Costs of Cloud Computing for a Biometry Department A Case Study
Costs of Cloud Computing for a Biometry Department A Case Study
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DOI：
10.3414/me11-02-0048
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发表时间：
2013-01-01
影响因子：
1.7
通讯作者：
Schwarzer, G.
中科院分区：
文献类型：
--
作者：
Knaus, J.;Hieke, S.;Schwarzer, G.
背景资料：“云”计算提供商，如亚马逊网络服务（AWS），提供基于硬件虚拟化的稳定和可扩展的计算资源，计费周期短，通常为每小时。按使用付费的想法似乎对那些只能有限地访问大学或企业数据中心资源或网格的生物统计研究单位很有吸引力。目标：本案例研究比较了医疗生物统计和统计部门现有异构现场硬件池的成本与AWS提供的同类产品。方法：包括所有直接费用在内的“总拥有成本”是根据2011年期间的实际系统利用率确定的，每小时价格是根据2011年期间的实际系统利用率计算的。间接费用难以量化，因此没有列入比较，但从我们的经验中得到了一些粗略的指导。为了说明方法研究项目的成本规模，我们使用AWS和现场硬件对基于置换的统计方法进行了模拟研究。结果：在所展示的案例中，系统利用率为25- 30%，摊销期为3-5年，现场硬件可以导致更小的成本，与云计算中的小时租金相比，这取决于所选择的实例。租用具有足够主内存的云实例是这一比较的决定性因素。结论：现场硬件的成本可能会有所不同，这取决于研究单位的具体基础设施，但对整体比较和随后获得负担得起的科学计算资源的决策只有适度的影响。总体利用率的影响要大得多，因为它决定了每年所需的实际计算小时数。考虑到这一点，云计算可能仍然是成熟度有限的项目的可行选择，或者作为需求短期高峰的补充。
Background: "Cloud" computing providers, such as the Amazon Web Services (AWS), offer stable and scalable computational resources based on hardware virtualization, with short, usually hourly, billing periods. The idea of pay-as-you-use seems appealing for biometry research units which have only limited access to university or corporate data center resources or grids.Objectives: This case study compares the costs of an existing heterogeneous on-site hardware pool in a Medical Biometry and Statistics department to a comparable AWS offer.Methods: The "total cost of ownership", including all direct costs, is determined for the on-site hardware, and hourly prices are derived, based on actual system utilization during the year 2011. Indirect costs, which are difficult to quantify are not included in this comparison, but nevertheless some rough guidance from our experience is given. To indicate the scale of costs for a methodological research project, a simulation study of a permutation-based statistical approach is performed using AWS and on-site hardware.Results: In the presented case, with a system utilization of 25-30 percent and 3-5-year amortization, on-site hardware can result in smaller costs, compared to hourly rental in the cloud dependent on the instance chosen. Renting cloud instances with sufficient main memory is a deciding factor in this comparison.Conclusions: Costs for on-site hardware may vary, depending on the specific infrastructure at a research unit, but have only moderate impact on the overall comparison and subsequent decision for obtaining affordable scientific computing resources. Overall utilization has a much stronger impact as it determines the actual computing hours needed per year. Taking this into account, cloud computing might still be a viable option for projects with limited maturity, or as a supplement for short peaks in demand.