On-Line Data Reconstruction in Redundant Disk Arrays.

Abstract

There exists a wide variety of applications in which data availability must be continuous, that is, where the system is never taken off- line and any interruption in the accessibility of stored data causes significant disruption in the service provided by the application. Examples include on-line transaction processing systems such as airline reservation systems and automated teller networks in banking systems. In addition, there exist many applications for which a high degree of data availability is important, but continuous operation is not required. An example is a research and development environment, where access to a centrally-stored CAD system is often necessary to make progress on a design project. These applications and many others mandate both high performance and high availability from their storage subsystems. Redundant disk arrays are systems in which a high level of I/O performance is obtained by grouping together a large number of small disks, rather than building one large, expensive drive. The high component count of such systems leads to unacceptably high rates of data loss due to component failure, and so they typically incorporate redundancy to achieve fault tolerance.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1994
Accession Number
ADA282709

Entities

People

  • Mark Holland

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Application Software
  • Coding
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Control Simulators
  • Data Storage Systems
  • Databases
  • Device Drivers
  • Failure Mode And Effect Analysis
  • Fault Tolerance
  • Host Computers
  • Operating Systems
  • Systems Engineering
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Parallel and Distributed Computing.
  • Software Engineering.
  • Systems Analysis and Design