Classifying Data to Reduce Long Term Data Movement

Appeared in Proceedings of the 31st International Conference on Massive Storage Systems and Technology (MSST 2015). Status: Accepted Publication Date: Jun 4, 2015

Abstract

Shingled Magnetic Recording (SMR) is a means of increasing the density of hard drives that brings a new set of challenges. Due to the nature of SMR disks, updating in place is not an option. Holes left by invalidated data can only be filled if the entire band is reclaimed, and a poor band compaction algorithm could result in spending a lot of time moving blocks over the lifetime of the device. We propose using write frequency to separate blocks to reduce data movement and develop a band compaction algorithm that implements this heuristic. We demonstrate how our algorithm results in improved data management, resulting in an up to 47% reduction in required data movements when compared to naive approaches to band management.

Publication date:
May 2015

Authors:
Stephanie Jones
Ahmed Amer
Ethan L. Miller
Darrell D. E. Long
Rekha Pitchumani
Christina Strong

Projects:
Shingled Disk

Available media

Full paper text: PDF

Bibtex entry

@inproceedings{snjones-mssta15,
  author       = {Stephanie Jones and Ahmed Amer and Ethan L. Miller and Darrell D. E. Long and Rekha Pitchumani and Christina Strong},
  title        = {Classifying Data to Reduce Long Term Data Movement},
  booktitle    = {Proceedings of the 31st International Conference on Massive Storage Systems and Technology (MSST 2015)},
  month        = may,
  year         = {2015},
}