Extensible block-level storage virtualization in cluster-based systems

  • Authors:

  • Michail D. Flouris;Renaud Lachaize;Konstantinos Chasapis;Angelos Bilas

  • Affiliations:

  • Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), 100 N. Plastira Ave., Vassilika Vouton, Heraklion GR-70013, Greece;Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), 100 N. Plastira Ave., Vassilika Vouton, Heraklion GR-70013, Greece;Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), 100 N. Plastira Ave., Vassilika Vouton, Heraklion GR-70013, Greece and Department of Computer Science, ...;Institute of Computer Science (ICS), Foundation for Research and Technology - Hellas (FORTH), 100 N. Plastira Ave., Vassilika Vouton, Heraklion GR-70013, Greece and Department of Computer Science, ...

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2010

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Abstract

High-performance storage systems are evolving towards decentralized commodity clusters that can scale in capacity, processing power, and network throughput. Building such systems requires: (a) Sharing physical resources among applications; (b) Sharing data among applications; (c) Allowing customized data views. Current solutions typically satisfy the first two requirements through a cluster file-system, resulting in monolithic, hard-to-manage systems. In this paper we present a storage system that addresses all three requirements by extending the block layer below the file-system. First, we discuss how our system provides customized (virtualized) storage views within a single node. Then, we discuss how it scales in clustered setups. To achieve efficient resource and data sharing we support block-level allocation and locking as in-band mechanisms. We implement a prototype under Linux and use it to build a shared cluster file-system. Our evaluation in a 24-node cluster setup concludes that our approach offers flexibility, scalability and reduced effort to implement new functionality.