Reducing energy usage in drive storage clusters through intelligent allocation of incoming commands

Edward Smart, David Brown, Kais Toumi Borges, Nick Granger-Brown

Research output: Contribution to journalArticlepeer-review

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Abstract

Although significant research has been undertaken to reduce high level energy consumption in a data centre, there has been very little focus on reducing storage drive energy consumption via the intelligent allocation of workload commands at the file system level. This paper presents a method for optimising drive energy consumption within a custom built storage cluster containing multiple drives, using multi-objective goal attainment optimisation. Significantly, the model developed was based on actual power consumption values (from current/voltage sensors on the drives themselves), which is rare in this field.

The results showed that command energy savings of up to 87% (17% over-all energy) could be made by optimising the allocation of incoming commands for execution to drives within a storage cluster for different workloads. More significantly, the transparency of the method meant that it showed exactly how such savings could be made and on which drives. It also highlighted that whilst it is well known that solid state drives use less energy than traditional hard disk drives, the difference is not consistent for different sizes of data transfers. It is far larger for small data transfers (less than or equal to 4 kB) and our algorithm utilised this.

Significantly, it highlights how much larger energy savings can be made through using the optimisation results to show which drives can be safely put into a low power state without affecting storage cluster performance.
Original languageEnglish
Pages (from-to)673-686
Number of pages13
JournalApplied Soft Computing
Volume52
Early online date17 Oct 2016
DOIs
Publication statusPublished - Mar 2017

Keywords

  • decision support systems
  • disk drives
  • data storage systems
  • pareto optimisation
  • optimal scheduling

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