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Efficient VM Memory Balancing Algorithm Design and Implementation

机译:高效的VM Memory Balancing算法设计和实现

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A common strategy to manage memory resources of VMs under changing workloads is Dynamic VM memory management via hotplug. However, in order to estimate the VM working set size, most researchers are utilizing approaches that rely on kernel instrumentation but this most often results to high runtime overhead. This will result in system administrate to exercise a tradeoff between the estimate accuracy and system performance. The novelty of this work is to present a light weight accurate and transparent prediction algorithm for re-balancing memory resources among VMs. Experiments result attained on Dacapo and SPECjvm2008 from renowned benchmarks shows that with only 4% performance overhead our proposed method is capable of accurately adjusting virtual machine memory size on its real time requirements, and improve application performance in the virtual machine more than 10% better when virtual machine has 2 CPUs and 20% better when it has 4 CPUs. In case there is no free memory available our proposed method will try first to use host's free memory but if there is no free memory, it starts memory over-commitment for a fixed duration to help the requested VM complete its task.
机译:在更改工作负载下管理VM的内存资源的共同策略是通过Hotplug的动态VM内存管理。然而,为了估计VM工作集规模,大多数研究人员正在利用依赖核仪器的方法,但这通常会导致高运行时开销。这将导致系统管理在估算准确性和系统性能之间行使权衡。这项工作的新颖性是提供一种重量轻的准确和透明预测算法,用于重新平衡VM之间的内存资源。来自着名基准的Dacapo和SpecJVM2008达到了实验结果表明,只有4%的性能开销,我们所提出的方法能够在其实时要求上准确调整虚拟机器内存大小,并在虚拟机中提高应用程序性能超过10%虚拟机有2个CPU和20%的CPU时更好。如果没有免费内存可用我们的建议方法将首先尝试使用主机的释放内存,但如果没有空闲内存,则启动内存过度承诺,​​以帮助请求的VM完成其任务。

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