虚拟机系统的混合调度框架

Chuliang Weng, Zhigang Wang, Minglu Li, Xinda Lu
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引用次数: 104

摘要

虚拟化技术使得在单个物理机器上运行多个客户机操作系统成为可能。它是虚拟机监视器,根据调度策略动态地将虚拟机的虚拟CPU映射到物理CPU。Xen的调度策略对虚拟机的虚拟CPU进行异步调度,同时保证CPU的权重所对应的时间比例,最大限度地提高系统的吞吐量。但是,当虚拟机用于执行并行程序或多线程程序等并发应用程序时,这种调度策略可能会降低性能。本文从理论上分析了虚拟机监控中的CPU调度问题,指出当系统工作负载为并发应用时,异步CPU调度策略会浪费大量的物理CPU时间。在此基础上,提出了一种虚拟机监控系统中CPU调度的混合调度框架。系统中有两种类型的虚拟机:高吞吐量类型和并发类型。当虚拟机的大部分工作负载是并发应用程序时,可以将其设置为并发类型,以降低同步成本。否则,将设置为默认的高吞吐量类型。此外,我们还实现了基于Xen的混合调度框架,并详细描述了我们的实现。最后,在多核平台上对所提出的调度框架和策略进行了性能测试,实验结果表明该调度框架和策略对于提高虚拟机系统的性能是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The hybrid scheduling framework for virtual machine systems
The virtualization technology makes it feasible that multiple guest operating systems run on a single physical machine. It is the virtual machine monitor that dynamically maps the virtual CPU of virtual machines to physical CPUs according to the scheduling strategy. The scheduling strategy in Xen schedules virtual CPUs of a virtual machines asynchronously while guarantees the proportion of the CPU time corresponding to its weight, maximizing the throughput of the system. However, this scheduling strategy may deteriorate the performance when the virtual machine is used to execute the concurrent applications such as parallel programs or multithreaded programs. In this paper, we analyze the CPU scheduling problem in the virtual machine monitor theoretically, and the result is that the asynchronous CPU scheduling strategy will waste considerable physical CPU time when the system workload is the concurrent application. Then, we present a hybrid scheduling framework for the CPU scheduling in the virtual machine monitor. There are two types of virtual machines in the system: the high-throughput type and the concurrent type. The virtual machine can be set as the concurrent type when the majority of its workload is concurrent applications in order to reduce the cost of synchronization. Otherwise, it is set as the high-throughput type as the default. Moreover, we implement the hybrid scheduling framework based on Xen, and we will give a description of our implementation in details. At last, we test the performance of the presented scheduling framework and strategy based on the multi-core platform, and the experiment result indicates that the scheduling framework and strategy is feasible to improve the performance of the virtual machine system.
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