Eco-Storage: A Hybrid Storage System with Energy-Efficient Informed Prefetching

  • Authors:

  • Maen M. Al Assaf;Xunfei Jiang;Mohamed Riduan Abid;Xiao Qin

  • Affiliations:

  • King Abdullah II School for Information Technology, The University of Jordan, Amman, Jordan;Department of Computer Science and Software Engineering, Auburn University, Auburn, USA 36849-5347;Alakhawayn University in Ifrane, Ifrane, Morocco;Department of Computer Science and Software Engineering, Auburn University, Auburn, USA 36849-5347

  • Venue:
  • Journal of Signal Processing Systems
  • Year:
  • 2013

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Abstract

In this paper, we present an energy-aware informed prefetching technique called Eco-Storage that makes use of the application-disclosed access patterns to group the informed prefetching process in a hybrid storage system (e.g., hard disk drive and solid state disks). Since the SSDs are more energy efficient than HDDs, aggressive prefetching for the data in the HDD level enables it to have as much standby time as possible in order to save power. In the Eco-Storage system, the application can still read its on-demand I/O reading requests from the hybrid storage system while the data blocks are prefetched in groups from HDD to SSD. We show that these two steps can be handled in parallel to decreases the system's power consumption. Our Eco-Storage technique differs from existing energy-aware prefetching schemes in two ways. First, Eco-Storage is implemented in a hybrid storage system where the SDD level is more energy efficient. Second, it can group the informed prefetching process and quickly prefetch the data from the HDD to the SSD to increase the frequent HDD standby times. This will makes the application finds most of its on-demand I/O reading requests in the SSD level. Finally, we develop a simulator to evaluate our Eco-Storage system performance. Our results show that our Eco-Storage reduces the power consumption by at least 75 % when compared with the worst case of non-Eco-Storage case using a real-world I/O trace.