Skip to main content

Advertisement

Springer Nature Link
Log in

Multi-Channel Allocation Algorithm for Anti-interference and Extending Connected Lifetime in Wireless Sensor Network

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In wireless sensor network, the large interference makes some nodes prematurely fail. And the premature failure of any important node will accelerate the network to be disconnected and even paralyzed. Due to the limited energy and topology connectivity, three factors should be considered in channel allocation: path gain, residual energy and importance of node. Path gain more accurately describes the node interference. The consideration of residual energy enables the node select an available channel to protect the less residual energy node. In the same way, the node importance protects the network topology. In this paper, the path gain, residual energy and node importance are mathematically formulated as an optimization problem with the Game Theory. A channel allocation algorithm called ACBR is proposed. The theoretical analyses prove that for the ACBR algorithm, Nash Equilibrium (NE) exists at least once and the sub-optimality of NE is also analyzed. Simulation results demonstrate that ACBR significantly reduces the interference and dramatically improves the network performance in terms of energy consumption, network connected lifetime, channel fairness and convergence speed.

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

Similar content being viewed by others

References

  1. Yu, X. T., Shi, X. X., & Hua, J. Y. (2013). A distributed channel allocation algorithm for multi-channel wireless network. Information Technology Journal, 12(1), 209–213.

    Article  Google Scholar 

  2. Hou, C. Y. (2010). Research on minimum interference channel assignment in multiradio wireless mesh networks. Mathematics in Practice and Theory, 40(7), 181–184.

    Google Scholar 

  3. Peng, L. M., & Liu, H. (2009). Channel assignment algorithm in multi-channel wireless mesh networks. Journal of Computer Applications, 29(7), 1849–1851.

    Article  Google Scholar 

  4. Chen, J. M., Yu, Q., Cheng, P., et al. (2011). Game theoretical approach for channel allocation in wireless sensor and actuator networks. IEEE Transactions on Automatic Control, 56(10), 2332–2343.

    Article  MathSciNet  Google Scholar 

  5. Komali, R.S., & MacKenzie, A.B. (2009). Analyzing selfish topology control in multi-radio multi-channel multi-hop wireless networks Communications, 2009. ICC’09. IEEE International Conference on. IEEE, 1–6.

  6. Long, C. N., Chi, Q., Guan, X. P., et al. (2011). Joint random access and power control game in ad hoc networks with non-cooperative users. Ad Hoc Networks, 9(2), 142–151.

    Article  Google Scholar 

  7. Ramachandran, K.N., & Belding, E.M., Almeroth, K.C., et al. (2006). Interference-aware channel assignment in multi-radio wireless mesh networks. In Proceedings of the 25th IEEE international Conference on Computer Communications (INFOCOM) (Vol. 6, pp. 1–12). doi: 10.1109/INFOCOM.2006.177.

  8. Xu, J., Yang, Z. K., & Yuan, W. (2012). Heterogeneous channel assignment of multi-radio multi-channel wireless networks: A game theoretic approach. Journal of Chinese Computer Systems, 33(5), 1053–1056.

    Google Scholar 

  9. Teng, Z. J., Han, X., & Yang, X. (2011). Spectrum allocation algorithm based on game theory in cognitive radio. Application Research of Computers, 28(7), 2661–2663.

    Google Scholar 

  10. Li, X. L., & Liu, H. T. (2010). Spectrum allocation algorithm of cognitive radio based on supermodel game. Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), 22(2), 151–155.

    Google Scholar 

  11. Ni, Z.F., Shan, H.G., Shen, W., et al. (2013). Dynamic channel allocation-based call admission control in cognitive radio networks. In Proceedings of the 2013 international conference on wireless communications and Signal Processing (WCSP). IEEE (pp. 1–6). doi:10.1109/WCSP.2013.6677288.

  12. Karaoglu, B., & Heinzelman, W. (2014). Cooperative load balancing and dynamic channel allocation for cluster-based mobile ad hoc networks. In IEEE transactions on mobile computing (pp. 1–13). doi: 10.1109/TMC.2014.2339215.

  13. Goel, A., Sheezan, M., & Ahmed, M. (2014). Distributed dynamic channel allocation scheme in interference-limited sectored cellular network. In Proceedings of the 2014 international conference on computing for sustainable global development (INDIACom) (pp. 856–860). IEEE. doi:10.1109/indiaCom.2014.6828084.

