Skip to main content
Log in

HyMPRo: a hybrid multi-path routing algorithm for cognitive radio ad hoc networks

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

Routing is one of the major challenges in cognitive radio ad hoc networks. In finding new routes, not only the less impacted paths due the primary user activity, but also bottleneck formations over time in the secondary network and multiple connections initiated by the secondary users are important issues to be investigated. Besides, route search confined to a small fraction of all possible paths can lead to miss the appropriate one. This paper introduces a hybrid method employing three atomic metrics related to route stability, congestion awareness and path diversity based on active connections. Also, the number of alternative paths is kept on a limited scale which avoids the emergence of excessive traffic load in the network. The simulation results demonstrate the effectiveness of the proposed approach in terms of packet delivery ratio, end-to-end delay and throughput. It is also shown that the performance of our routing mechanism outperforms the existing baseline schemes.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Mitola III, J. (1999). Cognitive radio for flexible mobile multimedia communication. In IEEE international workshop on mobile multimedia communications (pp. 3–10). San Diego, California, USA.

  2. Akyildiz, F., Lee, W., Vuran, M. C., & Mohanty, S. (2006). Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Networks, 50(13), 2127–2159.

    Article  Google Scholar 

  3. Salim, S., & Moh, S. (2013). On-demand routing protocols for cognitive radio ad hoc networks. EURASIP Journal on Wireless Communications and Networking, 2013(1), 1–10.

    Article  Google Scholar 

  4. El Garoui, L., Ajib, W., & Elbiaze H. (2014). CO-TORA on-demand routing protocol for cognitive radio ad-hoc networks. In: International wireless communications and mobile computing conference (IWCMC). (pp. 654–659), Nicosia, Cyprus.

  5. Joshi, G. P., Kim, S. W., & Nam, S. Y. (2015). Routing layer solution for mitigating frequent channel switching in ad hoc cognitive radio networks. IEEE Communications Letters, 19(11), 1917–1920.

    Article  Google Scholar 

  6. Chowdhury, K. R., & Di Felice, M. (2009). SEARCH: A routing protocol for mobile cognitive radio ad-Hoc networks. In :IEEE sarnoff symposium. (pp. 1–6), Princeton, NJ, USA.

  7. Habak, K., Abdelatif, M., Hagrass, H., Rizc, & K., Youssef, M. (2013). A location-aided routing protocol for cognitive radio networks. In: International conference on computing, networking and communications (ICNC). (pp. 729–733), San Diego, USA.

  8. Tang, F., Barolli, L., & Li, J. (2014). A joint design for distributed stable routing and channel assignment over multihop and multiflow mobile ad hoc cognitive networks. IEEE Transactions on Industrial Informatics, 10(2), 1606–1615.

    Article  Google Scholar 

  9. Lee, J. J., & Lim, J. (2014). Cognitive routing for multi-hop mobile cognitive radio ad hoc networks. Communications and Networks, 16(2), 155–161.

    Article  Google Scholar 

  10. Caleffi, M., Akyildiz, I. F., & Paura, L. (2012). OPERA: Optimal routing metric for cognitive radio ad hoc networks. IEEE Transactions on Wireless Communications, 11(8), 2884–2894.

    Google Scholar 

  11. Althunibat, S., Wang, Q., & Granelli, F. (2016). Flexible channel selection mechanism for cognitive radio based last mile smart grid communications. Ad Hoc Networks, 41, 47–56.

    Article  Google Scholar 

  12. Chowdhury, R., & Akyildiz, I. F. (2011). CRP: A routing protocol for cognitive radio ad hoc networks. IEEE Journal on Selected Areas in Communications, 29(4), 794–804.

    Article  Google Scholar 

  13. Karmoose, M., Habak, K., ElNainay, M., & Youssef, M. (2013). Dead zone penetration protocol for cognitive radio networks. In IEEE International conference on wireless and mobile computing, networking and communications (WiMob). (pp. 529–536), Lyon, France.

  14. Gui, L., Zhong, X., & Zou, S. (2013). Traffic assignment algorithm for multi-path routing in cognitive radio ad hoc networks. In: IEEE wireless communications and networking conference (WCNC). (pp. 1168–1173), Shanghai, China.

