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Enhancing Software Reliability Against Soft Error Using Critical Data Model

  • Li Wei
  • Mingwei Xu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 747)

Abstract

In modern life, software plays an increasingly important role and ensuring the reliability of software is of particular importance. In space, a Single Event Upset occurs because of the strong radiation effects of cosmic rays, which can lead to errors in software. In order to guarantee the reliability of software, many software-based fault tolerance methods have been proposed. The majority of them are based on data redundancy, which duplicates all data to prevent data corruption during the software execution. But this fault tolerant approach will make the data redundant and increase memory overhead and time overhead. Duplicating critical variables only can significantly reduce the memory and performance overheads, while still guaranteeing very high reliable results in terms of fault-tolerance improvement. In this paper, we propose an analysis model, named CDM (Critical Data Model), which can compute the critical of variables in the programs and achieve the purpose of reducing redundancy for the reliable program. According to the experimental results, the model proposed in this paper can enhance the reliability of the software, reduce the time and memory cost, and improve the efficiency of the reliable program.

Keywords

Reliability Redundancy Critical data Fault tolerance 

References

  1. 1.
    Ziegler, J.F., et al.: IBM experiments in soft fails in computer electronics (1978–1994). IBM J. Res. Dev. 40(1), 318 (1996)Google Scholar
  2. 2.
    Clerk Maxwell, J.: A Treatise on Electricity and Magnetism, vol. 2, 3rd edn, pp. 68–73. Clarendon, Oxford (1892)Google Scholar
  3. 3.
    Baumann, R.C.: Soft errors in advanced semiconductor devices-part I: the three radiation sources. IEEE Trans. Device Mater. Reliab. 1(1), 17–22 (2001)CrossRefGoogle Scholar
  4. 4.
    Shirvani, P.P., Oh, N., McCluskey, E.J., Wood, D.L., Lovellette, M.N., Wood, K.S.: Software-implemented hardware fault tolerance experiments: COTS in space. In: International Conference on Dependable Systems and Networks (FTCS-30 and DCCA-8), New York, NY, pp. B56–B57. Elissa (2000). Title of paper if known, unpublishedGoogle Scholar
  5. 5.
    Shirvani, P.P., Saxena, N.R., McCluskey, E.J.: Software-implemented EDAC protection against SEUs. IEEE Trans. Reliab. 49(3), 273–284 (2000)CrossRefGoogle Scholar
  6. 6.
    Benso, A., Chiusano, S., Prinetto, P., Tagliaferri, L.: C/C++ source-to-source compiler for dependable applications. In: International Conference on Dependable Systems and Networks, (FTCS-30 and DCCA-8), New York, NY, pp. 71–78 (2000)Google Scholar
  7. 7.
    Silva, J.G., Carreira, J., Maderia, H., Costa, D., Moreira, F.: Experimental assessment of parallel systems. In: Proceedings of FTCS-26, Sendaj (J), pp. 415–424 (1996)Google Scholar
  8. 8.
    Zenha Rela, M., Maderia, H., Silva, J.G.: Experimental evaluation of the fail-silent behavior in programs with consistency checks. In: Proceedings of FTCS-26, Sendaj (J), pp. 394–403 (1996)Google Scholar
  9. 9.
    Hiller, M.: Executable assertions for detecting data errors in embedded control systems. In: Proceedings of International Conference on Dependable Systems and Networks, p. 24 (2000)Google Scholar
  10. 10.
    Oh, N., Shirvani, P.P., McCluskey, E.J.: Control-flow checking by software signatures. IEEE Trans. Reliab. 51, 111–122 (2002)CrossRefGoogle Scholar
  11. 11.
    Li, A., Hong, B.: Software implemented transient fault detection in space computer. Aerosp. Sci. Technol. 11(2–3), 245–252 (2007)CrossRefGoogle Scholar
  12. 12.
    Reis, G.A., Chang, J., Vachharajani, N., et al.: SWIFT: software implemented fault tolerance. In: Proceedings of International Symposium Code Generation and Optimization (2005)Google Scholar
  13. 13.
    Xu, J., Shen, R., Tan, Q.: PRASE: an approach for program reliability analysis with soft errors. In: Proceedings of Pacific Rim International Symposium on Dependable Computing (2008, to appear)Google Scholar
  14. 14.
    Keshtgar, A., Araste, B.: Enhancing software reliablity against soft-error using minimum redundancy on Criticalata. Int. J. Comput. Netw. Inf. Secur. 9(5), 21 (2017)Google Scholar
  15. 15.
    Benso, A., Di Carlo, S., Di Natale, G., Prinetto, P., Tagliaferri, L.: Data criticality estimation in software applications. In: International Test Conference (2003)Google Scholar
  16. 16.
    Xu, J., Shen, R., Tan, Q.: A novel optimum data duplication approach for soft error detection. In: Proceedings of Pacific Rim International Symposium on Dependable Computing (2008, to appear)Google Scholar
  17. 17.
    Burger, D., Austin, T.M., Bennett, S.: Evaluating future microprocessors: the SimpleScalar tool set. UW Madison CS Technical report #1342 (1997)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Beijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Tsinghua UniversityBeijingChina

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