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Self-Organization for Fault-Tolerance

  • Elena Dubrova
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5343)

Abstract

In the last decade, there has been a considerable increase of interest in fault-tolerant computing due to dependability problems related to process scaling, embedded systems, and ubiquitous computing. In this paper, we present an approach to fault-tolerance inspired by gene regulatory networks of living cells. Living cells are capable of maintaining their functionality under a variety of genetic changes and external perturbations. They have natural self-healing, self-maintaining, self-replicating, and self-assembling mechanisms. The fault-tolerance of living cells is due to the ability of their gene regulatory network to self-organize and produce a stable attractors’ landscape. We introduce a computational scheme which exploits the intrinsic stability of attractors to achieve fault-tolerant computation. We also test fault-tolerance of the presented scheme on the example of a gene regulatory network model of Arabidopsis thaliana and show that it can tolerate 68% single-point mutations in the outputs of the defining tables of gene functions.

Keywords

Boolean Function Gene Regulatory Network Ubiquitous Computing Boolean Network Soft Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Elena Dubrova
    • 1
  1. 1.Department of Electronics, Computers, and Software, Royal Institute of TechnologyKistaSweden

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