An Analysis of Performance Interference Effects on Energy-Efficiency of Virtualized Cloud Environments
An Analysis of Performance Interference Effects on Energy-Efficiency of Virtualized Cloud Environments
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DOI：
10.1109/cloudcom.2013.22
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发表时间：
2013-12
期刊：
影响因子：
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通讯作者：
Renyu Yang;Ismael Solís Moreno;Jie Xu;Tianyu Wo
中科院分区：
文献类型：
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作者：
Renyu Yang;Ismael Solís Moreno;Jie Xu;Tianyu Wo
虚拟化计算环境中的共同分配的工作负载通常必须竞争资源，从而遭受性能干扰。虽然这种现象对提供给客户的服务质量有直接影响，但它也改变了资源利用的模式，并减少了每瓦消耗的工作量。不幸的是，只有有限的研究如何性能干扰影响能源效率的服务器在这样的环境中。在现实中，资源利用率、性能干扰和能量效率之间存在高度动态和复杂的关系。本文提出了一个全面的分析，量化的负面影响的性能干扰的能源效率的虚拟化服务器。我们的分析方法考虑了从真实的云环境中识别的异构工作负载特征。特别是，我们调查的影响，由于不同的工作负载类型的组合，并开发了一种方法近似的性能干扰和能源效率下降的水平。所提出的方法是基于现有的工作负载类型和模式的分析得出的对组合的配置文件。我们的实验结果揭示了干扰的增加和能量效率的降低之间的非线性关系，以及两个参数估计的平均精度在+/-5%的误差范围内。这些发现为研究数据中心的资源利用率、性能和能源效率之间的动态权衡提供了重要信息。
Co-allocated workloads in a virtualized computing environment often have to compete for resources, thereby suffering from performance interference. While this phenomenon has a direct impact on the Quality of Service provided to customers, it also changes the patterns of resource utilization and reduces the amount of work per Watt consumed. Unfortunately, there has been only limited research into how performance interference affects energy-efficiency of servers in such environments. In reality, there is a highly dynamic and complicated correlation among resource utilization, performance interference and energy-efficiency. This paper presents a comprehensive analysis that quantifies the negative impact of performance interference on the energy-efficiency of virtualized servers. Our analysis methodology takes into account the heterogeneous workload characteristics identified from a real Cloud environment. In particular, we investigate the impact due to different workload type combinations and develop a method for approximating the levels of performance interference and energy-efficiency degradation. The proposed method is based on profiles of pair combinations of existing workload types and the patterns derived from the analysis. Our experimental results reveal a non-linear relationship between the increase in interference and the reduction in energy-efficiency as well as an average precision within +/-5% of error margin for the estimation of both parameters. These findings provide vital information for research into dynamic trade-offs between resource utilization, performance, and energy-efficiency of a data center.