Journal
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
Volume 22, Issue -, Pages 1087-1098Publisher
SPRINGER
DOI: 10.1007/s10586-017-1055-5
Keywords
Cloud computing; Task scheduling; Multi-objective model; Whale optimization algorithm; Makespan
Ask authors/readers for more resources
One of the important steps in cloud computing is the task scheduling. The task scheduling process needs to schedule the tasks to the virtual machines while reducing the makespan and the cost. Number of scheduling algorithms are proposed by various researchers for scheduling the tasks in cloud computing environments. This paper proposes the task scheduling algorithm called W-Scheduler based on the multi-objective model and the whale optimization algorithm (WOA). Initially, the multi-objective model calculates the fitness value by calculating the cost function of the central processing unit (CPU) and the memory. The fitness value is calculated by adding the makespan and the budget cost function. The proposed task scheduling algorithm with the whale optimization algorithm can optimally schedule the tasks to the virtual machines while maintaining the minimum makespan and cost. Finally, we analyze the performance of the proposed W-Scheduler with the existing methods, such as PBACO, SLPSO-SA, and SPSO-SA for the evaluation metrics makespan and cost. From the experimental results, we conclude that the proposed W-Scheduler can optimally schedule the tasks to the virtual machines while having the minimum makespan of 7 and minimum average cost of 5.8.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available