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Attaining Fault Tolerance through Self-adaption: The Strengths and Weaknesses of Evolvable Hardware Approaches

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Abstract

Self-adaptive systems autonomously change their behavior to compensate for faults or to improve their performance. Evolvable hardware, which combines evolutionary algorithms with reconfigurable hardware, is often proposed as the cornerstone for systems that use self-adaption for fault recovery. Although evolvable hardware was first introduced over 15 years ago, there are few, if any, fault tolerant self-adaptive systems in operation today. One primary reason why these unfortunate circumstances have arisen is many designers—and not limited to just designers from the computational intelligence community—do not really understand how to build a basic fault tolerant system, let alone a self-adaptive fault tolerant system. This chapter describes how fault tolerant systems are built. A model for designing fault tolerant systems that rely on evolvable hardware for fault recovery is presented.

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References

  1. Greenwood, G., Tyrrell, A.: Introduction to Evolvable Hardware: A Practical Guide for Designing Self-Adaptive Systems. Wiley-IEEE Press (2006)

    Google Scholar 

  2. Burns, A., Wellings, A.: Real-Time Systems and Programming Languages, 3rd edn. Addison-Wesley-Longmain, Reading (2001)

    Google Scholar 

  3. Linden, D.: Optimizing signal strength in-situ using an evolvable antenna system. In: Proceedings of the 2002 NASA/DOD Conf. On Evolvable Hardware, pp. 147–151 (2002)

    Google Scholar 

  4. Avizienis, A.: Towards systematic design of fault tolerant systems. IEEE Computer 30(4), 51–58 (2004)

    Google Scholar 

  5. Belk, C., Robinson, J., Alexander, M., Cooke, W., Pavelitz, S.: Meteoroids and orbital debris: effects on spacecraft. In: NASA Reference Bulletin, p. 1408 (1997)

    Google Scholar 

  6. Keymeulen, D., Zebulum, R., Jin, Y., Stoica, A.: Fault tolerant evolvable hardware using field-programmable transistor arrays. IEEE Transactions on Reliability 49(3), 305–316 (2000)

    Article  Google Scholar 

  7. Mange, D., Sipper, M., Stauffer, A., Tempesti, G.: Embryonics: a new methodology for designing field programmable gate arrays with self-repair and self-replicating properties. Proceedings of the IEEE 88(4), 416–541 (2000)

    Article  Google Scholar 

  8. Sekanina, L., Drabek, V.: Relation between fault tolerance and reconfiguration in cellular systems. In: Proceedings of the 6th IEEE online testing workshop, pp. 25–30 (2000)

    Google Scholar 

  9. Greenwood, G., Hunter, D., Ramsden, E.: Fault recovery in linear systems via intrinsic evolution. In: Proc. 2004 NASA/DOD Conf. on Evol. Hdwe, pp. 115–122 (2004)

    Google Scholar 

  10. Greenwood, G.: On the practicality of using intrinsic reconfiguration for fault recovery. IEEE Transactions on Evolutionary Computation 9(4), 398–405 (2005)

    Article  Google Scholar 

  11. NGST yardstick mission, NGST Monograph No. 1, Next Generation Space Telescope Project Study Office, Goddard Space Flight Center (1999)

    Google Scholar 

  12. Hughes, H., Benedetto, J.: Radiation effects and hardening of MOS technology: devices and circuits. IEEE Transactions on Nuclear Science 50(3), 500–521 (2003)

    Article  Google Scholar 

  13. Wismer, M.: Steady-state operation of a high-voltage multiresonant converter in a high-temperature environment. IEEE Transactions on Power Electronics 18(3), 740–774 (2003)

    Article  Google Scholar 

  14. Dunn, W.: Practical Design of Safety-Critical Computer Systems. Reliability Press (2002)

    Google Scholar 

  15. NASA-STD-8719.7, Facility system safety guidebook (January 1998)

    Google Scholar 

  16. Goddard, P.: Software FMEA techniques. In: Proc. 2000 Reliab. & Maintain. Symp., pp. 118–123 (2000)

    Google Scholar 

  17. Bowles, J., Wan, C.: Software failure modes and effects analysis for a small embedded control system. In: Proc. 2001 Reliab. & Maintain. Symp. pp. 1–6 (2001)

    Google Scholar 

  18. Craig, J.: A software reliability methodology using software sneak analysis: SW FMEA and the integrated system analysis approach. In: Proc. 2003 Reliab. & Maintain. Symp. pp. 12–18(2003)

    Google Scholar 

  19. Fadlovich, E.: Performing failure modes and effect analysis. Embedded Technology Magazine (January 2008)

    Google Scholar 

  20. Stamatis, D.: Failure Mode and Effect Analysis: FMEA from Theory to Execution. American Society for Quality (2003)

    Google Scholar 

  21. Didier Keymeulen, NASA JPL (private communication) (2007)

    Google Scholar 

  22. Vigraham, S., Gallagher, J.: A case for using minipop as the evolutionary engine in a CTRNN-EEH control device: an analysis of area requirements and search efficacy. In: Proc. 2005 NASA/DoD Conf. of Evol. Hdwe pp. 221–228 (2005)

    Google Scholar 

  23. Harik, G., Lobo, F., Goldberg, D.: The compact genetic algorithm. IEEE Trans. on Evol. Comput. 3(4), 287–297 (1999)

    Article  Google Scholar 

  24. Jorgensen, C., Greenwood, G., Arefi, P.: Practical considerations for implementing intrinsic fault recovery in embedded systems. In: Proc. Congress on Evol. Comput. (to appear, 2004)

    Google Scholar 

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Jacek M. Zurada Gary G. Yen Jun Wang

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Greenwood, G.W. (2008). Attaining Fault Tolerance through Self-adaption: The Strengths and Weaknesses of Evolvable Hardware Approaches. In: Zurada, J.M., Yen, G.G., Wang, J. (eds) Computational Intelligence: Research Frontiers. WCCI 2008. Lecture Notes in Computer Science, vol 5050. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68860-0_18

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  • DOI: https://doi.org/10.1007/978-3-540-68860-0_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68858-7

  • Online ISBN: 978-3-540-68860-0

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