Towards Metaheuristic Scheduling Techniques in Cloud and Fog: An Extensive Taxonomic Review

R. Singh, L. Awasthi, Geeta Sikka
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引用次数: 19

Abstract

Task scheduling is a critical issue in distributed computing environments like cloud and fog. The objective is to provide an optimal distribution of tasks among the resources. Several research initiatives to use metaheuristic techniques for finding near-optimal solutions to task scheduling problems are under way. This study presents a comprehensive taxonomic review and analysis of recent metaheuristic scheduling techniques using exhaustive evaluation criteria in the cloud and fog environment. A taxonomy of metaheuristic scheduling algorithms is presented. Besides, we have considered an extensive list of scheduling objectives along with their associated metrics. Rigorous evaluation of existing literature is performed, and limitations highlighted. We have also focused on hybrid algorithms as they tend to improve scheduling performance. We believe that this work will encourage researchers to conduct further research for removing the limitations in existing studies.
云与雾中的元启发式调度技术:一个广泛的分类综述
任务调度是云、雾等分布式计算环境中的一个关键问题。目标是在资源之间提供任务的最佳分配。一些使用元启发式技术寻找任务调度问题的接近最优解决方案的研究计划正在进行中。这项研究提出了一个全面的分类审查和分析,最近的元启发式调度技术使用详尽的评估标准,在云和雾环境。提出了一种元启发式调度算法的分类。此外,我们还考虑了调度目标及其相关指标的广泛列表。对现有文献进行了严格的评估,并强调了局限性。我们也关注混合算法,因为它们倾向于提高调度性能。我们相信这项工作将鼓励研究人员进行进一步的研究,以消除现有研究中的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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