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 Experiment Video

Updated: Mar 18, 2026

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

1.2K

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship

Shafi'i Muhammad Abdulhamid1,2, Muhammad Shafie Abd Latiff1, Gaddafi Abdul-Salaam3

  • 1Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia.

Plos One
|July 8, 2016
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Enhanced convolutional block attention module with Learnable Gated Fusion (LGF-CBAM) for cocoa pod disease identification.

PloS one·2026
Same author

K-Means Based Bee Colony Optimization for Clustering in Heterogeneous Sensor Network.

Sensors (Basel, Switzerland)·2024
Same author

Cyberattack patterns in blockchain-based communication networks for distributed renewable energy systems: A study on big datasets.

Data in brief·2024
Same author

Imbalanced class distribution and performance evaluation metrics: A systematic review of prediction accuracy for determining model performance in healthcare systems.

PLOS digital health·2023
Same author

Factors Influencing the Adoption of IoT for E-Learning in Higher Educational Institutes in Developing Countries.

Frontiers in psychology·2022
Same author

Emergency traffic adaptive MAC protocol for wireless body area networks based on prioritization.

PloS one·2019

This study introduces the Global League Championship Algorithm (GBLCA) for secure cloud computing task scheduling. GBLCA significantly improves scheduling efficiency and reduces response time for scientific applications.

Area of Science:

  • Cloud Computing
  • Distributed Systems
  • Optimization Algorithms

Background:

  • Cloud computing systems involve dynamic resource provisioning, making scientific application scheduling an NP-hard problem.
  • Existing metaheuristics for cloud scheduling often overlook secure global scheduling.
  • Heterogeneous resources and dynamic environments complicate efficient task allocation.

Purpose of the Study:

  • To present a novel Global League Championship Algorithm (GBLCA) for secure global task scheduling in cloud computing environments.
  • To evaluate the performance of GBLCA against established scheduling algorithms for scientific applications.
  • To demonstrate improved makespan and reduced response times for secure scheduling.

Main Methods:

  • Implementation of the Global League Championship Algorithm (GBLCA) for task scheduling.

More Related Videos

Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques
07:52

Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques

Published on: December 1, 2023

1.6K

Related Experiment Videos

Last Updated: Mar 18, 2026

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

1.2K
Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques
07:52

Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques

Published on: December 1, 2023

1.6K
  • Utilizing the CloudSim simulator for experimental validation.
  • Comparative analysis against MinMin, MaxMin, Genetic Algorithm (GA), and Ant Colony Optimization (ACO) techniques.

    • Main Results:

    • GBLCA achieved a performance improvement rate on makespan ranging from 14.44% to 46.41%.
    • The proposed GBLCA technique demonstrated a significant reduction in response time for secure application scheduling.
    • GBLCA outperformed MinMin, MaxMin, GA, and ACO in terms of scheduling quality and efficiency.

    Conclusions:

    • The GBLCA optimization technique offers a superior scheduling solution for scientific applications in cloud computing.
    • GBLCA effectively addresses the challenges of secure global task scheduling in dynamic cloud environments.
    • The proposed method provides a robust and efficient approach for optimizing cloud resource allocation for scientific workloads.