Replication Methods for Abstract Data Types,

Abstract

An advantage of distributed systems over centralized systems is that valuable data can be stored redundantly at multiple locations--a practica commonly called 'replication'. Replication can enhance the availability of data in the presence of failures, increasing the likelihood that the data will be accessible when needed. This thesis introduces a new method for managing replicated data. We propose new techniques to address four problems associated with replication: the representation and manipulation of replicated data, concurrency control, on-the-fly reconfiguration, and enhancing availability in the presence of partitions. Unlike many methods that support replication only for uninterpreted files, our method makes use of type-specific properties of objects (such as sets, queues, or directories) to provide more effective replication. Associated with each operation of the data type is a set of quorums, which are collections of sites whose cooperation suffices to execute the operation. Analysis of the algebraic structure of the data type is used to derive a set of constraints on quorum intersections. Any choice of quorums that satisfies these constraints yields a correct implementation, and it can be shown that no smaller set of constraints guarantees correctness. By taking advantage of type-specific properties in a general and systematic way, our method can realize a wider range of availability properties, more concurrency, more flexible reconfiguration, and better tolerance of partitions than existing replication methods. Keywords: Atomicity, Availability, Concurrency control, Partitions, Reconfiguration, and Reliability.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1984
Accession Number
ADA153648

Entities

People

  • M. P. Herlihy

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Commerce
  • Computations
  • Computer Programming
  • Computer Science
  • Computers
  • Data Storage Systems
  • Databases
  • Distributed Computing
  • Information Processing
  • Language
  • Lisp Programming Language
  • Massachusetts
  • Notation
  • Programming Languages
  • Reliability

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Distributed Systems and Data Platform Development
  • Mathematical Modeling and Probability Theory.