Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Multi-layer based multi-path routing algorithm for maximizing spectrum availability

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

Last 2 decades have witnessed the spectrum resources scarcity which is caused by wireless networks’ ubiquitous applications. To utilize the rare spectrum resources more efficiently, Cognitive Radio (CR) technology has been developed as a promising scheme. However, in CR networks, a novel NP-Hard disjoint multi-path routing problem has been encountered due to the Primary Users’ (PUs’) random movements. To settle this problem, we present a Spectrum History Matrix mechanism to define long-term spectrum sensing information on time-spectrum level such that spectrum availability and communication efficiency can be quantized in CR networks. To lessen the possibility for an active PU to interrupt all paths simultaneously, a sub-optimal Multi-layer based Multi-path Routing Algorithm (MMRA) is provided to determine how to route multiple paths which are not under the same PUs’ interference ranges. Through theoretical and simulation analyses, MMRA can not only settle the disjoint multi-path routing problem in polynomial time complexity, but also maximize communication efficiency.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

References

  1. Cormio, C., & Chowdhury, K. R. (2009). A survey on MAC protocols for cognitive radio networks. Ad Hoc Networks, 7(7), 1315–1329.

    Article  Google Scholar 

  2. Yucek, T., & Arslan, H. (2009). A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Communications Surveys Tutorials, 11(1), 116–130. First.

    Article  Google Scholar 

  3. Hasan, Z., Boostanimehr, H., & Bhargava, V. (2011). Green cellular networks: A survey, some research issues and challenges. IEEE Communications Surveys Tutorials, 13(4), 524–540.

    Article  Google Scholar 

  4. FCC Spectrum Policy Task Force (2002) Report of the spectrum efficiency work group. Technical Report, Nov 2002.

  5. Akyildiz, I. F., Lee, W.-Y., & Chowdhury, K. R. (2009). Crahns: Cognitive radio ad hoc networks. Ad Hoc Networks, 7(5), 810–836.

    Article  Google Scholar 

  6. Marinho, J., & Monteiro, E. (2012). Cognitive radio: Survey on communication protocols, spectrum decision issues, and future research directions. Wireless Networks, 18(2), 147–164.

    Article  Google Scholar 

  7. Mitola, J. (2009). Cognitive radio architecture evolution. Proceedings of the IEEE, 97(4), 626–641.

    Article  Google Scholar 

  8. Mitola, J., Maguire, J., & Gerald, Q. (1999). Cognitive radio: Making software radios more personal. IEEE Personal Communications, 6(4), 13–18.

    Article  Google Scholar 

  9. Wang, B., & Liu, K. (2011). Advances in cognitive radio networks: A survey. IEEE Journal of Selected Topics in Signal Processing, 5(1), 5–23.

    Article  Google Scholar 

  10. Letaief, K., & Zhang, W. (2009). Cooperative communications for cognitive radio networks. Proceedings of the IEEE, 97(5), 878–893.

    Article  Google Scholar 

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

    Article  Google Scholar 

  12. Saleem, Y., Salim, F., & Rehmani, M. H. (2015). Routing and channel selection from cognitive radio network’s perspective: A survey. Computers & Electrical Engineering, 42, 117–134.

    Article  Google Scholar 

  13. Akyildiz, I., Lee, W.-Y., Vuran, M. C., & Mohanty, S. (2008). A survey on spectrum management in cognitive radio networks. IEEE Communications Magazine, 46(4), 40–48.

    Article  Google Scholar 

  14. Beltagy, I., Youssef, M., & El-Derini, M. (2011). A new routing metric and protocol for multipath routing in cognitive networks. In Wireless communications and networking conference (WCNC), 2011 IEEE, March 2011 (pp. 974–979).

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

  16. Ju, S., & Evans, J. B. (2010). Cognitive multipath multi-channel routing protocol for mobile ad-hoc networks. In GLOBECOM—IEEE global telecommunications conference.

  17. Mustafa, H., Zhang, X., Liu, Z., Xu, W., & Perrig, A. (2012). Jamming-resilient multipath routing. IEEE Transactions on Dependable and Secure Computing, 9(6), 852–864.

    Article  Google Scholar 

  18. Zhang, X., & Perrig, A. (2010). Correlation-resilient path selection in multi-path routing. In GLOBECOM—IEEE global telecommunications conference.

  19. Valera, A., Seah, W. K., & Rao, S. (2003). Cooperative packet caching and shortest multipath routing in mobile ad hoc networks. In Proceedings—IEEE INFOCOM (Vol. 1, pp. 260–269).

  20. Wu, K., & Harms, J. (2001). Performance study of a multipath routing method for wireless mobile ad hoc networks. In IEEE international workshop on modeling, analysis, and simulation of computer and telecommunication systems—Proceedings (pp. 99–107).

Download references

Acknowledgments

This research is supported by National Natural Science Foundation of China (Grant Nos. 51305319 and 61672395), International Science & Technology Cooperation Program of China (Grant No. 2015DFA70340), and Wuhan Chengguang Youth Science and Technology Program (Grant No. 2014072704011247).

Author information

Authors and Affiliations

  1. School of Information Engineering, Wuhan University of Technology, Wuhan, China

    Duzhong Zhang, Quan Liu, Wenjun Xu & Kehao Wang

  2. Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan, China

    Duzhong Zhang, Quan Liu, Wenjun Xu & Kehao Wang

  3. Laboratoire de Recherche Informatique (LRI-CNRS UMR 8623), University of Paris-Sud, 91405, Orsay, France

    Lin Chen

Authors
  1. Duzhong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Quan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wenjun Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kehao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Duzhong Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, D., Liu, Q., Chen, L. et al. Multi-layer based multi-path routing algorithm for maximizing spectrum availability. Wireless Netw 24, 897–909 (2018). https://doi.org/10.1007/s11276-016-1377-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-016-1377-x

Keywords

Search

Navigation