Modeling of I/O Performance Interference in Virtualized Environments with Queueing Petri Nets
Modeling of I/O Performance Interference in Virtualized Environments with Queueing Petri Nets
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DOI：
10.1109/mascots.2014.48
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发表时间：
2014-09
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影响因子：
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通讯作者：
Qais Noorshams;Kiana Rostami;Samuel Kounev;Ralf H. Reussner
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作者：
Qais Noorshams;Kiana Rostami;Samuel Kounev;Ralf H. Reussner
虚拟化技术允许共享IT基础架构中使用的物理资源，以实现高效、灵活的系统操作。然而，共享物理资源通常是以性能为代价的，并且由于应用程序之间的相互性能干扰，对遵守整合的数据密集型应用程序的服务质量构成了重大挑战。可以使用显式性能分析技术预测工作负载整合对I/O性能的重要影响。然而，在当前的实践中，由于其复杂性，通常避免对虚拟环境中的I/O性能干扰影响进行显式建模。提出了一种基于排队网的虚拟环境I/O性能干扰的显式性能建模方法。更具体地说，我们首先强调在对虚拟环境中的I/O性能进行建模时面临的主要挑战。然后，我们创建一个单虚拟机I/O性能模型，该模型使用响应时间测量进行校准，以捕获基于IBM System z和IBM DS8700服务器硬件的具有代表性的真实环境的复杂行为。最后，我们使用I/O性能模型来评估工作负载在并置的虚拟机上异地分布时的I/O性能。总体而言，我们有效地创建了一个I/O性能干扰模型，该模型能够在平均预测误差不到10%的情况下捕获多虚拟机环境中的I/O性能影响。
Virtualization technology allows to share the physical resources used in IT infrastructures for efficient and flexible system operation. Sharing of physical resources, however, comes usually at the cost of performance and poses significant challenges to respect the Quality-of-Service of consolidated data-intensive applications due to the mutual performance interference among the applications. The non-trivial impact of workload consolidation on the I/O performance can be anticipated using explicit performance analysis techniques. In current practice, however, explicit modeling of I/O performance interference effects in virtualized environments is usually avoided due to their complexity. In this paper, we present an explicit performance modeling approach of I/O performance interference in virtualized environments with queueing Petri nets (QPNs). More specifically, we first highlight major challenges when modeling I/O performance in virtualized environments. Then, we create a single-VM I/O performance model calibrated with response time measurements to capture the complex behavior of a representative, real-world environment based on IBM System z and IBM DS8700 server hardware. Finally, we use the I/O performance model to evaluate the I/O performance when the workload is distributed heterogeneously on colocated virtual machines. Overall, we effectively create an I/O performance interference model capturing the I/O performance effects in a multi-VM environment with less than 10% prediction error on average.