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T*GreenHDFS: A Cyber-Physical, Data-Centric Cooling Energy Costs Reduction Approach for Big Data Analytics Cloud

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Title: T*GreenHDFS: A Cyber-Physical, Data-Centric Cooling Energy Costs Reduction Approach for Big Data Analytics Cloud
Author(s): Kaushik, Rini T
Contributor(s): Nahrstedt, Klara; Abdelzaher, Tarek F.
Subject(s): Energy hadoop data-intensive computing HDFS cooling Flovent Thermal-Management Cooling Energy Costs Thermal-Aware Data Placement Data center cluster
Abstract: Big Data explosion and surge in large-scale Big Data analytics cloud infrastructure have led to burgeoning energy costs and present a challenge to the existing run-time cooling energy management techniques. T*GreenHDFS, a thermal-aware cloud file system, takes a novel, data-centric approach to reduce cooling energy costs. On the physical-side, T*GreenHDFS is cognizant of the uneven thermal-profile in the data centers due to complex airflow patterns, varying ability of the cooling system to cool different parts of the data center, and run-time load distribution. On the cyber-side, T*GreenHDFS is aware of the differences in the data-semantics of the data placed on the clusters. Based on this knowledge, and coupled with its predictive data models, T*GreenHDFS does proactive, thermal-aware data placement, which implicitly results in thermal-aware computation placement in the Big Data analytics cloud compute model. Evaluation results show up to 59% reduction in the cooling energy costs with T*GreenHDFS.
Issue Date: 2011-05
Genre: Technical Report
Type: TextOther
Language: English
URI: http://hdl.handle.net/2142/30404
Publication Status: unpublished
Date Available in IDEALS: 2012-11-27
 

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