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Probabilistic model for nanocell reliability evaluation in presence of transient errors

Probabilistic model for nanocell reliability evaluation in presence of transient errors

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In this study, the authors propose a novel extended continuous time birth–death model for reliability analysis of a nanocell device. A nanocell consists of conducting nanoparticles connected via randomly placed self-assembled monolayer of molecules. These molecules behave as a negative differential resistor. The mathematical expression for expected nanocell lifetime and its availability, in presence of transient errors is computed. On the basis of the model, an algorithm is developed and implemented in MATLAB, PERL and HSPICE, to automatically generate the proposed model representation for a given nanocell. It is used to estimate the success_ratio as well as the nanocell reliability, while considering the uncertainties induced by transient errors. The theoretical results for reliability are validated by simulating HSPICE model of nanocell in presence of varying defect rates. It is observed that the device reliability increases with increase in the number of nanoparticles and molecules. A lower and upper bounds for nanocell reliability are calculated in theory which is validated in simulations.

References

    1. 1)
      • 1. ‘International Technology Roadmap for semiconductors’, http://www.itrs.net/links/2013ITRS/Home2013.htm, accessed March 2014.
        .
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
      • R. Kumawat .
        10. Kumawat, R., et al: ‘Probabilistic modeling and analysis of molecular memory’, ACM J. Emerging Technol. Comput. Syst. (JETC), 2014, 11, (1), pp. 6:16:16.
        . ACM J. Emerging Technol. Comput. Syst. (JETC) , 1 , 6:1 - 6:16
    11. 11)
      • S.M. Ross . (2008)
        11. Ross, S.M.: ‘Introduction to probability models’ (Academic Press, 2008, 9th edn.).
        .
    12. 12)
      • K.S. Trivedi . (2001)
        12. Trivedi, K.S.: ‘Probability and statistics with reliability, queuing and computer science applications’ (Prentice-Hall, 2001, 12th edn.).
        .
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cdt.2014.0124
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