  14. Kim, Y., Shin, H., & Cha, H. (2008). Y-MAC: An energy-efficient multi-channel mac protocol for dense wireless sensor networks, In Proceedings of the 7th international conference on Information processing in sensor networks. IEEE Computer Society (pp. 53–63).

  15. Hao, X. C., Zhang, Y. X., Jia, N., & Liu, B. (2013). Joint algorithm of channel allocation and power control in multi-channel wireless sensor network. Wireless Personal Communications, 73(3), 1169–1186. doi:10.1007/s11277-013-1272-z.

    Article  Google Scholar 

  16. Polastre, J., Hill, J., & Culler, D. Versatile low power media access for wireless sensor networks In Proceedings of the 2nd international conference on embedded networked sensor system (pp. 95–107).

  17. Elbatt, T., & Ephremides, A. (2004). Joint scheduling and power control for wireless ad hoc networks. IEEE Transactions on Wireless Communications, 3(1), 74–85.

    Article  Google Scholar 

  18. Song, Y., Zhang, C., & Fang, Y. G. (2008). Joint channel and power allocation in wireless mesh networks: a game theoretical perspective. IEEE Journal on Selected Areas in Communications, 26(7), 1149–1159.

    Article  Google Scholar 

  19. Hao, X. C., Zhang, Y. X., Jia, N., et al. (2013). Virtual game-based energy balanced topology control algorithm for wireless sensor networks. Wireless Personal Communications, 69(4), 1289–1308. doi:10.1007/s11277-012-0634-2.

    Article  Google Scholar 

  20. Wu, Y. (2011) The recognition algorithm and research of bottleneck node in sensor network. Xi’an: Southwest Jiaotong University (pp. 28–32).

  21. Nishimori, K., Di Taranto, R., Yomo, H., & Popovski, P. (2011). Cognitive radio operation under directional primary interference and practical path loss models. IEICE Transactions on Communications, 94(5), 1243–1253.

    Article  Google Scholar 

  22. Li, P. Y., He, Z. F., & Lin, G. H. (2013). Sampling average approximation method for a class of stochastic Nash equilibrium problems. Optimization Methods and Software, 28(4), 785–795.

    Article  MathSciNet  MATH  Google Scholar 

  23. Beaude, O., Lasaulce, S., & Hennebel, M. (2012). Charging games in networks of electrical vehicles. In Proceedings of the 6th international conference on network games, control and optimization (NetGCoop) (pp. 96-103).

  24. Fanelli, A., Moscardelli, L., & Skopalik, A. On the impact of fair best response dynamics. In Proceedings of the 37th international symposium on mathematical foundations of computer science (MFCS) (pp. 360–371).

  25. Koutsoupias, E., & Papadimitriou C. (1999) Worst-case equilibria. In Proceedings of STACS’99 (pp. 404–413).

Download references

Acknowledgments

The authors would like to thank the reviewers for their constructive comments on the Manuscript. This work is supported by the National Natural Science Foundation of China under Grant No. 61403336, the Natural Science Foundation of Hebei Province of China under Grant No. F2015203342 and the Independent Research Project Topics A Category for Young Teacher of Yanshan University of China under Grant No. 13LGA008.

Author information

Author notes

    Authors and Affiliations

    1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China

      Xiao-Chen Hao, Ning Yao & Wei-Jing Liu

    2. Institute of Information Science and Engineering, Yanshan University, Qinhuangdao, China

      Xi-Da Li

    Authors
    1. Xiao-Chen Hao
      View author publications

      You can also search for this author inPubMed Google Scholar

    2. Ning Yao
      View author publications

      You can also search for this author inPubMed Google Scholar

    3. Xi-Da Li
      View author publications

      You can also search for this author inPubMed Google Scholar

    4. Wei-Jing Liu
      View author publications

      You can also search for this author inPubMed Google Scholar

    Corresponding author

    Correspondence to Xiao-Chen Hao.

    Additional information

    Xiao-Chen Hao and Ning Yao are joint first authors. These authors contributed equally to this work.

    Rights and permissions

    Reprints and permissions

    About this article

    Check for updates. Verify currency and authenticity via CrossMark

    Cite this article

    Hao, XC., Yao, N., Li, XD. et al. Multi-Channel Allocation Algorithm for Anti-interference and Extending Connected Lifetime in Wireless Sensor Network. Wireless Pers Commun 87, 1299–1318 (2016). https://doi.org/10.1007/s11277-015-3054-2

    Download citation

    • Published:

    • Issue Date:

    • DOI: https://doi.org/10.1007/s11277-015-3054-2

    Keywords