Multi-objective scheduling strategy for scientific workflows in cloud environment: A Firefly-based approach-Reference-Cited by-同舟云学术

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Multi-objective scheduling strategy for scientific workflows in cloud environment: A Firefly-based approach

Published:2020-08 Issue: Volume:93 Page:106411
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Adhikari Mainak,Amgoth Tarachand^ORCID,Srirama Satish Narayana

Publisher

Elsevier BV

Subject

Software

Reference37 articles.

1. A comprehensive survey for scheduling techniques in cloud computing;Kumar;J. Netw. Comput. Appl.,2019

2. Multi-objective accelerated particle swarm optimization with a container-based scheduling for Internet-of-Things in cloud environment;Adhikari;J. Netw. Comput. Appl.,2019

3. Task scheduling techniques in cloud computing: A literature survey;Arunarani;Future Gener. Comput. Syst.,2019

4. Development and analysis of a new cloudlet allocation strategy for QoS improvement in cloud;Banerjee;Arab. J. Sci. Eng.,2015

5. VMSAGE: A virtual machine scheduling algorithm based on the gravitational effect for green cloud computing;Xu;Simul. Model. Pract. Theory,2019

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1. Information interaction and partial growth-based multi-population growable genetic algorithm for multi-dimensional resources utilization optimization of cloud computing;Swarm and Evolutionary Computation;2024-06

2. Deep reinforcement learning-based methods for resource scheduling in cloud computing: a review and future directions;Artificial Intelligence Review;2024-04-23

3. Makespan and Security-Aware Workflow Scheduling for Cloud Service Cost Minimization;IEEE Transactions on Cloud Computing;2024-04

4. A two-stage preference driven multi-objective evolutionary algorithm for workflow scheduling in the Cloud;Expert Systems with Applications;2024-03

5. Optimizing data regeneration and storage with data dependency for cloud scientific workflow systems;Expert Systems with Applications;2024-03

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