  15. Jin, X., Zhang, R., Sun, J., & Zhang, Y. (2014). TIGHT: A geographic routing protocol for cognitive radio mobile ad hoc networks. IEEE Transactions on Wireless Communications, 13(8), 4670–4681.

    Article  Google Scholar 

  16. Ping, S., Aijaz, A., Holland, O., & Aghvami, A. (2015). SACRP: A spectrum aggregation-based cooperative routing protocol for cognitive radio ad-hoc networks. IEEE Transactions on Communications, 63(6), 2015–2030.

    Article  Google Scholar 

  17. Kamruzzaman, S. M., Kim, E., Jeong, D. G., & Jeon, W. S. (2012). Energy-aware routing protocol for cognitive radio ad hoc networks. IET Communications, 6(14), 2159–2168.

    Article  Google Scholar 

  18. Hassnawi, L. A., Ahmad, R. B., Yahya, A., Aljunid, S. A., & Elshaikh, M. (2012). Performance analysis of various routing protocols for motorway surveillance system cameras’ network. International Journal of Computer Sciences, 9(2), 7–21.

    Google Scholar 

  19. Ji, S., Yan, M., Beyah, R., & Cai, Z. (2016). Semi-structure routing and analytical frameworks for cognitive radio networks. IEEE Transactions on Mobile Computing, 15(4), 996–1008.

    Google Scholar 

  20. Pourpeighambar, B., Dehghan, M., & Sabaei, M. (2017). Multi-agent learning based routing for delay minimization in cognitive radio networks. Journal of Network and Computer Applications, 84, 82–92.

    Article  Google Scholar 

  21. Omar, S., Ghandour, O. E., & El-Haleem, A. M. A. (2017). Multipath activity based routing protocol for mobiley cognitive radio ad hoc networks. Wireless Communications and Mobile Computing, 2017, 1–12.

    Article  Google Scholar 

  22. Cui, C., Man, H., Wang, Y., & Liu, S. (2016). Optimal cooperative spectrum aware opportunistic routing in cognitive radio ad hoc networks. Wireless Personal Communications, 91(1), 101–118.

    Article  Google Scholar 

  23. Liu, Y., Cai, L. X., & Shen, X. S. (2012). Spectrum-aware opportunistic routing in multi-hop cognitive radio networks. IEEE Journal on Selected Areas in Communications, 30(10), 1958–1968.

    Article  Google Scholar 

  24. Youssef, M., Ibrahim, M., Abdelatif, M., Chen, L., & Vasilakos, A. V. (2014). Routing metrics of cognitive radio networks: A survey. IEEE Communications Surveys & Tutorials, 16(1), 92–109.

    Article  Google Scholar 

  25. Güler, E., Sadreddini, Z., & Çavdar, T. (2015). Multi-path route discovery algorithm for cognitive radio ad hoc networks using algebraic connectivity. In International conference on telecommunications and signal processing (TSP). (pp. 54–59), Prague, Czech Republic.

  26. Cesana, M., Cuomo, F., & Ekici, E. (2011). Routing in cognitive radio networks: Challenges and solutions. Ad Hoc Networks, 9(3), 228–248.

    Article  Google Scholar 

  27. Garcia, N. M., Lenkiewicz, P., Freire, M. M., & Monteiro, P. P. (2007). On the Performance of Shortest Path Routing Algorithms for Modeling and Simulation of Static Source Routed Networks - an Extension to the Dijkstra Algorithm. In 2007 Second international conference on systems and networks communications (ICSNC 2007). (pp. 60–60), Cap Esterel, France

  28. Abbagnale, A., & Cuomo, F. (2012). Leveraging the Algebraic connectivity of a cognitive network for routing design. IEEE Transactions on Mobile Computing, 11(7), 1163–1178.

    Article  Google Scholar 

  29. Ding, L., Melodia, T., Batalama, S. N., Matyjas, J. D., & Medley, M. J. (2010). Cross-layer routing and dynamic spectrum allocation in cognitive radio ad hoc networks. IEEE Transactions on Vehicular Technology, 59(4), 1969–1979.

    Article  Google Scholar 

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

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tuğrul Çavdar.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Çavdar, T., Güler, E. HyMPRo: a hybrid multi-path routing algorithm for cognitive radio ad hoc networks. Telecommun Syst 69, 61–76 (2018). https://doi.org/10.1007/s11235-018-0426-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-018-0426-4

Keywords

Navigation