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Performance Analysis of Network I/O Workloads in Virtualized Data Centers

机译:虚拟数据中心中网络I / O工作负载的性能分析

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Server consolidation and application consolidation through virtualization are key performance optimizations in cloud-based service delivery industry. In this paper, we argue that it is important for both cloud consumers and cloud providers to understand the various factors that may have significant impact on the performance of applications running in a virtualized cloud. This paper presents an extensive performance study of network I/O workloads in a virtualized cloud environment. We first show that current implementation of virtual machine monitor (VMM) does not provide sufficient performance isolation to guarantee the effectiveness of resource sharing across multiple virtual machine instances (VMs) running on a single physical host machine, especially when applications running on neighboring VMs are competing for computing and communication resources. Then we study a set of representative workloads in cloud-based data centers, which compete for either CPU or network I/O resources, and present the detailed analysis on different factors that can impact the throughput performance and resource sharing effectiveness. For example, we analyze the cost and the benefit of running idle VM instances on a physical host where some applications are hosted concurrently. We also present an in-depth discussion on the performance impact of colocating applications that compete for either CPU or network I/O resources. Finally, we analyze the impact of different CPU resource scheduling strategies and different workload rates on the performance of applications running on different VMs hosted by the same physical machine.
机译:通过虚拟化进行服务器整合和应用整合是基于云的服务交付行业的关键性能优化。在本文中,我们认为对于云消费者和云提供商而言,重要的是要了解可能对虚拟化云中运行的应用程序的性能产生重大影响的各种因素。本文对虚拟化云环境中的网络I / O工作负载进行了广泛的性能研究。我们首先显示,虚拟机监控器(VMM)的当前实现无法提供足够的性能隔离,无法保证在单个物理主机上运行的多个虚拟机实例(VM)之间进行资源共享的有效性,尤其是当在相邻VM上运行的应用程序争夺计算和通信资源。然后,我们研究了基于云的数据中心中一组具有代表性的工作负载,它们争夺CPU或网络I / O资源,并对可能影响吞吐量性能和资源共享有效性的不同因素进行了详细分析。例如,我们分析了在并发托管某些应用程序的物理主机上运行空闲VM实例的成本和收益。我们还将就竞争CPU或网络I / O资源的并置应用程序对性能的影响进行深入讨论。最后,我们分析了不同的CPU资源调度策略和不同的工作负载速率对在同一物理计算机上托管的不同VM上运行的应用程序性能的影响。

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