Exploring Virtual Machine Scheduling Algorithms: A Meta-Analysis

Salman Mahmood, Nor Adnan Yahaya
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Abstract

This review paper provides a comprehensive assessment of scheduling methods for cloud computing, with an emphasis on optimizing resource allocation in cloud computing systems. The PRISMA methodology was utilized to identify 2,487 articles for this comprehensive review of scheduling methods in cloud computing systems. Following a rigorous screening process, 30 papers published between 2018 and 2023 were selected for inclusion in the review. These papers were analyzed in-depth to provide an extensive overview of the current state of scheduling methods in cloud computing, along with the challenges and opportunities for improving resource allocation. The review evaluates various scheduling approaches, including heuristics, optimization, and machine learning-based methods, discussing their strengths and limitations and comparing results from multiple studies. The paper also highlights the latest trends and future directions in cloud computing scheduling research, offering insights for practitioners and researchers in this field.
探索虚拟机调度算法:一个元分析
这篇综述文章提供了云计算调度方法的综合评估,重点是优化云计算系统中的资源分配。利用PRISMA方法确定了2,487篇文章,用于对云计算系统中的调度方法进行全面审查。经过严格的筛选程序,2018年至2023年期间发表的30篇论文被选中纳入审查。对这些论文进行了深入的分析,以提供对云计算中调度方法的当前状态的广泛概述,以及改进资源分配的挑战和机遇。本文评估了各种调度方法,包括启发式、优化和基于机器学习的方法,讨论了它们的优势和局限性,并比较了多项研究的结果。本文还重点介绍了云计算调度研究的最新趋势和未来方向,为该领域的从业者和研究人员提供了见解。
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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