DVFS-Aware Consolidation for Energy-Efficient Clouds

2015 International Conference on Parallel Architecture and Compilation (PACT) Pub Date : 2015-10-18 DOI:10.1109/PACT.2015.59

Patricia Arroba, Jose M. Moya, J. Ayala, R. Buyya

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引用次数: 39

Abstract

Nowadays, data centers consume about 2% of the worldwide energy production, originating more than 43 million tons of CO2 per year. Cloud providers need to implement an energy-efficient management of physical resources in order to meet the growing demand for their services and ensure minimal costs. From the application-framework viewpoint, Cloud workloads present additional restrictions as 24/7 availability, and SLA constraints among others. Also, workload variation impacts on the performance of two of the main strategies for energy-efficiency in Cloud data centers: Dynamic Voltage and Frequency Scaling (DVFS) and Consolidation. Our work proposes two contributions: 1) a DVFS policy that takes into account the trade-offs between energy consumption and performance degradation; 2) a novel consolidation algorithm that is aware of the frequency that would be necessary when allocating a Cloud workload in order to maintain QoS. Our results demonstrate that including DVFS awareness in workload management provides substantial energy savings of up to 39.14% for scenarios under dynamic workload conditions.

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支持dvfs的节能云整合

如今，数据中心消耗了全球约2%的能源生产，每年产生超过4300万吨的二氧化碳。云提供商需要对物理资源实施节能管理，以满足对其服务日益增长的需求，并确保将成本降至最低。从应用程序框架的角度来看，云工作负载提供了额外的限制，如24/7可用性和SLA约束等。此外，工作负载变化会影响云数据中心中两种主要能效策略的性能:动态电压和频率缩放(DVFS)和整合。我们的工作提出了两个贡献:1)考虑到能耗和性能下降之间权衡的DVFS政策;2)一种新的整合算法，它知道在分配云工作负载以保持QoS时所需的频率。我们的研究结果表明，在工作负载管理中包含DVFS意识可以为动态工作负载条件下的场景节省高达39.14%的能源。

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2015 International Conference on Parallel Architecture and Compilation (PACT)

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