Workload decomposition for power efficient storage systems

  • Authors:
  • Lanyue Lu;Peter Varman

  • Affiliations:
  • Rice University, Houston, TX;Rice University, Houston, TX

  • Venue:
  • HotPower'08 Proceedings of the 2008 conference on Power aware computing and systems
  • Year:
  • 2008

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Abstract

Power consumption and cooling costs of hosted storage services and shared storage infrastructure in data centers account for a growing percentage of the total cost of ownership. The bursty nature of storage workloads requires significant over provisioning of the capacity and power consumption to meet traditional response-time QoS guarantees. In this paper, we propose a graduated, distribution-based QoS model and a runtime scheduler for power efficient storage servers. Through the evaluation of the real storage workload traces, we show a new general tradeoff between the performance and power consumption.