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A model-based strategy for quantifying the impact of availability on the energy flow of data centers

机译:一种基于模型的策略,用于量化可用性对数据中心能量流量的影响

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The demand for higher computing power increases and, as a result, also leads to an increased demand for services hosted in cloud computing environments. It is known, for example, that in 2018 more than 4 billion people made daily access to these services through the Internet, corresponding to more than half of the world's population. To support such services, these clouds are made available by large data centers. These systems are responsible for the increasing consumption of electricity, given the increasing number of accesses, increasing the demand for greater communication capacity, processing and high availability. Since electricity is not always obtained from renewable resources, the relentless pursuit of cloud services can have a significant environmental impact. In this context, this paper proposes an integrated and dynamic strategy that demonstrates the impact of the availability of data center architecture equipment on energy consumption. For this, we used the technique of modeling colored Petri nets (CPN), responsible for quantifying the cost, environmental impact and availability of the electricity infrastructure of the data centers under analysis. Such proposed models are supported by the developed tool, where data center designers do not need to know CPN to compute the metrics of interest. A case study was proposed to show the applicability of the proposed strategy. Significant results were obtained, showing an increase in system availability of 100%, with equivalents operating cost and environmental impact.
机译:对更高计算能力的需求增加,因此,也导致云计算环境中托管的服务的需求增加。例如,众所周知,2018年超过40亿人通过互联网日常访问这些服务,对应于世界上一半以上的人口。为了支持此类服务,大型数据中心可提供这些云。考虑到越来越多的访问,增加了对更大的通信容量,处理和高可用性的需求,这些系统负责越来越多的电力消耗。由于电力并不总是从可再生资源获得,因此对云服务的无情追求可能具有重要的环境影响。在这方面,本文提出了一种集成和动态策略,展示了数据中心架构设备可用性对能耗的影响。为此,我们使用了彩色Petri网(CPN)的建模技术,负责量化在分析中数据中心的电力基础设施的成本,环境影响和可用性。开发工具支持此类提出的模型,其中数据中心设计人员不需要知道CPN来计算感兴趣的指标。提出了一个案例研究以表明拟议的策略的适用性。获得了显着的结果,显示了系统可用性的增加100%,具有等同的运营成本和环境影响。

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