Advertisement

Genetic Programming and Evolvable Machines

, Volume 11, Issue 1, pp 35–59 | Cite as

Automated synthesis of resilient and tamper-evident analog circuits without a single point of failure

  • Kyung-Joong Kim
  • Adrian Wong
  • Hod LipsonEmail author
Original Paper

Abstract

This study focuses on the use of genetic programming to automate the design of robust analog circuits. We define two complementary types of failure modes: partial short-circuit and partial disconnect, and demonstrated novel circuits that are resilient across a spectrum of fault levels. In particular, we focus on designs that are uniformly robust, and unlike designs based on redundancy, do not have any single point of failure. We also explore the complementary problem of designing tamper-proof circuits that are highly sensitive to any change or variation in their operating conditions. We find that the number of components remains similar both for robust and standard circuits, suggesting that the robustness does not necessarily come at significant increased circuit complexity. A number of fitness criteria, including surrogate models and co-evolution were used to accelerate the evolutionary process. A variety of circuit types were tested, and the practicality of the generated solutions was verified by physically constructing the circuits and testing their physical robustness.

Keywords

Analog circuit Robustness Evolutionary strategies Low-pass filter Hardware implementation Tamper-evident circuits 

Notes

Acknowledgments

This work was supported in part by US National Science Foundation (NSF) CAREER grant number DMI 0547376. Co-author K.-J.K. was supported by the Korea Research Foundation Grant (KRF-2007-357-D00220) funded by the Korean Government (MOEHRD) and Korea Health 21 R&D Project, Ministry for Health, Welfare and Family Affairs (A040163).

