Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Distributed Loads: Problem Solving

Distributed Loads: Problem Solving

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...

Multimachine Stability

Multimachine Stability

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:

Distributed Loads

Distributed Loads

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...

Relation Between the Distributed Load and Shear

Relation Between the Distributed Load and Shear

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.

Maxwell-Boltzmann Distribution: Problem Solving

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by

Maximum Power Flow and Line Loadability

Maximum Power Flow and Line Loadability

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.

You might also read

Related Articles

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

Sort by

Same author

Comment on "Integrating machine learning into fracture liaison services: Toward precision risk stratification in osteoporosis care: A prospective cohort study".

Journal of the Formosan Medical Association = Taiwan yi zhi·2026

Same author

Comprehensive review of heart disease prediction: A comparative study from 2019 onwards.

Artificial intelligence in medicine·2026

Same author

Elite Bernoulli-based mutated dung beetle algorithm for global complex problems and parameter estimation of solar photovoltaic models.

Scientific reports·2025

Same author

PIFR: A novel approach for analyzing pose angle-based human activity to automate fall detection in videos.

PloS one·2025

Same author

A novel methodology based on Contrast-Adaptive Threshold Model for accurate optic disc detection in retinal images of premature infants.

Physical and engineering sciences in medicine·2025

Same author

Analysis of internet educational websites on tobacco cessation: A content analysis.

F1000Research·2024

Search research articles

Related Experiment Video

Updated: Dec 23, 2025

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

Published on: December 13, 2016

Game theoretical approach for load balancing using SGMLB model in cloud environment.

R Swathy¹, B Vinayagasundaram¹, G Rajesh²

¹Computer Center, MIT Campus, Anna University, Chennai, Tamil Nadu, India.

|April 21, 2020

Summary

This summary is machine-generated.

This study introduces a Stackelberg game-theoretical model for cloud computing load balancing. The proposed algorithm optimizes host selection for long-term efficiency, reducing task failures and improving throughput.

More Related Videos

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Related Experiment Videos

Last Updated: Dec 23, 2025

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

Published on: December 13, 2016

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Area of Science:

Computer Science
Cloud Computing
Artificial Intelligence

Background:

Cloud computing faces load imbalance due to high task volumes from IoT and real-time analytics.
Existing load balancing algorithms offer short-term solutions but lack long-term execution efficiency.

Purpose of the Study:

To propose a novel load balancing algorithm for cloud data centers.
To enhance long-term task execution efficiency and resource utilization.

Main Methods:

Developed a Stackelberg (leader-follower) game-theoretical model.
Incorporated a satisfaction factor into the model for host selection.
Proposed the Stackelberg Game Theoretical Model for Load Balancing (SGMLB) algorithm.

Main Results:

Achieved an average resource utilization of 60%.
Reduced task failures by 47% and decreased makespan by 17%.
Increased throughput by 6% and lowered front-end error rates.

Conclusions:

The SGMLB algorithm effectively balances cloud data center loads using optimal host selection.
The game-theoretical approach with a satisfaction index improves overall execution efficiency and resource management.