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Improvement of Network Throughput by Providing CAODV-Based Routing Algorithm in Cognitive Radio Ad Hoc Networks

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Abstract

In this paper, a CAODV-based routing approach is proposed which uses multi-channel and multi-path forwarding techniques to deal with the time-varying activities of PUs. We also benefited from a suitable channel selection strategy with the goal of increasing throughput. Our method allocates interference-free channels and, if data is entered or activated, each node will select a path. The proposed routing mechanism, in turn, considers the relay loading, and the interference of the common channel in the primary and secondary nodes. We use the Lyapunov optimization queuing model in a multi-channel network. What is clear from the simulation results is that the proposed protocol improves end to end delay, PDR and throughput performance significantly in comparison to another protocols such as SEARCH and CAODV.

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References

  1. Akyildiz, I. F., Lee, W.-Y., & Chowdhury, K. R. (2009). CRAHNs: Cognitive radio ad hoc networks. Ad Hoc Networks,7, 810–836.

    Article  Google Scholar 

  2. Caleffi, M., Akyildiz, I. F., & Paura, L. (2012). OPERA: Optimal routing metric for cognitive radio ad hoc networks. IEEE Transactions on Wireless Communications,11, 2884–2894.

    Google Scholar 

  3. Chowdhury, K. R., & Akyildiz, I. F. (2011). CRP: A routing protocol for cognitive radio ad hoc networks. IEEE Journal on Selected Areas in Communications,29, 794–804.

    Article  Google Scholar 

  4. Di Felice, M., Chowdhury, K. R., & Bononi, L. (2009) Modeling and performance evaluation of transmission control protocol over cognitive radio Ad Hoc networks. In Proceedings of the 12th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems, 2009.

  5. Xie, M., Zhang, W., & Wong, K.-K. (2010). A geometric approach to improve spectrum efficiency for cognitive relay networks. IEEE Transactions on Wireless Communications,9, 268–281.

    Article  Google Scholar 

  6. Zhu, M., Akyildiz, I. F., & Kuo, G-S. (2008) STOD-RP: A spectrum tree based on-demand routing protocol for multi-hop cognitive radio networks. In Proc. IEEE Globecom (2008).

  7. Chowdhury, K. R., & Felice, M. D. (2009). Search: A routing protocol for mobile cognitive radio ad-hoc networks. Computer Communications,32(18), 1983–1997.

    Article  Google Scholar 

  8. IEEE Xplore-CAODV (2010) Routing in mobile ad-hoc cognitive radio. IEEE xplore.ieee.org, wireless days 2010 IFIP.

  9. Ahn, H., Kim, J., & Ko, Y. B. (2015). CLSR: cognitive link state routing for Cr-based tactical ad hoc networks. KSII Transactions on Internet and Information Systems,9(1), 50–67.

    Google Scholar 

  10. CHE-Aron, Z., Abdalla, A. H., Abdullah, K., Hassan, W. H., & Rahman, M. D. A. (2015). RACARP: A robustness aware routing protocol for cognitive radio ad-hoc network. Journal of Theoretical and Applied Information Technology,76(2), 246–257.

    Google Scholar 

  11. Indhumathi, L., & Vadivel, R. B. (2015). Adaptive delay tolerant routing protocol (adtrp) for cognitive radio mobile ad hoc networks. International Journal of Computer Applications,128(6), 0975–8887.

    Article  Google Scholar 

  12. Hou, L., Wong, A. K Y., & Yeung, A. K. H. (2016) Exploring the impact of node co-operation level on routing in cognitive radio network. In The Sixth International Conference on Advances in Cognitive Radio, 2016.

  13. Liu, Y., Cai, L. X., & Shen, X. (2012). Spectrum-aware opportunistic routing in multi-hop cognitive radio networks. IEEE Journal on Selected Areas in Communications,30, 1958–1968.

    Article  Google Scholar 

  14. Abbagnale, A., & Cuomo, F. (2010) Gymkhana: A connectivity-based routing scheme for cognitive radio ad hoc networks. In IEEE Conference on computer communications workshops in INFOCOM.

  15. Lee, W. Y., & Akyildiz, I. (2008). Optimal spectrum sensing framework for cognitive radio networks. IEEE Transactions onWireless Communications,7(10), 3845–3857.

    Article  Google Scholar 

  16. Min, A. W., & Shin, K. G. (2008) Exploiting multi-channel diversity in spectrum-agile networks. In INFOCOM 2008, The 27thConference on Computer Communications, IEEE, 2008.

  17. Geirhofer, S., Tong, L., & Sadler B. M. (2006) Dynamic spectrum access in WLAN channels: Emperical model and its stochastic analysis. In ACMTAPAS, Aug 2006.

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Correspondence to Nahid Ardalani.

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Shakeri, M., Ardalani, N. & Derakhshan-Barjoei, P. Improvement of Network Throughput by Providing CAODV-Based Routing Algorithm in Cognitive Radio Ad Hoc Networks. Wireless Pers Commun 113, 893–903 (2020). https://doi.org/10.1007/s11277-020-07258-6

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