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Virtual machine placement based on the VM performance models in cloud

机译:基于云中VM性能模型的虚拟机放置

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Cloud service providers can offer users virtual machines (VMs) on-demand as a service over the Internet. VMs running on top of a physical machine (PM) share physical resources (CPU, memory, and/or bandwidth), and there may be a great resource contention among them, which results in VMs performance degradation. To prevent this, cloud providers need to study how to place VMs on PMs efficiently. However, the existing virtual machine placement (VMP) methods mainly tried to optimize the cloud resources instead of the VM performance. In this paper, we propose a VMP method based on the VM performance models in cloud. Firstly, with a real OpenStack cloud platform, we study the virtualization resource scheduling principle, analyze the interaction among VMs with shared hardware, consider the relationship between VMs and the host PM, and then we introduce the VM performance models to present the VM performance degradation problem. Secondly, to choose an appropriate PM for placing VM, we take into consideration the application-aware resource consumption characteristic, the VM resource requirement and the VM performance models, so as to minimize the PM performance degradation and guarantee the VM performance. Finally, we take the streaming media services for examples, and conduct some experiments to evaluate our method. The results show it works better than others and guarantees the VM performance significantly.
机译:云服务提供商可以通过互联网按需向用户提供虚拟机(VM)作为服务。在物理机(PM)上运行的VM共享物理资源(CPU,内存和/或带宽),并且它们之间可能存在很大的资源争用,这会导致VM性能下降。为了防止这种情况,云提供商需要研究如何有效地将VM放置在PM上。但是,现有的虚拟机放置(VMP)方法主要尝试优化云资源而不是VM性能。在本文中,我们提出了一种基于云中虚拟机性能模型的VMP方法。首先,在一个真实的OpenStack云平台上,研究虚拟化资源调度原理,分析虚拟机与共享硬件之间的交互,考虑虚拟机与主机PM之间的关系,然后介绍虚拟机性能模型来说明虚拟机性能下降的情况。问题。其次,在选择合适的PM来放置VM时,我们要考虑应用程序感知的资源消耗特性,VM资源需求和VM性能模型,以最大程度地减少PM性能下降并保证VM性能。最后,我们以流媒体服务为例,并进行一些实验以评估我们的方法。结果表明,它比其他软件更好,并且可以显着保证VM性能。

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