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Cloud task scheduling using enhanced sunflower optimization algorithm
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DOI：10.1016/j.icte.2021.08.001.png)
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Abstract
En 中文
The objective of cloud task scheduling is to partition tasks on shared resources to minimize energy consumption and makespan. Recently, several meta-heuristics for task scheduling were proposed and achieved encouraging results. However, their performance is far from the ideal state and needs more improvement. This paper introduces an enhanced sunflower optimization (ESFO) algorithm for improving the performance of existing task scheduling. It finds optimal scheduling in a polynomial time. The experiments show that ESFO outperformed its counterparts. The amount of improvement in comparison with the best counterpart is 0.73% and 2.24% respectively in terms of makespan and energy consumption. (C) 2021 The Korean Institute of Communications and Information Sciences (KICS). Publishing services by Elsevier B.V.
Keywords:
Cloud computing
Task scheduling
Energy consumption
Enhanced sunflower optimization algorithm
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