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Software Techniques for Making Cloud Data Centers Energy-efficient: A Systematic Mapping Study

机译:使云数据中心节能的软件技术:系统映射研究

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Due to high demand, many cloud data centers have been developed across the world, consuming a large amount of energy. Making cloud datacenters energy efficient has become essential. Energy consumption of data centers can be minimized by designing energy-efficient hardware, software, and infrastructure. In this paper, we aim at giving an overview of software techniques, affected stakeholders, performance features, datasets, and tools used to make cloud data centers energy-efficient. To achieve this goal, we conducted a systematic mapping study using five online databases. After applying inclusion/exclusion and quality criteria, we selected 58 publications for further analysis. Our results indicate that all publications are solution and validation type of publications. We did not find publications containing evaluations in industry. We found that workload scheduling is the most frequently proposed technique used to improve cloud datacenters’ energy efficiency. We found that not considering violations of service level agreements mostly affects end-users of cloud data centers. When analyzing how suggested solutions are validated, we identified the need to develop a standardized set of performance measures to benchmark software techniques proposed to make cloud data centers greener.
机译:由于需求量大,全世界已经开发了许多云数据中心,消耗了大量能源。使云数据中心高效节能已变得至关重要。通过设计节能的硬件,软件和基础架构,可以将数据中心的能耗降至最低。在本文中,我们旨在概述软件技术,受影响的利益相关者,性能特征,数据集以及用于使云数据中心节能的工具。为了实现这一目标,我们使用五个在线数据库进行了系统的制图研究。应用纳入/排除和质量标准后,我们​​选择了58种出版物进行进一步分析。我们的结果表明,所有出版物均为解决方案和出版物的验证类型。我们找不到包含行业评估的出版物。我们发现工作负载调度是提高云数据中心能效的最常用的技术。我们发现,不考虑违反服务水平协议的情况会严重影响云数据中心的最终用户。在分析建议的解决方案的验证方式时,我们发现有必要开发一套标准的性能指标,以对旨在使云数据中心更环保的基准软件技术进行基准测试。

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