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Self-stabilization

Published: 01 March 1993 Publication History

Abstract

In 1973 Dijkstra introduced to computer science the notion of self-stabilization in the context of distributed systems. He defined a system as self-stabilizing when “regardless of its initial state, it is guaranteed to arrive at a legitimate state in a finite number of steps.” A system which is not self-stabilizing may stay in an illegitimate state forever. Dijkstra's notion of self-stabilization, which originally had a very narrow scope of application, is proving to encompass a formal and unified approach to fault tolerance under a model of transient failures for distributed systems. In this paper we define self-stabilization, examine its significance in the context of fault tolerance, define the important research themes that have arisen from it, and discuss the relevant results. In addition to the issues arising from Dijkstra's original presentation as well as several related issues, we discuss methodologies for designing self-stabilizing systems, the role of compilers with respect to self-stabilization, and some of the factors that prevent self-stabilization.

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David James Taylor

Self-stabilization is the property that guarantees that a system placed in an arbitrary state will return to a legitimate state within a finite number of state transitions. This paper provides an extensive survey of research into self-stabilization and such related notions as probabilistic self-stabilization and pseudo-stabilization. Although it provides a good general background and historical summary, the paper is likely to prove frustrating for a reader unfamiliar with the field. The authors frequently introduce a topic too briefly for it to be really appreciated and then refer the reader to the original work for details. In addition, the paper does not provide any proofs for self-stabilization. With no examples, the reader may be left without a grasp of the type of argument required. For the original Dijkstra unidirectional ring, it would not have been difficult to sketch a proof rather than leave the reader with the statement, “Furthermore it can be shown quite easily that if started in an arbitrary state, the system will stabilize.” The paper claims, as does much of the cited literature, that self-stabilization is a useful technique for fault tolerance. A critical reading of the paper suggests that the field has instead provided a number of impossibility results. In some instances, self-stabilization can only be achieved if a system has an infinite number of states; elsewhere it is indicated that termination and self-stabilization are frequently mutually exclusive. (The attempt to equate distributed systems with nonterminating systems and, thus, claim that termination is not a significant issue is unrealistic.) The quote from L. Lamport near the beginning of the paper, “I regard it [E. W. Dijkstra's original work on self-stabilization] to be a milestone in work on fault tolerance,” needs to be balanced by a reasonable assessment of the limited practical application that self-stabilization has had and is likely to have.

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Published In

cover image ACM Computing Surveys
ACM Computing Surveys  Volume 25, Issue 1
March 1993
62 pages
ISSN:0360-0300
EISSN:1557-7341
DOI:10.1145/151254
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 March 1993
Published in CSUR Volume 25, Issue 1

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Author Tags

  1. convergence
  2. fault tolerance
  3. self-stabilization
  4. self-stabilizing systems
  5. stabilization
  6. transient errors
  7. transient failures

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