A systematic literature review on contemporary and future trends in virtual machine scheduling techniques in cloud and multi-access computing

Nadim Rana, Fathe Jeribi, Zeba Khan, Wagdi Alrawagfeh, Imed Ben Dhaou, Mohammad Haseebuddin, Mueen Uddin
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Abstract

The migration of business and scientific operations to the cloud and the surge in data from IoT devices have intensified the complexity of cloud resource scheduling. Ensuring efficient resource distribution in line with user-specified SLA and QoS demands novel scheduling solutions. This study scrutinizes contemporary Virtual Machine (VM) scheduling strategies, shedding light on the complexities and future prospects of VM design and aims to propel further research by highlighting existing obstacles and untapped potential in the ever-evolving realm of cloud and multi-access edge computing (MEC).Implementing a Systematic Literature Review (SLR), this research dissects VM scheduling techniques. A meticulous selection process distilled 67 seminal studies from an initial corpus of 722, spanning from 2008 to 2022. This critical filtration has been pivotal for grasping the developmental trajectory and current tendencies in VM scheduling practices.The in-depth examination of 67 studies on VM scheduling has produced a taxonomic breakdown into three principal methodologies: traditional, heuristic, and meta-heuristic. The review underscores a marked shift toward heuristic and meta-heuristic methods, reflecting their growing significance in the advancement of VM scheduling.Although VM scheduling has progressed markedly, the focus remains predominantly on metaheuristic and heuristic approaches. The analysis enlightens ongoing challenges and the direction of future developments, highlighting the necessity for persistent research and innovation in this sector.
关于云计算和多访问计算中虚拟机调度技术的当代和未来趋势的系统性文献综述
业务和科学运营向云计算的迁移以及物联网设备数据的激增,加剧了云计算资源调度的复杂性。要确保高效的资源分配符合用户指定的 SLA 和 QoS,就需要新颖的调度解决方案。本研究仔细研究了当代虚拟机(VM)调度策略,揭示了虚拟机设计的复杂性和未来前景,旨在通过强调云计算和多访问边缘计算(MEC)领域不断发展的现有障碍和未开发潜力,推动进一步的研究。通过缜密的筛选过程,从最初的 722 篇文献中提炼出 67 篇开创性研究,时间跨度从 2008 年到 2022 年。通过对 67 篇有关虚拟机调度的研究进行深入研究,将其分类为三种主要方法:传统方法、启发式方法和元启发式方法。虽然虚拟机调度取得了显著进展,但重点仍主要集中在元启发式和启发式方法上。分析揭示了当前的挑战和未来的发展方向,强调了在这一领域进行持续研究和创新的必要性。
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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