Quantifying the performance isolation properties of virtualization systems

Matthews, Jeanna; Hu, Wenjin; Hapuarachchi, Madhujith; Deshane, Todd; Dimatos, Demetrios; Hamilton, Gary G.; McCabe, Michael A.; Owens, James W. M.

doi:10.1145/1281700.1281706

Cited by 118 publications

(53 citation statements)

References 5 publications

(2 reference statements)

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“…Performance isolation in virtualized systems has been studied from several perspectives, including the role of virtual machine monitors in I/O performance [29], design of fair virtual I/O schedulers [26], and benchmarking suites for evaluating performance isolation [12,21]. We build on this existing work by focusing on multimedia and latency-sensitive application performance at a user level.…”

Section: Related Workmentioning

confidence: 99%

Empirical evaluation of latency-sensitive application performance in the cloud

Barker

Shenoy

2010

Proceedings of the First Annual ACM SIGMM Conference on Multimedia Systems

154

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Cloud computing platforms enable users to rent computing and storage resources on-demand to run their networked applications and employ virtualization to multiplex virtual servers belonging to different customers on a shared set of servers. In this paper, we empirically evaluate the efficacy of cloud platforms for running latency-sensitive multimedia applications. Since multiple virtual machines running disparate applications from independent users may share a physical server, our study focuses on whether dynamically varying background load from such applications can interfere with the performance seen by latency-sensitive tasks. We first conduct a series of experiments on Amazon's EC2 system to quantify the CPU, disk, and network jitter and throughput fluctuations seen over a period of several days. We then turn to a laboratory-based cloud and systematically introduce different levels of background load and study the ability to isolate applications under different settings of the underlying resource control mechanisms. We use a combination of micro-benchmarks and two realworld applications-the Doom 3 game server and Apple's Darwin Streaming Server-for our experimental evaluation. Our results reveal that the jitter and the throughput seen by a latency-sensitive application can indeed degrade due to background load from other virtual machines. The degree of interference varies from resource to resource and is the most pronounced for disk-bound latencysensitive tasks, which can degrade by nearly 75% under sustained background load. We also find that careful configuration of the resource control mechanisms within the virtualization layer can mitigate, but not eliminate, this interference.

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Section: Related Workmentioning

confidence: 99%

Empirical evaluation of latency-sensitive application performance in the cloud

Barker

Shenoy

2010

Proceedings of the First Annual ACM SIGMM Conference on Multimedia Systems

154

View full text Add to dashboard Cite

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“…Application virtualization differs depending on the running application on the local computer and management application logic which is remotely running on a virtual computer (Daniels 2009, Matthews et al 2007). …”

Section: Application Virtualizationmentioning

confidence: 99%

“…These processors support virtualization by the help of virtualization extensions such as the AMD-V and Intel-VT. The x86's 64 processors helping the virtualization process is quite recent technique but it is becoming common (Armstrong et al 2005, Matthews et al 2007). …”

Section: Native Virtualizationmentioning

confidence: 99%

Virtualization Tools and Techniques: Survey

Masood

Sharif

Yasmin

et al. 2015

Nepal Journal of Science and Technology

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Virtualization is a technique in which the user required services run remotely in a ubiquitous environment which gives scalable resources. Virtualization is being used in cloud computing for load balancing and aggregation of cloud resources. Virtualization provides higher hardware utilization. It is also being used for partitioning of computational resources and hence supports sharing of resources. Virtualization has different types such as Native virtualization, Full virtualization, Operating system level virtualization and Para virtualization. Other than these there is Resources virtualization, Desktop virtualization, Server virtualization, Data centres virtualization and application virtualization. The resources virtualization is implemented in different forms such as the Full virtualization, Native virtualization, Para virtualization, Operating system (OS) layer virtualization or Hosted virtualization. Virtual machines and Virtual machine monitors (VMMs) have been developed to offer better energy efficient solutions to the virtualization problems. Virtualization tools like OpenVz, Xen, VmWare etc. are widely used in the computing industry.

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“…In addition, complex applications may have individual components that are tested separately. Therefore, computing power and performance isolation [1], [2] for each test become essential. The first requirement can be met with an off-the-shelf cluster, whereas the second one with virtualization.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Load Generation in Virtualized Environments for Software Performance Testing

Netto

Menon

Vieira

et al. 2011

2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PHD Forum

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Abstract-Before placing a software system into production, it is necessary to guarantee it provides users with a certain level of Quality-of-Service. Intensive performance testing is then necessary to achieve such a level and the tests require an isolated computing environment. Virtualization can therefore play an important role for saving energy costs by reducing the number of servers required to run performance tests and for allowing performance isolation when executing multiple tests in the same computing infrastructure. Load generation is an important component in performance testing as it simulates users interacting with the target application. This paper presents our experience in using a virtualized environment for load generation aimed at performance testing. We measured several performance metrics and varied system load, number of virtual machines per physical resource, and the CPU pinning schema for comparison of virtual and physical machines. The two main findings from our experiments are that physical machines produced steadier and faster response times under heavy load and that the pinning schema is an important aspect when setting up a virtualized environment for load generation.

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Quantifying the performance isolation properties of virtualization systems

Cited by 118 publications

References 5 publications

Empirical evaluation of latency-sensitive application performance in the cloud

Empirical evaluation of latency-sensitive application performance in the cloud

Virtualization Tools and Techniques: Survey

Evaluating Load Generation in Virtualized Environments for Software Performance Testing

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