Multilayered Cloud Applications Autoscaling Performance Estimation

Anshul Jindal, Vladimir Podolskiy, M. Gerndt
{"title":"Multilayered Cloud Applications Autoscaling Performance Estimation","authors":"Anshul Jindal, Vladimir Podolskiy, M. Gerndt","doi":"10.1109/SC2.2017.12","DOIUrl":null,"url":null,"abstract":"A multilayered autoscaling gets an increasing attention both in research and business communities. Introduction of new virtualization layers such as containers, pods, and clusters has turned a deployment and a management of cloud applications into a simple routine. Each virtualization layer usually provides its own solution for scaling. However, synchronization and collaboration of these solutions on multiple layers of virtualization remains an open topic. In the scope of the paper, we consider a wide research problem of the autoscaling across several layers for cloud applications. A novel approach to multilayered autoscalers performance measurement is introduced in this paper. This approach is implemented in Autoscaling Performance Measurement Tool (APMT), which architecture and functionality are also discussed. Results of model experiments on different requests patterns are also provided in the paper.","PeriodicalId":188326,"journal":{"name":"2017 IEEE 7th International Symposium on Cloud and Service Computing (SC2)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 7th International Symposium on Cloud and Service Computing (SC2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SC2.2017.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

Abstract

A multilayered autoscaling gets an increasing attention both in research and business communities. Introduction of new virtualization layers such as containers, pods, and clusters has turned a deployment and a management of cloud applications into a simple routine. Each virtualization layer usually provides its own solution for scaling. However, synchronization and collaboration of these solutions on multiple layers of virtualization remains an open topic. In the scope of the paper, we consider a wide research problem of the autoscaling across several layers for cloud applications. A novel approach to multilayered autoscalers performance measurement is introduced in this paper. This approach is implemented in Autoscaling Performance Measurement Tool (APMT), which architecture and functionality are also discussed. Results of model experiments on different requests patterns are also provided in the paper.
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
多层云应用程序自动伸缩性能估计
多层自动伸缩在研究和商业领域都受到越来越多的关注。新的虚拟化层(如容器、pod和集群)的引入将云应用程序的部署和管理变成了简单的例程。每个虚拟化层通常提供自己的扩展解决方案。然而,这些解决方案在多个虚拟化层上的同步和协作仍然是一个开放的话题。在本文的范围内,我们考虑了一个广泛的研究问题,即云应用的跨多层自动伸缩。本文介绍了一种多层自标度器性能测量的新方法。该方法在自动缩放性能测量工具(APMT)中实现,并对其架构和功能进行了讨论。文中还给出了不同请求模式下的模型实验结果。
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
Multilayered Cloud Applications Autoscaling Performance Estimation Optimal Placement of Network Security Monitoring Functions in NFV-Enabled Data Centers Application-Aware Traffic Redirection: A Mobile Edge Computing Implementation Toward Future 5G Networks A Mobile Cloud-Based Biofeedback Platform for Evaluating Medication Response Platform-as-a-Service for Human-Based Applications: Ontology-Driven Approach
×
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