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

R. Singh, L. Awasthi, Geeta Sikka
{"title":"Towards Metaheuristic Scheduling Techniques in Cloud and Fog: An Extensive Taxonomic Review","authors":"R. Singh, L. Awasthi, Geeta Sikka","doi":"10.1145/3494520","DOIUrl":null,"url":null,"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.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"5 1","pages":"1 - 43"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Computing Surveys (CSUR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3494520","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Experimental Comparisons of Clustering Approaches for Data Representation On the Structure of the Boolean Satisfiability Problem: A Survey A Brief Overview of Universal Sentence Representation Methods: A Linguistic View The Eye in Extended Reality: A Survey on Gaze Interaction and Eye Tracking in Head-worn Extended Reality A Comprehensive Report on Machine Learning-based Early Detection of Alzheimer's Disease using Multi-modal Neuroimaging Data
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1