| Autor: |
Nuha Alruwais, Eatedal Alabdulkreem, Fadoua Kouki, Nojood O. Aljehane, Randa Allafi, Radwa Marzouk, Mohammed Assiri, Amani A. Alneil |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Ain Shams Engineering Journal, Vol 15, Iss 6, Pp 102738- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2090-4479 |
| DOI: |
10.1016/j.asej.2024.102738 |
| Popis: |
Resource scheduling (RS) for makespan optimization in a cloud computing (CC) environment is an important aspect of handling effective resources in the cloud. Makespan optimization defines the minimization of time required to complete a collection of tasks in a computational environment. In the context of CC, makespan optimization aims to reduce the overall time required to execute tasks while effectively allocating and managing resources. RS in CC is a difficult task because of the number and variation of resources accessible and the volatility of usage-patterns of the resource assuming that the resource setting is on the service providers. Therefore, this article presents a Farmland Fertility Algorithm based Resource Scheduling for Makespan Optimization (FFARS-MSO) in Cloud Computing Environment. The presented FFARS-MSO technique is mainly based on FFA, which is stimulated by the farmland fertility in nature where the farmers split the various regions of the farm based on soil quality, and thereby every region's soil quality is distinct from others. In addition, the presented FFARS-MSO technique is utilized for load balancing and uniform distribution of resources depending upon the demand. The simulation outcomes ensure that the FFARS-MSO approach has reached effectual resource allocation over other optimization algorithms. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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