计算机工程Issue(4)：41-47,7.DOI:10.3969/j.issn.1000-3428.2015.04.008
大数据处理中基于热感知的能源冷却技术
Energy Cooling Technology Based on Thermal-aware in Big Data Processing
摘要
Abstract
Explosion in big data has led to a surge in extremely large scale big data analytics platforms, resulting in burgeoning energy costs. In order to ensure the thermal-reliability of the servers, this paper proposes a data-centric technology for reducing cooling energy costs. It considers the uneven thermal-profile of the servers,the differences in their thermal-reliability-driven load thresholds,and differences in the data-semantics of the big data placed in the cluster. Based on this knowledge,the proposed technology does proactive,thermal-aware file placement,which ensures to reduce cooling energy costs and ensures thermal-reliability in the big data analytics cluster without any performance impact. Evaluation results with one-month long real-world big data analytics production traces from Yahoo Experimental results show that the technology reaches 42% reduction in the cooling energy costs and 9 x better performance than the state-of-the-art data-agnostic cooling techniques.关键词
大数据/热感知/热可靠性/服务器/能源冷却成本/集群Key words
big data/thermal-aware/thermal-reliability/server/energy cooling costs/clusters分类
信息技术与安全科学引用本文复制引用
金伟林,陈国顺..大数据处理中基于热感知的能源冷却技术[J].计算机工程,2015,(4):41-47,7.
