Multi-objective auto-scaling scheduling for micro-service workflows in hybrid clouds

IF 4.4 4区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Enterprise Information Systems Pub Date : 2022-05-03 DOI:10.1080/17517575.2022.2069478
Shi Wang, X. Liu, Ming Gao, Mingxia Chen, K. Yung, Shancheng Jiang
{"title":"Multi-objective auto-scaling scheduling for micro-service workflows in hybrid clouds","authors":"Shi Wang, X. Liu, Ming Gao, Mingxia Chen, K. Yung, Shancheng Jiang","doi":"10.1080/17517575.2022.2069478","DOIUrl":null,"url":null,"abstract":"ABSTRACT A novel multi-objective (cost, delay, and reliability) auto-scaling optimisation model is proposed for micro-service workflows in containerised hybrid clouds. We compare the container-based model with VM-based model and conclude that the former significantly supersedes. The benchmark of three mainstream algorithms is conducted by the Hypervolume metric, showed that the performance of MOEA/D is inferior to NSGA family, and NSGA-III is not always superior to NSGA-II. So we design an improved NSGA-II based on dynamically changing crossover and mutation operators, which outperforms NSGA-III both in stability and performance by over 60% and 80% in all multi-scale tests.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2022-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Enterprise Information Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/17517575.2022.2069478","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 1

Abstract

ABSTRACT A novel multi-objective (cost, delay, and reliability) auto-scaling optimisation model is proposed for micro-service workflows in containerised hybrid clouds. We compare the container-based model with VM-based model and conclude that the former significantly supersedes. The benchmark of three mainstream algorithms is conducted by the Hypervolume metric, showed that the performance of MOEA/D is inferior to NSGA family, and NSGA-III is not always superior to NSGA-II. So we design an improved NSGA-II based on dynamically changing crossover and mutation operators, which outperforms NSGA-III both in stability and performance by over 60% and 80% in all multi-scale tests.
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
混合云中微服务工作流的多目标自动伸缩调度
摘要针对容器化混合云中的微服务工作流,提出了一种新的多目标(成本、延迟和可靠性)自动缩放优化模型。我们比较了基于容器的模型和基于VM的模型,并得出结论,前者显著取代了前者。通过Hypervolume度量对三种主流算法进行了基准测试,结果表明,MOEA/D的性能不如NSGA家族,NSGA-III并不总是优于NSGA-II。因此,我们设计了一种基于动态变化的交叉和突变算子的改进NSGA-II,它在所有多尺度测试中的稳定性和性能都优于NSGA-III,分别超过60%和80%。
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
Enterprise Information Systems
Enterprise Information Systems 工程技术-计算机:信息系统
CiteScore
11.00
自引率
6.80%
发文量
24
审稿时长
6 months
期刊介绍: Enterprise Information Systems (EIS) focusses on both the technical and applications aspects of EIS technology, and the complex and cross-disciplinary problems of enterprise integration that arise in integrating extended enterprises in a contemporary global supply chain environment. Techniques developed in mathematical science, computer science, manufacturing engineering, and operations management used in the design or operation of EIS will also be considered.
期刊最新文献
Decentralized finance (DeFi): a paradigm shift in the Fintech Credit risk evaluation on technological SMEs in China An exploratory data analysis of malware/ransomware cyberattacks: insights from an extensive cyber loss dataset Co-creating value in manufacturing supply chains: unravelling the dynamics of innovation ecosystems A systematic data-driven approach for targeted marketing in enterprise information system
×
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