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A Jamming-resilient opportunistic QoS-constrained multi-channel routing for green IoT networking

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Abstract

Employing the cognitive radio (CR) technology in IoT networks, referred to as CR-IoT, is considered a promising solution for providing the spectrum opportunities needed for massive IoT deployments. Jamming attacks can significantly increase energy consumption in CR-IoT networks by increasing the number of dropped packets, and hence the number of needed packet re-transmissions. Designing jamming-aware communication protocols that attempt to reduce the number of dropped packets in the network results in green CR-IoT networking. In this paper, we develop an energy-efficient, QoS-constrained, and jamming-aware routing scheme for green CR-IoT networks. The proposed routing protocol employs a probabilistic channel assignment scheme that provides reliable data delivery under both dynamic and static jamming attacks. The underlying channel assignment problem is mathematically formulated as a binary linear programming optimization problem with the goal of maximizing the end-to-end throughput using the least number of frequency channels while meeting a set of QoS requirements. This optimization is known to be NP-hard. The sequential fixing technique is adopted to provide a sub-optimal solution in polynomial time. Simulation results indicate that the proposed routing scheme provides a remarkable performance improvement over existing schemes.

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References

  1. Adem, N., & Hamdaoui, B. (2017). Jamming resiliency and mobility management in cognitive-communication networks. In Proceeding IEEE International Conference on Communications (ICC), pp. 1-6.

  2. Ali, A., & Hamouda, W. (2017). Advances on spectrum sensing for cognitive radio networks: Theory and applications. IEEE Communications Surveys and Tutorials, 19(2), 1277–1304. https://doi.org/10.1109/COMST.2016.2631080

    Article  Google Scholar 

  3. Ben Halima, N., & Boujemâa, H. (2021). Energy harvesting with adaptive transmit power for multi-antenna multihop cognitive radio networks. Sustainable Computing: Informatics and Systems, 31, 100567.

    Google Scholar 

  4. Bhunia, S., Sengupta, S., & Vazquez-Abad, F. (2014) Cr-honeynet: A learning &and decoy based sustenance mechanism against jamming attack in CRN. In IEEE Military Communications Conference (MILCOM), pp. 1173– 1180.

  5. Chen, Y., Li, Y., Xu, D., & Xiao, L. (2018). Dan-based power control for iot transmission against jamming. In IEEE 87th Vehicular Technology Conference (VTC Spring), pp. 1–5.

  6. Darabkh, K. A., & Amro, O. M. (2020). New routing protocol for half-duplex cognitive radio ad-hoc networks over IoT environment. In: 2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), pp. 1–5.

  7. D’Oro, S., Ekici, E., & Palazzo, S. (2017). Optimal power allocation and scheduling under jamming attacks. IEEE/ACM Transactions on Networking, 25(3), 1310–1323.

    Article  Google Scholar 

  8. Gallager, R. (2013). Stochastic Processes: Theory for Applications. Cambridge: Cambridge University Press.

    Book  MATH  Google Scholar 

  9. Halloush, R. D., Salaimeh, R., & Al-Dalqamoni, R. (2022). Availability-aware channel allocation for multi-cell cognitive radio 5G networks. In IEEE Transactions on Vehicular Technology (vol. 71, no. 4, pp. 3931–3947). https://doi.org/10.1109/TVT.2022.3148063

  10. Hou, L., Wong, A. K. Y., Yeung, A. K. H., & Choy, S. S. O. (2016). Using trust management to defend against routing disruption attacks for cognitive radio networks. In: IEEE International Conference on Consumer Electronics-China, pp. 1-4.

  11. Hu, N., Tian, Z., Du, X., & Guizani, M. (2021). An energy-efficient in-network computing paradigm for 6G. IEEE Transactions on Green Communications and Networking, 5(4), 1722–1733. https://doi.org/10.1109/TGCN.2021.3099804

    Article  Google Scholar 

  12. Khan, A. A., Rehmani, M. H., & Rachedi, A. (2017). Cognitive radio based Internet of Things: Applications architectures spectrum related functionalities and future research directions. IEEE Wireless Communications, 24(3), 17–25.

    Article  Google Scholar 

  13. Kim, Y. S., DeBruhl, B., & Tague, P. (2014). JADE: Jamming-averse routing on cognitive radio mesh networks. In 2014 IEEE Conference on Communications and Network Security, pp. 21–28.

