HAG： An Energy-Proportional Data Storage Scheme for Disk Array Systems  

作　　者：金培权 谢希科 Christian S. Jensen 金勇 岳丽华 

机构地区：[1]School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China [2]Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei 230027, China [3]Department of Computer Science, Aalborg University, Aalborg, DK-9220, Denmark

出　　处：《Journal of Computer Science & Technology》2015年第4期679-695,共17页计算机科学技术学报（英文版）

基　　金：The work was partially supported by the National Natural Science Foundation of China under Grant Nos, 61379037 and 61472376, and the Oversea Academic Training Funds （OATF） sponsored by the University of Science and Technology of China. Acknowledgements We would like to thank the anonymous reviewers and editors for their valuable sug- gestions and comments to improve the quality of the paper.

摘　　要：Energy consumption has been a critical issue for data storage systems, especially for modern data centers. A recent survey has showed that power costs amount to about 50%of the total cost of ownership in a typical data center, with about 27% of the system power being consumed by storage systems. This paper aims at providing an effective solution to reducing the energy consumed by disk storage systems, by proposing a new approach to reduce the energy consumption. Differing from previous approaches, we adopt two new designs. 1） We introduce a hotness-aware and group-based system model （HAG） to organize the disks, in which all disks are partitioned into a hot group and a cold group. We only make file migration between the two groups and avoid the migration within a single group, so that we are able to reduce the total cost of file migration. 2） We use an on-demand approach to reorganize files among the disks that is based on workload change as well as the change of data hotness. We conduct trace-driven experiments involving two real and nine synthetic traces and we make detailed comparisons between our method and competitor methods according to different metrics. The results show that our method can dynamically select hot files and disks when the workload changes and that it is able to reduce energy consumption for all the traces. Furthermore, its time performance is comparable to that of the compared algorithms. In general, our method exhibits the best energy e？ciency in all experiments, and it is capable of maintaining an improved trade-off between performance and energy consumption.Energy consumption has been a critical issue for data storage systems, especially for modern data centers. A recent survey has showed that power costs amount to about 50%of the total cost of ownership in a typical data center, with about 27% of the system power being consumed by storage systems. This paper aims at providing an effective solution to reducing the energy consumed by disk storage systems, by proposing a new approach to reduce the energy consumption. Differing from previous approaches, we adopt two new designs. 1） We introduce a hotness-aware and group-based system model （HAG） to organize the disks, in which all disks are partitioned into a hot group and a cold group. We only make file migration between the two groups and avoid the migration within a single group, so that we are able to reduce the total cost of file migration. 2） We use an on-demand approach to reorganize files among the disks that is based on workload change as well as the change of data hotness. We conduct trace-driven experiments involving two real and nine synthetic traces and we make detailed comparisons between our method and competitor methods according to different metrics. The results show that our method can dynamically select hot files and disks when the workload changes and that it is able to reduce energy consumption for all the traces. Furthermore, its time performance is comparable to that of the compared algorithms. In general, our method exhibits the best energy e？ciency in all experiments, and it is capable of maintaining an improved trade-off between performance and energy consumption.

关 键 词：energy-aware system file organization storage management 

分 类 号：TP333.35[自动化与计算机技术—计算机系统结构] TK018[自动化与计算机技术—计算机科学与技术]