A dynamic weight–assignment load balancing approach for workflow scheduling in edge-cloud computing using ameliorated moth flame and rock hyrax optimization algorithms-Reference-Cited by-同舟云学术

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A dynamic weight–assignment load balancing approach for workflow scheduling in edge-cloud computing using ameliorated moth flame and rock hyrax optimization algorithms

Published:2024-06 Issue: Volume:155 Page:465-485
ISSN:0167-739X
Container-title:Future Generation Computer Systems
language:en
Short-container-title:Future Generation Computer Systems

Author:

Khaleel Mustafa Ibrahim^ORCID

Publisher

Elsevier BV

Reference53 articles.

1. Multi-objective fuzzy approach to scheduling and offloading workflow tasks in Fog–Cloud computing;Mokni;Simul. Model. Pract. Theory,2023

2. MOHBA:multi-objective workflow scheduling in cloud computing using hybrid BAT algorithm;Sobhanayak;Computing,2023

3. Energy-efficient computation offloading strategy with task priority in cloud assisted multi-access edge computing;He;Future Gener. Comput. Syst.,2023

4. Improvement of tasks scheduling algorithm based on load balancing candidate method under cloud computing environment;Chiang;Expert Syst. Appl.,2023

5. An energy-optimized embedded load balancing using DVFS computing in cloud data centers;Javadpour;Comput. Commun.,2023

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Failure-aware resource provisioning for hybrid computation offloading in cloud-assisted edge computing using gravity reference approach;Swarm and Evolutionary Computation;2024-12

2. Edge-Cloud Solutions for Big Data Analysis and Distributed Machine Learning - 1;Future Generation Computer Systems;2024-10

3. Efficient resource allocation in cloud environment using SHO-ANN-based hybrid approach;Sustainable Operations and Computers;2024

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