Fair multiple-workflow scheduling with different quality-of-service goals

Rezaeian, Amin; Naghibzadeh, Mahmoud; Epema, Dick

doi:10.1007/s11227-018-2604-2

Cited by 12 publications

(3 citation statements)

References 23 publications

(33 reference statements)

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“…Where, 𝑒 represents the number of edges interconnected with every task 𝑇 𝑗 , and 𝑄 = 0, if two tasks are scheduled on similar VMs, else one [25][26][27]. In this manuscript, the DA-AGSA technique is used to find the optimal schedule in the workflows: Montage, CyberShake and Epigenomics, for minimizing the total execution time and cost.…”

Section: Problem Definitionmentioning

confidence: 99%

Effective Workflow Scheduling in Cloud Platform Using Data Aware based Adaptive Gravitational Search Algorithm

2023

IJIES

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In recent periods, cloud-computing environments are widely utilizing scientific workflows for executing large-scale applications. The workflow scheduling with the scientific standard for optimizing quality of service (QoS) parameters is a hard task. In the existing research studies, several metaheuristics optimization algorithms are employed for satisfying the QoS parameters such as resource utilization, cost, and makespan. Still, the existing metaheuristics optimization algorithms are insignificant for maintaining the balance between exploitation and exploration in a search space, because the algorithms are easily trapped in local optima. For addressing the above-stated issues, a data aware based adaptive gravitational search algorithm (DA-AGSA) technique is implemented to minimize the cost and makespan, and to schedule workflows in the cloud-computing platform. In the conventional GSA technique, a random coefficient is replaced by an adaptive weight function for improving convergence rate, and further, the weight function is multiplied with an acceleration term for facilitating quicker convergence. In this article, the performance of the DA-AGSA technique is validated by utilizing workflow sim for scheduling multiple workflows. An extensive experimental investigation showed that the DA-AGSA technique almost reduced 20% of the cost and 15% of the makespan compared to the conventional optimization algorithms on the Montage, CyberShake, and Epigenomics workflows with 1000 tasks. In addition, the DA-AGSA technique achieved a reliability of 0.99, 0.98, and 0.98 on the Montage, CyberShake and Epigenomics workflows with 1000 tasks.

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Section: Problem Definitionmentioning

confidence: 99%

Effective Workflow Scheduling in Cloud Platform Using Data Aware based Adaptive Gravitational Search Algorithm

2023

IJIES

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“…Related problems have been explored in the literature such as selecting which workflows to processes to run in scenarios where not all deadlines can be reliably met (e.g. [40,2]). While problems such as these do contain workflows and some form of selection, these are very different…”

Section: Related Workmentioning

confidence: 99%

“…Research in related scientific domains has looked at optimising efficiency and not effectiveness, and only consider a limited number of complete workflow structures (e.g. [40,2]).…”

Section: Introductionmentioning

confidence: 99%