Almomani, A, Lakhwani, Kamlesh, Sharma, Gajanand, Sandhu, Ramandeep, Nagwani, Naresh Kumar, Bhargava, Sandeep and Arya, Varsha (2023) Adaptive and Convex Optimization-Inspired Workflow Scheduling for Cloud Environment. International Journal of Cloud Applications and Computing, 13 (1). pp. 1-25. ISSN 2156-1834
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Abstract
Scheduling large-scale and resource-intensive workflows in cloud infrastructure is one of the main challenges for cloud service providers (CSPs). Cloud infrastructure is more efficient when virtual machines and other resources work up to their full potential. The main factor that influences the quality of cloud services is the distribution of workflow on virtual machines (VMs). Scheduling tasks to VMs depends on the type of workflow and mechanism of resource allocation. Scientific workflows include large-scale data transfer and consume intensive resources of cloud infrastructures. Therefore, scheduling of tasks from scientific workflows on VMs requires efficient and optimized workflow scheduling techniques. This paper proposes an optimised workflow scheduling approach that aims to improve the utilization of cloud resources without increasing execution time and execution cost.
Affiliation: | Skyline University College |
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SUC Author(s): | Almomani, A ORCID: https://orcid.org/0000-0002-8808-6114 |
All Author(s): | Almomani, A, Lakhwani, Kamlesh, Sharma, Gajanand, Sandhu, Ramandeep, Nagwani, Naresh Kumar, Bhargava, Sandeep and Arya, Varsha |
Item Type: | Article |
Subjects: | B Information Technology > BV Cloud Computing |
Divisions: | Skyline University College > School of IT |
Depositing User: | Mr Mosys Team |
Date Deposited: | 25 Dec 2023 13:33 |
Last Modified: | 25 Dec 2023 13:33 |
URI: | https://research.skylineuniversity.ac.ae/id/eprint/737 |
Publisher URL: | https://doi.org/10.4018/IJCAC.324809 |
Publisher OA policy: | https://v2.sherpa.ac.uk/id/publication/12705 |
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