Skip to main content

Advertisement

SpringerLink
Log in

An Effective Channel Selection Solution for Reliable Scheduling in Industrial IoT Networks

  • Published:
Journal of Network and Systems Management Aims and scope Submit manuscript

Abstract

The IEEE 802.15.4 Time Slotted Channel Hopping (TSCH) communication mode is a key standard in the Industrial Internet of Things (IIoT). To schedule communications, TSCH uses deterministic transmissions to deal with latency requirements and channel hopping to cope with interference in IIoT environments. Nonetheless, this latter might not be sufficient to ensure reliable delivery of critical data since industrial networks are prone to severe external interference, which impacts the quality of wireless channels. In this paper, we propose an effective local Channel Selection approach for Reliable communication Scheduling in TSCH networks, dubbed CSRS. CSRS leans on effective assessment metrics to estimate the quality of available communication channels and stateless local exchange of bad-channels blacklists. CSRS is schedule-independent; hence it can be combined with any TSCH schedule, including the standardized Minimal Scheduling Function (MSF), to reduce the negative impact of bad channels. CSRS integration with MSF is implemented in Contiki and validated through extensive realistic trace-based simulations and public testbed experiments. Obtained results demonstrate the efficiency of our proposal in terms of reliability, latency, and energy consumption when compared with state-of-the-art solutions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

Notes

  1. https://indriya.comp.nus.edu.sg/.

  2. https://www.github.com/mohamadimed/dataset.

  3. https://www.IoT-Lab.github.io/docs/boards/IoT-Lab-m3/.

References

  1. IEEE: IEEE standard for low-rate wireless networks. IEEE Std 802.15.4-2015, pp. 1–709 (2016)

  2. Stanislowski, D., Vilajosana, X., Wang, Q., Watteyne, T., Pister, K.S.: Adaptive synchronization in IEEE802.15.4 e networks. IEEE TII 10(1), 795–802 (2014)

    Google Scholar 

  3. Papadopoulos, G.Z., Mavromatis, A., Fafoutis, X., Montavont, N., Piechocki, R., Tryfonas, T., Oikonomou, G.: Guard time optimisation and adaptation for energy efficient multi-hop TSCH networks. In: 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), pp. 301–306. IEEE (2016)

  4. I. ISA: 100.11 a-2009: Wireless Systems for Industrial Automation: Process Control and Related Applications. International Society of Automation, Research Triangle Park, NC (2009)

    Google Scholar 

  5. S. WirelessHART: 75: Tdma data-link layer. HART Commun. Found. Std. Rev. 1(1) (2008)

  6. Kotsiou, V., Papadopoulos, G. Z., Chatzimisios, P., Tholeyre, F.: Is local blacklisting relevant in slow channel hopping low-power wireless networks?. In: 2017 IEEE International Conference on Communications (ICC), pp. 1–6. IEEE (2017)

  7. Elsts, A., Fafoutis, X., Piechocki, R., Craddock, I.: Adaptive channel selection in IEEE 802.15. 4 TSCH networks. In: 2017 Global Internet of Things Summit (GIoTS), pp. 1–6. IEEE (2017)

  8. Zorbas, D., Papadopoulos, G. Z., Douligeris, C.: Local or global radio channel blacklisting for IEEE 802.15. 4-TSCH networks?. In: 2018 IEEE International Conference on Communications (ICC), pp. 1–6. IEEE (2018)

  9. Gomes, P.H., Watteyne, T., Krishnamachari, B.: Mabo-TSCH: Multihop and blacklist-based optimized time synchronized channel hopping. Trans. Emerg. Telecommun. Technol. 29(7), e3223 (2018)

    Article  Google Scholar 

  10. Kotsiou, V., Papadopoulos, G.Z., Zorbas, D., Chatzimisios, P., Theoleyre, F.: Blacklisting-based channel hopping approaches in low-power and lossy networks. IEEE Commun. Mag. 57(2), 48–53 (2019)

