Latency-Based Benchmarking of Cloud Service Providers

Vojtech Uhlir, Ondrej Tomanek, L. Kencl
{"title":"Latency-Based Benchmarking of Cloud Service Providers","authors":"Vojtech Uhlir, Ondrej Tomanek, L. Kencl","doi":"10.1145/2996890.3007870","DOIUrl":null,"url":null,"abstract":"With the ever-increasing trend of migration of applications to the Cloud environment, there is a growing need to thoroughly evaluate quality of the Cloud service itself, before deciding upon a hosting provider. Benchmarking the Cloud services is difficult though, due to the complex nature of the Cloud Computing setup and the diversity of locations, of applications and of their specific service requirements. However, such comparison may be crucial for decision making and for troubleshooting of services offered by the intermediate businesses - the so-called Cloud tenants. Existing cross–sectional studies and benchmarking methodologies provide only a shallow comparison of Cloud services, whereas state-of-the-art tooling for specific comparisons of application-performance parameters, such as for example latency, is insufficient. In this work, we propose a novel methodology for benchmarking of Cloud-service providers, which is based on latency measurements collected via active probing, and can be tailored to specific application needs. Furthermore, we demonstrate its applicability on a practical longitudinal study of real measurements of two major Cloud-service providers – Amazon and Microsoft.","PeriodicalId":350701,"journal":{"name":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","volume":"54 69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACM 9th International Conference on Utility and Cloud Computing (UCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2996890.3007870","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

With the ever-increasing trend of migration of applications to the Cloud environment, there is a growing need to thoroughly evaluate quality of the Cloud service itself, before deciding upon a hosting provider. Benchmarking the Cloud services is difficult though, due to the complex nature of the Cloud Computing setup and the diversity of locations, of applications and of their specific service requirements. However, such comparison may be crucial for decision making and for troubleshooting of services offered by the intermediate businesses - the so-called Cloud tenants. Existing cross–sectional studies and benchmarking methodologies provide only a shallow comparison of Cloud services, whereas state-of-the-art tooling for specific comparisons of application-performance parameters, such as for example latency, is insufficient. In this work, we propose a novel methodology for benchmarking of Cloud-service providers, which is based on latency measurements collected via active probing, and can be tailored to specific application needs. Furthermore, we demonstrate its applicability on a practical longitudinal study of real measurements of two major Cloud-service providers – Amazon and Microsoft.
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
基于延迟的云服务提供商基准测试
随着应用程序迁移到云环境的趋势不断增加,在决定选择托管提供商之前,越来越需要彻底评估云服务本身的质量。但是,由于云计算设置的复杂性以及应用程序及其特定服务需求的位置多样性,对云服务进行基准测试是困难的。然而,这种比较对于中间业务(所谓的云租户)提供的服务的决策和故障排除可能是至关重要的。现有的横断面研究和基准测试方法只能对云服务进行肤浅的比较,而用于特定比较应用程序性能参数(例如延迟)的最先进工具是不够的。在这项工作中,我们提出了一种新的云服务提供商基准测试方法,该方法基于通过主动探测收集的延迟测量,并且可以根据特定的应用需求进行定制。此外,我们在两个主要云服务提供商——亚马逊和微软的实际测量的实际纵向研究中证明了它的适用性。
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
Towards a Smart Learning Environment for Smart City Governance Public Auditing Scheme for Cloud-Based Wireless Body Area Network (t,p)-Threshold Point Function Secret Sharing Scheme Based on Polynomial Interpolation and Its Application Enterprise IoT Security and Scalability: How Unikernels can Improve the Status Quo Service Topic Model with Probability Distance
×
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