Conserving disk energy in network servers
ICS '03 Proceedings of the 17th annual international conference on Supercomputing
DRPM: dynamic speed control for power management in server class disks
Proceedings of the 30th annual international symposium on Computer architecture
Ghosts in the machine: interfaces for better power management
Proceedings of the 2nd international conference on Mobile systems, applications, and services
PB-LRU: a self-tuning power aware storage cache replacement algorithm for conserving disk energy
Proceedings of the 18th annual international conference on Supercomputing
Power-Aware Storage Cache Management
IEEE Transactions on Computers
Modeling Hard-Disk Power Consumption
FAST '03 Proceedings of the 2nd USENIX Conference on File and Storage Technologies
Power reduction techniques for microprocessor systems
ACM Computing Surveys (CSUR)
Drive-Thru: fast, accurate evaluation of storage power management
ATEC '05 Proceedings of the annual conference on USENIX Annual Technical Conference
ACM Transactions on Storage (TOS)
Proceedings of the 2009 ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
Power efficient real-time disk scheduling
Proceedings of the 18th international workshop on Network and operating systems support for digital audio and video
Optimizing energy and performance for server-class file system workloads
ACM Transactions on Storage (TOS)
Evaluating performance and energy in file system server workloads
FAST'10 Proceedings of the 8th USENIX conference on File and storage technologies
Modeling hard-disk power consumption
FAST'03 Proceedings of the 2nd USENIX conference on File and storage technologies
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Hard disks for portable devices, and the operating systems that manage them, incorporate spin-down policies that idle the disk after a certain period of inactivity. In essence, these policies use a recent period of inactivity to predict that the disk will remain inactive in the near future. We propose an alternative strategy, in which the operating system deliberately seeks to cluster disk operations in time, to maximize the utilization of the disk when it is spun up and the time that the disk can be spun down. In order to cluster disk operations we postpone the service of non-urgent operations, and use aggressive prefetching and file prediction to reduce the likelihood that synchronous reads will have to go to disk. In addition, we present a novel predictive spin-down/spin-up policy that exploits high level operating system knowledge to decrease disk idle time prior to spin-down, and application wait time due to spin-up. We evaluate our strategy through trace-driven simulation of several different workload scenarios. Our results indicate that the deliberate creation of bursty activity can save up to 55% of the energy consumed by an IBM TravelStar disk, while simultaneously decreasing significantly the negative impact of disk spin-up latency on application performance.