Immune system and fault-tolerant computing

  • S. Xanthakis
  • S. Karapoulios
  • R. Pajot
  • A. Rozz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1063)


Immune system (IS) is capable of evolving, learning, recognising and eliminating foreign molecules which invade organisms. Fault tolerant approaches consist in detecting erroneous states of an algorithm and executing recovery procedures. They are generally implemented by adding formal properties to be satisfied by state variables during execution. However, defining fault-tolerant procedures can be error-prone and sometimes equivalent to a formal proof. Moreover, it is always very difficult to make a sound assumption about the typology and frequency of real. We propose an analogy between IS and fault tolerant computing. After a brief presentation of immune algorithms and especially lymphocyte simulation (B-cells, suppressor T-cells, etc.) using genetic operators, we present an immune model for detecting and recovering erroneous states during execution. Program states are examined by procedures playing the role of B-cells. Those properties have previously been learnt, automatically, during testing phase using mutation analysis techniques. When a program state has to be recovered, T-cells procedures are activated in order to recover erroneous states. In this way, each software algorithm may develop automatically its own immune system capable of evolving and stimulating specific responses to software failures. We finish by a brief discussion of the main possibilities of an immune approach to fault-tolerant computing.


Fault-Tolerant computing Immune System Genetic Algorithms Mutation Testing Error-recovery 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [AGRAWAL85]
    V. Agrawal V.: “Proc, Coll. on Fault Tolerance” Montreal, 1985.Google Scholar
  2. [BERSINI92]
    H. Bersini: “Immune Network & Adaptive Control” Paris, Décembre 1992.Google Scholar
  3. [BERTONI92]
    H. Bertoni & M. Dorigo: “Implicit Parallelism in Genetic Algorithms” Artificial Intelligence, 61, 2, 307–314.Google Scholar
  4. [DEMILLO80]
    R. A. DeMillo & al.:“Mutation Analysis as a Tool for Software Quality Assurance”, Proc. COMPSAC 80, (October 1980)Google Scholar
  5. [FARMER85]
    J. Doyne Farmer, N.H. Packard, A. S. Perelson: “The Immune System, Adaptation, and Machine Learning” in Evolution, Game and Learning, Proc. of 5th Annual Inter. conference, Los Alamos, (May 1985).Google Scholar
  6. [FARMER90]
    J. Doyne Farmer: “A Rosetta Stone for Connectionism” in Emergent Computation, Ed. S. Forrest, MIT, North-Holland (1990).Google Scholar
  7. [GOLDBERG 89]
    D.E. Goldberg: “Genetic Algorithms in Search, Optimization, and Machine Learning” Addison Wesley Publ. Company, (1989).Google Scholar
  8. [HILLIS90]
    W. D. Hillis: “Co-evolving parasites improve simulated evolution as an optimization procedure” in Emergent Computation, S. Forrest, MIT, North-Holland (1990).Google Scholar
  9. [HOLLAND73]
    J.H. Holland: “Schemata and intrinsically parallel adaptation”, Proce. of the NSF Workshop of Learning System Theory and its applications (pp 43–46), Univ. of Florida, (1973).Google Scholar
  10. [JERNE74]
    N. K. Jerne: “Towards a network theory of the Immune System”, Ann. Immunol. (Inst. Pasteur) 125 C (1974).Google Scholar
  11. [MAXION90]
    R. A. Maxion: “Toward diagnosis as an emergent behavior in a network ecosystem” in Emergent Computation, Ed. S. Forrest, MIT, North-Holland (1990).Google Scholar
    Z. Michalewicz: “Genetic Algorithms+Data Structures=Evolution Programs”, Springer Verlag, (1992).Google Scholar
  13. [MICHALSKI83]
    “Machine Learning — An Artificial Intelligence Approach”, ed. Michalski R. S. & al, Tioga Publishing Company, Palo Alto, CA, 1983.Google Scholar
  14. [MILI90]
    A. Mili: “Program Fault Tolerance. A structured programming approach”, Prentice Hall International (1990).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • S. Xanthakis
    • 1
  • S. Karapoulios
    • 1
  • R. Pajot
    • 1
  • A. Rozz
    • 2
  1. 1.LOGICOMLabege CedexFrance
  2. 2.VERILOGToulouseFrance

Personalised recommendations