    Article  Google Scholar 

  11. Du, P., Roussos, G.: Adaptive time slotted channel hopping for wireless sensor networks. In 2012 4th Computer Science and Electronic Engineering Conference (CEEC), pp. 29–34. IEEE (2012)

  12. Li, P., Vermeulen, T., Liy, H., Pollin, S.: An adaptive channel selection scheme for reliable TSCH-based communication. In: 2015 International Symposium on Wireless Communication Systems (ISWCS), pp. 511–515. IEEE (2015)

  13. Kotsiou, V., Papadopoulos, G. Z., Chatzimisios, P., Theoleyre, F.: “Label: Link-based adaptive blacklisting technique for 6TiSCH wireless industrial networks,” in Proceedings of the 20th ACM International Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems, pp. 25–33, (2017)

  14. Zorbas, D., Kotsiou, V., Theoleyre, F., Papadopoulos, G. Z., Douligeris, C.: Lost: localized blacklisting aware scheduling algorithm for IEEE 802.15. 4-TSCH networks. In: 2018 Wireless Days (WD), pp. 110–115. IEEE (2018)

  15. Queiroz, D.V., Gomes, R.D., Benavente-Peces, C., Fonseca, I.E., Alencar, M.S.: Evaluation of channels blacklists in TSCH networks with star and tree topologies. In: Proceedings of the 14th ACM International Symposium on QoS and Security for Wireless and Mobile Networks, pp. 116–123 (2018)

  16. Gunatilaka, D., Sha, M., Lu, C.: Impacts of channel selection on industrial wireless sensor-actuator networks. In IEEE INFOCOM 2017-IEEE Conference on Computer Communications, pp. 1–9. IEEE (2017)

  17. Brandt, A., Hui, J., Kelsey, R., Levis, P., Pister, K., Struik, R., Vasseur, J., Alexander, R.: RPL: IPV6 routing protocol for low-power and lossy networks. In: RFC 6550 (2012)

  18. De Guglielmo, D., Brienza, S., Anastasi, G.: IEEE 802.15.4e: a survey. Comput. Commun. 88, 1–24 (2016)

    Article  Google Scholar 

  19. Hithnawi, A., Shafagh, H., Duquennoy, S.: Understanding the impact of cross technology interference on IEEE 802.15. 4. In Proceedings of the 9th ACM International Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization, pp. 49–56 (2014)

  20. Tytgat, L., Yaron, O., Pollin, S., Moerman, I., Demeester, P.: Analysis and experimental verification of frequency-based interference avoidance mechanisms in IEEE 802.15. 4. IEEE/ACM Trans. Netw. 23(2), 369–382 (2014)

    Article  Google Scholar 

  21. Papadopoulos, G.Z., Gallais, A., Schreiner, G., Noël, T.: Importance of repeatable setups for reproducible experimental results in IoT. In: Proceedings of the 13th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks, pp. 51–59 (2016)

  22. Papadopoulos, G.Z., Gallais, A., Schreiner, G., Jou, E., Noel, T.: Thorough iot testbed characterization: From proof-of-concept to repeatable experimentations. Comput. Netw. 119, 86–101 (2017)

    Article  Google Scholar 

  23. Watteyne, T., Mehta, A., Pister, K.: Reliability through frequency diversity: why channel hopping makes sense. In: Proceedings of the 6th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks, pp. 116–123 (2009)

  24. Baccour, N., Koubâa, A., Mottola, L., Zúñiga, M.A., Youssef, H., Boano, C.A., Alves, M.: Radio link quality estimation in wireless sensor networks: a survey. ACM Trans. Sensor Netw (TOSN) 8(4), 1–33 (2012)

    Article  Google Scholar 

  25. Sindjoung, M.L.F., Minet, P.: Wireless link quality prediction in iot networks. In: 2019 8th International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN), pp. 1–6. IEEE (2019)

