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Farmland fertility algorithm based resource scheduling for makespan optimization in cloud computing environment

Ain Shams Engineering Journal, ISSN: 2090-4479, Vol: 15, Issue: 6, Page: 102738
2024
  • 3
    Citations
  • 0
    Usage
  • 22
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    3
  • Captures
    22
  • Mentions
    1
    • News Mentions
      1
      • News
        1

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Data from King Saud University Advance Knowledge in Farmland (Farmland fertility algorithm based resource scheduling for makespan optimization in cloud computing environment)

2024 JUN 07 (NewsRx) -- By a News Reporter-Staff News Editor at Information Technology Daily -- Current study results on farmland have been published. According

Article Description

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.

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