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首页> 外文期刊>Journal of Computers >I/O Behavior Characterizing and Predicting of Virtualization Workloads
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I/O Behavior Characterizing and Predicting of Virtualization Workloads

机译：I / O行为表征和预测虚拟化工作负载

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—In virtual machine system, different workloads are consolidated into a single platform to fully utilize the hardware resources. However, the diversity and strong variation of applications always make it difficult to optimize the resource allocation and thus reduce the system performance and efficiency. Therefore, how to accurately analyze and predict the runtime behavior of applications has become an important basement for virtual machine system optimization. In order to study the characteristic and predictability of virtualization applications, this paper proposes a dynamic behavior characterizing and predicting methodology under Xen virtual machine. We analyze the characteristics of several typical virtualization workloads with fine temporal granularity and apply several online predictors to predict application’s runtime I/O behavior. Experiment results demonstrate that the I/O behavior of virtualization workloads can be efficiently predicted by using proper predicting model and configuration. With this result, we further investigate the possibility of virtual machine scheduler optimizing based on I/O behavior characterizing. Several important issues are discussed including I/O computing jobs isolation through asymmetric scheduling, VM dynamic migration based on execution phase tracking and co-scheduling of multiple cooperative virtual machines. Preliminary test results demonstrate that this approach could efficiently reduce the performance degradation caused by scheduling competition in virtual machine system.
机译：-IN虚拟机系统，将不同的工作负载合并到单个平台中以充分利用硬件资源。但是，应用的多样性和强大变化始终使得难以优化资源分配，从而降低系统性能和效率。因此，如何准确分析和预测应用程序的运行时行为已成为虚拟机系统优化的重要地下室。为了研究虚拟化应用的特征和可预测性，本文提出了一种动态行为，在Xen虚拟机下表征和预测方法。我们分析了几种典型虚拟化工作负载的特征，具有精细的时间粒度，并应用几个在线预测因子来预测应用程序的运行时I / O行为。实验结果表明，可以通过使用正确的预测模型和配置有效地预测虚拟化工作负载的I / O行为。通过此结果，我们进一步调查了基于I / O行为的虚拟机调度器优化的可能性。讨论了几个重要问题，包括通过非对称调度，基于执行相位跟踪和多个协作虚拟机的共调度，VM动态迁移的I / O计算作业隔离。初步测试结果表明，这种方法可以有效地降低虚拟机系统中调度竞争引起的性能下降。

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