{"title":"A Performance Study on the VM Startup Time in the Cloud","authors":"Ming Mao, M. Humphrey","doi":"10.1109/CLOUD.2012.103","DOIUrl":null,"url":null,"abstract":"One of many advantages of the cloud is the elasticity, the ability to dynamically acquire or release computing resources in response to demand. However, this elasticity is only meaningful to the cloud users when the acquired Virtual Machines (VMs) can be provisioned in time and be ready to use within the user expectation. The long unexpected VM startup time could result in resource under-provisioning, which will inevitably hurt the application performance. A better understanding of the VM startup time is therefore needed to help cloud users to plan ahead and make in-time resource provisioning decisions. In this paper, we study the startup time of cloud VMs across three real-world cloud providers -- Amazon EC2, Windows Azure and Rackspace. We analyze the relationship between the VM startup time and different factors, such as time of the day, OS image size, instance type, data center location and the number of instances acquired at the same time. We also study the VM startup time of spot instances in EC2, which show a longer waiting time and greater variance compared to on-demand instances.","PeriodicalId":214084,"journal":{"name":"2012 IEEE Fifth International Conference on Cloud Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"559","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Fifth International Conference on Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLOUD.2012.103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 559
Abstract
One of many advantages of the cloud is the elasticity, the ability to dynamically acquire or release computing resources in response to demand. However, this elasticity is only meaningful to the cloud users when the acquired Virtual Machines (VMs) can be provisioned in time and be ready to use within the user expectation. The long unexpected VM startup time could result in resource under-provisioning, which will inevitably hurt the application performance. A better understanding of the VM startup time is therefore needed to help cloud users to plan ahead and make in-time resource provisioning decisions. In this paper, we study the startup time of cloud VMs across three real-world cloud providers -- Amazon EC2, Windows Azure and Rackspace. We analyze the relationship between the VM startup time and different factors, such as time of the day, OS image size, instance type, data center location and the number of instances acquired at the same time. We also study the VM startup time of spot instances in EC2, which show a longer waiting time and greater variance compared to on-demand instances.
云的众多优势之一是弹性,即根据需求动态获取或释放计算资源的能力。但是,这种弹性只有在获得的虚拟机(vm)能够及时供应并在用户期望的范围内准备好使用时才对云用户有意义。长时间的意外VM启动时间可能导致资源供应不足,这将不可避免地损害应用程序性能。因此,需要更好地了解VM启动时间,以帮助云用户提前计划并及时做出资源配置决策。在本文中,我们研究了三个现实世界的云提供商(Amazon EC2, Windows Azure和Rackspace)的云vm启动时间。我们分析了虚拟机启动时间与不同因素之间的关系,例如一天中的时间、操作系统映像大小、实例类型、数据中心位置以及同时获取的实例数量。我们还研究了EC2中现货实例的VM启动时间,与按需实例相比,它显示出更长的等待时间和更大的差异。