  26. Farahmandand, M., Nabi, M.: Channel quality prediction for TSCH blacklisting in highly dynamic networks: a self-supervised deep learning approach. IEEE Sens. J. 21(18), 21059–21068 (2021)

    Article  Google Scholar 

  27. Yoo, D., Chung, S., Park, J.: Analysis and evaluation of channel-hopping-based mac in industrial iot environment. J. Comput. Sci. Eng. 15(4), 160–174 (2021)

    Article  Google Scholar 

  28. Chetot, L., Egan, M., Gorce, J.-M.: Joint identification and channel estimation for fault detection in industrial iot with correlated sensors. IEEE Access 9, 116692–116701 (2021)

    Article  Google Scholar 

  29. Wang, H., Xu, L., Yan, Z., Gulliver, T.A.: Low-complexity mimo-fbmc sparse channel parameter estimation for industrial big data communications. IEEE Trans. Industr. Inf. 17(5), 3422–3430 (2020)

    Article  Google Scholar 

  30. Valdovinos, I.A., Millán, P.E.F., Pérez-Díaz, J.A., Vargas-Rosales, C.: Distributed channel ranking scheduling function for dense industrial 6TiSCH networks. Sensors 21(5), 1593 (2021)

  31. Chang, T., Vučinić, M., Vilajosana, X., Duquennoy, S., Dujovne, D.: “6TiSCH Minimal Scheduling Function (MSF),” Internet-Draft draft-IETF-6TiSCH-MSF-18, Internet Engineering Task Force, (Sept. 2020). Work in Progress

  32. Bormann, C., Ersue, M., Keranen, A.: Terminology for constrained-node networks. Internet Engineering Task Force (IETF): Fremont, pp. 2070–1721 (2014)

  33. Gnawali, O., Fonseca, R., Jamieson, K., Kazandjieva, M., Moss, D., Levis, P.: CTP: an efficient, robust, and reliable collection tree protocol for wireless sensor networks. ACM Trans. Sensor Netw (TOSN) 10(1), 1–49 (2013)

    Article  Google Scholar 

  34. Boano, C.A., Zúniga, M.A., Voigt, T., Willig, A., Römer, K.: The triangle metric: fast link quality estimation for mobile wireless sensor networks. In: 2010 Proceedings of 19th International Conference on Computer Communications and Networks, pp. 1–7. IEEE (2010)

  35. Strübe, M., Böhm, S., Kapitza, R., Dressler, F.: Realsim: real-time mapping of real world sensor deployments into simulation scenarios. In: Proceedings of the 6th ACM International Workshop on Wireless Network Testbeds, Experimental Evaluation and Characterization, pp. 95–96 (2011)

  36. Tanaka, Y., Brun-Laguna, K., Watteyne, T.: Trace-based simulation for 6TiSCH. Internet Technol. Lett. (2020)

  37. Adjih, C., Baccelli, E., Fleury, E., Harter, G., Mitton, N., Noel, T., Pissard-Gibollet, R., Saint-Marcel, F., Schreiner, G., Vandaele, J., et al.: Fit IoT-Lab: a large scale open experimental iot testbed. In: 2015 IEEE 2nd World Forum on Internet of Things, pp. 459–464. IEEE (2015)

Download references

Author information

Authors and Affiliations

  1. Distributed & Complex Systems Laboratory, Ecole Militaire Polytechnique, Algiers, Algeria

    Mohamed Mohamadi, Badis Djamaa, Mustapha Reda Senouci, Yacine Grine & Riad Laribi

Authors
  1. Mohamed Mohamadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Badis Djamaa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mustapha Reda Senouci
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yacine Grine
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Riad Laribi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohamed Mohamadi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mohamadi, M., Djamaa, B., Senouci, M.R. et al. An Effective Channel Selection Solution for Reliable Scheduling in Industrial IoT Networks. J Netw Syst Manage 30, 59 (2022). https://doi.org/10.1007/s10922-022-09679-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10922-022-09679-z

Keywords

Search

Navigation