HEPGA: A new effective hybrid algorithm for scientific workflow scheduling in cloud computing environment-Reference-Cited by-同舟云学术

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HEPGA: A new effective hybrid algorithm for scientific workflow scheduling in cloud computing environment

Published:2024-01 Issue: Volume:130 Page:102864
ISSN:1569-190X
Container-title:Simulation Modelling Practice and Theory
language:en
Short-container-title:Simulation Modelling Practice and Theory

Author:

Mikram Hind,El Kafhali Said^ORCID,Saadi Youssef

Publisher

Elsevier BV

Subject

Hardware and Architecture,Modeling and Simulation,Software

Reference27 articles.

1. Dynamic scalability model for containerized cloud services;El Kafhali;Arab. J. Sci. Eng.,2020

2. Metaheuristic Algorithms Based Server Consolidation for Tasks Scheduling in Cloud Computing Environment;Mikram,2023

3. Performance Analysis of Scheduling Algorithms for Virtual Machines and Tasks in Cloud Computing;Mikram,2022

4. A hybrid genetic algorithm for optimization of scheduling workflow applications in heterogeneous computing systems;Ahmad;J. Parallel Distrib. Comput.,2016

5. Processing Time Performance Analysis of Scheduling Algorithms for Virtual Machines Placement in Cloud Computing Environment;Mikram,2022

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1. Optimizing scientific workflow scheduling in cloud computing: a multi-level approach using whale optimization algorithm;Journal of Engineering and Applied Science;2024-08-19

2. An Efficient Workflow Scheduling in Cloud–Fog Computing Environment Using a Hybrid Particle Whale Optimization Algorithm;Wireless Personal Communications;2024-07

3. An Efficient Model based on Machine Learning Algorithms for Virtual Machines Classification in Cloud Computing Environment;2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET);2024-05-16

4. A multiobjective optimization of task workflow scheduling using hybridization of PSO and WOA algorithms in cloud-fog computing;Cluster Computing;2024-05-13

5. AI-based & heuristic workflow scheduling in cloud and fog computing: a systematic review;Cluster Computing;2024-05-08

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