Performance and power modeling and evaluation of virtualized servers in IaaS clouds
Performance and power modeling and evaluation of virtualized servers in IaaS clouds
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DOI：
10.1016/j.ins.2017.02.024
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发表时间：
2017-07
期刊：
影响因子：
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通讯作者：
Reza Entezari-Maleki;L. Sousa;A. Movaghar
中科院分区：
文献类型：
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作者：
Reza Entezari-Maleki;L. Sousa;A. Movaghar
在本文中，利用随机活动网络（SAN）对云计算中虚拟化服务器的功耗和性能进行建模和评估。所提出的SAN以三种不同的功耗和配置延迟模式对物理服务器进行建模，如果需要的话根据相应集群的工作负载切换服务器的状态。所提出的模型考虑了动态电压和频率调节 (DVFS) 技术，用于动态控制 CPU 的电源电压和时钟频率。因此，物理服务器之上的虚拟机 (VM) 可以分为多个功耗和处理速度组。根据系统的工作负载和等待请求的数量，所提出的SAN决定扩展或缩小VM，因此它有助于整个系统在仍然保持令人满意的性能的同时节省电力。使用 SAN 形式对服务器和虚拟机进行建模后，在建议的模型上定义了一些与性能相关的度量以及功耗指标。通过求解配置有实际数据的所提出的 SAN 模型所获得的结果表明，与一些基线和先前提出的模型相比，所提出的模型具有突出的优势。
In this paper, Stochastic Activity Networks (SANs) are exploited to model and evaluate the power consumption and performance of virtualized servers in cloud computing. The proposed SAN models the physical servers in three different power consumption and provisioning delay modes, switching the status of the servers according to the workload of the corresponding cluster if required. The Dynamic Voltage and Frequency Scaling (DVFS) technique is considered in the proposed model for dynamically controlling the supply voltage and clock frequency of CPUs. Thus, Virtual Machines (VMs) on top a physical server can be divided into several power consumption and processing speed groups. According to the workload of the system and the number of waiting requests, the proposed SAN decides to scale up or down the VMs, so it helps the overall system to save power when it still preserves satisfiable performance. After modeling the servers and VMs using SAN formalism, some performance related measures together with the power consumption metric are defined on the proposed model. The results obtained by solving the proposed SAN model configured with real data show the prominence of the proposed model in comparison with some baselines and previously proposed models.