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ReFIT: Reliability Challenges and Failure Rate Mitigation Techniques for IoT Systems

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Innovations for Community Services (I4CS 2020)

Abstract

As the number of Internet-of-Things (IoT) devices increases, ensuring the reliability of the IoT system has become a challenging job. Apart from the emerging security issues, reliable IoT system design depends on many other factors. In this work, for the first time, we have shown all the reliability challenges of an IoT system in details, which may arise due to the random faults. We have also proposed a mathematical formulation of the lifetime of the IoT system. Subsequently, we devise an algorithm which uses Lévy distribution-based duty cycling approach to improve the IoT network lifetime. We have validated our proposed method using Cooja simulation software. The simulation results show 1.5 \(\times \) increment in network lifetime for the IoT system using our proposed method than the state-of-the-artwork. We have also demonstrated that our proposed method does not degrade the network performance.

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References

  1. Wollschlaeger, M., Sauter, T., Jasperneite, J.: The future of industrial communication: automation networks in the era of the internet of things and industry 4.0. IEEE Ind. Electron. Mag. 11(1), 17–27 (2017)

    Article  Google Scholar 

  2. Lucas-Estañ, M.C., Raptis, T.P., Sepulcre, M., Passarella, A., Regueiro, C., Lazaro, O.: A software defined hierarchical communication and data management architecture for industry 4.0. In: 2018 14th Annual Conference on Wireless On-Demand Network Systems and Services (WONS), pp. 37–44. IEEE (2018)

    Google Scholar 

  3. Shao, L., et al.: Compact modeling of thin film transistors for flexible hybrid IoT design. IEEE Des. Test 36, 6–14 (2019)

    Article  Google Scholar 

  4. Ahmad, M.: Reliability models for the Internet of Things: a paradigm shift. In: 2014 IEEE International Symposium on Software Reliability Engineering Workshops, pp. 52–59. IEEE (2014)

    Google Scholar 

  5. Rosing, T.S.: Reliability and maintainability of IoT systems (2018)

    Google Scholar 

  6. Xing, L., Zhao, G., Wang, Y., Mandava, L.: Competing failure analysis in IoT systems with cascading functional dependence. In: 2018 Annual Reliability and Maintainability Symposium (RAMS), pp. 1–6. IEEE (2018)

    Google Scholar 

  7. Thomas, M.O., Rad, B.B.: Reliability evaluation metrics for Internet of Things, car tracking system: a review. Int. J. Inf. Technol. Comput. Sci. (IJITCS) 9(2), 1–10 (2017)

    Google Scholar 

  8. Raptis, T.P., Passarella, A., Conti, M.: Maximizing industrial IoT network lifetime under latency constraints through edge data distribution. In: 2018 IEEE Industrial Cyber-Physical Systems (ICPS), pp. 708–713. IEEE (2018)

    Google Scholar 

  9. Valls, V., Iosifidis, G., Salonidis, T.: Maximum lifetime analytics in IoT networks. In: IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pp. 1369–1377. IEEE (2019)

    Google Scholar 

  10. Morin, E., Maman, M., Guizzetti, R., Duda, A.: Comparison of the device lifetime in wireless networks for the Internet of Things. IEEE Access 5, 7097–7114 (2017)

    Article  Google Scholar 

  11. Airehrour, D., Gutiérrez, J., Ray, S.K.: Greening and optimizing energy consumption of sensor nodes in the Internet of Things through energy harvesting: challenges and approaches (2016)

    Google Scholar 

  12. Fafoutis, X., Elsts, A., Vafeas, A., Oikonomou, G., Piechocki, R.J.: On predicting the battery lifetime of IoT devices: experiences from the sphere deployments. In: RealWSN@ SenSys, pp. 7–12 (2018)

    Google Scholar 

  13. Cao, K., Xu, G., Zhou, J., Wei, T., Chen, M., Hu, S.: Qos-adaptive approximate real-time computation for mobility-aware IoT lifetime optimization. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 38, 1799–1810 (2018)

    Article  Google Scholar 

  14. Li, Q., Gochhayat, S.P., Conti, M., Liu, F.: EnergIoT: a solution to improve network lifetime of IoT devices. Pervasive Mob. Comput. 42, 124–133 (2017)

    Article  Google Scholar 

  15. Weibull, W., et al.: A statistical distribution function of wide applicability. J. Appl. Mech. 18(3), 293–297 (1951)

    MATH  Google Scholar 

  16. Black, J.R.: Electromigration–a brief survey and some recent results. IEEE Trans. Electron Devices 16(4), 338–347 (1969)

    Article  Google Scholar 

  17. Laidler, K.J.: Chemical Kinetics, vol. 42. Harper & Row, New York (1987)

    Google Scholar 

  18. Guo, X., Verma, V., Gonzalez-Guerrero, P., Stan, M.R.: When “things” get older: exploring circuit aging in IoT applications. In: 2018 19th International Symposium on Quality Electronic Design (ISQED), pp. 296–301. IEEE (2018)

    Google Scholar 

  19. Dey, S., Dash, S., Nandi, S., Trivedi, G.: PGIREM: reliability-constrained IR drop minimization and electromigration assessment of VLSI power grid networks using cooperative coevolution. In: 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), pp. 40–45. IEEE (2018)

    Google Scholar 

  20. Dey, S., Nandi, S., Trivedi, G.: PGRDP: reliability, delay, and power-aware area minimization of large-scale VLSI power grid network using cooperative coevolution. In: Mandal, J.K., Sinha, D. (eds.) Intelligent Computing Paradigm: Recent Trends. SCI, vol. 784, pp. 69–84. Springer, Singapore (2020). https://doi.org/10.1007/978-981-13-7334-3_6

    Chapter  Google Scholar 

  21. Dey, S., Dash, S., Nandi, S., Trivedi, G.: Markov chain model using lévy flight for VLSI power grid analysis. In: 2017 30th International Conference on VLSI Design and 2017 16th International Conference on Embedded Systems (VLSID), pp. 107–112. IEEE (2017)

    Google Scholar 

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Acknowledgements

The work is done as a part of the project title “Information Security Research and Development Centre (ISRDC)” under Information Security Education and Awareness (ISEA) Project (Phase-II) at IIT Guwahati. The authors would like to thank Ministry of Electronics and Information Technology (MeitY) and IIT Guwahati for the support.

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Correspondence to Sukanta Dey .

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Dey, S., Bhale, P., Nandi, S. (2020). ReFIT: Reliability Challenges and Failure Rate Mitigation Techniques for IoT Systems. In: Rautaray, S., Eichler, G., Erfurth, C., Fahrnberger, G. (eds) Innovations for Community Services. I4CS 2020. Communications in Computer and Information Science, vol 1139. Springer, Cham. https://doi.org/10.1007/978-3-030-37484-6_7

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  • DOI: https://doi.org/10.1007/978-3-030-37484-6_7

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  • Online ISBN: 978-3-030-37484-6

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