  14. Kim, H., & Shin, K. G. (2008). Efficient discovery of spectrum opportunities with mac-layer sensing in cognitive radio networks. IEEE Transactions on Mobile Computing, 7(5), 533–545.

    Article  Google Scholar 

  15. Kumar Jain, V., Mazumdar, A., Faruki, P., & Govil, M. (2022). Congestion control in Internet of Things: Classification, challenges, and future directions. Sustainable Computing: Informatics and Systems, 35, 100678.

    Google Scholar 

  16. Patel, K. K., Patel, S. M., Scholar, P. G., & Carlos, S. (2016). Internet of Things-IoT: Definition, characteristics, architecture, enabling technologies, application & future challenges. International Journal of Engineering Science and Computing, 6(5), 6122–6131.

    Google Scholar 

  17. Perera, C., Barhamgi, M., & Vecchio, M. (2021). Envisioning Tool support for designing privacy-aware internet of thing applications. IEEE Internet of Things Magazine, 4(1), 78–83.

    Article  Google Scholar 

  18. Ping, S., Aijaz, A., Holland, O., & Aghvami, A. H. (2014). Energy and interference aware cooperative routing in cognitive radio ad-hoc networks. In 2014 IEEE Wireless Communications and Networking Conference (WCNC), pp. 87–92.

  19. Ramirez, I.U., & Barboza Tello, N.A. (2014). A survey of challenges in green wireless communications research. In 2014 International Conference on Mechatronics, Electronics and Automotive Engineering, pp. 197-200, https://doi.org/10.1109/ICMEAE.2014.29.

  20. Rappaport, T. (2001). Wireless Communications: Principles and Practice (2nd ed.). Upper Saddle River: Prentice Hall PTR.

    MATH  Google Scholar 

  21. Derbas, R. (August 2018). Routing Algorithm for Mutli-hop IoT Cognitive Radio Networks under Proactive Jamming Attacks, [Master Thesis, Yarmouk University, Irbid, Jordan]. Arabic Digital Library-Yarmouk University Publishing.

  22. Sheikholeslami, A., Ghaderi, M., Pishro-Nik, H., & Goeckel, D. (2014). Jamming-aware minimum energy routing in wireless networks. In 2014 IEEE International Conference on Communications (ICC), pp. 2313–2318. https://doi.org/10.1109/ICC.2014.6883668

  23. Slimeni, F., Scheers, B., Chtourou, Z., & Le Nir V. (2015). Jamming mitigation in cognitive radio networks using a modified q-learning algorithm. In International Conference on Military Communications and Information Systems, pp. 1–7.

  24. Smith, S. W. (2020). Securing the Internet of Things: An ongoing challenge. Computer, 53(6), 62–66.

    Article  Google Scholar 

  25. Wang, J., et al. (2017). Spectrum-aware anypath routing in multi-hop cognitive radio networks. IEEE Transactions on Mobile Computing, 16(4), 1176–87.

    Article  Google Scholar 

  26. Xiao, L., Chen, T., Liu, J., & Dai, H. (2015). Anti-jamming transmission Stackelberg game with observation errors. IEEE Communications Letters, 19(6), 949–952.

    Article  Google Scholar 

  27. Zhu, Z., Qian, Y., & Hu, R. Q. (2015). Delay based channel allocations in multi-hop cognitive radio networks. In Proceedings of IWCMC 2015, Dubrovnik, Croatia.

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Authors and Affiliations

  1. Telecommunications Engineering Department, Yarmouk University, Irbid, Jordan

    Rami Halloush, Haythem Bany Salameh, Mariam Al-Tamimi & Ahmed Musa

  2. College of Engineering, Al Ain University, Al Ain, UAE

    Haythem Bany Salameh

  3. College of Computing, Staffordshire University, Stoke-on-Trent, UK

    Haythem Bany Salameh

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  1. Rami Halloush
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  2. Haythem Bany Salameh
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  3. Mariam Al-Tamimi
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  4. Ahmed Musa
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Correspondence to Rami Halloush.

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Halloush, R., Salameh, H.B., Al-Tamimi, M. et al. A Jamming-resilient opportunistic QoS-constrained multi-channel routing for green IoT networking. Wireless Netw 29, 2685–2701 (2023). https://doi.org/10.1007/s11276-023-03344-2

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