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An effective cache algorithm for heterogeneous storage systems.

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A new cache algorithm, HCM, improves performance in heterogeneous storage systems by partitioning cache and balancing workloads. This approach significantly outperforms existing storage-aware algorithms.

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Area of Science:

  • Computer Science
  • Data Storage Systems

Background:

  • Modern storage systems utilize heterogeneous devices, posing challenges for traditional cache algorithms.
  • Existing cache algorithms are not optimized for the diverse performance characteristics of mixed storage environments.

Purpose of the Study:

  • To introduce a novel cache algorithm, HCM (Heterogeneous Cache Management), designed for heterogeneous storage systems.
  • To enhance data access performance in environments with varied storage device types.

Main Methods:

  • HCM partitions cache space among different storage devices.
  • It implements a work-balancing scheme to distribute load effectively across disks.
  • Benefit-cost analysis is employed for optimal cache block allocation.

Main Results:

  • Simulations using diverse traces and cache sizes demonstrated HCM's effectiveness.
  • HCM significantly outperformed existing state-of-the-art storage-aware cache algorithms.

Conclusions:

  • The proposed HCM algorithm offers a superior approach to caching in heterogeneous storage environments.
  • HCM's intelligent partitioning and allocation strategies lead to substantial performance gains.