes and consequently have short lifespans. Iteroparous species, by contrast, have many reproductive events during their lifetimes but have relatively few offspring. These two...
9.2K

You might also read

Related Articles

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

Sort by
Same author

Nanobubbles: a promising efficient tool for therapeutic delivery of antibacterial agents for the <i>Staphylococcus aureus</i> infections.

Applied nanoscience·2023
Same author

Investigations on coronary artery plaque detection and subclassification using machine learning classifier.

Journal of X-ray science and technology·2022
Same author

Diagnosis of Delusion and Hallucination from Schizophrenia Patient Using RADWT.

Journal of medical systems·2019
Same author

Evaluation of emission, performance and combustion characteristics of dual fuelled research diesel engine.

Environmental technology·2018
Same author

Data on Heavy metal in coastal sediments from South East Coast of Tamilnadu, India using Energy Dispersive X-ray Fluorescence (EDXRF) Technique.

Data in brief·2016
Same author

Polymorphism and overexpression of HER2/neu among ovarian carcinoma women from Tiruchirapalli, Tamil Nadu, India.

Archives of gynecology and obstetrics·2013

Related Experiment Video

Updated: Jun 12, 2025

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

3.9K

Energy and time-aware scheduling in diverse virtualized cloud computing environments using optimized self-attention

G Senthilkumar1, S Anandamurugan1

  • 1Department of Information Technology, Kongu Engineering College, Perundurai, India.

Network (Bristol, England)
|September 25, 2024
PubMed
Summary

This study introduces SAPGAN-DMA-DAS-HVCC, an advanced scheduling algorithm for cloud computing. It significantly reduces costs and improves makespan in heterogeneous virtual environments.

Keywords:
Task schedulingcloud computingdeadlinedwarf mongoose optimization algorithmmakespan energy consumptionself-attention-based progressive generative adversarial networkvirtual machines

More Related Videos

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

496
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

8.0K

Related Experiment Videos

Last Updated: Jun 12, 2025

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

3.9K
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

496
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

8.0K

Area of Science:

  • Computer Science
  • Cloud Computing
  • Artificial Intelligence

Background:

  • Cloud computing adoption is growing, leading to complex, heterogeneous virtualized environments.
  • Optimizing energy consumption in these environments is challenging due to workload variability.
  • Existing scheduling algorithms struggle to balance makespan and energy efficiency.

Purpose of the Study:

  • To propose a novel scheduling algorithm for heterogeneous virtual cloud computing environments.
  • To optimize energy consumption and makespan simultaneously.
  • To enhance the efficiency of task scheduling in dynamic cloud infrastructures.

Main Methods:

  • A self-attention-based progressive generative adversarial network (SAPGAN) was developed for activity scheduling.
  • The Dwarf Mongoose algorithm was employed to optimize SAPGAN's weight parameters.
  • Energy and Deadline Aware Scheduling (DAS) was integrated into the heterogeneous virtualized cloud computing (HVCC) framework.

Main Results:

  • The proposed SAPGAN-DMA-DAS-HVCC approach demonstrated a higher right-skewed makespan.
  • Significant reductions in cost were observed: 31.52%, 33.28%, and 29.14% lower compared to existing models.
  • The algorithm effectively balances energy consumption and task completion time.

Conclusions:

  • SAPGAN-DMA-DAS-HVCC offers a superior solution for task scheduling in heterogeneous virtual cloud environments.
  • The integration of SAPGAN and the Dwarf Mongoose algorithm optimizes performance and energy efficiency.
  • This approach addresses key challenges in cloud resource management and cost reduction.