Decreasing power consumption with energy efficient data aware strategies

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• 作者：Susan V. Vrbsky ; ^{vrbsky@cs.ua.edu}Author Vitae ; Michael Galloway ^{jmgalloway@cs.ua.edu}Author Vitae ; Robert CarrAuthor Vitae ; Rahul NoriAuthor Vitae ; David GrubicAuthor Vitae
• 关键词：Data backfilling ; Data cluster ; Data grid ; Data intensive computing ; Data replication ; Energy ; Power consumption ; QLFU
• 刊名：Future Generation Computer Systems
• 出版年：2013
• 出版时间：July, 2013
• 年：2013
• 卷：29
• 期：5
• 页码：1152-1163
• 全文大小：1767 K

文摘

Regardless of whether data is stored in a cluster, grid, or cloud, data management is being recognized as a significant bottleneck. Computing elements can be located far away from the data storage elements. The energy efficiency of the data centers storing this data is one of the biggest issues in data intensive computing. In order to address such issues, we are designing and analyzing a series of energy efficient data aware strategies involving data replication and CPU scheduling. In this paper, we present a new strategy for data replication, called Queued Least-Frequently-Used (QLFU), and study its performance to determine if it is an energy efficient strategy. We also study the benefits of using a data aware CPU scheduling strategy, called data backfilling, which uses job preemption in order to maximize CPU usage and allows for longer periods of suspension time to save energy. We measure the performance of QLFU and existing replica strategies on a small green cluster to study the running time and power consumption of the strategies with and without data backfilling. Results from this study have demonstrated that energy efficient data management can reduce energy consumption without negatively impacting response time.