This paper presents results of the performance benchmarks of the Open Source hypervisor Xen. The study focuses on the network related performance as well as on the application related performance of multiple virtual machines that were running on the same Xen hypervisor. The comparison was carried out using a self-developed benchmark suite that consists of easily available Open Source tools. The goal is to measure the performance of the hypervisor in typical real-world application scenarios when used for "mass virtual hosting", such as hosting solutions of so called virtual private servers for small-to-medium sized businesses environments. The results of the benchmarks show, that the tested Xen setup offers good performance with respect to network traffic stress tests, but only 75 of the performance of the non-virtualized reference environment. This application performance score decreases as more virtual machines are running simultaneously.
The measurement of the performance of hypervisors like Xen has been subject to many studies, including barham2003 , @cite_1 , deshane2008 , apparao2006 , cherkasova2005 , matthews2007 , xu2008 , @cite_11 .
@cite_1 @cite_11
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Given the ease that humans have with using a keyboard and mouse in typical, non-colocated computer interaction, many studies have investigated the value of colocating the visual field and motor workspaces using immersive display modalities. Significant understanding has been gained by previous work comparing physical tasks against virtual tasks, visuomotor colocation versus non-colocation, and even visuomotor rotational misalignments in virtual environments (VEs). However, few studies have explored all of these paradigms in context with each other, and it is difficult to perform interstudy comparisons because of the variation in tested motor tasks. Therefore, using a stereoscopic fish tank display setup, the goal for the current study was to characterize human performance of a 3D Fitts' point-to-point reaching task using a stylus-based haptic interface in the physical, colocated non-colocated, and rotated VE visualization conditions. Five performance measures---throughput, efficiency, initial movement error, corrective movements, and peak velocity---were measured and used to evaluate task performance. These measures were studied in 22 subjects (11 male, 11 female, ages 20--32) performing a 3D variant of Fitts' serial task under 10 task conditions: physical, colocated VE, non-colocated VE, and rotated VEs from 45---315° in 45° increments. Hypotheses: All performance measures in the colocated VE were expected to reflect significantly reduced task performance over the real condition, but also reflect increased performance over the non-colocated VE condition. For rotational misalignments, all performance measures were expected to reflect the highest performance at 0°, reduce to the lowest performance at 90°, and rise again to a local maximum at 180° (symmetric about 0°). Results: All performance measures showed that the colocated VE condition resulted in significantly lower task performance than the physical condition and higher mean performance than the non-colocated VE condition, but the difference was not statistically significant. Also, rotation misalignments showed that task performance was mostly reduced to a minimum at 90°, 135°, and 225°. We conclude that colocated VEs may not significantly improve point-to-point reaching performance over non-colocated VEs. Also, visual rotations of ±45° affected throughput, efficiency, peak velocity, and initial movement error, but the number of corrective movements were not affected until ± 90°. Xen is an x86 virtual machine monitor produced by the University of Cambridge Computer Laboratory and released under the GNU General Public License. Performance results comparing XenoLinux (Linux running in a Xen virtual machine) to native Linux as well as to other virtualization tools such as User Mode Linux (UML) were recently published in the paper "Xen and the Art of Virtualization" at the Symposium on Operating Systems Principles (October 2003). In this study, we repeat this performance analysis of Xen. We also extend the analysis in several ways, including comparing XenoLinux on x86 to an IBM zServer. We use this study as an example of repeated research. We argue that this model of research, which is enabled by open source software, is an important step in transferring the results of computer science research into production environments. Papers on functional language implementations frequently set the goal of achieving performance "comparable to C", and sometimes report results comparing benchmark results to concrete C implementations of the same problem. A key pair of questions for such comparisons is: what C program to compare to, and what C compiler to compare with? In a 2012 paper, [9] compare naive serial C implementations of a range of throughput-oriented benchmarks to best-optimized implementations parallelized on a six-core machine and demonstrate an average 23X (up to 53X) speedup. Even accounting for thread parallel speedup, these results demonstrate a substantial performance gap between naive and tuned C code. In this current paper, we choose a subset of the benchmarks studied by to port to Haskell. We measure performance of these Haskell benchmarks compiled with the standard Glasgow Haskell Compiler and with our experimental Intel Labs Haskell Research Compiler and report results as compared to our best reconstructions of the algorithms used by Results are reported as measured both on an Intel Xeon E5-4650 32-core machine, and on an Intel Xeon Phi co-processor. We hope that this study provides valuable data on the concrete performance of Haskell relative to C. Hypervisors, popularized by Xen and VMware, are quickly becoming commodity. They are appropriate for many usage scenarios, but there are scenarios that require system virtualization with high degrees of both isolation and efficiency. Examples include HPC clusters, the Grid, hosting centers, and PlanetLab. We present an alternative to hypervisors that is better suited to such scenarios. The approach is a synthesis of prior work on resource containers and security containers applied to general-purpose, time-shared operating systems. Examples of such container-based systems include Solaris 10, Virtuozzo for Linux, and Linux-VServer. As a representative instance of container-based systems, this paper describes the design and implementation of Linux-VServer. In addition, it contrasts the architecture of Linux-VServer with current generations of Xen, and shows how Linux-VServer provides comparable support for isolation and superior system efficiency.