References

  1. 1.
    G.A. Hollinger, D.A. Gawaltney, Evolutionary design of fault-tolerant analog control for a piezoelectric pipe-crawling robot. In: Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation (2006), pp. 761–768Google Scholar
  2. 2.
    J. Hu, X. Zhong, E.D. Goodman, Open-ended robust design of analog filters using genetic programming. In: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation (2005), pp. 1619–1626Google Scholar
  3. 3.
    R.S. Zebulum, A. Stoica, D. Keymeulen, L. Sekanina, R. Ramesham, X. Guo, Evolvable hardware system at extreme low temperature. Lect. Notes Comput. Sci. 3637, 37–45 (2005)CrossRefGoogle Scholar
  4. 4.
    J. Torresen, A scalable approach to evolvable hardware. Genet. Program Evolvable Mach. 3(3), 259–282 (2002)zbMATHCrossRefGoogle Scholar
  5. 5.
    J.R. Koza, M.A. Keane, J. Yu, F.H. Bennett, W. Mydlowec, Automatic creation of human-competitive programs and controllers by means of genetic programming. Genet. Program Evolvable Mach. 1(1–2), 121–164 (2000)zbMATHCrossRefGoogle Scholar
  6. 6.
    A. Ciccazzo, P. Conca, G. Nicosia, G. Stracquadanio, An advanced clonal selection algorithm with Ad-Hoc network-based hypermutation operators for synthesis of topology and sizing of analog electrical circuits. Lect. Notes Comput. Sci. 5132, 60–70 (2008)CrossRefGoogle Scholar
  7. 7.
    R.S. Zebulum, M.A. Pacheco, M. Vellasco, H.T. Sinohara, Evolvable hardware: on the automatic synthesis of analog control systems. Proc. IEEE. Aerosp. Conference 5, 451–463 (2000)Google Scholar
  8. 8.
  9. 9.
    J.R. Koza, F.H. Bennett III, D. Andre, M.A. Keane, F. Dunlap, Automated synthesis of analog electrical circuits by means of genetic programming. IEEE. Trans. Evol. Comput. 1(2), 109–128 (1997)CrossRefGoogle Scholar
  10. 10.
    C. Goh, Y. Li, GA automated design and synthesis of analog circuits with practical constraints. In: Proceedings of the 2001 congress on evolutionary computation. 1, 170–177 (2001)Google Scholar
  11. 11.
    J.F. Miller, D. Job, V.K. Vassilev, Principles in the evolutionary design of digital circuits-Part I. Genet. Program Evolvable Mach. 1(1–2), 7–35 (2000)zbMATHCrossRefGoogle Scholar
  12. 12.
    S. Zhao, L. Jiao, Multi-objective evolutionary design and knowledge discovery of logic circuits based on an adaptive genetic algorithm. Genet. Program Evolvable Mach. 7(3), 195–210 (2006)CrossRefGoogle Scholar
  13. 13.
    J.R. Koza, M.A. Keane, M.J. Streeter, Routine automated synthesis of five patented analog circuits using genetic programming. Soft. Comput. 8, 318–324 (2004)Google Scholar
  14. 14.
    F. Wang, Y. Li, L. Li, K. Li, Automated analog circuit design using two-layer genetic programming. Appl. Math. Comput. 185, 1087–1097 (2007)zbMATHCrossRefGoogle Scholar
  15. 15.
    T. Sripramong, C. Toumazou, The invention of CMOS amplifiers using genetic programming and current-flow analysis. IEEE. Trans. Comput. Aided Des. Integr. Circuits Syst. 21(11), 1237–1252 (2002)CrossRefGoogle Scholar
  16. 16.
    D. Keymeulen, R.S. Zebulum, Y. Jin, A. Stoica, Fault-tolerant evolvable hardware using field-programmable transistor arrays. IIEEE. Trans. Reliability 49(3), 305–316 (2000)CrossRefGoogle Scholar
  17. 17.
    J.D. Lohn, S.P. Colombano, Automated analog circuit synthesis using a linear representation. In: Proceedings of the 2nd international conference on evolvable systems, pp. 125–133 (1998)Google Scholar
  18. 18.
    P. Layzell, A. Thompson, Understanding inherent qualities of evolved circuits: evolutionary history as a predictor of fault tolerance. Lect. Notes Comput. Sci. 1801, 133–144 (2000)CrossRefGoogle Scholar
  19. 19.
    M. Natsui, N. Homma, T. Aoki, T. Higuchi, Topology-oriented design of analog circuits based on evolutionary graph generation. Lect. Notes Comput. Sci. 3242, 342–351 (2004)Google Scholar
  20. 20.
    T.R. Dastidar, P.P. Chakrabarti, P. Ray, A synthesis system for analog circuits based on evolutionary search and topological reuse. IEEE. Trans. Evol. Comput 9(2), 211–224 (2005)CrossRefGoogle Scholar
  21. 21.
    S. Ando, H. Iba, Analog circuit design with a variable length chromosome. In: Proceedings of the 2000 congress on evolutionary computation, vol. 2, pp. 994–1001 (2000)Google Scholar
  22. 22.
    C. Mattiussi, D. Floreano, Analog genetic encoding for the evolution of circuits and networks. IEEE. Trans. Evol. Comput 11(5), 596–607 (2007)CrossRefGoogle Scholar
  23. 23.
    X. Xia, Y. Li, W. Ying, L. Chen, Automated design approach for analog circuit using genetic algorithm. Lect. Notes Comput. Sci. 4490, 1124–1130 (2007)CrossRefGoogle Scholar
  24. 24.
    J.B. Grimbleby, Hybrid genetic algorithms for analogue network synthesis. In: Proceedings of the 1999 congress on evolutionary computation, vol. 3, pp. 1781–1787 (1999)Google Scholar
  25. 25.
    D. Berenson, N. Estevez, H. Lipson, Hardware evolution of analog circuits for in-situ robotic fault-recovery. In: Proceedings of NASA/DOD conference on evolvable hardware, pp. 12–19 (2005)Google Scholar
  26. 26.
    Y. Sapargaliyev, T. Kalganova, Constrained and unconstrained evolution of “LCR” low-pass filters with oscillating length representation. In: Proceedings of IEEE congress on evolutionary computation, pp. 1529–1536 (2006)Google Scholar
  27. 27.
    T. Biondi, A. Ciccazzo, V. Cutello, S. D’Antona, G. Nicosia, S. Spinella, Multi-objective evolutionary algorithms and pattern search methods for circuit design problems. J. Univ. Comput. Sci. 12(4), 432–449 (2006)Google Scholar
  28. 28.
    G. Nicosia, S. Rinaudo, E. Sciacca, An evolutionary algorithm-based approach to robust analog circuit design using constrained multi-objective optimization. Knowl.-Based Syst. 21(3), 175–183 (2008)CrossRefGoogle Scholar
  29. 29.
    L. Zinchenko, H. Muhlenbein, V. Kureichik, T. Mahnig, A comparison of different circuit representations for evolutionary analog circuit design. Lect. Notes Comput. Sci. 2606, 13–23 (2003)CrossRefGoogle Scholar
  30. 30.
    M.D. Schmidt, H. Lipson, Coevolution of fitness predictors, IEEE Trans. Evol. Comput. 12(6), 736–749 (2008)CrossRefGoogle Scholar
  31. 31.
    J.B. Hagen, Radio-Frequency Electronics-Circuits and Applications (Cambridge University Press, Cambridge, 1996)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Mechanical and Aerospace EngineeringCornell UniversityIthacaUSA
  2. 2.Department of Computer EngineeringSejong UniversitySeoulRepublic of Korea
  3. 3.Electrical and Computer EngineeringCornell UniversityIthacaUSA
  4. 4.Sandia National LaboratoriesLivermoreUSA
  5. 5.Computing and Information ScienceCornell UniversityIthacaUSA

Personalised recommendations