Massive arrays of idle disks for storage archives
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Idletime scheduling with preemption intervals
Proceedings of the twentieth ACM symposium on Operating systems principles
Disk drive level workload characterization
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
TCON'95 Proceedings of the USENIX 1995 Technical Conference Proceedings
PARAID: a gear-shifting power-aware RAID
FAST '07 Proceedings of the 5th USENIX conference on File and Storage Technologies
Write off-loading: practical power management for enterprise storage
FAST'08 Proceedings of the 6th USENIX Conference on File and Storage Technologies
Restrained utilization of idleness for transparent scheduling of background tasks
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Energy proportionality for storage: impact and feasibility
ACM SIGOPS Operating Systems Review
Autonomic exploration of trade-offs between power and performance in disk drives
Proceedings of the 7th international conference on Autonomic computing
SRCMap: energy proportional storage using dynamic consolidation
FAST'10 Proceedings of the 8th USENIX conference on File and storage technologies
Power-Aware Consolidation of Scientific Workflows in Virtualized Environments
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Adaptive workload shaping for power savings on disk drives
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Busy bee: how to use traffic information for better scheduling of background tasks
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
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As storage in data centers is increasing rapidly, it has become critical to find ways to operate efficiently this important component of a data center. Often, it has been proposed to consolidate the storage workload into a subset of storage devices and shutdown the unused ones with the purpose of preserving power. In many cases storage workload consolidation requires some amount of data to be copied from one device or set to the next. While storage workload consolidation techniques focus on extending power savings with minimal penalty in the performance of a data center, less attention is paid to the process of seamlessly integrating the data copy phase into the overall storage workload consolidation technique. Specifically, in this paper, we propose an analytic framework that synchronizes the pace of copying data between two storage devices (or nodes) such that performance is maintained within predefined targets. As such, we avoid either undesired performance degradation caused by aggressively scheduling the data copy task or a slow copy process caused by conservative scheduling. We show with extensive experimentation that the framework is robust and that it provides an important step toward automating storage consolidation and high power savings.