Adaptive Overlapped Declustering: A Highly Available Data-Placement Method Balancing Access Load and Space Utilization

  • Authors:

  • Akitsugu Watanabe;Haruo Yokota

  • Affiliations:

  • Tokyo Institute of Technology;Tokyo Institute of Technology

  • Venue:
  • ICDE '05 Proceedings of the 21st International Conference on Data Engineering
  • Year:
  • 2005

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Abstract

This paper proposes a new data-placement method named Adaptive Overlapped Declustering, which can be applied to a parallel storage system using a value range partitioning-based distributed directory and primary-backup data replication, to improve the space utilization by balancing their access loads. The proposed method reduces data skews generated by data migration for balancing access load. While some data-placement methods capable of balancing access load or reducing data skew have been proposed, both requirements satisfied simultaneously. The proposed method also improves the reliability and availability of the system because it reduces recovery time for damaged backups after a disk failure. The method achieves this acceleration by reducing a large amount of network communications and disk I/O. Mathematical analysis shows the efficiency of space utilization under skewed access workloads. Queuing simulations demonstrated that the proposed method halves backup restoration time, compared with the traditional chained declustering method.