Optimization of Max-Min and Min-Min Task Scheduling Algorithms Using G.A in Cloud Computing

Aref, Ismael Salih; Kadum, Juliet; Kadum, Amaal

doi:10.1109/iiceta54559.2022.9888542

Cited by 13 publications

(2 citation statements)

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“…Several researchers have designed and presented their work to address and solve this LB issue. To shorten the make-span and improve resource load balances, the researchers have demonstrated a hybrid task scheduling algorithm based on the Max-Min, Min-Min, and genetic algorithms [6]. The evolutionary algorithm, which determines which tasks should utilize Max -Min and which ones should use Min -Min, is the main application of this hybrid method.…”

Section: Related Workmentioning

confidence: 99%

“…Hence, the principal objective of this research paper is to study these RS algorithms from the LB perspective and suggest intelligent solutions to enhance and optimize the LB process. The RS algorithms considered for the study of LB include First Come, First Serve (FCFS), Maximum -Minimum (Max -Min), Minimum Completion Time (MCT), Minimum -Minimum (Min -Min), and Round -Robin (RR) [6] [31] [40]. This paper includes an experimental study in a simulation environment where Sipht dataset tasks were processed and computed in several phases.…”

Section: Introductionmentioning

confidence: 99%

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Reinforcement Learning Approach for Optimizing Cloud Resource Utilization With Load Balancing

Lahande,

Kaveri,

Saini

et al. 2023

IEEE Access

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Cloud computing is a technology that enables the delivery of various computing services over the Internet. The Resource Scheduling (RS) and Load Balancing (LB) mechanisms are essential for the cloud to provide consistent results. The submitted tasks by the users are computed on the cloud platform using its Virtual Machines (VMs). The cloud ensures an ideal LB mechanism, where no VMs will be overloaded or idle. This research paper focuses on this LB mechanism by experimenting in the WorkflowSim environment and computing tasks using the Sipht task dataset. The RS algorithms First Come First Serve (FCFS), Maximum -Minimum (Max -Min), Minimum Completion Time (MCT), Minimum -Minimum (Min -Min), and Round-Robin (RR) are utilized to balance the computational load of VMs. The experiment was conducted in four phases, where the Sipht task dataset varied in task length in each phase. Each phase included sixteen scenarios, where each scenario differed from another by the number of VMs used. The final results of this experiment convey that the load balanced by the algorithms

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%